In research, in business, and in life, we all have to make choices, and to prioritise some choices over others. Whenever we make choices we are prioritising, often based on “gut feeling” that is developed from a series of conscious or unconscious judgments of the relative merits of certain criteria for those choices or “options”.
For personal choices it is fine to review internally and make a choice based on “what we think”. For more complex choices, particularly those that involve other stakeholders, there needs to be a more structured approach and transparency around the reasons for a particular choice. For these situations it may be better to use more structured prioritisation tools and techniques that will ensure that:
- We are making comparisons in a systematic way using agreed and relevant criteria, and
- We gain consensus amongst stakeholders, which will then make it more likely that the prioritised options are accepted.
This article will introduce the basics of common prioritisation approaches and introduce some useful tools for more effective prioritisation.
One of the simplest techniques for prioritisation is the “paired comparison” technique. This is ideal if your options are comparable and developed to a similar level. It is also a reliable, quick technique to use with a group to quickly gain consensus on the relative priority of different options.
In this technique each option is compared with every other option. For example in a choice between five options A to E, choice A is compared with Choice B, then with Choice C, then with Choice D, and finally with Choice E. Next Choice B is compared with Choices C, D, and E… and so on. It is simple to build a tool in a spreadsheet as depicted in Figure 1. On comparing A to B, if B is preferred then B “wins” and you would enter B in the AB box; in comparing A and C, if A was preferred then A ‘wins’ and you would put A in the AC box, and so on. In the end you add up the row wins and the column wins for each option and rank on the total wins scores. In the simple illustration in Table 1, we see that the ranking order based on the total wins scores is B, D, A, C, E. With a simple binary choice paired comparison like this you should never get any two options with the same score. If you do then it is probably because you have broken a rule of logic somewhere. If B is better than A and A is better than C, then B must also be better than C.
This technique is ideal for less complex prioritisation and can be done in a group or separately and then average the results. Doing it in a group is a great way to ensure consensus and speed up the process. However, for more complex prioritisation with many options and several criteria, we need a different approach and here we can turn to the technique of Multi-Criteria Decision Analysis (MCDA).
Multi-Criteria Decision Analysis (MCDA)
One of the simplest tools that one can use for MCDA is that of the Cause and Effect (C&E) matrix, which came out of the world of Six Sigma and process optimisation. It was originally used to help identify the key inputs into a process that were affecting a specific process output that you were trying to improve. However, once you grasp the essentials of this technique you can use it for all kinds of prioritisation – choosing a car or house, deciding between jobs, ranking projects or grant applications, ranking competitors, choosing between strategic options such as “which market segments should we address”, “where should the government invest”, etc.
MCDA using, for example, a C&E matrix can be approached as a process, as outlined below:
- Establish your list of “options” – the things you are deciding between.
- Choose, define and develop the “criteria” which you will use to differentiate between your options.
- Once the criteria are established, gather information on each option relating to the criteria, e.g. if you are going to be choosing a car and one of your criteria is fuel economy then you will need data on the fuel economy of each car between which you are choosing.
- Include financial cost/benefit information, especially if you are also later going to assess “bang for buck”.
- It may be appropriate to also include a criterion of risk and/or a counterbalance.
- Assign an importance rating (weight) for each of the criteria – not all criteria are equal. This is best done with group input for complex and multi-stakeholder prioritisation to aid consensus on the results (see reference 3 on “decision conferencing”).
- Develop a scoring system for your criteria, one that ensures good differentiation and avoids “middle choices”. A good basic scoring system used often in C&E matrices is 0, 1, 3, 9. You will also need to define what each score means. For example, going back to the car choice example and taking the fuel economy criterion in miles per gallon, then the scoring could be:
- 9 means mpg > 60
- 3 means 60 > mpg >= 45
- 1 means 45> mpg >= 20
- 0 means mpg < 20
- Hold a prioritisation session with all relevant stakeholders, first reviewing the criteria and their weightings and the scoring definitions; then score your options and rank using the total scores. Notes:
- Remember – garbage in, garbage out. Use good data for all your options
- “Sense check” the final ranking. If there are doubts then review the weightings of the criteria.
Figure 2 shows how such a simple C&E matrix can be built using a spreadsheet.
This basic MCDA concept can be build upon to handle some quite complex decision making such as for prioritising strategic options. Figure 3 shows an example of this.
Real Win Worth Analysis
In fact, taking many of the established business success criteria, you can build these into a C&E prioritisation matrix. For example taking the Dominick (Don) Schrello “Real, Win, Worth” criteria1 for business success, you can build these into a specialised prioritisation matrix known as a Real Win Worth (RWW) matrix. Schrello asked three basic questions about a company’s new product idea that could then be divided into sub-questions, some of which are highlighted below2.
- Is it Real?
- Is the market Real and attractive?
- Is there a want or need for the product?
- Are there identifiable customers for the product?
- Is the product Real?
- Do we have a product or concept that addresses an identifiable need?
- Do we have the technology to make the product?
- Do we have manufacturing capability and capacity?
- Is the market Real and attractive?
- Can we Win?
- Is the product competitive?
- Does the product compare well to direct or indirect competition?
- Will the product compete with our current range?
- Does the product meet customer expectations?
- Is the company competitive?
- Can we leverage our core technology or do we need to invest?
- Do we have a route to market?
- Do we have the resources and skills within the company to deliver this product?
- Is the product competitive?
- Is it Worth doing?
- Is it profitable?
- What is the Net Present Value (NPV) and Return on Investment (ROI) on the project?
- What are the investment costs?
- Projected annual sales?
- Is it strategic?
- Does it align with the company strategic plan?
- Will it develop into a new platform?
- Is it profitable?
These questions can then be built up into a RWW matrix for the evaluation of different options such as new product ideas as shown in figure 4 and the Real, Win, and Worth scores for each option can be built up. The options can then be prioritised based on overall RWW score but also checking that none of them fail any of the primary (R-W-W) or secondary questions. If they do then the option needs to be rejected or revisited as this represents a potential failure mode for that option.
Prioritising on Value
There is one further variant of the Multi Criteria Decision Analysis approach that can be very useful in a more complex prioritisation process. This technique can be referred to as the Risk Adjusted Cost-Benefit (RAC-B) MCDA, which takes into account both the effect of Risk on the attractiveness of your options and the Cost of implementing each option. This is particularly useful for prioritising business projects across different business groups, where we are trying to maximize the output for a given, finite budget.
The basic premise of this technique is that:
- The benefits of any particular option/project need to be adjusted for Risk in order to more realistically judge their worth in any comparison technique
- If you had infinite resources then it does not matter what order you do your projects, but this is not usually the case – we cannot afford to do everything, so it makes sense to do the ones that give you the best value first (“more bang for your buck”) by prioritising those projects with the highest Risk Adjusted Benefit to Cost ratio first and so maximizing your benefits for a given budget. This is illustrated graphically in Figure 5. For more detail on this technique see reference 3.
Hopefully this brief article will have been of benefit to any readers needing to more formally structure the way they prioritise their projects, activities, business options, or personal choices.
References and links:
- Schrello – see HBR article and HBR edition, December 2007, P110
- Real, Win, Worth example
- RAC-B MCDA – see “Transparent prioritisation, budgeting and resource allocation with multi-criteria decision analysis and decision conferencing” – Lawrence D. Phillips, and Carlos A. Bana e Costa, ISBN 0 7530 1697 4