Home » Decision Making
Plus, Minus, Interesting
3:28 AM |Imagine that you're trying to get your IT team to agree on a process for people to follow when they need help.
You think that this will reduce the number of queries coming through to your helpdesk, but some of your team members doubt that the process will work for many users.
Despite your best efforts, you can't get your people to agree on a best way forward; so, you decide to use the PMI tool to reach a decision.
After a few minutes of frenetic brainstorming and good-natured shouting of ideas, you tally the scores and come to a surprising conclusion. The group that opposed the process may be right: it may not be a good idea for the average user. You could be wrong!
PMI stands for "Plus/Minus/Interesting," and it's a useful improvement to the "weighing pros and cons" technique that people have used for centuries. In this article, we'll look at how you can use PMI to make better decisions, and even see problems and issues in different ways.
About the Tool
Edward de Bono developed the PMI tool and published it in his 1982 book, " De Bono's Thinking Course ." However, he draws on the tool in many of his published books.
PMI helps you make decisions quickly by weighing the pros and cons of a decision. It's also useful for widening your perception of a problem or decision, and for uncovering issues that you might not ordinarily have considered.
PMI is particularly helpful with a group, especially when you have team members who strongly favor a particular idea, point of view or plan. The tool encourages everyone to consider other perspectives, and it can help the group reach a balanced, informed decision (or at least see an issue from someone else's point of view).
Note:
PMI is useful for making quick, non-critical, go/no-go decisions . You'll need to use other techniques if you need to compare many different options, or if you need to explore some options in greater depth. For these situations, decision-making tools such as Grid Analysis or Decision Tree Analysis are more appropriate.
How to Use the Tool
It shouldn't take long to use PMI. Complete your analysis quickly, especially when you're working with a group: having a tight time limit pushes you to
brainstorm issues without overanalyzing them.
First, draw up three columns on a piece of paper. Head them "Plus," "Minus," and "Interesting."
In the column underneath "Plus," write down all of the possible positive consequences of taking the action. Underneath "Minus," write down all of the negative effects. In the "Interesting" column, write down all of the "interesting" implications and possible outcomes of taking the action. These may not immediately seem to be good or bad, but could, possibly, lead to new opportunities.
By this stage, it may already be obvious whether or not you should implement the decision. If it isn't, consider each of the points that you've written down, and assign a positive or negative score to it appropriately. (The scores that you assign may be quite subjective.)
Once you've finished, add up the scores. A positive score indicates that you should take an action, while a negative score suggests that you should avoid it.
It's important to remember to "sense check" your scores. If your intuition is telling you that an answer isn't right, take some time to check to see if you've missed something from your analysis.
Example
Daniel's boss has unexpectedly offered him a promotion. Daniel is excited about the opportunity, but he knows that there are several downsides to leaving his current team and taking on a new role. He decides to weigh the pros and cons of the decision using the PMI tool.
Plus
Minus
Interesting
Higher income (+4)
Much more responsibility (-2)
Challenge myself professionally? (+4)
Get to meet new people
(+3)
Likely to be more stress (-4)
Will be living in a new area
(+3)
Self-Confidence improves
(+5)
Have to sell house and move (-5)
Must learn how to manage others (-2)
+12
-13
+7
Daniel scores the table as 12 (Plus) – 13 (Minus) + 7 (Interesting) = +6
For him, the promotion will be worth the stress and inconvenience that comes with the new role.
Key Points
PMI is a quick and useful tool for weighing the pros, cons, and implications of a decision.
To use the technique, draw up a table with three columns, headed "Plus," "Minus," and "Interesting." Within the table, write down all of the possible benefits of following the course of action, all of the negative outcomes, and all of the interesting implications and possible results.
If you're still not sure about your decision, you can then score the table to show the importance of individual items. The total score will help you decide whether it's worth going ahead with the decision.
Read more…
You think that this will reduce the number of queries coming through to your helpdesk, but some of your team members doubt that the process will work for many users.
Despite your best efforts, you can't get your people to agree on a best way forward; so, you decide to use the PMI tool to reach a decision.
After a few minutes of frenetic brainstorming and good-natured shouting of ideas, you tally the scores and come to a surprising conclusion. The group that opposed the process may be right: it may not be a good idea for the average user. You could be wrong!
PMI stands for "Plus/Minus/Interesting," and it's a useful improvement to the "weighing pros and cons" technique that people have used for centuries. In this article, we'll look at how you can use PMI to make better decisions, and even see problems and issues in different ways.
About the Tool
Edward de Bono developed the PMI tool and published it in his 1982 book, " De Bono's Thinking Course ." However, he draws on the tool in many of his published books.
PMI helps you make decisions quickly by weighing the pros and cons of a decision. It's also useful for widening your perception of a problem or decision, and for uncovering issues that you might not ordinarily have considered.
PMI is particularly helpful with a group, especially when you have team members who strongly favor a particular idea, point of view or plan. The tool encourages everyone to consider other perspectives, and it can help the group reach a balanced, informed decision (or at least see an issue from someone else's point of view).
Note:
PMI is useful for making quick, non-critical, go/no-go decisions . You'll need to use other techniques if you need to compare many different options, or if you need to explore some options in greater depth. For these situations, decision-making tools such as Grid Analysis or Decision Tree Analysis are more appropriate.
How to Use the Tool
It shouldn't take long to use PMI. Complete your analysis quickly, especially when you're working with a group: having a tight time limit pushes you to
brainstorm issues without overanalyzing them.
First, draw up three columns on a piece of paper. Head them "Plus," "Minus," and "Interesting."
In the column underneath "Plus," write down all of the possible positive consequences of taking the action. Underneath "Minus," write down all of the negative effects. In the "Interesting" column, write down all of the "interesting" implications and possible outcomes of taking the action. These may not immediately seem to be good or bad, but could, possibly, lead to new opportunities.
By this stage, it may already be obvious whether or not you should implement the decision. If it isn't, consider each of the points that you've written down, and assign a positive or negative score to it appropriately. (The scores that you assign may be quite subjective.)
Once you've finished, add up the scores. A positive score indicates that you should take an action, while a negative score suggests that you should avoid it.
It's important to remember to "sense check" your scores. If your intuition is telling you that an answer isn't right, take some time to check to see if you've missed something from your analysis.
Example
Daniel's boss has unexpectedly offered him a promotion. Daniel is excited about the opportunity, but he knows that there are several downsides to leaving his current team and taking on a new role. He decides to weigh the pros and cons of the decision using the PMI tool.
Plus
Minus
Interesting
Higher income (+4)
Much more responsibility (-2)
Challenge myself professionally? (+4)
Get to meet new people
(+3)
Likely to be more stress (-4)
Will be living in a new area
(+3)
Self-Confidence improves
(+5)
Have to sell house and move (-5)
Must learn how to manage others (-2)
+12
-13
+7
Daniel scores the table as 12 (Plus) – 13 (Minus) + 7 (Interesting) = +6
For him, the promotion will be worth the stress and inconvenience that comes with the new role.
Key Points
PMI is a quick and useful tool for weighing the pros, cons, and implications of a decision.
To use the technique, draw up a table with three columns, headed "Plus," "Minus," and "Interesting." Within the table, write down all of the possible benefits of following the course of action, all of the negative outcomes, and all of the interesting implications and possible results.
If you're still not sure about your decision, you can then score the table to show the importance of individual items. The total score will help you decide whether it's worth going ahead with the decision.
Risk Analysis and Risk Management
3:26 AM |Risk Analysis and Risk Management
Evaluating and Managing Risks
Find out how to do a risk analysis, with James Manktelow and Amy Carlson.
Whatever your role, it's likely that you'll need to make a decision that involves an element of risk at some point.
Risk is made up of two parts: the probability of something going wrong, and the negative consequences if it does.
Risk can be hard to spot, however, let alone prepare for and manage. And, if you're hit by a consequence that you hadn't planned for, costs, time, and reputations could be on the line.
This makes Risk Analysis an essential tool when your work involves risk. It can help you idenfity and understand the risks that you could face in your role. In turn, this helps you manage these risks, and minimize their impact on your plans.
In this article, we'll look at how you can use Risk Analysis to identify and manage risk effectively.
What is Risk Analysis?
Risk Analysis is a process that helps you identify and manage potential problems that could undermine key business initiatives or projects.
To carry out a Risk Analysis, you must first identify the possible threats that you face, and then estimate the likelihood that these threats will materialize.
Risk Analysis can be complex, as you'll need to draw on detailed information such as project plans, financial data, security protocols, marketing forecasts, and other relevant information. However, it's an essential planning tool, and one that could save time, money, and reputations.
When to Use Risk Analysis
Risk analysis is useful in many situations:
When you're planning projects, to help you anticipate and neutralize possible problems.
When you're deciding whether or not to move forward with a project.
When you're improving safety and managing potential risks in the workplace.
When you're preparing for events such as equipment or technology failure, theft, staff sickness, or natural disasters.
When you're planning for changes in your environment, such as new competitors coming into the market, or changes to government policy.
How to Use Risk Analysis
To carry out a risk analysis, follow these steps:
1. Identify Threats
The first step in Risk Analysis is to identify the existing and possible threats that you might face. These can come from many different sources. For instance, they could be:
Human – Illness, death, injury, or other loss of a key individual.
Operational – Disruption to supplies and operations, loss of access to essential assets, or failures in distribution.
Reputational – Loss of customer or employee confidence, or damage to market reputation.
Procedural – Failures of accountability, internal systems, or controls, or from fraud.
Project – Going over budget, taking too long on key tasks, or experiencing issues with product or service quality.
Financial – Business failure, stock market fluctuations, interest rate changes, or non-availability of funding.
Technical – Advances in technology, or from technical failure.
Natural – Weather, natural disasters, or disease.
Political – Changes in tax, public opinion, government policy, or foreign influence.
Structural – Dangerous chemicals, poor lighting, falling boxes, or any situation where staff, products, or technology can be harmed.
You can use a number of different approaches to carry out a thorough analysis:
Run through a list such as the one above to see if any of these threats are relevant.
Think about the systems, processes, or structures that you use, and analyze risks to any part of these. What vulnerabilities can you spot within them?
Ask others who might have different perspectives. If you're leading a team, ask for input from your people, and consult others in your organization, or those who have run similar projects.
Tools such as SWOT Analysis and Failure Mode and Effects Analysis can also help you uncover threats, while
Scenario Analysis helps you explore possible future threats.
2. Estimate Risk
Once you've identified the threats you're facing, you need to calculate out both the likelihood of these threats being realized, and their possible impact.
One way of doing this is to make your best estimate of the probability of the event occurring, and then to multiply this by the amount it will cost you to set things right if it happens. This gives you a value for the risk:
Risk Value = Probability of Event x Cost of Event
As a simple example, imagine that you've identified a risk that your rent may increase substantially.
You think that there's an 80 percent chance of this happening within the next year, because your landlord has recently increased rents for other businesses. If this happens, it will cost your business an extra $500,000 over the next year.
So the risk value of the rent increase is:
0.80 (Probability of Event) x $500,000 (Cost of Event) = $400,000 (Risk Value)
You can also use a Risk Impact/Probability Chart to assess risk. This will help you to identify which risks you need to focus on.
Tip:
Don't rush this step. Gather as much information as you can so that you can accurately estimate the probability of an event occurring, and the associated costs. Use past data as a guide if you don't have an accurate means of forecasting.
How to Manage Risk
Once you've identified the value of the risks you face, you can start to look at ways of managing them.
Tip:
Look for cost-effective approaches – it's rarely sensible to spend more on eliminating a risk than the cost of the event if it occurs. It may be better to accept the risk than it is to use excessive resources to eliminate it.
Be sensible in how you apply this, though, especially if ethics or personal safety are in question.
Avoid the Risk
In some cases, you may want to avoid the risk altogether. This could mean not getting involved in a business venture, passing on a project, or skipping a high-risk activity. This is a good option when taking the risk involves no advantage to your organization, or when the cost of addressing the effects is not worthwhile.
Remember that when you avoid a potential risk entirely, you might miss out on an opportunity. Conduct a "What If?" Analysis to explore your options when making your decision.
Share the Risk
You could also opt to share the risk – and the potential gain – with other people, teams, organizations, or third parties.
For instance, you share risk when you insure your office building and your stock with a third-party insurance company, or when you partner with another organization in a joint product development initiative.
Accept the Risk
Your last option is to accept the risk. This option is usually best when there's nothing you can do to prevent or mitigate a risk, when the potential loss is less than the cost of insuring against the risk, or when the potential gain is worth accepting the risk.
For example, you might accept the risk of a project launching late if the potential sales will still cover your costs.
Before you decide to accept a risk, conduct an Impact Analysis to see the full consequences of the risk. You may not be able to do anything about the risk itself, but you can likely come up with a
contingency plan
to cope with its consequences.
Controlling Risk
If you choose to accept the risk, there are a number of ways in which you can reduce its impact.
Business Experiments are an effective way to reduce risk. They involve rolling out the high-risk activity but on a small scale, and in a controlled way. You can use experiments to observe where problems occur, and to find ways to introduce preventative and detective actions before you introduce the activity on a larger scale.
Preventative action involves aiming to prevent a high-risk situation from happening. It includes health and safety training, firewall protection on corporate servers, and cross-training your team.
Detective action involves identifying the points in a process where something could go wrong, and then putting steps in place to fix the problems promptly if they occur. Detective actions include double-checking finance reports, conducting safety testing before a product is released, or installing sensors to detect product defects.
Plan-Do-Check-Act is a similar method of controlling the impact of a risky situation. Like a Business Experiment, it involves testing possible ways to reduce a risk. The tool's four phases guide you though an analysis of the situation, creating and testing a solution, checking how well this worked, and implementing the solution.
Key Points
Risk Analysis is a proven way of identifying and assessing factors that could negatively affect the success of a business or project. It allows you to examine the risks that you or your organization face, and helps you decide whether or not to move forward with a decision.
You do a Risk Analysis by identify threats, and estimating the likelihood of those threats being realized.
Once you've worked out the value of the risks you face, you can start looking at ways to manage them effectively. This may include choosing to avoid the risk, sharing it, or accepting it while reducing its impact.
It's essential that you're thorough when you're working through your Risk Analysis, and that you're aware of all of the possible impacts of the risks revealed. This includes being mindful of costs, ethics, and people's safety.
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What members say... Dianna wrote That's great! Thanks for your comments and tips- always appreciated!
Dianna July 5, 2013 rtab wrote Hi Dianna
We do have a similar framework at work for managing project risk. It is a very useful tool.
Cheers
rtab July 4, 2013 Dianna wrote Hi rtab,
Do you ever use the Risk Impact/Probability Chart? http://www.mindtools.com/community/pages/article/newPPM_78.php it's another extension tool that helps prioritize risk and then you can deal with the most probable and develop contingencies for the top ones.
Dianna July 4, 2013 rtab wrote Hi
Risk management is an important activity for all organisations and at any stage of the business cycle. This is a great tool.
My opinion is that this tool can be further extended by identifying what will trigger these risks to become issues and also by calculating the residual risk. This is where the impact and likelihood is re-assessed after applying the mitigating actions. I think this will allow decision to be made as to whether the risk is acceptable even after the mitigating actions are in place.
cheers
rtab July 3, 2013 James wrote Hi Everyone
We’ve given this popular article a review, and the updated version is now at
http://www.mindtools.com/community/pages/article/newTMC_07.php
Discuss the article by replying to this post!
Thanks
James June 19, 2013 James wrote Hi everyone
Just letting your know that we’ve just published a new video for this topic.
Click here to watch the video:
http://www.mindtools.com/community/pages/main/videos.php#risk-analysis
James June 30, 2011 bigk wrote Hi James
There are many uses in the guidance, it could also be used in personal risk assessment or to help decide planning, direction and action.
When used with cost and impact for decisions, it can give information about the risk in a task or project and also give information about the bigger picture risk or plan.
Bigk June 12, 2010
Read more…
Evaluating and Managing Risks
Find out how to do a risk analysis, with James Manktelow and Amy Carlson.
Whatever your role, it's likely that you'll need to make a decision that involves an element of risk at some point.
Risk is made up of two parts: the probability of something going wrong, and the negative consequences if it does.
Risk can be hard to spot, however, let alone prepare for and manage. And, if you're hit by a consequence that you hadn't planned for, costs, time, and reputations could be on the line.
This makes Risk Analysis an essential tool when your work involves risk. It can help you idenfity and understand the risks that you could face in your role. In turn, this helps you manage these risks, and minimize their impact on your plans.
In this article, we'll look at how you can use Risk Analysis to identify and manage risk effectively.
What is Risk Analysis?
Risk Analysis is a process that helps you identify and manage potential problems that could undermine key business initiatives or projects.
To carry out a Risk Analysis, you must first identify the possible threats that you face, and then estimate the likelihood that these threats will materialize.
Risk Analysis can be complex, as you'll need to draw on detailed information such as project plans, financial data, security protocols, marketing forecasts, and other relevant information. However, it's an essential planning tool, and one that could save time, money, and reputations.
When to Use Risk Analysis
Risk analysis is useful in many situations:
When you're planning projects, to help you anticipate and neutralize possible problems.
When you're deciding whether or not to move forward with a project.
When you're improving safety and managing potential risks in the workplace.
When you're preparing for events such as equipment or technology failure, theft, staff sickness, or natural disasters.
When you're planning for changes in your environment, such as new competitors coming into the market, or changes to government policy.
How to Use Risk Analysis
To carry out a risk analysis, follow these steps:
1. Identify Threats
The first step in Risk Analysis is to identify the existing and possible threats that you might face. These can come from many different sources. For instance, they could be:
Human – Illness, death, injury, or other loss of a key individual.
Operational – Disruption to supplies and operations, loss of access to essential assets, or failures in distribution.
Reputational – Loss of customer or employee confidence, or damage to market reputation.
Procedural – Failures of accountability, internal systems, or controls, or from fraud.
Project – Going over budget, taking too long on key tasks, or experiencing issues with product or service quality.
Financial – Business failure, stock market fluctuations, interest rate changes, or non-availability of funding.
Technical – Advances in technology, or from technical failure.
Natural – Weather, natural disasters, or disease.
Political – Changes in tax, public opinion, government policy, or foreign influence.
Structural – Dangerous chemicals, poor lighting, falling boxes, or any situation where staff, products, or technology can be harmed.
You can use a number of different approaches to carry out a thorough analysis:
Run through a list such as the one above to see if any of these threats are relevant.
Think about the systems, processes, or structures that you use, and analyze risks to any part of these. What vulnerabilities can you spot within them?
Ask others who might have different perspectives. If you're leading a team, ask for input from your people, and consult others in your organization, or those who have run similar projects.
Tools such as SWOT Analysis and Failure Mode and Effects Analysis can also help you uncover threats, while
Scenario Analysis helps you explore possible future threats.
2. Estimate Risk
Once you've identified the threats you're facing, you need to calculate out both the likelihood of these threats being realized, and their possible impact.
One way of doing this is to make your best estimate of the probability of the event occurring, and then to multiply this by the amount it will cost you to set things right if it happens. This gives you a value for the risk:
Risk Value = Probability of Event x Cost of Event
As a simple example, imagine that you've identified a risk that your rent may increase substantially.
You think that there's an 80 percent chance of this happening within the next year, because your landlord has recently increased rents for other businesses. If this happens, it will cost your business an extra $500,000 over the next year.
So the risk value of the rent increase is:
0.80 (Probability of Event) x $500,000 (Cost of Event) = $400,000 (Risk Value)
You can also use a Risk Impact/Probability Chart to assess risk. This will help you to identify which risks you need to focus on.
Tip:
Don't rush this step. Gather as much information as you can so that you can accurately estimate the probability of an event occurring, and the associated costs. Use past data as a guide if you don't have an accurate means of forecasting.
How to Manage Risk
Once you've identified the value of the risks you face, you can start to look at ways of managing them.
Tip:
Look for cost-effective approaches – it's rarely sensible to spend more on eliminating a risk than the cost of the event if it occurs. It may be better to accept the risk than it is to use excessive resources to eliminate it.
Be sensible in how you apply this, though, especially if ethics or personal safety are in question.
Avoid the Risk
In some cases, you may want to avoid the risk altogether. This could mean not getting involved in a business venture, passing on a project, or skipping a high-risk activity. This is a good option when taking the risk involves no advantage to your organization, or when the cost of addressing the effects is not worthwhile.
Remember that when you avoid a potential risk entirely, you might miss out on an opportunity. Conduct a "What If?" Analysis to explore your options when making your decision.
Share the Risk
You could also opt to share the risk – and the potential gain – with other people, teams, organizations, or third parties.
For instance, you share risk when you insure your office building and your stock with a third-party insurance company, or when you partner with another organization in a joint product development initiative.
Accept the Risk
Your last option is to accept the risk. This option is usually best when there's nothing you can do to prevent or mitigate a risk, when the potential loss is less than the cost of insuring against the risk, or when the potential gain is worth accepting the risk.
For example, you might accept the risk of a project launching late if the potential sales will still cover your costs.
Before you decide to accept a risk, conduct an Impact Analysis to see the full consequences of the risk. You may not be able to do anything about the risk itself, but you can likely come up with a
contingency plan
to cope with its consequences.
Controlling Risk
If you choose to accept the risk, there are a number of ways in which you can reduce its impact.
Business Experiments are an effective way to reduce risk. They involve rolling out the high-risk activity but on a small scale, and in a controlled way. You can use experiments to observe where problems occur, and to find ways to introduce preventative and detective actions before you introduce the activity on a larger scale.
Preventative action involves aiming to prevent a high-risk situation from happening. It includes health and safety training, firewall protection on corporate servers, and cross-training your team.
Detective action involves identifying the points in a process where something could go wrong, and then putting steps in place to fix the problems promptly if they occur. Detective actions include double-checking finance reports, conducting safety testing before a product is released, or installing sensors to detect product defects.
Plan-Do-Check-Act is a similar method of controlling the impact of a risky situation. Like a Business Experiment, it involves testing possible ways to reduce a risk. The tool's four phases guide you though an analysis of the situation, creating and testing a solution, checking how well this worked, and implementing the solution.
Key Points
Risk Analysis is a proven way of identifying and assessing factors that could negatively affect the success of a business or project. It allows you to examine the risks that you or your organization face, and helps you decide whether or not to move forward with a decision.
You do a Risk Analysis by identify threats, and estimating the likelihood of those threats being realized.
Once you've worked out the value of the risks you face, you can start looking at ways to manage them effectively. This may include choosing to avoid the risk, sharing it, or accepting it while reducing its impact.
It's essential that you're thorough when you're working through your Risk Analysis, and that you're aware of all of the possible impacts of the risks revealed. This includes being mindful of costs, ethics, and people's safety.
Mark this article as completed on your Personal Learning Plan
Did you find this article helpful?
Click to vote no
No
Click to vote yes
Yes
Thank you for your vote!
Thank you for your vote.
Please take a moment to tell us why you didn't find this article helpful.
Where to go from here: Next article Next Solve and Decide Learning Stream article
View print friendly version
Ask questions, or share your experience
What members say... Dianna wrote That's great! Thanks for your comments and tips- always appreciated!
Dianna July 5, 2013 rtab wrote Hi Dianna
We do have a similar framework at work for managing project risk. It is a very useful tool.
Cheers
rtab July 4, 2013 Dianna wrote Hi rtab,
Do you ever use the Risk Impact/Probability Chart? http://www.mindtools.com/community/pages/article/newPPM_78.php it's another extension tool that helps prioritize risk and then you can deal with the most probable and develop contingencies for the top ones.
Dianna July 4, 2013 rtab wrote Hi
Risk management is an important activity for all organisations and at any stage of the business cycle. This is a great tool.
My opinion is that this tool can be further extended by identifying what will trigger these risks to become issues and also by calculating the residual risk. This is where the impact and likelihood is re-assessed after applying the mitigating actions. I think this will allow decision to be made as to whether the risk is acceptable even after the mitigating actions are in place.
cheers
rtab July 3, 2013 James wrote Hi Everyone
We’ve given this popular article a review, and the updated version is now at
http://www.mindtools.com/community/pages/article/newTMC_07.php
Discuss the article by replying to this post!
Thanks
James June 19, 2013 James wrote Hi everyone
Just letting your know that we’ve just published a new video for this topic.
Click here to watch the video:
http://www.mindtools.com/community/pages/main/videos.php#risk-analysis
James June 30, 2011 bigk wrote Hi James
There are many uses in the guidance, it could also be used in personal risk assessment or to help decide planning, direction and action.
When used with cost and impact for decisions, it can give information about the risk in a task or project and also give information about the bigger picture risk or plan.
Bigk June 12, 2010
The Futures Wheel
3:20 AM |If you've ever needed to explore the full impact of a proposed change, you'll know how hard it can be to identify all possible outcomes.
In situations like these, many people panic, and list the first consequences that they can think of, resulting in a list that's shallow, incomplete, and tricky to analyze.
This is where the Futures Wheel can help. This visual tool gives you a structured way of brainstorming the direct and indirect consequences of a decision, event, or trend.
About the Tool
The Futures Wheel (see figure 1, below) was created by Jerome Glenn in 1972. Glenn has since become a recognized expert and speaker on Future Studies.
Figure 1 – The Futures Wheel
(Click here to view diagram full size.)
Glenn originally created the Futures Wheel to identify the potential consequences of trends and events, but you can also use it in decision making (to choose between options) and in change management (to identify the consequences of change). The tool is especially useful during the brainstorming stage of Impact Analysis .
How to Use the Tool
Step 1: Identify the Change
Write the change that you need to consider in the center of a piece of paper, or on a flipchart. This could be an event, trend, problem, or possible solution.
Step 2: Identify Direct, First-Order Consequences
Now, brainstorm possible direct consequences of that change. Write each consequence in a circle, and connect it from the central idea with an arrow. These are "first-order" consequences.
Step 3: Identify Indirect, Second-Order Consequences
You now need to brainstorm all the possible "second-order" consequences of each of the first-order (direct) consequences that you wrote down in Step 2, and add them to your diagram in the same way.
Then, repeat this by identifying the third-order consequences, fourth-order consequences, and so on.
Tip 1:
You may find it useful to color-code each "level" of the wheel, as we have in Figure 1, above. This makes it easier to prioritize and analyze consequences once you've completed your brainstorming.
Tip 2:
Remember that consequences are not necessarily negative.
Step 4: Analyze Implications
Once you've completed all of the levels of the Futures Wheel, you'll have a clear picture of the possible direct and indirect consequences resulting from the change. List these.
Step 5: Identify Actions
Where the possible consequences that you've identified are negative, think about how you'll manage them(our article on Risk Analysis gives some useful pointers). Where consequences are positive, think about what you'll do to take full advantage of them.
Futures Wheel Example
Judith's departmental budget is going to be cut by 20 percent in six weeks. She gets her managers together, and completes a Futures Wheel (see figure 2) to identify all of the possible consequences.
Figure 2 – Judith's Futures Wheel
(Click here to view diagram full size.)
Judith can now see that cutting staff will have a significant impact on her team. If she's going to work around her budget shortfall, she knows that she'll need to try every other option first. Trimming staff will be a last resort.
She can also see that low motivation and low productivity could be indirect consequences of this budget cut. So she needs to be ready to rebuild team morale, and to help people be more productive. She may also find it hard to increase sales volumes, so she needs to manage expectations accordingly.
There are also some positive consequences from the budget cut – there will be more opportunities for sharing skills and for on-the-job training in the team.
Key Points
The Futures Wheel is a simple, practical tool that helps you brainstorm the direct and indirect consequences of a decision, event, or trend.
To use the Futures Wheel, first identify what's changing. Then, enter each possible direct consequence of that change in a circle, and connect it from the central circle with an arrow.
Then, repeat this by identifying the second-order consequences, third-order consequences, fourth-order consequences, and so on.
Once you're finished, you'll have a visual map that lays out all of the implications of the problem or event, allowing you to manage the situation appropriately.
Read more…
In situations like these, many people panic, and list the first consequences that they can think of, resulting in a list that's shallow, incomplete, and tricky to analyze.
This is where the Futures Wheel can help. This visual tool gives you a structured way of brainstorming the direct and indirect consequences of a decision, event, or trend.
About the Tool
The Futures Wheel (see figure 1, below) was created by Jerome Glenn in 1972. Glenn has since become a recognized expert and speaker on Future Studies.
Figure 1 – The Futures Wheel
(Click here to view diagram full size.)
Glenn originally created the Futures Wheel to identify the potential consequences of trends and events, but you can also use it in decision making (to choose between options) and in change management (to identify the consequences of change). The tool is especially useful during the brainstorming stage of Impact Analysis .
How to Use the Tool
Step 1: Identify the Change
Write the change that you need to consider in the center of a piece of paper, or on a flipchart. This could be an event, trend, problem, or possible solution.
Step 2: Identify Direct, First-Order Consequences
Now, brainstorm possible direct consequences of that change. Write each consequence in a circle, and connect it from the central idea with an arrow. These are "first-order" consequences.
Step 3: Identify Indirect, Second-Order Consequences
You now need to brainstorm all the possible "second-order" consequences of each of the first-order (direct) consequences that you wrote down in Step 2, and add them to your diagram in the same way.
Then, repeat this by identifying the third-order consequences, fourth-order consequences, and so on.
Tip 1:
You may find it useful to color-code each "level" of the wheel, as we have in Figure 1, above. This makes it easier to prioritize and analyze consequences once you've completed your brainstorming.
Tip 2:
Remember that consequences are not necessarily negative.
Step 4: Analyze Implications
Once you've completed all of the levels of the Futures Wheel, you'll have a clear picture of the possible direct and indirect consequences resulting from the change. List these.
Step 5: Identify Actions
Where the possible consequences that you've identified are negative, think about how you'll manage them(our article on Risk Analysis gives some useful pointers). Where consequences are positive, think about what you'll do to take full advantage of them.
Futures Wheel Example
Judith's departmental budget is going to be cut by 20 percent in six weeks. She gets her managers together, and completes a Futures Wheel (see figure 2) to identify all of the possible consequences.
Figure 2 – Judith's Futures Wheel
(Click here to view diagram full size.)
Judith can now see that cutting staff will have a significant impact on her team. If she's going to work around her budget shortfall, she knows that she'll need to try every other option first. Trimming staff will be a last resort.
She can also see that low motivation and low productivity could be indirect consequences of this budget cut. So she needs to be ready to rebuild team morale, and to help people be more productive. She may also find it hard to increase sales volumes, so she needs to manage expectations accordingly.
There are also some positive consequences from the budget cut – there will be more opportunities for sharing skills and for on-the-job training in the team.
Key Points
The Futures Wheel is a simple, practical tool that helps you brainstorm the direct and indirect consequences of a decision, event, or trend.
To use the Futures Wheel, first identify what's changing. Then, enter each possible direct consequence of that change in a circle, and connect it from the central circle with an arrow.
Then, repeat this by identifying the second-order consequences, third-order consequences, fourth-order consequences, and so on.
Once you're finished, you'll have a visual map that lays out all of the implications of the problem or event, allowing you to manage the situation appropriately.
The Quantitative Strategic Planning Matrix (QSPM)
3:18 AM |Organizations spend a lot of time and effort on strategy formulation.
Often, there are several different approaches or strategies that the organization could follow.
But how do you decide which option is best?
Do you rely on intuition, or take a more objective approach?
Not surprisingly, you need to base your decision on facts, not gut feelings. But how do you do this, particularly when the effects of different strategies can be so different?
The Quantitative Strategic Planning Matrix (QSPM) helps you address this question. It gives you a systematic approach
for evaluating alternate strategies, and helps you decide which strategy is best suited to your organization. The tool was developed by Fred R. David, and was first published in the Long Range Planning Journal in 1986.
Understanding the Matrix
QSPM is based on three primary inputs:
The critical success factors of your business unit.
The relative importance of each of these critical success factors.
How you rate a particular strategy by each success factor.
These inputs are used to evaluate the relative attractiveness of different strategies. This relative attractiveness is expressed in terms of a number, the "Sum Total Attractiveness Score". The higher this score is, the more attractive the strategy is.
Follow the step-by-step guide below for constructing a QSPM. Start by printing our
free worksheet , and use it to compute your answer.
Step 1: List the Critical Success Factors
Make a comprehensive list of the critical success factors that apply to your business unit. These can be divided into two groups: internal factors and external factors. Internal factors can relate to your company's inherent strengths and weaknesses,
whereas external factors can relate to the opportunities and threats in the market environment.
Internal factors could includemaintenance of sufficient production capacity; a strong flow of new technologies from R&D; efficient treasury management; and so on. Examples of external success factors include the rapid adaptation to new government policies; effective competitive analysis; and quick understanding of the implications of demographic trends.
At this stage it's important that you try to generate a comprehensive list of the most important critical success factors. This helps to ensure that the key issues are addressed in the comparative analysis process.
Now use this list to fill the first column of your matrix. Make sure that each critical success factor is listed under the appropriate internal or external category.
Tip:
QSPM uses Critical Success Factors as the basis of analysis. This can be a good starting point for an existing organization. However, these will not yet exist for a start-up organization, and approaches like use of core competences may be more appropriate for some organizations. Challenge the criteria you're using to make sure that you're using appropriate ones.
Step 2: Assign Weights
Assign a weight to each of these critical success factors, depending on how important it is to the success of your work unit.
The higher the importance, the higher weight it will carry. The sum of all weights attached to internal factors should equal 1.0,
as should the sum of factors attached to external factors.
Note down the weight you have assigned to each factor in the second column, adjacent to the name of that factor.
Tip 1:
Giving internal and external factors the same weight in the decision can seem arbitrary. Decide for yourself whether this is appropriate.
Tip 2:
If you’re struggling to assign weights, techniques like Paired Comparison Analysis can help.
Step 3: List the Strategies
Now record the different strategies and approaches that you want to compare as column headings in the top row of your QSPM. The best part about QSPM is that you can compare as many strategies you like simultaneously.
Step 4: Assign Attractiveness Scores
For each strategy, work your way through the rows of your QSPM, assessing the attractiveness of the strategy as it affects each critical success factor. Score each CSF on a scale of 1 – 4, where the strategy is:
1 = Not attractive at all
2 = Slightly attractive
3 = Attractive
4 = Very attractive
Record this score in the Attractiveness Score (AS) column. This score represents how attractive the strategy is when looked at from the perspective of the listed critical success factor.
If a strategy does not impact one or more of the Critical Success factors, then no AS is assigned for that factor for any strategy. In this situation simply put a dash instead of a score for all the strategies.
Tip:
QSPM uses the 1 – 4 scale above. You may prefer to rank using a different scale, for example -4 to +4, where -4
applies to a strategic approach that seriously harms progress towards a Critical Success Factor.
Step 5: Calculate the Weighted Attractiveness Scores
For each Attractiveness Score/Weight combination on your QSPM table, calculate the Weighted Attractiveness Score (WAS) by
multiplying the weight by the AS you have assigned for that factor.
Step 6: Sum the Total Attractiveness Scores
Sum all the WASs for each column and arrive at the Sum Total Attractiveness Score for each strategy. Record it in the bottom
row. This represents the desirability of that particular strategy.
Example
Company A is a small but a growing business and is looking to expand. Based on external and internal factors it has come up with two mutually exclusive strategies:
Expand using franchises.
Expand the current facility.
It has drafted this QPSM to identify which is the better option.
A QSPM for New and Growing Business
Alternative Strategies
Expand through franchises
Expand current facility
Key External Factors
Weight
AS
WAS
AS
WAS
Opportunities
1. Taking full advantage of "first mover advantage".
0.10
4
0.40
2
0.20
2. Taking advantage of projected market growth of 30% per annum.
0.20
4
0.80
2
0.40
3. Building awareness of product category.
0.10
4
0.40
2
0.20
4. Tapping a new customer base.
0.25
4
1.00
1
0.25
Threats
1. Minimizing sharing of profit with
"middle-men"
0.15
1
0.15
4
0.60
2. Possible IP Infringement by franchisees
0.10
1
0.10
4
0.40
3. Minimizing entry of new competitors into market
0.10
–
–
–
–
Total
1.00
Key Internal Factors
Weight
AS
WAS
AS
WAS
Strengths
1. Developing highly experienced staff
0.10
2
0.20
4
0.40
2. Building R&D strength in product development
0.10
–
–
–
–
3. Refining an enhancing our new IT system
0.10
2
0.20
4
0.40
4. Building a strong management team
0.15
3
0.45
4
0.60
Weaknesses
1. Enhancing our limited ability to borrow capital
0.25
4
1.00
2
0.50
2. Improving weak customer feedback mechanisms
0.10
3
0.30
2
0.20
3. Increasing limited manpower
0.20
4
0.80
1
0.20
Total
1.00
Sum Total Attractiveness
Score
5.80
4.35
Looking at the Sum Total Attractiveness Scores on the QSPM, the better option is to expand using franchises.
Tip 1:
Many business decisions are made using financial models that take into account investment and expected outcomes, with options offering the greatest Return on Investment being chosen as the way forward.
While this is correct from one point of view, it excludes non-financial factors from the decision-making process. For example, it can cause the business to lose strategic focus, as the company follows financially attractive projects that may go against the long-term interest of the organization.
This is where it can be useful to bring a technique like QSPM into the decision-making process, to act as a "sanity check" on decisions made.
Tip 2:
If you're considering using this approach, also take a look at Grid Analysis , which does a similar thing in a more streamlined way.
Key Points
QSPM is a useful analytical tool that helps you determine the relative attractiveness of different strategies.
It asks you to identify the important external and internal critical success factors for your business unit, and then helps you assess these strategies in the light of these critical success factors. This effect is evaluated in numerical terms. The strategy that scores the highest is usually your best choice.
Download Worksheet
Read more…
Often, there are several different approaches or strategies that the organization could follow.
But how do you decide which option is best?
Do you rely on intuition, or take a more objective approach?
Not surprisingly, you need to base your decision on facts, not gut feelings. But how do you do this, particularly when the effects of different strategies can be so different?
The Quantitative Strategic Planning Matrix (QSPM) helps you address this question. It gives you a systematic approach
for evaluating alternate strategies, and helps you decide which strategy is best suited to your organization. The tool was developed by Fred R. David, and was first published in the Long Range Planning Journal in 1986.
Understanding the Matrix
QSPM is based on three primary inputs:
The critical success factors of your business unit.
The relative importance of each of these critical success factors.
How you rate a particular strategy by each success factor.
These inputs are used to evaluate the relative attractiveness of different strategies. This relative attractiveness is expressed in terms of a number, the "Sum Total Attractiveness Score". The higher this score is, the more attractive the strategy is.
Follow the step-by-step guide below for constructing a QSPM. Start by printing our
free worksheet , and use it to compute your answer.
Step 1: List the Critical Success Factors
Make a comprehensive list of the critical success factors that apply to your business unit. These can be divided into two groups: internal factors and external factors. Internal factors can relate to your company's inherent strengths and weaknesses,
whereas external factors can relate to the opportunities and threats in the market environment.
Internal factors could includemaintenance of sufficient production capacity; a strong flow of new technologies from R&D; efficient treasury management; and so on. Examples of external success factors include the rapid adaptation to new government policies; effective competitive analysis; and quick understanding of the implications of demographic trends.
At this stage it's important that you try to generate a comprehensive list of the most important critical success factors. This helps to ensure that the key issues are addressed in the comparative analysis process.
Now use this list to fill the first column of your matrix. Make sure that each critical success factor is listed under the appropriate internal or external category.
Tip:
QSPM uses Critical Success Factors as the basis of analysis. This can be a good starting point for an existing organization. However, these will not yet exist for a start-up organization, and approaches like use of core competences may be more appropriate for some organizations. Challenge the criteria you're using to make sure that you're using appropriate ones.
Step 2: Assign Weights
Assign a weight to each of these critical success factors, depending on how important it is to the success of your work unit.
The higher the importance, the higher weight it will carry. The sum of all weights attached to internal factors should equal 1.0,
as should the sum of factors attached to external factors.
Note down the weight you have assigned to each factor in the second column, adjacent to the name of that factor.
Tip 1:
Giving internal and external factors the same weight in the decision can seem arbitrary. Decide for yourself whether this is appropriate.
Tip 2:
If you’re struggling to assign weights, techniques like Paired Comparison Analysis can help.
Step 3: List the Strategies
Now record the different strategies and approaches that you want to compare as column headings in the top row of your QSPM. The best part about QSPM is that you can compare as many strategies you like simultaneously.
Step 4: Assign Attractiveness Scores
For each strategy, work your way through the rows of your QSPM, assessing the attractiveness of the strategy as it affects each critical success factor. Score each CSF on a scale of 1 – 4, where the strategy is:
1 = Not attractive at all
2 = Slightly attractive
3 = Attractive
4 = Very attractive
Record this score in the Attractiveness Score (AS) column. This score represents how attractive the strategy is when looked at from the perspective of the listed critical success factor.
If a strategy does not impact one or more of the Critical Success factors, then no AS is assigned for that factor for any strategy. In this situation simply put a dash instead of a score for all the strategies.
Tip:
QSPM uses the 1 – 4 scale above. You may prefer to rank using a different scale, for example -4 to +4, where -4
applies to a strategic approach that seriously harms progress towards a Critical Success Factor.
Step 5: Calculate the Weighted Attractiveness Scores
For each Attractiveness Score/Weight combination on your QSPM table, calculate the Weighted Attractiveness Score (WAS) by
multiplying the weight by the AS you have assigned for that factor.
Step 6: Sum the Total Attractiveness Scores
Sum all the WASs for each column and arrive at the Sum Total Attractiveness Score for each strategy. Record it in the bottom
row. This represents the desirability of that particular strategy.
Example
Company A is a small but a growing business and is looking to expand. Based on external and internal factors it has come up with two mutually exclusive strategies:
Expand using franchises.
Expand the current facility.
It has drafted this QPSM to identify which is the better option.
A QSPM for New and Growing Business
Alternative Strategies
Expand through franchises
Expand current facility
Key External Factors
Weight
AS
WAS
AS
WAS
Opportunities
1. Taking full advantage of "first mover advantage".
0.10
4
0.40
2
0.20
2. Taking advantage of projected market growth of 30% per annum.
0.20
4
0.80
2
0.40
3. Building awareness of product category.
0.10
4
0.40
2
0.20
4. Tapping a new customer base.
0.25
4
1.00
1
0.25
Threats
1. Minimizing sharing of profit with
"middle-men"
0.15
1
0.15
4
0.60
2. Possible IP Infringement by franchisees
0.10
1
0.10
4
0.40
3. Minimizing entry of new competitors into market
0.10
–
–
–
–
Total
1.00
Key Internal Factors
Weight
AS
WAS
AS
WAS
Strengths
1. Developing highly experienced staff
0.10
2
0.20
4
0.40
2. Building R&D strength in product development
0.10
–
–
–
–
3. Refining an enhancing our new IT system
0.10
2
0.20
4
0.40
4. Building a strong management team
0.15
3
0.45
4
0.60
Weaknesses
1. Enhancing our limited ability to borrow capital
0.25
4
1.00
2
0.50
2. Improving weak customer feedback mechanisms
0.10
3
0.30
2
0.20
3. Increasing limited manpower
0.20
4
0.80
1
0.20
Total
1.00
Sum Total Attractiveness
Score
5.80
4.35
Looking at the Sum Total Attractiveness Scores on the QSPM, the better option is to expand using franchises.
Tip 1:
Many business decisions are made using financial models that take into account investment and expected outcomes, with options offering the greatest Return on Investment being chosen as the way forward.
While this is correct from one point of view, it excludes non-financial factors from the decision-making process. For example, it can cause the business to lose strategic focus, as the company follows financially attractive projects that may go against the long-term interest of the organization.
This is where it can be useful to bring a technique like QSPM into the decision-making process, to act as a "sanity check" on decisions made.
Tip 2:
If you're considering using this approach, also take a look at Grid Analysis , which does a similar thing in a more streamlined way.
Key Points
QSPM is a useful analytical tool that helps you determine the relative attractiveness of different strategies.
It asks you to identify the important external and internal critical success factors for your business unit, and then helps you assess these strategies in the light of these critical success factors. This effect is evaluated in numerical terms. The strategy that scores the highest is usually your best choice.
Download Worksheet
Decision Trees
3:16 AM |Decision Trees are excellent tools for helping
you to choose between several courses of action. They provide a
highly effective structure within which you can lay out options and
investigate the possible outcomes of choosing those options. They
also help you to form a balanced picture of the risks and rewards
associated with each possible course of action.
Drawing a Decision Tree
You start a Decision Tree with a decision that you need to make.
Draw a small square to represent this towards the left of a large
piece of paper.
From this box draw out lines towards the right for each possible
solution, and write that solution along the line. Keep the lines
apart as far as possible so that you can expand your thoughts.
At the end of each line, consider the results. If the result of
taking that decision is uncertain, draw a small circle. If the
result is another decision that you need to make, draw another
square. Squares represent decisions, and circles represent uncertain
outcomes. Write the decision or factor above the square or circle.
If you have completed the solution at the end of the line, just
leave it blank.
Starting from the new decision squares on your diagram, draw out
lines representing the options that you could select. From the
circles draw lines representing possible outcomes. Again make a
brief note on the line saying what it means. Keep on doing this
until you have drawn out as many of the possible outcomes and
decisions as you can see leading on from the original decisions.
An example of the sort of thing you will end up with is shown in Figure 1:
Once you have done this, review your tree diagram. Challenge each
square and circle to see if there are any solutions or outcomes you
have not considered. If there are, draw them in. If necessary,
redraft your tree if parts of it are too congested or untidy. You
should now have a good understanding of the range of possible
outcomes of your decisions.
Evaluating Your Decision Tree
Now you are ready to evaluate the decision tree. This is where you
can work out which option has the greatest worth to you. Start by
assigning a cash value or score to each possible outcome. Estimate
how much you think it would be worth to you if that outcome came
about.
Next look at each circle (representing an uncertainty point) and
estimate the probability of each outcome. If you use percentages,
the total must come to 100% at each circle. If you use fractions,
these must add up to 1. If you have data on past events you may be
able to make rigorous estimates of the probabilities. Otherwise
write down your best guess.
This will give you a tree like the one shown in Figure 2:
Calculating Tree Values
Once you have worked out the value of the outcomes, and have
assessed the probability of the outcomes of uncertainty, it is time
to start calculating the values that will help you make your
decision.
Start on the right hand side of the decision tree, and work back
towards the left. As you complete a set of calculations on a node
(decision square or uncertainty circle), all you need to do is to
record the result. You can ignore all the calculations that lead to
that result from then on.
Calculating The Value of Uncertain Outcome Nodes
Where you are calculating the value of uncertain outcomes (circles
on the diagram), do this by multiplying the value of the outcomes by
their probability. The total for that node of the tree is the total
of these values.
In the example in Figure 2, the value for "new product, thorough development" is:
0.4 (probability good outcome) x $1,000,000 (value) =
$400,000
0.4 (probability moderate outcome) x $50,000 (value) =
$20,000
0.2 (probability poor outcome) x $2,000 (value) =
$400
TOTAL
$420,400
Figure 3 shows the calculation of uncertain outcome nodes:
Note that the values calculated for each node are shown in the
boxes.
Calculating the Value of Decision Nodes
When you are evaluating a decision node, write down the cost of each
option along each decision line. Then subtract the cost from the
outcome value that you have already calculated. This will give you a
value that represents the benefit of that decision.
Note that amounts already spent do not count for this analysis – these are 'sunk costs' and (despite emotional counter-arguments) should not be factored into the decision.
When you have calculated these decision benefits, choose the option that has the largest benefit, and take that as the decision made. This is the value of that decision node.
Figure 4 shows this calculation of decision nodes in our example:
In this example, the benefit we previously calculated for 'new
product, thorough development' was $420,400. We estimate the future
cost of this approach as $150,000. This gives a net benefit of
$270,400.
The net benefit of 'new product, rapid development' was $31,400. On
this branch we therefore choose the most valuable option, 'new
product, thorough development', and allocate this value to the
decision node.
Result
By applying this technique we can see that the best option is to
develop a new product. It is worth much more to us to take our time
and get the product right, than to rush the product to market. It is
better just to improve our existing products than to botch a new
product, even though it costs us less.
Key Points
Decision trees provide an effective method of Decision Making because they:
Clearly lay out the problem so that all options can be challenged.
Allow us to analyze fully the possible consequences of a decision.
Provide a framework to quantify the values of outcomes and the probabilities of achieving them.
Help us to make the best decisions on the basis of existing information and best guesses.
As with all Decision Making methods, decision tree analysis should be used in conjunction with common sense – decision trees are just one important part of your Decision Making tool kit.
Read more…
you to choose between several courses of action. They provide a
highly effective structure within which you can lay out options and
investigate the possible outcomes of choosing those options. They
also help you to form a balanced picture of the risks and rewards
associated with each possible course of action.
Drawing a Decision Tree
You start a Decision Tree with a decision that you need to make.
Draw a small square to represent this towards the left of a large
piece of paper.
From this box draw out lines towards the right for each possible
solution, and write that solution along the line. Keep the lines
apart as far as possible so that you can expand your thoughts.
At the end of each line, consider the results. If the result of
taking that decision is uncertain, draw a small circle. If the
result is another decision that you need to make, draw another
square. Squares represent decisions, and circles represent uncertain
outcomes. Write the decision or factor above the square or circle.
If you have completed the solution at the end of the line, just
leave it blank.
Starting from the new decision squares on your diagram, draw out
lines representing the options that you could select. From the
circles draw lines representing possible outcomes. Again make a
brief note on the line saying what it means. Keep on doing this
until you have drawn out as many of the possible outcomes and
decisions as you can see leading on from the original decisions.
An example of the sort of thing you will end up with is shown in Figure 1:
Once you have done this, review your tree diagram. Challenge each
square and circle to see if there are any solutions or outcomes you
have not considered. If there are, draw them in. If necessary,
redraft your tree if parts of it are too congested or untidy. You
should now have a good understanding of the range of possible
outcomes of your decisions.
Evaluating Your Decision Tree
Now you are ready to evaluate the decision tree. This is where you
can work out which option has the greatest worth to you. Start by
assigning a cash value or score to each possible outcome. Estimate
how much you think it would be worth to you if that outcome came
about.
Next look at each circle (representing an uncertainty point) and
estimate the probability of each outcome. If you use percentages,
the total must come to 100% at each circle. If you use fractions,
these must add up to 1. If you have data on past events you may be
able to make rigorous estimates of the probabilities. Otherwise
write down your best guess.
This will give you a tree like the one shown in Figure 2:
Calculating Tree Values
Once you have worked out the value of the outcomes, and have
assessed the probability of the outcomes of uncertainty, it is time
to start calculating the values that will help you make your
decision.
Start on the right hand side of the decision tree, and work back
towards the left. As you complete a set of calculations on a node
(decision square or uncertainty circle), all you need to do is to
record the result. You can ignore all the calculations that lead to
that result from then on.
Calculating The Value of Uncertain Outcome Nodes
Where you are calculating the value of uncertain outcomes (circles
on the diagram), do this by multiplying the value of the outcomes by
their probability. The total for that node of the tree is the total
of these values.
In the example in Figure 2, the value for "new product, thorough development" is:
0.4 (probability good outcome) x $1,000,000 (value) =
$400,000
0.4 (probability moderate outcome) x $50,000 (value) =
$20,000
0.2 (probability poor outcome) x $2,000 (value) =
$400
TOTAL
$420,400
Figure 3 shows the calculation of uncertain outcome nodes:
Note that the values calculated for each node are shown in the
boxes.
Calculating the Value of Decision Nodes
When you are evaluating a decision node, write down the cost of each
option along each decision line. Then subtract the cost from the
outcome value that you have already calculated. This will give you a
value that represents the benefit of that decision.
Note that amounts already spent do not count for this analysis – these are 'sunk costs' and (despite emotional counter-arguments) should not be factored into the decision.
When you have calculated these decision benefits, choose the option that has the largest benefit, and take that as the decision made. This is the value of that decision node.
Figure 4 shows this calculation of decision nodes in our example:
In this example, the benefit we previously calculated for 'new
product, thorough development' was $420,400. We estimate the future
cost of this approach as $150,000. This gives a net benefit of
$270,400.
The net benefit of 'new product, rapid development' was $31,400. On
this branch we therefore choose the most valuable option, 'new
product, thorough development', and allocate this value to the
decision node.
Result
By applying this technique we can see that the best option is to
develop a new product. It is worth much more to us to take our time
and get the product right, than to rush the product to market. It is
better just to improve our existing products than to botch a new
product, even though it costs us less.
Key Points
Decision trees provide an effective method of Decision Making because they:
Clearly lay out the problem so that all options can be challenged.
Allow us to analyze fully the possible consequences of a decision.
Provide a framework to quantify the values of outcomes and the probabilities of achieving them.
Help us to make the best decisions on the basis of existing information and best guesses.
As with all Decision Making methods, decision tree analysis should be used in conjunction with common sense – decision trees are just one important part of your Decision Making tool kit.
Pareto Analysis
3:14 AM |Imagine that you've just stepped into a new role as head of department. Unsurprisingly, you've inherited a whole host of problems that need your attention.
Ideally, you want to focus your attention on fixing the most important problems. But how do you decide which problems you need to deal with first? And are some problems caused by the same underlying issue?
Pareto Analysis is a simple technique for prioritizing possible changes by identifying the problems that will be resolved by making these changes. By using this approach, you can prioritize the individual changes that will most improve the situation.
Pareto Analysis uses the Pareto Principle – also known as the "80/20 Rule" – which is the idea that 20 percent of causes generate 80 percent of results. With this tool, we're trying to find the 20 percent of work that will generate 80 percent of the results that doing all of the work would deliver.
Note:
The figures 80 and 20 are illustrative – the Pareto Principle illustrates the lack of symmetry that often appears between work put in and results achieved. For example, 13 percent of work could generate 87 percent of returns. Or 70 percent of problems could be resolved by dealing with 30 percent of the causes.
How to Use the Tool
Step 1: Identify and List Problems
Firstly, write a list of all of the problems that you need to resolve. Where possible, talk to clients and team members to get their input, and draw on surveys, helpdesk logs and suchlike, where these are available.
Step 2: Identify the Root Cause of Each Problem
For each problem, identify its fundamental cause. (Techniques such as Brainstorming , the 5 Whys , Cause and Effect Analysis , and Root Cause Analysis will help with this.)
Step 3: Score Problems
Now you need to score each problem. The scoring method you use depends on the sort of problem you're trying to solve.
For example, if you're trying to improve profits, you might score problems on the basis of how much they are costing you. Alternatively, if you're trying to improve customer satisfaction, you might score them on the basis of the number of complaints eliminated by solving the problem.
Step 4: Group Problems Together By Root Cause
Next, group problems together by cause. For example, if three of your problems are caused by lack of staff, put these in the same group.
Step 5: Add up the Scores for Each Group
You can now add up the scores for each cause group. The group with the top score is your highest priority, and the group with the lowest score is your lowest priority.
Step 6: Take Action
Now you need to deal with the causes of your problems, dealing with your top-priority problem, or group of problems, first.
Keep in mind that low scoring problems may not even be worth bothering with - solving these problems may cost you more than the solutions are worth.
Note:
While this approach is great for identifying the most important root cause to deal with, it doesn't take into account the cost of doing so. Where costs are significant, you'll need to use techniques such as
Cost/Benefit Analysis , and use IRRs and NPVs to determine which changes you should implement.
Pareto Analysis Example
Jack has taken over a failing service center, with a host of problems that need resolving. His objective is to increase overall customer satisfaction.
He decides to score each problem by the number of complaints that the center has received for each one. (In the table below, the second column shows the problems he has listed in step 1 above, the third column shows the underlying causes identified in step 2, and the fourth column shows the number of complaints about each column identified in step 3.)
#
Problem (Step 1)
Cause (Step 2)
Score
(Step 3)
1
Phones aren't answered quickly enough.
Too few service center staff.
15
2
Staff seem distracted and under pressure.
Too few service center staff.
6
3
Engineers don't appear to be well organized. They need second visits to bring extra parts.
Poor organization and preparation.
4
4
Engineers don't know what time they'll arrive. This means that customers may have to be in all day for an engineer to visit.
Poor organization and preparation.
2
5
Service center staff don't always seem to know what they're doing.
Lack of training.
30
6
When engineers visit, the customer finds that the problem could have been solved over the phone.
Lack of training.
21
Jack then groups problems together (steps 4 and 5). He scores each group by the number of complaints, and orders the list as follows:
Lack of training (items 5 and 6) – 51 complaints.
Too few service center staff (items 1 and 42) – 21 complaints.
Poor organization and preparation (items 3 and 4) – 6 complaints.
As you can see from figure 1 above, Jack will get the biggest benefits by providing staff with more training. Once this is done, it may be worth looking at increasing the number of staff in the call center. It's possible, however, that this won't be necessary: the number of complaints may decline, and training should help people to be more productive.
By carrying out a Pareto Analysis, Jack is able to focus on training as an issue, rather than spreading his effort over training, taking on new staff members, and possibly installing a new computer system to help engineers be more prepared.
Key Points
Pareto Analysis is a simple technique for prioritizing problem-solving work so that the first piece of work you do resolved the greatest number of problems. It's based on the Pareto Principle (also known as the 80/20 Rule) – the idea that 80 percent of problems may be caused by as few as 20 percent of causes.
To use Pareto Analysis, identify and list problems and their causes. Then score each problem and group them together by their cause. Then add up the score for each group. Finally, work on finding a solution to the cause of the problems in group with the highest score.
Pareto Analysis not only shows you the most important problem to solve, it also gives you a score showing how severe the problem is.
Read more…
Ideally, you want to focus your attention on fixing the most important problems. But how do you decide which problems you need to deal with first? And are some problems caused by the same underlying issue?
Pareto Analysis is a simple technique for prioritizing possible changes by identifying the problems that will be resolved by making these changes. By using this approach, you can prioritize the individual changes that will most improve the situation.
Pareto Analysis uses the Pareto Principle – also known as the "80/20 Rule" – which is the idea that 20 percent of causes generate 80 percent of results. With this tool, we're trying to find the 20 percent of work that will generate 80 percent of the results that doing all of the work would deliver.
Note:
The figures 80 and 20 are illustrative – the Pareto Principle illustrates the lack of symmetry that often appears between work put in and results achieved. For example, 13 percent of work could generate 87 percent of returns. Or 70 percent of problems could be resolved by dealing with 30 percent of the causes.
How to Use the Tool
Step 1: Identify and List Problems
Firstly, write a list of all of the problems that you need to resolve. Where possible, talk to clients and team members to get their input, and draw on surveys, helpdesk logs and suchlike, where these are available.
Step 2: Identify the Root Cause of Each Problem
For each problem, identify its fundamental cause. (Techniques such as Brainstorming , the 5 Whys , Cause and Effect Analysis , and Root Cause Analysis will help with this.)
Step 3: Score Problems
Now you need to score each problem. The scoring method you use depends on the sort of problem you're trying to solve.
For example, if you're trying to improve profits, you might score problems on the basis of how much they are costing you. Alternatively, if you're trying to improve customer satisfaction, you might score them on the basis of the number of complaints eliminated by solving the problem.
Step 4: Group Problems Together By Root Cause
Next, group problems together by cause. For example, if three of your problems are caused by lack of staff, put these in the same group.
Step 5: Add up the Scores for Each Group
You can now add up the scores for each cause group. The group with the top score is your highest priority, and the group with the lowest score is your lowest priority.
Step 6: Take Action
Now you need to deal with the causes of your problems, dealing with your top-priority problem, or group of problems, first.
Keep in mind that low scoring problems may not even be worth bothering with - solving these problems may cost you more than the solutions are worth.
Note:
While this approach is great for identifying the most important root cause to deal with, it doesn't take into account the cost of doing so. Where costs are significant, you'll need to use techniques such as
Cost/Benefit Analysis , and use IRRs and NPVs to determine which changes you should implement.
Pareto Analysis Example
Jack has taken over a failing service center, with a host of problems that need resolving. His objective is to increase overall customer satisfaction.
He decides to score each problem by the number of complaints that the center has received for each one. (In the table below, the second column shows the problems he has listed in step 1 above, the third column shows the underlying causes identified in step 2, and the fourth column shows the number of complaints about each column identified in step 3.)
#
Problem (Step 1)
Cause (Step 2)
Score
(Step 3)
1
Phones aren't answered quickly enough.
Too few service center staff.
15
2
Staff seem distracted and under pressure.
Too few service center staff.
6
3
Engineers don't appear to be well organized. They need second visits to bring extra parts.
Poor organization and preparation.
4
4
Engineers don't know what time they'll arrive. This means that customers may have to be in all day for an engineer to visit.
Poor organization and preparation.
2
5
Service center staff don't always seem to know what they're doing.
Lack of training.
30
6
When engineers visit, the customer finds that the problem could have been solved over the phone.
Lack of training.
21
Jack then groups problems together (steps 4 and 5). He scores each group by the number of complaints, and orders the list as follows:
Lack of training (items 5 and 6) – 51 complaints.
Too few service center staff (items 1 and 42) – 21 complaints.
Poor organization and preparation (items 3 and 4) – 6 complaints.
As you can see from figure 1 above, Jack will get the biggest benefits by providing staff with more training. Once this is done, it may be worth looking at increasing the number of staff in the call center. It's possible, however, that this won't be necessary: the number of complaints may decline, and training should help people to be more productive.
By carrying out a Pareto Analysis, Jack is able to focus on training as an issue, rather than spreading his effort over training, taking on new staff members, and possibly installing a new computer system to help engineers be more prepared.
Key Points
Pareto Analysis is a simple technique for prioritizing problem-solving work so that the first piece of work you do resolved the greatest number of problems. It's based on the Pareto Principle (also known as the 80/20 Rule) – the idea that 80 percent of problems may be caused by as few as 20 percent of causes.
To use Pareto Analysis, identify and list problems and their causes. Then score each problem and group them together by their cause. Then add up the score for each group. Finally, work on finding a solution to the cause of the problems in group with the highest score.
Pareto Analysis not only shows you the most important problem to solve, it also gives you a score showing how severe the problem is.
Conjoint Analysis
3:11 AM |What's the best way to introduce a new product, or change an existing one?
You could just move forward boldly with a new idea and keep your fingers crossed that it works.
Or you could reduce risk by doing market research – before you go through all the trouble of creating something customers don't want or don't like.
Getting a product 'right' involves a lot of variables.
The most obvious feature is functionality – how it works. However, other things also play a role in the final purchase decision – such as packaging, promotion, materials, and even where a product is manufactured.
For example, people buy cars to get from point A to point B. The type of car they buy is based on many things, including fuel consumption, styling, reliability, and color. While any of these product attributes may be the primary selling feature, people make decisions by considering all the attributes together.
Getting all of these features in the right combination is pretty difficult if you just rely on guesswork. So, how can you evaluate your goods and services by considering their attributes all together, or jointly? 'Conjoint Analysis' accomplishes exactly that.
What is Conjoint Analysis?
First and foremost, conjoint analysis is a tool that measures buyer preferences. Using statistical analysis, it establishes the impact on the buying decision of one combination of product attributes compared with other combinations. By doing this, you get an understanding of consumer preferences that's much deeper than simply asking consumers to rate individual product attributes.
For instance, a typical preferences survey tells a restaurant that customers rank their priorities as service, price, location, and then cleanliness. So the restaurant makes improvements to service and price, but sales don't increase significantly. They wonder what went wrong… until they try a conjoint analysis, which tells them that the combination of service and location actually ranks higher than the combination of service and price.
Conjoint analysis helps you truly understand consumer trade-offs. What are customers willing to trade if they can't get the perfect set of attributes? To get the warranty they want, will they pay a higher purchase price? To get the 10% discount they want, will they buy a package of eight, rather than a package of six? To get the performance they want, will they settle for fewer color options?
Conducting a Conjoint Analysis
Conjoint analysis determines the utility (usefulness or desirability) values that consumers attach to different levels of a product's attributes. By showing potential consumers different product offer combinations, and asking them to rank the various offers, you can identify the most appealing combination of attributes. From there, you can make a business decision using parameters like estimated market share and profit potential.
To illustrate this approach, we'll use an example of a consumer goods company developing a new glass cleaner.
Step One: Identify product attributes to be studied.
For the glass cleaner, five product attributes were chosen:
Format.
Price.
Scent.
Ingredients.
Promotion.
Step Two: Choose options and/or value levels for the attributes.
Our glass cleaner manufacturer thinks that the following options are likely to be the most popular alternatives.
Formats
Spray liquid, Foam, Wipes
Prices
$2.49, $2.69, $2.99
Scents
Unscented, Floral, Lemon
Ingredients
Organic, Chemical
Promotions
Buy 2 get 1 free, $1.00 off coupon
Step Three: Determine which product attribute combinations to evaluate.
It's usually not reasonable to ask respondents to rank every possible combination of attributes. In our example, there are 108 (3 x 3 x 3 x 2 x 2) different combinations to consider!
The glass cleaner manufacturer chooses 12 combinations that it wants people to rank.
Design
Format
Price
Scent
Ingredients
Promotion
A
Spray
$2.49
Unscented
Organic
Buy 2, get 1 free
B
Foam
$2.49
Lemon
Chemical
Buy 2, get 1 free
C
Wipes
$2.49
Unscented
Organic
Buy 2, get 1 free
D
Spray
$2.69
Floral
Chemical
$1.00 off
E
Foam
$2.69
Lemon
Organic
Buy 2, get 1 free
F
Wipes
$2.69
Unscented
Organic
$1.00 off
G
Spray
$2.99
Lemon
Organic
$1.00 off
H
Foam
$2.99
Floral
Chemical
Buy 2, get 1 free
I
Wipes
$2.99
Lemon
Organic
$1.00 off
J
Spray
$2.49
Lemon
Chemical
Buy 2, get 1 free
K
Foam
$2.69
Unscented
Chemical
$1.00 off
L
Wipes
$2.69
Lemon
Chemical
Buy 2, get 1 free
Step Four: Determine how to present the product attribute combinations.
You may use a simple grid or chart to present to respondents. Other options include describing the combination in paragraph form, using pictures, and even creating prototypes that people can examine.
Here is how one respondent ranked the 12 combinations.
Design
Format
Price
Scent
Ingredients
Promotion
Rank
A
Spray
$2.49
Unscented
Organic
Buy 2, get 1 free
6
B
Foam
$2.49
Lemon
Chemical
Buy 2, get 1 free
11
C
Wipes
$2.49
Unscented
Organic
Buy 2, get 1 free
3
D
Spray
$2.69
Floral
Chemical
$1.00 off
9
E
Foam
$2.69
Lemon
Organic
Buy 2, get 1 free
7
F
Wipes
$2.69
Unscented
Organic
$1.00 off
1
G
Spray
$2.99
Lemon
Organic
$1.00 off
5
H
Foam
$2.99
Floral
Chemical
Buy 2, get 1 free
12
I
Wipes
$2.99
Lemon
Organic
$1.00 off
2
J
Spray
$2.49
Lemon
Chemical
Buy 2, get 1 free
10
K
Foam
$2.69
Unscented
Chemical
$1.00 off
8
L
Wipes
$2.69
Lemon
Chemical
Buy 2, get 1 free
4
Step Five: Analyze and interpret the data.
Using statistical programs, you can analyze data, and determine the utility of each attribute. Utility is a measure between 1 and 0 (the higher the utility, the stronger the consumer preference).
If you look at the sample data (without using statistical analysis), the top four choices are all wipes, and the top three choices are organic. This consumer is even willing to pay top price for organic wipes.
Design
Format
Price
Scent
Ingredients
Promotion
Rank
F
Wipes
$2.69
Unscented
Organic
$1.00 off
1
I
Wipes
$2.99
Lemon
Organic
$1.00 off
2
C
Wipes
$2.49
Unscented
Organic
Buy 2, get 1 free
3
L
Wipes
$2.69
Lemon
Chemical
Buy 2, get 1 free
4
The lowest-ranked combinations (not including the chemical wipes) used chemical agents, regardless of the other factors.
A full conjoint analysis reveals all of the utilities, and helps you determine the attributes that are most important to your customers.
When you collect preference data from a large sample of target consumers, you can estimate the market share that any specific offer is likely to achieve (given any assumptions about competitive response). Your company, however, may not choose to offer the most attractive combination due to cost considerations. If the most attractive option is also the most expensive to produce, you may use the results of conjoint analysis to determine the most profitable option as well.
Key Points
Knowing the relative value that consumers place on various product attributes is essential to launching a new product or service successfully. Conjoint analysis is a powerful tool to get this information quickly, and it has become one of the most popular concept development and testing tools used. Conjoint analysis has three basic parts: a designed experiment, the statistical analysis of the resulting data, and the business decisions based on the analysis. Organizations can use the information gained from this to make better, and less risky, decisions than they would have made by using individual factors alone to determine the best combination of product attributes.
Read more…
You could just move forward boldly with a new idea and keep your fingers crossed that it works.
Or you could reduce risk by doing market research – before you go through all the trouble of creating something customers don't want or don't like.
Getting a product 'right' involves a lot of variables.
The most obvious feature is functionality – how it works. However, other things also play a role in the final purchase decision – such as packaging, promotion, materials, and even where a product is manufactured.
For example, people buy cars to get from point A to point B. The type of car they buy is based on many things, including fuel consumption, styling, reliability, and color. While any of these product attributes may be the primary selling feature, people make decisions by considering all the attributes together.
Getting all of these features in the right combination is pretty difficult if you just rely on guesswork. So, how can you evaluate your goods and services by considering their attributes all together, or jointly? 'Conjoint Analysis' accomplishes exactly that.
What is Conjoint Analysis?
First and foremost, conjoint analysis is a tool that measures buyer preferences. Using statistical analysis, it establishes the impact on the buying decision of one combination of product attributes compared with other combinations. By doing this, you get an understanding of consumer preferences that's much deeper than simply asking consumers to rate individual product attributes.
For instance, a typical preferences survey tells a restaurant that customers rank their priorities as service, price, location, and then cleanliness. So the restaurant makes improvements to service and price, but sales don't increase significantly. They wonder what went wrong… until they try a conjoint analysis, which tells them that the combination of service and location actually ranks higher than the combination of service and price.
Conjoint analysis helps you truly understand consumer trade-offs. What are customers willing to trade if they can't get the perfect set of attributes? To get the warranty they want, will they pay a higher purchase price? To get the 10% discount they want, will they buy a package of eight, rather than a package of six? To get the performance they want, will they settle for fewer color options?
Conducting a Conjoint Analysis
Conjoint analysis determines the utility (usefulness or desirability) values that consumers attach to different levels of a product's attributes. By showing potential consumers different product offer combinations, and asking them to rank the various offers, you can identify the most appealing combination of attributes. From there, you can make a business decision using parameters like estimated market share and profit potential.
To illustrate this approach, we'll use an example of a consumer goods company developing a new glass cleaner.
Step One: Identify product attributes to be studied.
For the glass cleaner, five product attributes were chosen:
Format.
Price.
Scent.
Ingredients.
Promotion.
Step Two: Choose options and/or value levels for the attributes.
Our glass cleaner manufacturer thinks that the following options are likely to be the most popular alternatives.
Formats
Spray liquid, Foam, Wipes
Prices
$2.49, $2.69, $2.99
Scents
Unscented, Floral, Lemon
Ingredients
Organic, Chemical
Promotions
Buy 2 get 1 free, $1.00 off coupon
Step Three: Determine which product attribute combinations to evaluate.
It's usually not reasonable to ask respondents to rank every possible combination of attributes. In our example, there are 108 (3 x 3 x 3 x 2 x 2) different combinations to consider!
The glass cleaner manufacturer chooses 12 combinations that it wants people to rank.
Design
Format
Price
Scent
Ingredients
Promotion
A
Spray
$2.49
Unscented
Organic
Buy 2, get 1 free
B
Foam
$2.49
Lemon
Chemical
Buy 2, get 1 free
C
Wipes
$2.49
Unscented
Organic
Buy 2, get 1 free
D
Spray
$2.69
Floral
Chemical
$1.00 off
E
Foam
$2.69
Lemon
Organic
Buy 2, get 1 free
F
Wipes
$2.69
Unscented
Organic
$1.00 off
G
Spray
$2.99
Lemon
Organic
$1.00 off
H
Foam
$2.99
Floral
Chemical
Buy 2, get 1 free
I
Wipes
$2.99
Lemon
Organic
$1.00 off
J
Spray
$2.49
Lemon
Chemical
Buy 2, get 1 free
K
Foam
$2.69
Unscented
Chemical
$1.00 off
L
Wipes
$2.69
Lemon
Chemical
Buy 2, get 1 free
Step Four: Determine how to present the product attribute combinations.
You may use a simple grid or chart to present to respondents. Other options include describing the combination in paragraph form, using pictures, and even creating prototypes that people can examine.
Here is how one respondent ranked the 12 combinations.
Design
Format
Price
Scent
Ingredients
Promotion
Rank
A
Spray
$2.49
Unscented
Organic
Buy 2, get 1 free
6
B
Foam
$2.49
Lemon
Chemical
Buy 2, get 1 free
11
C
Wipes
$2.49
Unscented
Organic
Buy 2, get 1 free
3
D
Spray
$2.69
Floral
Chemical
$1.00 off
9
E
Foam
$2.69
Lemon
Organic
Buy 2, get 1 free
7
F
Wipes
$2.69
Unscented
Organic
$1.00 off
1
G
Spray
$2.99
Lemon
Organic
$1.00 off
5
H
Foam
$2.99
Floral
Chemical
Buy 2, get 1 free
12
I
Wipes
$2.99
Lemon
Organic
$1.00 off
2
J
Spray
$2.49
Lemon
Chemical
Buy 2, get 1 free
10
K
Foam
$2.69
Unscented
Chemical
$1.00 off
8
L
Wipes
$2.69
Lemon
Chemical
Buy 2, get 1 free
4
Step Five: Analyze and interpret the data.
Using statistical programs, you can analyze data, and determine the utility of each attribute. Utility is a measure between 1 and 0 (the higher the utility, the stronger the consumer preference).
If you look at the sample data (without using statistical analysis), the top four choices are all wipes, and the top three choices are organic. This consumer is even willing to pay top price for organic wipes.
Design
Format
Price
Scent
Ingredients
Promotion
Rank
F
Wipes
$2.69
Unscented
Organic
$1.00 off
1
I
Wipes
$2.99
Lemon
Organic
$1.00 off
2
C
Wipes
$2.49
Unscented
Organic
Buy 2, get 1 free
3
L
Wipes
$2.69
Lemon
Chemical
Buy 2, get 1 free
4
The lowest-ranked combinations (not including the chemical wipes) used chemical agents, regardless of the other factors.
A full conjoint analysis reveals all of the utilities, and helps you determine the attributes that are most important to your customers.
When you collect preference data from a large sample of target consumers, you can estimate the market share that any specific offer is likely to achieve (given any assumptions about competitive response). Your company, however, may not choose to offer the most attractive combination due to cost considerations. If the most attractive option is also the most expensive to produce, you may use the results of conjoint analysis to determine the most profitable option as well.
Key Points
Knowing the relative value that consumers place on various product attributes is essential to launching a new product or service successfully. Conjoint analysis is a powerful tool to get this information quickly, and it has become one of the most popular concept development and testing tools used. Conjoint analysis has three basic parts: a designed experiment, the statistical analysis of the resulting data, and the business decisions based on the analysis. Organizations can use the information gained from this to make better, and less risky, decisions than they would have made by using individual factors alone to determine the best combination of product attributes.
The Analytic Hierarchy Process (AHP)
3:09 AM |How do you make a choice in a complex, subjective
situation with more than a few realistic options?
You could sit and think over each option, hoping for divine inspiration
– but you may end up more confused than when you started.
You could leave it to fate – draw straws or pick a number.
Of
course, this won't win you the Decision Maker of the Year award!
An all-too-common strategy is to simply wait out the problem,
doing nothing proactively, until a solution is somehow chosen
for you by circumstances.
None of these approaches are very effective. What you need is
a systematic, organized way to evaluate your choices and figure
out which one offers the best solution to your problem.
As rational beings, we usually like to quantify variables and
options to make objective decisions. However, the problem is that
not all criteria are easy to measure.
So what do you do when you're faced with a decision that needs
significant personal judgment and subjective evaluation? How do
you avoid getting caught in the "thinking over" stage?
And how can you be more objective?
Combining Qualitative and Quantitative
To address this problem, Thomas Saaty created
the Analytic Hierarchy Process (AHP) in the 1970s. This system
is useful because it combines two approaches – the "black
and white" of mathematics, and the subjectivity and intuitiveness
of psychology – to evaluate information and make decisions that
are easy to defend.
Let's look at an (admittedly slightly trivial) example. If you
want to determine the best route to work in the morning, and travel
time is your deciding factor, the decision making process is very
straightforward and simple. You would use each alternative route
for a week, time the commute, and choose the one that's fastest
on average.
If, however, you carpool with other riders, and you have to consider
everyone's priorities, the decision becomes much more complex.
Larry is concerned about his personal safety, because one route
goes through a dangerous part of town. Joanne wants to factor
in a stop at a drive-through coffee shop, so that everyone can
get coffee. Richard points out that Java Jolt is better than Cuppa Jo.
There are several branches of each in the city, with both types
accessible from all routes, although at different distances.
Now you've got tangible and intangible, and quantitative and qualitative,
factors to think about. And you have to consider the different
perspectives and priorities of the various people.
AHP can combine these different types of factors and turn them
into a standardized numerical scale. You can use this to make
your choice objectively, while including all the decision criteria.
AHP Snapshot
Here's a quick overview of the Analytic Hierarchy
Process.
Build your "hierarchy"
Define your goal or objective.
Identify the choices you're considering.
Outline the major factors you'll use to evaluate each option.
Identify criteria (and any subcriteria of these) that you need to consider for each of these major factors. Link these to the major factors (see figure 1 below for an example of this.)
Continue to build a hierarchy of decision criteria until all factors are identified and linked.
Establish your priorities
Using paired comparison , determine your criteria preferences (perhaps A is a little more preferred than B, B is much more preferred than C, and so on).
Rate these preferences from 1-9.
Repeat this for each level in your hierarchy. (The example below will make this clearer.)
Synthesize, or combine, the ratings
Calculate weighted criteria scores that combine all of the ranking data.
Compare the alternatives
Using those combined scores, calculate a final score for each alternative.
Tip 1:
If you're familiar with Paired Comparison Analysis , then this approach might sound familiar. The power of AHP is that it uses paired comparison to determine the relative weights of various criteria, and then it transfers them across each level of criteria to calculate overall weightings. From this you can calculate an objective score for each alternative.
Tip 2:
This is a complicated approach, and one that needs careful
thought and calculation. Only use it if Paired Comparison
Analysis isn't giving you the answer you want, or where
the problem to be solved is complex and significant, and
involves many different subjective factors.
Let's work through our example to determine
which route – A, B, or C – is best for the group of carpoolers.
Step 1: Build Your Hierarchy
Define your goal at the top of the hierarchy:
Find the best route to work.
Identify your first level of evaluation criteria:
Commute time.
Safety.
Drive-through access (to coffee).
Decide if there are second level criteria,
or subcriteria of these, related to any of your Level 1 criteria:
Drive-through access has two subcriteria:
Java Jolt.
Cuppa Jo.
Under each bottom level criterion, write down the alternatives you're considering:
Route A.
Route B.
Route C.
Figure 1: An Example Hierarchy
Step 2: Establish Your Priorities
Have each decision maker rate the relative importance
or preference for each criterion, at each level. Use a paired
comparison approach.
Set up a matrix to compare each criterion to the others. We have three Level 1 criteria, therefore we need a 3x3 matrix.
Criterion
Commute Time
Safety
Drive-through Access
Commute Time
Safety
Drive-through Access
Rank the importance of each criterion relative
to the others, using the scale below.
Relative Importance
Value
Equal importance/quality
1
Somewhat more important/better
3
Definitely more important/better
5
Much more important/better
7
Very much more important/better
9
Note 1:
The numbers 2, 4, 6, and 8 are half way positions
between the values above.
Note 2:
The scale assumes that the ROW (first)
criterion being ranked is of equal or greater importance
than the COLUMN (second) criterion. If you have a pairing
where the row criterion is less important than the column,
use the reciprocal value (1/3, 1/5, 1/7, or 1/9).
Compare the criteria in the columns to the
criteria in the rows.
Commute time is [much MORE important] than safety
Commute time is [somewhat MORE important] than drive-through access
Drive-through access is [extremely MORE important] than safety
Safety is [extremely LESS important] than drive-through access
Safety is [much LESS important] than commute time
Drive-through access is [somewhat LESS important] than commute time
Criterion
Commute Time
Safety
Drive-through Access
Commute Time
1
7
3
Safety
1/7
1
1/9
Drive-through Access
1/3
9
1
Step 3: Calculate the Ratings
Now you have to calculate the overall weighting for each criterion. This is called a "priority vector" (PV) (don't worry about this term – it's not very helpful.)
Add each column in your ratings matrix.
Criterion
Commute Time
Safety
Drive-through Access
Commute Time
1
7
3
Safety
0.14
1
0.11
Drive-through Access
0.33
9
1
TOTAL
1.47
17
4.11
Divide each entry by the total of its column.
Examples:
Commute time ÷ Commute time total = 1/1.47
Safety ÷ Commute time total = 0.14/1.47
Criterion
Commute Time
Safety
Drive-through Access
Commute Time
0.68
0.41
0.73
Safety
0.10
0.06
0.03
Drive-through Access
0.22
0.53
0.24
Notice how the columns add up to approximately 1.0. This is because the weights have now been standardized.
Because the ratings are subjective, we sometimes see inconsistencies. To "smooth" these out, calculate the average of each row. This is the final weight (priority vector) for each criterion.
Criterion
Commute Time
Safety
Drive-through Access
Priority Vector
Commute Time
0.68
0.41
0.73
0.61
Safety
0.10
0.06
0.03
0.06
Drive-through Access
0.22
0.53
0.24
0.33
This weighted score suggests the following:
Commute time represents about 61% of the final decision
Nearness to a coffee drive-through represents about 33% of the decision
Safety represents about 6% of the decision
Level 2 Criteria – If you had no subcriteria,
you could move onto the next step and calculate final scores
for each alternative route. In our example, drive-through access
has another variable to consider – whether the coffee shop on
the route is Java Jolt or Cuppa Jo.
Following the same steps as the Level
1 criteria, start with a 2x2 matrix.
Then add the ratings. For our example,
we'll assume that Java Jolt is somewhat better (3) than
Cuppa Jo.
Brand
Java Jolt
Cuppa Jo
Java Jolt
1
3
Cuppa Jo
0.33
1
Calculate the overall weighting.
Add each column.
Brand
Java Jolt
Cuppa Jo
Java Jolt
1
3
Cuppa Jo
0.33
1
Total
1.33
4
Divide each entry by the column total. Then average each row.
Brand
Java Jolt
Cuppa Jo
Average/Priority Vector
Java Jolt
0.75
0.75
0.75
Cuppa Jo
0.25
0.25
0.25
Access to a Java Jolt
is three times more preferred than access to Cuppa Jo.
Step 4: Compare the Alternatives
Compare each alternative based on the lowest
level in your hierarchy of decision criteria. In our example
(see figure 1), the lowest-level criteria are as follows:
Commute time
Safety
Java Jolt
Cuppa Jo
Note:
The weighting for
drive-through access will be included as 33% of the final
decision. It will be split 75/25 between nearness to Java
Jolt or Cuppa Jo.
By using the lowest level of your hierarchy,
you ensure that all variations of all options are considered.
You can have as many levels of subcriteria
as you need to make a final decision. If Java Jolt and Cuppa
Jo were relatively equal in their preference (score of 3 or
less), then you could further break down the decision into taste,
price, and muffin selection. With each level, the total weight
always adds to about 1.0, and the overall weight is spread up
the hierarchy through each subsequent calculation.
Create a comparison matrix for the first
decision criterion you want to evaluate. We'll use commute time.
Commute Time
Route A
Route B
Route C
Route A
Route B
Route C
Then use the same 1-9 rating scale to determine
how each route compares to the others, based on that decision
criterion. We'll assume the following:
Route A is somewhat faster than Route
B.
Route A is very much faster than Route
C.
Route B is much faster than Route C.
Fill in the matrix, and calculate the priority
vector.
Commute
A
B
C
A
1
3
9
B
0.33
1
7
C
0.11
0.14
1
Total
1.44
4.14
17
Commute
A
B
C
Priority Vector
A
0.69
0.72
0.53
0.65
B
0.23
0.24
0.41
0.29
C
0.08
0.03
0.06
0.06
Repeat this comparison process for each
of the remaining decision criteria.
Which route is safer than the other?
How much closer to a Java Jolt is one route
than the other?
How much closer to a Cuppa Jo is one route
than the other?
Safety
A
B
C
A
1
0.14
0.14
B
7.00
1
0.2
C
7.00
5
1
Total
15
6.14
1.34
Safety
A
B
C
Priority Vector
A
0.07
0.02
0.11
0.07
B
0.47
0.16
0.15
0.26
C
0.47
0.81
0.74
0.68
Access to Java Jolt
A
B
C
A
1
4
7
B
0.25
1
3
C
0.14
0.33
1
Total
1.39
5.33
11
Access to Java Jolt
A
B
C
Priority Vector
A
0.72
0.75
0.64
0.70
B
0.18
0.19
0.27
0.21
C
0.10
0.06
0.09
0.09
Access to Cuppa Jo
A
B
C
A
1
1
0.11
B
1
1
0.2
C
9
5
1
Total
11
7
1.31
Access to Cuppa Jo
A
B
C
Priority Vector
A
0.09
0.14
0.08
0.11
B
0.09
0.14
0.15
0.13
C
0.82
0.71
0.76
0.77
Combine the overall weights, and determine
a value for each route. (See below for this.)
The value for each route is the weighted
sum of all rankings that are associated with it. The priority
values (PVs) for each criterion have been added to the hierarchy
below.
Figure 2: The Example Hierarchy Developed
Calculate Route A's final score:
Commute Time PV (0.61) x Route A's Commute PV (0.65) +
Safety PV (0.06 ) x Route A's Safety PV (0.07) +
Drive-through Access PV (0.33) x Java Jolt PV (0.75) x Route
A's JJ PV (0.7) +
Drive-through Access PV (0.33) x Cuppa Jo PV (0.25) x Route
A's CJ PV (0.11) +
= 0.40 + 0 + 0.17 + 0.01
= 0.58
Complete the calculations for Routes B and C.
Final Scores
Criterion
Route A
Route B
Route C
Commute Time
0.40
0.18
0.04
Safety
0.00
0.02
0.04
Java Jolt
0.17
0.05
0.02
Cuppa Jo
0.01
0.01
0.06
Total
0.58
0.26
0.16
Route A is the clear winner! You can interpret this to mean that Route A meets 58% of all the decision criteria considered. Route B meets only 26% of the criteria, and Route C meets 16%.
Key Points
The Analytic Hierarchy Process can help you
quantify the judgments you use in decision making. When problems
become complex, it's hard to justify and explain all the reasons
why one alternative is better, or more preferable, than another.
With AHP, you calculate weighted scores for each set of criteria
that you consider, and then you use those weights to calculate
a final score for each alternative. The result is an "apples to
apples," quantitative comparison of your choices. Whether you
use this method to make a final choice or as one of many tools
in your decision making process, the results can be remarkably
clear.
Read more…
situation with more than a few realistic options?
You could sit and think over each option, hoping for divine inspiration
– but you may end up more confused than when you started.
You could leave it to fate – draw straws or pick a number.
Of
course, this won't win you the Decision Maker of the Year award!
An all-too-common strategy is to simply wait out the problem,
doing nothing proactively, until a solution is somehow chosen
for you by circumstances.
None of these approaches are very effective. What you need is
a systematic, organized way to evaluate your choices and figure
out which one offers the best solution to your problem.
As rational beings, we usually like to quantify variables and
options to make objective decisions. However, the problem is that
not all criteria are easy to measure.
So what do you do when you're faced with a decision that needs
significant personal judgment and subjective evaluation? How do
you avoid getting caught in the "thinking over" stage?
And how can you be more objective?
Combining Qualitative and Quantitative
To address this problem, Thomas Saaty created
the Analytic Hierarchy Process (AHP) in the 1970s. This system
is useful because it combines two approaches – the "black
and white" of mathematics, and the subjectivity and intuitiveness
of psychology – to evaluate information and make decisions that
are easy to defend.
Let's look at an (admittedly slightly trivial) example. If you
want to determine the best route to work in the morning, and travel
time is your deciding factor, the decision making process is very
straightforward and simple. You would use each alternative route
for a week, time the commute, and choose the one that's fastest
on average.
If, however, you carpool with other riders, and you have to consider
everyone's priorities, the decision becomes much more complex.
Larry is concerned about his personal safety, because one route
goes through a dangerous part of town. Joanne wants to factor
in a stop at a drive-through coffee shop, so that everyone can
get coffee. Richard points out that Java Jolt is better than Cuppa Jo.
There are several branches of each in the city, with both types
accessible from all routes, although at different distances.
Now you've got tangible and intangible, and quantitative and qualitative,
factors to think about. And you have to consider the different
perspectives and priorities of the various people.
AHP can combine these different types of factors and turn them
into a standardized numerical scale. You can use this to make
your choice objectively, while including all the decision criteria.
AHP Snapshot
Here's a quick overview of the Analytic Hierarchy
Process.
Build your "hierarchy"
Define your goal or objective.
Identify the choices you're considering.
Outline the major factors you'll use to evaluate each option.
Identify criteria (and any subcriteria of these) that you need to consider for each of these major factors. Link these to the major factors (see figure 1 below for an example of this.)
Continue to build a hierarchy of decision criteria until all factors are identified and linked.
Establish your priorities
Using paired comparison , determine your criteria preferences (perhaps A is a little more preferred than B, B is much more preferred than C, and so on).
Rate these preferences from 1-9.
Repeat this for each level in your hierarchy. (The example below will make this clearer.)
Synthesize, or combine, the ratings
Calculate weighted criteria scores that combine all of the ranking data.
Compare the alternatives
Using those combined scores, calculate a final score for each alternative.
Tip 1:
If you're familiar with Paired Comparison Analysis , then this approach might sound familiar. The power of AHP is that it uses paired comparison to determine the relative weights of various criteria, and then it transfers them across each level of criteria to calculate overall weightings. From this you can calculate an objective score for each alternative.
Tip 2:
This is a complicated approach, and one that needs careful
thought and calculation. Only use it if Paired Comparison
Analysis isn't giving you the answer you want, or where
the problem to be solved is complex and significant, and
involves many different subjective factors.
Let's work through our example to determine
which route – A, B, or C – is best for the group of carpoolers.
Step 1: Build Your Hierarchy
Define your goal at the top of the hierarchy:
Find the best route to work.
Identify your first level of evaluation criteria:
Commute time.
Safety.
Drive-through access (to coffee).
Decide if there are second level criteria,
or subcriteria of these, related to any of your Level 1 criteria:
Drive-through access has two subcriteria:
Java Jolt.
Cuppa Jo.
Under each bottom level criterion, write down the alternatives you're considering:
Route A.
Route B.
Route C.
Figure 1: An Example Hierarchy
Step 2: Establish Your Priorities
Have each decision maker rate the relative importance
or preference for each criterion, at each level. Use a paired
comparison approach.
Set up a matrix to compare each criterion to the others. We have three Level 1 criteria, therefore we need a 3x3 matrix.
Criterion
Commute Time
Safety
Drive-through Access
Commute Time
Safety
Drive-through Access
Rank the importance of each criterion relative
to the others, using the scale below.
Relative Importance
Value
Equal importance/quality
1
Somewhat more important/better
3
Definitely more important/better
5
Much more important/better
7
Very much more important/better
9
Note 1:
The numbers 2, 4, 6, and 8 are half way positions
between the values above.
Note 2:
The scale assumes that the ROW (first)
criterion being ranked is of equal or greater importance
than the COLUMN (second) criterion. If you have a pairing
where the row criterion is less important than the column,
use the reciprocal value (1/3, 1/5, 1/7, or 1/9).
Compare the criteria in the columns to the
criteria in the rows.
Commute time is [much MORE important] than safety
Commute time is [somewhat MORE important] than drive-through access
Drive-through access is [extremely MORE important] than safety
Safety is [extremely LESS important] than drive-through access
Safety is [much LESS important] than commute time
Drive-through access is [somewhat LESS important] than commute time
Criterion
Commute Time
Safety
Drive-through Access
Commute Time
1
7
3
Safety
1/7
1
1/9
Drive-through Access
1/3
9
1
Step 3: Calculate the Ratings
Now you have to calculate the overall weighting for each criterion. This is called a "priority vector" (PV) (don't worry about this term – it's not very helpful.)
Add each column in your ratings matrix.
Criterion
Commute Time
Safety
Drive-through Access
Commute Time
1
7
3
Safety
0.14
1
0.11
Drive-through Access
0.33
9
1
TOTAL
1.47
17
4.11
Divide each entry by the total of its column.
Examples:
Commute time ÷ Commute time total = 1/1.47
Safety ÷ Commute time total = 0.14/1.47
Criterion
Commute Time
Safety
Drive-through Access
Commute Time
0.68
0.41
0.73
Safety
0.10
0.06
0.03
Drive-through Access
0.22
0.53
0.24
Notice how the columns add up to approximately 1.0. This is because the weights have now been standardized.
Because the ratings are subjective, we sometimes see inconsistencies. To "smooth" these out, calculate the average of each row. This is the final weight (priority vector) for each criterion.
Criterion
Commute Time
Safety
Drive-through Access
Priority Vector
Commute Time
0.68
0.41
0.73
0.61
Safety
0.10
0.06
0.03
0.06
Drive-through Access
0.22
0.53
0.24
0.33
This weighted score suggests the following:
Commute time represents about 61% of the final decision
Nearness to a coffee drive-through represents about 33% of the decision
Safety represents about 6% of the decision
Level 2 Criteria – If you had no subcriteria,
you could move onto the next step and calculate final scores
for each alternative route. In our example, drive-through access
has another variable to consider – whether the coffee shop on
the route is Java Jolt or Cuppa Jo.
Following the same steps as the Level
1 criteria, start with a 2x2 matrix.
Then add the ratings. For our example,
we'll assume that Java Jolt is somewhat better (3) than
Cuppa Jo.
Brand
Java Jolt
Cuppa Jo
Java Jolt
1
3
Cuppa Jo
0.33
1
Calculate the overall weighting.
Add each column.
Brand
Java Jolt
Cuppa Jo
Java Jolt
1
3
Cuppa Jo
0.33
1
Total
1.33
4
Divide each entry by the column total. Then average each row.
Brand
Java Jolt
Cuppa Jo
Average/Priority Vector
Java Jolt
0.75
0.75
0.75
Cuppa Jo
0.25
0.25
0.25
Access to a Java Jolt
is three times more preferred than access to Cuppa Jo.
Step 4: Compare the Alternatives
Compare each alternative based on the lowest
level in your hierarchy of decision criteria. In our example
(see figure 1), the lowest-level criteria are as follows:
Commute time
Safety
Java Jolt
Cuppa Jo
Note:
The weighting for
drive-through access will be included as 33% of the final
decision. It will be split 75/25 between nearness to Java
Jolt or Cuppa Jo.
By using the lowest level of your hierarchy,
you ensure that all variations of all options are considered.
You can have as many levels of subcriteria
as you need to make a final decision. If Java Jolt and Cuppa
Jo were relatively equal in their preference (score of 3 or
less), then you could further break down the decision into taste,
price, and muffin selection. With each level, the total weight
always adds to about 1.0, and the overall weight is spread up
the hierarchy through each subsequent calculation.
Create a comparison matrix for the first
decision criterion you want to evaluate. We'll use commute time.
Commute Time
Route A
Route B
Route C
Route A
Route B
Route C
Then use the same 1-9 rating scale to determine
how each route compares to the others, based on that decision
criterion. We'll assume the following:
Route A is somewhat faster than Route
B.
Route A is very much faster than Route
C.
Route B is much faster than Route C.
Fill in the matrix, and calculate the priority
vector.
Commute
A
B
C
A
1
3
9
B
0.33
1
7
C
0.11
0.14
1
Total
1.44
4.14
17
Commute
A
B
C
Priority Vector
A
0.69
0.72
0.53
0.65
B
0.23
0.24
0.41
0.29
C
0.08
0.03
0.06
0.06
Repeat this comparison process for each
of the remaining decision criteria.
Which route is safer than the other?
How much closer to a Java Jolt is one route
than the other?
How much closer to a Cuppa Jo is one route
than the other?
Safety
A
B
C
A
1
0.14
0.14
B
7.00
1
0.2
C
7.00
5
1
Total
15
6.14
1.34
Safety
A
B
C
Priority Vector
A
0.07
0.02
0.11
0.07
B
0.47
0.16
0.15
0.26
C
0.47
0.81
0.74
0.68
Access to Java Jolt
A
B
C
A
1
4
7
B
0.25
1
3
C
0.14
0.33
1
Total
1.39
5.33
11
Access to Java Jolt
A
B
C
Priority Vector
A
0.72
0.75
0.64
0.70
B
0.18
0.19
0.27
0.21
C
0.10
0.06
0.09
0.09
Access to Cuppa Jo
A
B
C
A
1
1
0.11
B
1
1
0.2
C
9
5
1
Total
11
7
1.31
Access to Cuppa Jo
A
B
C
Priority Vector
A
0.09
0.14
0.08
0.11
B
0.09
0.14
0.15
0.13
C
0.82
0.71
0.76
0.77
Combine the overall weights, and determine
a value for each route. (See below for this.)
The value for each route is the weighted
sum of all rankings that are associated with it. The priority
values (PVs) for each criterion have been added to the hierarchy
below.
Figure 2: The Example Hierarchy Developed
Calculate Route A's final score:
Commute Time PV (0.61) x Route A's Commute PV (0.65) +
Safety PV (0.06 ) x Route A's Safety PV (0.07) +
Drive-through Access PV (0.33) x Java Jolt PV (0.75) x Route
A's JJ PV (0.7) +
Drive-through Access PV (0.33) x Cuppa Jo PV (0.25) x Route
A's CJ PV (0.11) +
= 0.40 + 0 + 0.17 + 0.01
= 0.58
Complete the calculations for Routes B and C.
Final Scores
Criterion
Route A
Route B
Route C
Commute Time
0.40
0.18
0.04
Safety
0.00
0.02
0.04
Java Jolt
0.17
0.05
0.02
Cuppa Jo
0.01
0.01
0.06
Total
0.58
0.26
0.16
Route A is the clear winner! You can interpret this to mean that Route A meets 58% of all the decision criteria considered. Route B meets only 26% of the criteria, and Route C meets 16%.
Key Points
The Analytic Hierarchy Process can help you
quantify the judgments you use in decision making. When problems
become complex, it's hard to justify and explain all the reasons
why one alternative is better, or more preferable, than another.
With AHP, you calculate weighted scores for each set of criteria
that you consider, and then you use those weights to calculate
a final score for each alternative. The result is an "apples to
apples," quantitative comparison of your choices. Whether you
use this method to make a final choice or as one of many tools
in your decision making process, the results can be remarkably
clear.
Paired Comparison Analysis
3:03 AM |When you're choosing between many different options, how do you decide on the best way forward?
This is especially challenging if your choices are quite different from one another, if decision criteria are subjective, or if you don't have objective data to use for your decision.
Paired Comparison Analysis helps you to work out the relative importance of a number of different options – the classical case of "comparing apples with oranges."
In this article, we'll explore how you can use Paired Comparison Analysis to make decisions.
About the Tool
Paired Comparison Analysis (also known as Pairwise Comparison) helps you work out the importance of a number of options relative to one another.
This makes it easy to choose the most important problem to solve, or to pick the solution that will be most effective. It also helps you set priorities where there are conflicting demands on your resources.
The tool is particularly useful when you don't have objective data to use to make your decision. It's also an ideal tool to use to compare different, subjective options, for example, where you need to decide the relative importance of qualifications, skills, experience, and teamworking ability when hiring people for a new role.
Decisions like these are often much harder to make than, for example, comparing three similar IT systems, where Grid Analysis or some form of financial analysis can help you decide.
How to Use the Tool
To use the technique,
download our free worksheet , and then follow these six steps:
Make a list of all of the options that you want to compare. Assign each option a letter (A, B, C, D, and so on) and note this down.
Mark your options as both the row and column headings on the worksheet. This is so that you can compare options with one-another.
Note:
On the table, the cells where you will compare an option with itself are blocked out. The cells on the table where you would be duplicating a comparison are also blocked out. This ensures that you make each comparison only once.
Within each of the blank cells, compare the option in the row with the option in the column. Decide which of the two options is most important.
Write down the letter of the most important option in the cell. Then, score the difference in importance between the options, running from zero (no difference/same importance) to, say, three (major difference/one much more important than the other.)
Finally, consolidate the results by adding up the values for each of the options. You may want to convert these values into a percentage of the total score.
Use your common sense, and manually adjust the results if necessary.
Example
For example, a philanthropist is choosing between several different nonprofit organizations that are asking for funding. To maximize impact, she only wants to contribute to a few of these, and she has the following options:
An overseas development project.
A local educational project.
A bequest for her university.
Disaster relief.
First, she draws up the Paired Comparison Analysis table in Figure 1.
Figure 1 – Example Paired Comparison Analysis Table (not filled in):
A: Overseas Development
B: Local Educational
C: University
D: Disaster Relief
A: Overseas Development
B: Local Educational
C: University
D: Disaster Relief
Then she compares options, writes down the letter of the most important option, and scores their difference in importance to her. Figure 2 illustrates this step of the process.
Figure 2 – Example Paired Comparison Analysis Table (filled in):
A: Overseas Development
B: Local Educational
C: University
D: Disaster Relief
A: Overseas Development
A, 2
C, 1
A, 1
B: Local Educational
C, 1
B, 1
C: University
C, 2
D: Disaster Relief
Finally, she adds up the A, B, C, and D values and converts each into a percentage of the total. These calculations yield the following totals:
A = 3 (37.5 percent).
B = 1 (12.5 percent).
C = 4 (50 percent).
D = 0.
Here, she decides to make a bequest to her university (C) and to allocate some funding to overseas development (A).
Key Points
Paired Comparison Analysis is useful for weighing up the relative importance of different options. It's particularly helpful where priorities aren't clear, where the options are completely different, where evaluation criteria are subjective, or where they're competing in importance.
The tool provides a framework for comparing each option against all others, and helps to show the difference in importance between factors.
Download Worksheet
Read more…
This is especially challenging if your choices are quite different from one another, if decision criteria are subjective, or if you don't have objective data to use for your decision.
Paired Comparison Analysis helps you to work out the relative importance of a number of different options – the classical case of "comparing apples with oranges."
In this article, we'll explore how you can use Paired Comparison Analysis to make decisions.
About the Tool
Paired Comparison Analysis (also known as Pairwise Comparison) helps you work out the importance of a number of options relative to one another.
This makes it easy to choose the most important problem to solve, or to pick the solution that will be most effective. It also helps you set priorities where there are conflicting demands on your resources.
The tool is particularly useful when you don't have objective data to use to make your decision. It's also an ideal tool to use to compare different, subjective options, for example, where you need to decide the relative importance of qualifications, skills, experience, and teamworking ability when hiring people for a new role.
Decisions like these are often much harder to make than, for example, comparing three similar IT systems, where Grid Analysis or some form of financial analysis can help you decide.
How to Use the Tool
To use the technique,
download our free worksheet , and then follow these six steps:
Make a list of all of the options that you want to compare. Assign each option a letter (A, B, C, D, and so on) and note this down.
Mark your options as both the row and column headings on the worksheet. This is so that you can compare options with one-another.
Note:
On the table, the cells where you will compare an option with itself are blocked out. The cells on the table where you would be duplicating a comparison are also blocked out. This ensures that you make each comparison only once.
Within each of the blank cells, compare the option in the row with the option in the column. Decide which of the two options is most important.
Write down the letter of the most important option in the cell. Then, score the difference in importance between the options, running from zero (no difference/same importance) to, say, three (major difference/one much more important than the other.)
Finally, consolidate the results by adding up the values for each of the options. You may want to convert these values into a percentage of the total score.
Use your common sense, and manually adjust the results if necessary.
Example
For example, a philanthropist is choosing between several different nonprofit organizations that are asking for funding. To maximize impact, she only wants to contribute to a few of these, and she has the following options:
An overseas development project.
A local educational project.
A bequest for her university.
Disaster relief.
First, she draws up the Paired Comparison Analysis table in Figure 1.
Figure 1 – Example Paired Comparison Analysis Table (not filled in):
A: Overseas Development
B: Local Educational
C: University
D: Disaster Relief
A: Overseas Development
B: Local Educational
C: University
D: Disaster Relief
Then she compares options, writes down the letter of the most important option, and scores their difference in importance to her. Figure 2 illustrates this step of the process.
Figure 2 – Example Paired Comparison Analysis Table (filled in):
A: Overseas Development
B: Local Educational
C: University
D: Disaster Relief
A: Overseas Development
A, 2
C, 1
A, 1
B: Local Educational
C, 1
B, 1
C: University
C, 2
D: Disaster Relief
Finally, she adds up the A, B, C, and D values and converts each into a percentage of the total. These calculations yield the following totals:
A = 3 (37.5 percent).
B = 1 (12.5 percent).
C = 4 (50 percent).
D = 0.
Here, she decides to make a bequest to her university (C) and to allocate some funding to overseas development (A).
Key Points
Paired Comparison Analysis is useful for weighing up the relative importance of different options. It's particularly helpful where priorities aren't clear, where the options are completely different, where evaluation criteria are subjective, or where they're competing in importance.
The tool provides a framework for comparing each option against all others, and helps to show the difference in importance between factors.
Download Worksheet
Grid Analysis
3:01 AM |Imagine that your boss has put you in charge of taking on a new outsourced IT supplier. You've already identified several different suppliers, and you now need to decide which one to use.
You could decide to go with the low-cost option. But you don't want to make your decision on cost alone – factors such as contract length, underlying technology, and service levels need to be taken into consideration. So how can you make sure you make the best decision, while taking all of these different factors into account?
Grid Analysis is a useful technique to use for making a decision. It's particularly powerful where you have a number of good alternatives to choose from, and many different factors to take into account. This makes it a great technique to use in almost any important decision where there isn't a clear and obvious preferred option.
Being able to use Grid Analysis means that you can take decisions confidently and rationally, at a time when other people might be struggling to make a decision.
How to Use the Tool
Grid Analysis works by getting you to list your options as rows on a table, and the factors you need consider as columns. You then score each option/factor combination, weight this score by the relative importance of the factor, and add these scores up to give an overall score for each option.
While this sounds complex, this technique is actually quite easy to use. Here's a step-by-step guide with an example. Start by downloading our
free worksheet . Then work through these steps.
Step 1
List all of your options as the row labels on the table, and list the factors that you need to consider as the column headings. For example, if you were buying a new laptop computer, factors to consider might be cost, dimensions, and hard disk size.
Step 2
Next, work your way down the columns of your table, scoring each option for each of the factors in your decision. Score each option from 0 (poor) to 5 (very good). Note that you do not have to have a different score for each option – if none of them are good for a particular factor in your decision, then all options should score 0.
Step 3
The next step is to work out the relative importance of the factors in your decision. Show these as numbers from, say, 0 to 5, where 0 means that the factor is absolutely unimportant in the final decision, and 5 means that it is very important. (It's perfectly acceptable to have factors with the same importance.)
Tip:
These values may be obvious. If they are not, then use a technique such as Paired Comparison Analysis to estimate them.
Step 4
Now multiply each of your scores from step 2 by the values for relative importance of the factor that you calculated in step 3. This will give you weighted scores for each option/factor combination.
Step 5
Finally, add up these weighted scores for each of your options. The option that scores the highest wins!
Tip:
If your intuition tells you that the top scoring option isn’t the best one, then reflect on the scores and weightings that you’ve applied. This may be a sign that certain factors are more important to you than you initially thought.
Also, if an option scores very poorly for a factor, decide whether this rules it out altogether.
Example
A caterer needs to find a new supplier for his basic ingredients. He has four options.
Factors that he wants to consider are:
Cost.
Quality.
Location.
Reliability.
Payment options.
Firstly he draws up the table shown in Figure 1, and scores each option by how well it satisfies each factor:
Figure 1: Example Grid Analysis Showing Unweighted Assessment of How Each Supplier Satisfies Each Factor
Factors:
Cost
Quality
Location
Reliability
Payment Options
Total
Weights:
Supplier 1
1
0
0
1
3
Supplier 2
0
3
2
2
1
Supplier 3
2
2
1
3
0
Supplier 4
2
3
3
3
0
Next he decides the relative weights for each of the factors. He multiplies these by the scores already entered, and totals them. This is shown in Figure 2:
Figure 2: Example Grid Analysis Showing Weighted Assessment of How Each Supplier Satisfies Each Factor
Factors:
Cost
Quality
Location
Reliability
Payment Options
Total
Weights:
4
5
1
2
3
Supplier 1
4
0
0
2
9
15
Supplier 2
0
15
2
4
3
24
Supplier 3
8
10
1
6
0
25
Supplier 4
8
15
3
6
0
32
This makes it clear to the caterer that Supplier 4 is the best option, despite the lack of flexibility of its payment options.
Key Points
Grid Analysis helps you to decide between several options, where you need to take many different factors into account.
To use the tool, lay out your options as rows on a table. Set up the columns to show the factors you need to consider. Score each choice for each factor using numbers from 0 (poor) to 5 (very good), and then allocate weights to show the importance of each of these factors.
Multiply each score by the weight of the factor, to show its contribution to the overall selection. Finally add up the total scores for each option. The highest scoring option will be the best option.
Note:
Grid Analysis is the simplest form of Multiple Criteria Decision Analysis (MCDA), also known as Multiple Criteria Decision Aid or Multiple Criteria Decision Management (MCDM). Sophisticated MCDA can involve highly complex modelling of different potential scenarios, using advanced mathematics.
A lot of business decision making, however, is based on approximate or subjective data. Where this is the case, Grid Analysis may be all that’s needed.
Download Worksheet
Read more…
You could decide to go with the low-cost option. But you don't want to make your decision on cost alone – factors such as contract length, underlying technology, and service levels need to be taken into consideration. So how can you make sure you make the best decision, while taking all of these different factors into account?
Grid Analysis is a useful technique to use for making a decision. It's particularly powerful where you have a number of good alternatives to choose from, and many different factors to take into account. This makes it a great technique to use in almost any important decision where there isn't a clear and obvious preferred option.
Being able to use Grid Analysis means that you can take decisions confidently and rationally, at a time when other people might be struggling to make a decision.
How to Use the Tool
Grid Analysis works by getting you to list your options as rows on a table, and the factors you need consider as columns. You then score each option/factor combination, weight this score by the relative importance of the factor, and add these scores up to give an overall score for each option.
While this sounds complex, this technique is actually quite easy to use. Here's a step-by-step guide with an example. Start by downloading our
free worksheet . Then work through these steps.
Step 1
List all of your options as the row labels on the table, and list the factors that you need to consider as the column headings. For example, if you were buying a new laptop computer, factors to consider might be cost, dimensions, and hard disk size.
Step 2
Next, work your way down the columns of your table, scoring each option for each of the factors in your decision. Score each option from 0 (poor) to 5 (very good). Note that you do not have to have a different score for each option – if none of them are good for a particular factor in your decision, then all options should score 0.
Step 3
The next step is to work out the relative importance of the factors in your decision. Show these as numbers from, say, 0 to 5, where 0 means that the factor is absolutely unimportant in the final decision, and 5 means that it is very important. (It's perfectly acceptable to have factors with the same importance.)
Tip:
These values may be obvious. If they are not, then use a technique such as Paired Comparison Analysis to estimate them.
Step 4
Now multiply each of your scores from step 2 by the values for relative importance of the factor that you calculated in step 3. This will give you weighted scores for each option/factor combination.
Step 5
Finally, add up these weighted scores for each of your options. The option that scores the highest wins!
Tip:
If your intuition tells you that the top scoring option isn’t the best one, then reflect on the scores and weightings that you’ve applied. This may be a sign that certain factors are more important to you than you initially thought.
Also, if an option scores very poorly for a factor, decide whether this rules it out altogether.
Example
A caterer needs to find a new supplier for his basic ingredients. He has four options.
Factors that he wants to consider are:
Cost.
Quality.
Location.
Reliability.
Payment options.
Firstly he draws up the table shown in Figure 1, and scores each option by how well it satisfies each factor:
Figure 1: Example Grid Analysis Showing Unweighted Assessment of How Each Supplier Satisfies Each Factor
Factors:
Cost
Quality
Location
Reliability
Payment Options
Total
Weights:
Supplier 1
1
0
0
1
3
Supplier 2
0
3
2
2
1
Supplier 3
2
2
1
3
0
Supplier 4
2
3
3
3
0
Next he decides the relative weights for each of the factors. He multiplies these by the scores already entered, and totals them. This is shown in Figure 2:
Figure 2: Example Grid Analysis Showing Weighted Assessment of How Each Supplier Satisfies Each Factor
Factors:
Cost
Quality
Location
Reliability
Payment Options
Total
Weights:
4
5
1
2
3
Supplier 1
4
0
0
2
9
15
Supplier 2
0
15
2
4
3
24
Supplier 3
8
10
1
6
0
25
Supplier 4
8
15
3
6
0
32
This makes it clear to the caterer that Supplier 4 is the best option, despite the lack of flexibility of its payment options.
Key Points
Grid Analysis helps you to decide between several options, where you need to take many different factors into account.
To use the tool, lay out your options as rows on a table. Set up the columns to show the factors you need to consider. Score each choice for each factor using numbers from 0 (poor) to 5 (very good), and then allocate weights to show the importance of each of these factors.
Multiply each score by the weight of the factor, to show its contribution to the overall selection. Finally add up the total scores for each option. The highest scoring option will be the best option.
Note:
Grid Analysis is the simplest form of Multiple Criteria Decision Analysis (MCDA), also known as Multiple Criteria Decision Aid or Multiple Criteria Decision Management (MCDM). Sophisticated MCDA can involve highly complex modelling of different potential scenarios, using advanced mathematics.
A lot of business decision making, however, is based on approximate or subjective data. Where this is the case, Grid Analysis may be all that’s needed.
Download Worksheet
The Kepner-Tregoe Matrix
2:58 AM |No matter what position you hold, from the board
room to the mailroom, you make decisions every day.
And the end
result in business is directly linked to the quality of the
decisions made at each point along the way.
So not surprisingly,
decision-making is a universally important competence in business.
Some decisions clearly have a greater impact on the business than
others, but the underlying skill is the same: The difference is in
the scope and depth of the process you go through to reach your
decision.
One reason why decision-making can be so problematic is that the
most critical decisions tend to have to be made in the least amount
of time. You feel pressured and anxious. The time pressure means
taking shortcuts, jumping to conclusions, or relying heavily on
instinct to guide your way.
In your organization, you've probably heard of someone who made it
all the way to VP by relying on his gut to make decisions. At the
other extreme is the guy who simply can't make a decision because he
analyses the situation to death. The bottom line is, you have to
make decisions, and you have to make good decisions. Poor decisions
are bad for business. Worse still, one poor decision can lead to
others, and so the impact can be compounded and lead to more and
more problems down the line.
Thankfully, decision-making is a skill set that can be learned and
improved on. Somewhere between instinct and over-analysis is a
logical and practical approach to decision-making that doesn't
require endless investigation, but helps you weigh up the options
and impacts.
One such approach is called the Kepner-Tregoe Matrix. It provides an
efficient, systematic framework for gathering, organizing and
evaluating decision making information. The approach was developed
by Charles H. Kepner and Benjamin B. Tregoe in the 1960's and they
first wrote about it in the business classic, The Rational Manager
(1965). The approach is well-respected and used by many of the
world's top organizations including NASA and General Motors.
The Kepner-Tregoe Approach
The Kepner-Tregoe approach is based on the premise that the end goal
of any decision is to make the "best possible" choice. This is a
critical distinction: The goal is not to make the perfect choice, or
the choice that has no defects. So the decision maker must accept
some risk. And an important feature of the Kepner-Tregoe Matrix is
to help evaluate and mitigate the risks of your decision.
The Kepner-Tregoe Matrix approach guides you through the process of
setting objectives, exploring and prioritizing alternatives,
exploring the strengths and weaknesses of the top alternatives, and
of choosing the final "best" alternative. It then prompts you to
generate ways to control the potential problems that will crop up as
a consequence of your decision.
This type of detailed problem and risk analysis helps you to make an
unbiased decision. By skipping this analysis and relying on gut
instinct, your evaluation will be influenced by your preconceived
beliefs and prior experience – it's simply human nature. The
structure of the Kepner-Tregoe approach limits these conscious and
unconscious biases as much as possible.
The Kepner-Tregoe Matrix comprises four basic steps:
Situation Appraisal – identify concerns and outline the priorities.
Problem Analysis – describe the exact problem or issue by identifying and evaluating the causes.
Decision Analysis – identify and evaluate alternatives by performing a risk analysis for each and then make a final decision.
Potential Problem Analysis – evaluate the final decision for risk and identify the contingencies and preventive actions necessary to minimize that risk.
Going through each stage of this process will help you come to the "best possible choice", given your knowledge and understanding of the issues that bear on the decision.
How to Use the Tool
The Kepner-Tregoe Matrix is an in-depth approach that can be
supported by detailed instruction and worksheets. As an overview of
the approach, the following steps show the general principles of how
the Kepner-Tregoe approach can apply to a decision-making situation:
Prepare a decision statement:
This is a general overview of what the decision is expected to achieve (the key objective).
The statement should discuss the action that is required and the result that is desired.
Establish strategic requirements ("Must Haves"):
What "musts" will the final decision provide, allow for, include,
etc.? For example: We must have 10% cost saving, we must include
four color choices, the rope must hold 200 lbs.
These requirements are absolute – there is no compromise.
Establish operational objectives ("Want to Haves"):
What do you "want" the final decision to support?
By identifying the wants you can rank the alternatives according to
which ones satisfy the most, or most important, wants.
Identify the restraints (Limits):
What are the things that will limit your ability to do exactly what
you want/need?
These are typically resource constraints like money, materials, and
time.
Rank the operational objectives and assign relative weights:
For each "want", assign a rating of 1 – 10 based on the degree of
importance.
Objective
Weight
Want 1
8
Want 2
7
Want 3
9
Want 4
10
Generate a list of alternatives:
Think of as many alternative courses of action as you can. Don't be too concerned that they all meet the "musts" and "wants" you just defined. You will rank these alternatives in the next step.
Brainstorming is a good approach for generating your list of alternatives.
Assign a relative score for each alternative:
First eliminate any alternatives that do not meet the "musts" – these are not worth considering any further.
For the first alternative, go through each objective (want) and rate how well the alternative satisfies it using a 1 – 10 scale.
Multiply the weight of the objective by the satisfaction rating to come up with a weighted score for each objective.
Add the weighted scores to determine the total weighted score.
Repeat the process for each alternative.
Objective
Weight
Alternative A
Satisfaction Rating
Weighted Score
Want 1
8
4
32
Want 2
7
8
56
Want 3
9
9
81
Want 4
10
7
70
Total Weighted Score of
Alternative A
239
From the total weighted score for each alternative, rank the top two
or three alternatives:
Remember to make sure that the alternatives you choose meet all the
"must" criteria.
For the top alternatives, generate a list of potential problems
(adverse effects) for each:
Rank the potential problems for each alternative according to
probability and significance.
Obtain a total weighted score for the adverse effect (adversity
rating).
Adverse Effect
Probability
Significance
Weighted Score
1
5
9
45
2
3
10
30
3
8
6
48
Adversity Rating for Alternative 1
123
Analyze the alternative ranking and the adversity rating and make a
final decision
Decide on mitigating actions for the chosen alternative:
Look at each of the adverse effects already identified and generate
a list of proactive responses to reduce the probability of each
Continuously monitor these probabilities and take action as needed
Key Points
The Kepner-Tregoe Matrix is a well-respected and systematic approach
for making decisions. The matrix process forces users to be well
organized and thorough. By weighting and ranking both the benefits
and risks, it helps you choose the very best alternatives. Using the
Kepner-Tregoe approach requires patience and a commitment: The
payoff for the time invested is good, unbiased decision-making that
makes good business sense.
Read more…
room to the mailroom, you make decisions every day.
And the end
result in business is directly linked to the quality of the
decisions made at each point along the way.
So not surprisingly,
decision-making is a universally important competence in business.
Some decisions clearly have a greater impact on the business than
others, but the underlying skill is the same: The difference is in
the scope and depth of the process you go through to reach your
decision.
One reason why decision-making can be so problematic is that the
most critical decisions tend to have to be made in the least amount
of time. You feel pressured and anxious. The time pressure means
taking shortcuts, jumping to conclusions, or relying heavily on
instinct to guide your way.
In your organization, you've probably heard of someone who made it
all the way to VP by relying on his gut to make decisions. At the
other extreme is the guy who simply can't make a decision because he
analyses the situation to death. The bottom line is, you have to
make decisions, and you have to make good decisions. Poor decisions
are bad for business. Worse still, one poor decision can lead to
others, and so the impact can be compounded and lead to more and
more problems down the line.
Thankfully, decision-making is a skill set that can be learned and
improved on. Somewhere between instinct and over-analysis is a
logical and practical approach to decision-making that doesn't
require endless investigation, but helps you weigh up the options
and impacts.
One such approach is called the Kepner-Tregoe Matrix. It provides an
efficient, systematic framework for gathering, organizing and
evaluating decision making information. The approach was developed
by Charles H. Kepner and Benjamin B. Tregoe in the 1960's and they
first wrote about it in the business classic, The Rational Manager
(1965). The approach is well-respected and used by many of the
world's top organizations including NASA and General Motors.
The Kepner-Tregoe Approach
The Kepner-Tregoe approach is based on the premise that the end goal
of any decision is to make the "best possible" choice. This is a
critical distinction: The goal is not to make the perfect choice, or
the choice that has no defects. So the decision maker must accept
some risk. And an important feature of the Kepner-Tregoe Matrix is
to help evaluate and mitigate the risks of your decision.
The Kepner-Tregoe Matrix approach guides you through the process of
setting objectives, exploring and prioritizing alternatives,
exploring the strengths and weaknesses of the top alternatives, and
of choosing the final "best" alternative. It then prompts you to
generate ways to control the potential problems that will crop up as
a consequence of your decision.
This type of detailed problem and risk analysis helps you to make an
unbiased decision. By skipping this analysis and relying on gut
instinct, your evaluation will be influenced by your preconceived
beliefs and prior experience – it's simply human nature. The
structure of the Kepner-Tregoe approach limits these conscious and
unconscious biases as much as possible.
The Kepner-Tregoe Matrix comprises four basic steps:
Situation Appraisal – identify concerns and outline the priorities.
Problem Analysis – describe the exact problem or issue by identifying and evaluating the causes.
Decision Analysis – identify and evaluate alternatives by performing a risk analysis for each and then make a final decision.
Potential Problem Analysis – evaluate the final decision for risk and identify the contingencies and preventive actions necessary to minimize that risk.
Going through each stage of this process will help you come to the "best possible choice", given your knowledge and understanding of the issues that bear on the decision.
How to Use the Tool
The Kepner-Tregoe Matrix is an in-depth approach that can be
supported by detailed instruction and worksheets. As an overview of
the approach, the following steps show the general principles of how
the Kepner-Tregoe approach can apply to a decision-making situation:
Prepare a decision statement:
This is a general overview of what the decision is expected to achieve (the key objective).
The statement should discuss the action that is required and the result that is desired.
Establish strategic requirements ("Must Haves"):
What "musts" will the final decision provide, allow for, include,
etc.? For example: We must have 10% cost saving, we must include
four color choices, the rope must hold 200 lbs.
These requirements are absolute – there is no compromise.
Establish operational objectives ("Want to Haves"):
What do you "want" the final decision to support?
By identifying the wants you can rank the alternatives according to
which ones satisfy the most, or most important, wants.
Identify the restraints (Limits):
What are the things that will limit your ability to do exactly what
you want/need?
These are typically resource constraints like money, materials, and
time.
Rank the operational objectives and assign relative weights:
For each "want", assign a rating of 1 – 10 based on the degree of
importance.
Objective
Weight
Want 1
8
Want 2
7
Want 3
9
Want 4
10
Generate a list of alternatives:
Think of as many alternative courses of action as you can. Don't be too concerned that they all meet the "musts" and "wants" you just defined. You will rank these alternatives in the next step.
Brainstorming is a good approach for generating your list of alternatives.
Assign a relative score for each alternative:
First eliminate any alternatives that do not meet the "musts" – these are not worth considering any further.
For the first alternative, go through each objective (want) and rate how well the alternative satisfies it using a 1 – 10 scale.
Multiply the weight of the objective by the satisfaction rating to come up with a weighted score for each objective.
Add the weighted scores to determine the total weighted score.
Repeat the process for each alternative.
Objective
Weight
Alternative A
Satisfaction Rating
Weighted Score
Want 1
8
4
32
Want 2
7
8
56
Want 3
9
9
81
Want 4
10
7
70
Total Weighted Score of
Alternative A
239
From the total weighted score for each alternative, rank the top two
or three alternatives:
Remember to make sure that the alternatives you choose meet all the
"must" criteria.
For the top alternatives, generate a list of potential problems
(adverse effects) for each:
Rank the potential problems for each alternative according to
probability and significance.
Obtain a total weighted score for the adverse effect (adversity
rating).
Adverse Effect
Probability
Significance
Weighted Score
1
5
9
45
2
3
10
30
3
8
6
48
Adversity Rating for Alternative 1
123
Analyze the alternative ranking and the adversity rating and make a
final decision
Decide on mitigating actions for the chosen alternative:
Look at each of the adverse effects already identified and generate
a list of proactive responses to reduce the probability of each
Continuously monitor these probabilities and take action as needed
Key Points
The Kepner-Tregoe Matrix is a well-respected and systematic approach
for making decisions. The matrix process forces users to be well
organized and thorough. By weighting and ranking both the benefits
and risks, it helps you choose the very best alternatives. Using the
Kepner-Tregoe approach requires patience and a commitment: The
payoff for the time invested is good, unbiased decision-making that
makes good business sense.
The Vroom-Yetton-Jago Decision Model
2:55 AM |How you go about making a decision can involve
as many choices as the decision itself. Sometimes you have to
take charge and decide what to do on your own. Other times it's
better to make a decision using group consensus. How do you decide
which approach to use?
Making good decisions is one of the main leadership
tasks. Part of doing this is determining the most efficient and
effective means of reaching the decision.
You don't want to make autocratic decisions
when team acceptance is crucial for a successful outcome. Nor
do you want be involving your team in every decision you make,
because that is an ineffective use of time and resources. What
this means is you have to adapt your leadership style to the situation
and decision you are facing. Autocratic styles work some of the
time, highly participative styles work at other times, and various
combinations of the two work best in the times in between.
The Vroom-Yetton-Jago Decision Model provides
a useful framework for identifying the best leadership style to
adopt for the situation you're in.
Note:
This model was originally described by Victor Vroom and Philip Yetton in their 1973 book titled Leadership and Decision Making . Later in 1988, Vroom and Arthur Jago, replaced the decision tree system of the original model with an expert system based on mathematics. Hence you will see the model called Vroom-Yetton, Vroom-Jago, and Vroom-Yetton-Jago. The model here is based on the Vroom-Jago version of the model.
Understanding the Model
When you sit down to make a decision, your style, and the degree of participation you need to get from your team, are affected by three main factors:
Decision Quality – how important is it to come up with the "right" solution? The higher the quality of the decision needed, the more you should involve other people in the decision.
Subordinate Commitment – how important is it that your team and others buy into the decision? When teammates need to embrace the decision you should increase the participation levels.
Time Constraints – How much time do you have to make the decision? The more time you have, the more you have the luxury of including others, and of using the decision as an opportunity for teambuilding.
Specific Leadership Styles
The way that these factors impact on you helps you determine the best leadership and decision-making style to use. Vroom-Jago distinguishes three styles of leadership, and five different processes of decision-making that you can consider using:
Style:
Autocratic – you make the decision and inform others of it.
There are two separate processes for decision making in an autocratic style:
Processes:
Autocratic 1(A1) – you use the information you already have and make the decision
Autocratic 2 (A2) – you ask team members for specific information and once you have it, you make the decision. Here you don't necessarily tell them what the information is needed for.
Style:
Consultative – you gather information from the team and other and then make the decision.
Processes:
Consultative 1 (C1) – you inform team members of what you're doing and may individually ask opinions, however,
the group is not brought together for discussion. You make the decision.
Consultative 2 (C2) – you are responsible for making the decision, however, you get together as a group to discuss the situation, hear other perspectives, and solicit suggestions.
Style:
Collaborative – you and your team work together to reach a consensus.
Process:
Group (G2) – The team makes a decision together. Your role is mostly facilitative and you help the team come to a final decision that everyone agrees on.
Tip:
This is a useful model, but it's quite complex and long-winded.
Use it in new situations, or in ones which have unusual
characteristics: Using it, you'll quickly get an feel for
the right approach to use in more usual circumstances.
To determine which of these styles and processes
is most appropriate, there is a series of yes/no questions
that you ask yourself about the situation, and building a decision
tree based on the responses. There are seven questions in total.
These are:
Is the technical quality of the decision very important? Meaning, are the consequences of failure significant?
Does a successful outcome depend on your team members' commitment to the decision? Must there be buy-in for the solution to work?
Do you have sufficient information to be able to make the decision on your own?
Is the problem well-structured so that you can easily understand what needs to be addressed and what defines a good solution?
Are you reasonably sure that your team will accept your decision even if you make it yourself?
Are the goals of the team consistent with the goals the organization has set to define a successful solution?
Will there likely be conflict among the team as to which solution is best?
Use Figure 1 below to follow your answers through on the decision tree and identify the best decision process for your circumstances. Not that in some scenarios, you don't need to
In general, a consultative or collaborative style is most appropriate when:
You need information from others to solve a problem.
The problem definition isn't clear.
Team members' buy-in to the decision is important.
You have enough time to manage a group decision.
An autocratic style is most efficient when:
You have more expertise on the subject than others.
You are confident about acting alone.
The team will accept your decision.
There is little time available.
Key Points
The underlying assumption of the Vroom-Yetton-Jago Decision Models is that no one leadership style or decision making process fits all situations.
By analyzing the situation and evaluating the
problem based on time, team buy-in, and decision quality, a conclusion
about which style best fits the situation can be made. The model
defines a very logical approach to which style to adopt and is
useful for managers and leaders who are trying to balance the
benefits of participative management with the need to make decisions
effectively.
Read more…
as many choices as the decision itself. Sometimes you have to
take charge and decide what to do on your own. Other times it's
better to make a decision using group consensus. How do you decide
which approach to use?
Making good decisions is one of the main leadership
tasks. Part of doing this is determining the most efficient and
effective means of reaching the decision.
You don't want to make autocratic decisions
when team acceptance is crucial for a successful outcome. Nor
do you want be involving your team in every decision you make,
because that is an ineffective use of time and resources. What
this means is you have to adapt your leadership style to the situation
and decision you are facing. Autocratic styles work some of the
time, highly participative styles work at other times, and various
combinations of the two work best in the times in between.
The Vroom-Yetton-Jago Decision Model provides
a useful framework for identifying the best leadership style to
adopt for the situation you're in.
Note:
This model was originally described by Victor Vroom and Philip Yetton in their 1973 book titled Leadership and Decision Making . Later in 1988, Vroom and Arthur Jago, replaced the decision tree system of the original model with an expert system based on mathematics. Hence you will see the model called Vroom-Yetton, Vroom-Jago, and Vroom-Yetton-Jago. The model here is based on the Vroom-Jago version of the model.
Understanding the Model
When you sit down to make a decision, your style, and the degree of participation you need to get from your team, are affected by three main factors:
Decision Quality – how important is it to come up with the "right" solution? The higher the quality of the decision needed, the more you should involve other people in the decision.
Subordinate Commitment – how important is it that your team and others buy into the decision? When teammates need to embrace the decision you should increase the participation levels.
Time Constraints – How much time do you have to make the decision? The more time you have, the more you have the luxury of including others, and of using the decision as an opportunity for teambuilding.
Specific Leadership Styles
The way that these factors impact on you helps you determine the best leadership and decision-making style to use. Vroom-Jago distinguishes three styles of leadership, and five different processes of decision-making that you can consider using:
Style:
Autocratic – you make the decision and inform others of it.
There are two separate processes for decision making in an autocratic style:
Processes:
Autocratic 1(A1) – you use the information you already have and make the decision
Autocratic 2 (A2) – you ask team members for specific information and once you have it, you make the decision. Here you don't necessarily tell them what the information is needed for.
Style:
Consultative – you gather information from the team and other and then make the decision.
Processes:
Consultative 1 (C1) – you inform team members of what you're doing and may individually ask opinions, however,
the group is not brought together for discussion. You make the decision.
Consultative 2 (C2) – you are responsible for making the decision, however, you get together as a group to discuss the situation, hear other perspectives, and solicit suggestions.
Style:
Collaborative – you and your team work together to reach a consensus.
Process:
Group (G2) – The team makes a decision together. Your role is mostly facilitative and you help the team come to a final decision that everyone agrees on.
Tip:
This is a useful model, but it's quite complex and long-winded.
Use it in new situations, or in ones which have unusual
characteristics: Using it, you'll quickly get an feel for
the right approach to use in more usual circumstances.
To determine which of these styles and processes
is most appropriate, there is a series of yes/no questions
that you ask yourself about the situation, and building a decision
tree based on the responses. There are seven questions in total.
These are:
Is the technical quality of the decision very important? Meaning, are the consequences of failure significant?
Does a successful outcome depend on your team members' commitment to the decision? Must there be buy-in for the solution to work?
Do you have sufficient information to be able to make the decision on your own?
Is the problem well-structured so that you can easily understand what needs to be addressed and what defines a good solution?
Are you reasonably sure that your team will accept your decision even if you make it yourself?
Are the goals of the team consistent with the goals the organization has set to define a successful solution?
Will there likely be conflict among the team as to which solution is best?
Use Figure 1 below to follow your answers through on the decision tree and identify the best decision process for your circumstances. Not that in some scenarios, you don't need to
In general, a consultative or collaborative style is most appropriate when:
You need information from others to solve a problem.
The problem definition isn't clear.
Team members' buy-in to the decision is important.
You have enough time to manage a group decision.
An autocratic style is most efficient when:
You have more expertise on the subject than others.
You are confident about acting alone.
The team will accept your decision.
There is little time available.
Key Points
The underlying assumption of the Vroom-Yetton-Jago Decision Models is that no one leadership style or decision making process fits all situations.
By analyzing the situation and evaluating the
problem based on time, team buy-in, and decision quality, a conclusion
about which style best fits the situation can be made. The model
defines a very logical approach to which style to adopt and is
useful for managers and leaders who are trying to balance the
benefits of participative management with the need to make decisions
effectively.
