Whether you are working at an enterprise level or at smaller scale, establishing a clear product roadmap is key to maximising value from your digital products. Too often, that roadmap becomes confused or disjointed as internal perceptions and viewpoints override data and conclusive feedback. This usually results in unnecessary technical debt and wasted effort and investment. With financial pressures mounting in today’s uncertain world, the need for greater efficiency is more important than ever before.
Last month, my colleague Ian Greentree wrote an insightful article about How Value Stream Mapping Can Maximise the ROI of Digital Products. He made the valid point that losing sight of the original value proposition can lead to wasted investment. Bringing value to the forefront of decision making, particularly in articulating value streams and product roadmaps, is critical and the hypothesis statements you use to define that value have an important role to play.
There are many ways to construct a hypothesis statement. Personally, I favour the following:
We believe that… (your problem statement)
So, if we… (your high-level response)
Then we will see… (your measurement)
Constructing a strong hypothesis statement is an art unto itself and there are various pitfalls along the way. Here are five recommendations to help you build your hypothesis statements the right way:
#1 – Always consider your vision
A common pitfall is to craft hypothesis statements – whether that be at the product, epic or feature level – with tunnel vision. Care and attention are typically paid to ensuring that hypothesis statements at all levels are aligned with each other, but how do they relate to your vision?
Always check that the problem statement you are framing is aligned to your overall vision. If it isn’t, stop! Either you are looking at the wrong problem or your vision is incorrect. Explore why there are differences, adjust and then progress forwards. Not doing so can lead to complications in communication, delivery and, more importantly, your over-arching customer experience.
#2 – It’s all about the customer
Higher conversion rates are not always the driving force. In some cases, it may be about increasing efficiency or reducing / removing unnecessary costs. Both are equally valid, but when it comes to a hypothesis statement, it is all about the customer, even if your goal is to save money or boost efficiency. Remember, without customers (or members if you’re an official body) there is no business.
There are various techniques to delve into your goal to get to a customer-focused statement. Try the Five Whys to help determine the root cause as a starting point.
#3 – Make it more than an educated guess
The nature of the hypothesis statement is that it is an educated guess or a prediction of what you believe the problem to be and what you feel is the most appropriate response. However, in the current economic climate, an educated guess is likely to be too loaded with risk.
Data is your friend – whether that be analytics, commercial data, qualitative feedback or a mix of all three. It’s not a silver bullet that will give a 100%-accurate hypothesis statement that cannot fail but it will help to increase confidence and certainty in the direction you are proposing.
#4 – Don’t solutionise
This is the most common mistake when it comes to writing hypothesis statements. I’ve labelled the second part of the hypothesis statement as “the response” but more often than not it is referred to as “the solution”. This is a loaded word and is often why this mistake creeps in.
When you are producing a hypothesis statement at the product, epic or feature level, providing a solution is a dangerous thing to do. You’re likely imprinting what you believe the solution to be into the response, rather than determining the solution via discovery, definition and story-writing activities.
Before those activities are carried out, you should be general in the approach that you are suggesting. Imagine you’re at 10,000 feet, it’s a high-level overview of what you think the response should be to the problem statement. Suggesting solution specifics or technologies is inappropriate as you have no customer experience research or feedback (e.g. from wireframes) to suggest that this is the right path.
#5 – Be clear on your measurement
The final part is the measurement. As Ian stated in his article, visualising value is key. Your measurement within the hypothesis statement should follow the SMART pattern. If not, I would recommend revisiting your problem statement to ensure you are clear on the value you are trying to deliver to the business.
In an ideal world, the measurement will be of monetary value – a key part of success with value streams. But at smaller scale this is not always possible. In these cases, ensure that the measurement you introduce means something and clearly ties back to the KPIs underpinning your strategy.
At MMT Digital, we help clients build digital products that transform business performance and a structured, value-driven process is fundamental to our approach to Lean Product Delivery. If you feel that your organisation could benefit from support with product strategy and roadmaps, please drop me an email at firstname.lastname@example.org.