One of the most difficult tasks for product development is prioritizing features. It can turn into a contentious task with disagreement from different stakeholders. Features are usually drawn from a wish list based on customer feedback, sales and service feedback, management, etc. Unfortunately, some of this is biased. Management may not understand the market but insist on features discussed during their last customer visit or what they just read in the morning newspaper. Sales wants features based on their lost orders. Engineering wants to use this as an opportunity to fix the aging platform. In many instances, the squeakiest wheel, biggest mouth, or most persuasive people can get an unfair say. It a “darned if you do or darned if you don’t” scenario for Product Managers. Someone is going to be unhappy because you can’t do everything.
So that’s where Pugh’s Charts can help make the ranking and decision making easier and clearer.
Suppose that we have five possible new features to be considered, A, B, C, D. We already have an existing product and want to know if any of these possible five features would improve it.
We first must decide on the criteria used to judge the features against. In this case, we pick just five. The criteria should be based on your company goals, e.g. a specific market penetration, increased OTC sales, gaining a top 10 account, etc. and they should have upper management buy-in before you start.
Now we draw our Pugh matrix (chart). The possible features are drawn across the top, which will be judged against the selection criteria, which is shown on the left column. Notice the column named “Base Line”. This is our reference point which is the existing product that we are either improving upon or replacing. (It can also a competitor’s product or substitute.) We place a “0” for each criteria for the baseline as a start.
The next step is for the product manager or team to place a 0, +1, or -1 in each cell for "Considered New Feature" versus "Selection Criteria":
0 = no gain or loss
+1 = gain, improvement for the selected criteria
-1 = loss, detriment to the selected criteria
We then sum the values in each column for considered feature. The completed chart gives us an overall view what the rankings for each considered feature based on the sum. However, not all selection criteria are equal in importance to company goals so this particular chart should be considered unfinished and used only for “go” or “no-go” at most. In our example, "Flashing LED" and "Windows 8 Support" both appear to have the same importance because all selection criteria is treated as equal.
We now add a weight factor against each selection criteria. For example, if our first criteria of safety is a 2, and the second criteria (to meet a certain industry standard) is twice as important, we give that a weight value of four. The company edict is to grow the China market so that criterion gets a weight value of five.
If we now apply our weight factors per selection criteria against the initial assessment per desired feature, we get a much clearer and refined picture of the feature rankings.
However, we now have another missing factor: how much effort, e.g. resources and time, is needed to get each desired feature. A feature that takes 2 years to develop and release may not be as desirable as an equally normalized feature that takes 1 year, e.g. Flashing LED or Voice Recognition in this example. So we now add a row showing the relative effort required to get each feature. The value can be 1, 2, 3 or 1 and 2 in this case to represent a 1 year or 2 year effort (units for effort need to be decided). We now create a final decision factor based on the ratio of the Sum for each Possible Feature versus Effort needed – we call this the Value for each possible feature. The Value may be considered “the Bang for the Buck” very similar to the Marketing definition of product value as the ratio of benefits to cost. In our example, Chinese language becomes our top priority, followed by Windows 8 Support, Flashing LED, and Voice Recognition.
This modified Pugh Chart takes away some of the guesswork and emotions in selecting and prioritizing features. It still does not take into account those features that you always get on the wish list but miss the cut-off (they also tend to be the planned features that get chopped out when projects run out of time). In those cases, you have to either accept this as reality or twiddle with the pertinent weight value. Same principle applies to those favorite pet features of upper management. Either face up to the CEO and GM with the Pugh chart results or add another selection criteria named “The big Kahuna wants it ” aka “Keeping my job”.
The weights assigned for selection criteria and effort are not going to be 100% accurate but everything is relative so the scoring should still work out. These charts are by no means perfect so feedback is most welcome!
Much thanks to Martin Wright at Instron ITW (who studied under Stuart Pugh himself) for educating me about Pugh Charts and Bruce McCarthy for introducing me to decision matrix concepts. Bruce is a master at marketing and has a similar version (ref: http://www.slideshare.net/ProductCampBoston/prioritization-301-advanced-roadmapping-class-bruce-mccarthy).
Frank Lio is a Product Manager, Strategist, and Change Agent in the Hi-Tech industry. His growing track record of successes include creating 3 winning software products, leading nationwide seminars, and turning around a failing business unit. He is currently serving a dual role as Product Manager and Business Team Support Manager at Instron ITW.
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