Product Strategy – Feature Prioritization

For the past few months I have been advising a couple of start-ups with their product strategy. One of the questions I keep hearing is centered on product feature prioritization and sequencing. One such startup is an online platform focused on knowledge sharing between emerging markets and investment clientele  and they wanted to build out their MVP –  but were struggling with multiple questions around focus on an initial client type and minimum feature set to release that will result in the greatest value add.

My advice on a high level was to use 2 frameworks in order to map the highest value add features aligned with short-term and longer term business goals.

The first framework is the Value / Difficulty framework where features are plotted on business value effort complexity (time & cost).

value-difficulty-framework

So for example, you would to identify all feature sets that are a 1 i.e. they provide dual benefits – with a high business value and lower effort / complexity. Question mark in the bottom left corner implies features that are easy to build but will need to be market tested and validated in order to determine business value. The top right corner indicates feature sets that are both high in business value and high in terms of effort – there can be additional prioritization here, since it’s very likely that a building out a core feature set e.g. a ranking engine provides high business value as well as requiring a larger effort (e.g. a greater technology effort). Lastly, the “X” denotes feature sets that should be skipped – high complexity with low business value. Very often start-ups without a structured product strategy might build out a feature due to a “coolness” factor, inspired by UI design or a new underlying technology (e.g. there is no reason to move to NoSQL ala MongoDB if MySQL suffices)– but the key is to always ask yourself the question – how does this align with the business goals and where does it map to on the Value / Difficulty framework?

The second framework uses weighted scoring for a more quantitative approach and can also be used concurrently with the Value / Difficulty framework. The objective here is to rank various features based on several different dimensions:

quantitative-ranking-product-features

In the dimensions above, strategic value is the value add of the particular feature set and its alignment with business strategy. Customer Value is measurement of how well a particular feature set satisfies and helps solve the customer problem. Revenue Growth determines if a feature promotes revenue growth (or user growth / acquisition – for pre revenue projects) and lastly the cost dimensions (implementation cost and risk / complexity) allows for to take into account the complexity of implementing a particular feature set.

The dimensions above can obviously be changed based on the project / startup as different metrics / KPIs vary greatly. One thing to note, the above is focused for startups / projects that are still in the market validation phase. During this phase it’s not only important to stay nimble but also allow for unstructured experimentation – i.e. iterative development, scrum / agile.  A shorter road map is key here – 90 days, 6 months, 9 months since the external ambiguity will not align with a long term roadmap which is more applicable for a market tested product or the launch of a complimentary product to an established customer base.

Until then, happy building.

Did you like this? Share it:

Post Navigation