Three years ago this week, I introduced a scheme for prioritizing requirements that was aligned with strategic planning and market segmentation and brought some rigor and objectivity to the art of assigning a priority to requirements.

Initially, the scheme introduced 3 classifications: Commodity (or Table Stakes); Spoiler; and Differentiator. Later I realized a 4 category was required, Cost Saver. With two possible sub-classifications of cost saved by the customer (lower cost of operation or displacement of other costs), or cost saved to you the producer of the software / operator of a service. These four classifications have survived almost 2 years without revision and seem to be quite stable. I think of this system as a lightweight, and very fast alternative to Kano modeling.

Since 2006, I've been exposed to Chris Matts and Olav Maassen's Real Option Theory thinking. Some of you may recall I was skeptical about real options after seeing a presentation in Munich in early 2007, that attempted to use the Black-Scholes equation from financial option theory to assist prioritization decisions. I pointed out that we weren't ready for real options because we couldn't furnish the equation with sufficiently accurate data. Well the Matts-Maassen approach to real options does without Black-Scholes and is the better for it. Matts-Maassen tells us to push back decisions as far as possible and to gather information, create options and understand when they expire. This helps us to optimize decision making and minimum the risk of a decision being a bad one.

We can treat the requirements in a backlog of features/stories as options. Now we can consider the market risk and likelihood of change occurring to a specific requirement based on its classification. We see that commodity/table stakes features have the lowest market risk. When did you ever hear of the table stakes going down? and that differentiators have the highest market risk.

Figure 1. Mapping Requirement Classification to Market Risk

Commodity features are unlikely to change because the table stakes for market entry never go down. They only ever go up.

Cost Savers are more likely to suffer change during the life of a project but still very unlikely. There is some risk that the cost is mitigated in other ways or that shifts in the market, strategic plan, or go-to-market initiatives of the business may de-prioritize the need to save costs. Hence, there is some risk that cost savers may be dropped from scope or unneeded before the project is delivered.

Spoilers are features being introduced to spoil a competitors differentiator. They primarily protect market share. The main risk with spoilers is that by the time they are introduced they have essentially become table stakes. This doesn't really affect our planning decisions. What would affect a planning decision would be a choice to focus on a different market and concede an existing market to a competitor with a more compelling offer.

Differentiators are the most risky because they may turn out to be features that the customer will not want. They are essentially experimental in nature. If the customer likes them then they are worth a lot of new profit margin. If not then they don't produce profits. There is also a chance that a delayed differentiator is in fact a spoiler by the time it comes to market.

Now applying what we know about market risk and using a real options approach to decision making and prioritization, we should delay risky items that are likely to suffer change until the last possible moment. This implies we should code up all our commodity features first and delay differentiators until closer to the release date. This is shown in Figure 2.

Figure 2. Planning a series iterations using market risk and feature classification

[I first presented this material at the APLN Summit in Seattle in July 2008 in response to an audience question and then later as a 5 minute "lightning talk"at Agile 2008 in Toronto.]

I have more to say about this approach as the model presented is somewhat simplistic and only accounts for a single market segment. I also want to discuss how this approach relates to the Minimum Marketable Feature (MMF) approach first presented in Software By Numbers. Chris Matts has been marrying up MMFs, with his Feature Injection analysis technique and Real Option Theory. In a later post I'll discuss my own views on this and how I see it relating to the model I've presented here.

And finally, I'm looking for a name for this model. I've kicked around names like Strategic Alignment Prioritization Analysis (SAPA) but I'm not entirely happy with anything I've come up with. Please leave your suggestions in the comment box. Thanks.

Related Articles
Prioritizing Requirements, September 6th, 2005
Revisiting Prioritizing Requirements, December 26th, 2006
Why we are not Ready for Real Options, February 20th, 2007
Exploring Real Option-based Software Engineering, February 27th, 2007
InfoQ: "Real Options" Underlie Agile Practices, June 8th, 2007
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