Several years ago I was working with a Biotech client to help them define and release an MVP (minimum viable product) to their initial audience. One of their key business sponsors was newer to the concept, so I took some time to explain that the classic definition (as articulated by Eric Ries) is that it’s the initial version of a “product which allows a team to gather the most validated learning about customers with the least amount of effort”. After some discussion, I stopped to ask if he had questions. He said “I’m having a hard time getting over the phrase ‘minimum viable’ because in biology and biotech this would mean ‘barely alive.'” His response, while it made me chuckle at the time, changed the way I explained it from that point forward.
Instead of ‘viable’ I now use ‘valuable’ which is more aligned to the spirit of MVP anyways. The goal of every product manager should be to continuously deliver value to the customer and not just at the beginning of a product’s lifecycle but throughout the entirety. In fact, many organizations are moving away from the term MVP and are instead focusing on delivering value in every ongoing iteration of the product by tying each feature to a customer value theme (i.e. simplicity, ease of use, flexibility, etc.).
Some key things to consider as you iterate on your product:
- What do the customers like or dislike about the most recent set of features we released?
How do you tell what they like? Ask them for feedback, look at product metrics you’re tracking (i.e. usage of certain features…this is one reason it is important that you have analytics in place for ongoing data to supplement qualitative feedback), and ask your customer support team about the most common/frequent requests they receive. You want to avoid investing too much time and effort in features and capabilities that customers don’t want or need.
- What benefits hypotheses were validated last time and which ones were disproven?
This will give you insights into your customers, your market, and potentially your competitors as well, which can inform your next hypotheses and product feature choices. For example, if you are an insurance company and you predicted a certain feature would reduce the amount of time it takes for users to submit a claim by 25%, you can look to your claim metrics to see if you’ve achieved this or not and figure out what it would take to get you there this next time.
- What are our product goals for this next feature set and how do they align to our overall vision, roadmap?
It’s important to not lose sight of the near and long term vision, and to revisit it each product iteration to ensure it’s still where you want to go or if you need to adjust.
It requires a conscious effort and disciplined commitment from the product team – both business and technical – to think through these questions each iteration of your product. But ultimately by asking ‘why are we doing this?’ and ‘what value are we delivering?’ for each product feature, requirement you will build the habit of continuous value delivery to your customers.