Product Management digital newsletters are usually a good resource for more general management and leadership content. Since after all, regardless of our title, we are all product managers: we are tasked with solving a portfolio of problems to a diverse group of stakeholders, using our unique skill sets, through a set of services that we provide.
This summer, all the ones that I’m following on a regular basis seem to have experienced a disappointing drought, which has finally come to an end with this piece referenced in Pivot Product Hits by Scott Sehlhorst:
Minimum Viable Product (MVP) is a commonly used term in lean product development, which refers to “the least you can do” before shipping your product to market. Since the most critical learning, from a business perspective, happens when your product meets the market – aim to get to that milestone sooner rather than later.
MVP is typically discussed through a functionality lens – the minimum amount of features that we need to build in order to have a viable product.
Scott thoughtfully calls out a big challenge with this approach: since it’s an inside-out approach, it doesn’t give us any guidance as to “what is enough?”, increasing the risk of building too little or too much.
Instead, he proposes an outside-in approach: rather than asking what is the minimum viable product that we should build, we should be asking what is the minimum valuable problem that we should solve.
Asking that question from an outside-in, customer-centric perspective, increases our chances of building something that is of value to the customer, as measured by the problem that it is solving for the customer. If it’s only solving half the problem, it’s not that valuable.
In Scott’s words:
The minimum valuable problem is one you completely solve.
You may only solve it in a very narrow context or scope.
You may only solve it for a small group of users or a subset of your ultimate market.
You may only solve it adequately, without creating a truly competitive solution.
But for that one customer, in that one situation, you have completely solved it.