One of the easiest measures of the value of your product (or a feature) is to attribute revenue to the product. However early stage startups and pre-revenue products don’t have this yardstick with which to measure their value. In my current role, the product I primarily support is pre-revenue, but that hasn’t been an excuse not to provide stakeholders a sense of the value their features bring to market.
To support the decision-making processes, each feature is scored for its value–a combination of impact, pervasiveness, risk tolerance, and alignment to corporate strategies. In the current iteration the equation is:
(How many people want it × How big is the market opportunity × Risk tolerance) × % Aligned to Strategy
While not required for the mathematical operation, the purpose of the parenthesis is to illustrate that first half of the equation sees us increasing the value while the second half decreases the value the further the feature strays from the strategy. This is done to counteract executive whims that may otherwise overtake the prioritization process.
My team re-evaluates the scoring equation each quarter, so unfortunately comparing quarter over quarter is more difficult, but we’re okay with that–because we want to know the value of the feature right now.
I do, however, track how the value estimated is delivered to users. Stealing from the concept of Earned Value, our team scores all the features expected in a period (often a month, quarter, or release) and we award ourselves those points when we release the feature to market.
| Feature | Estimated Value | Awarded Value | Total Awarded |
| A | 10 points | 10 points | 10 |
| B | 15 points | not delivered = 0 | 10 |
| C | 5 points | 5 points | 15 |
| D | 10 points | 10 points | 25 |
At the end of the period we sum the points awarded to give us a sense of our earned value for the period. We also compare the estimated value (40 points in the above table) and the awarded value (25 points) as a ratio (25:40 = 62.5%) to measure ourselves on our ability to deliver the perceived value within the period in question.
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SAFe has a similar, albeit much simpler process: you simply ask the business owner to score the value of a given feature at the beginning and end of the program increment. One could compare the two measurements to better understand if the delivery of the feature met the business owners’ expectations. My current employer struggles with this method (and thus the more complicated equation above) because they discount the business owners’ opinions and instead prefer to rely on other data.