The Product Manager / Product Owner AS A Scientist
- Author: Roni Dolev Tamari
We’ve all heard it before – “Talented technology team builds amazing products!” That… doesn’t create the impact that they wanted, not enough customers end up buying or the users aren’t happy with it, or <some other disappointment>…
This is an especially common problem with companies that have a “brilliant” idea or technology that someone goes developing in their garage (if startup) / innovation product development group (if enterprise). This could be a new product or just a new feature of an existing product. Typically, the Product Owner or Product Manager in the organization specifies what to build. If they’re somewhat Agile, they even work closely with the organization to build it incrementally and hopefully deliver it continuously. But still, even then, too often the product or features don’t provide the expected impact/benefits. Overcoming this challenge is a common theme that is discussed by attendees at our SAFe POPM Course.
The POPM is often SURE they know what’s the right thing to build (aka the “God complex”) – usually this is based on market research, customer interviews, etc.
But too often, the POPM doesn’t know that they don’t really know. Other times, the POPM knows that they don’t know, but aren’t sure how to drive the learning so that more is known. The Agile approach is to build a working product and engage on an on-going basis with the customer, getting early feedback so that as a result of the customer’s interaction with your product – you will gain knowledge.
Does this sound familiar from another domain/world? Where else do people make concerted learning a matter of principle?
As can be guessed from the title of this article – the answer is in science – a close cousin of engineering. One of the basic pillars of modern science is using the scientific method and specifically its well-known-but-hard-to-pronounce hypothesis.
For those who are a bit fuzzy or unconvinced about how closely the hypothesis fits in here – the meaning of hypothesis as per the dictionary:
- A supposition or proposed explanation made on the basis of limited evidence is a starting point for further investigation.
- A proposition made as a basis for reasoning, without any assumption of its truth.
[emphasis added]
The famous British Biologist Thomas Huxley (a friend of Charles Darwin) once said:
“The great tragedy of science – the slaying of a beautiful hypothesis by an ugly fact.”
Who would have thought there could be such drama in science and the hypothesis 🙂
With this in mind, let’s see how “without any assumption of its truth” and “starting point for further investigation” applies to the POPM roles.
To approach things as a scientist, a POPM should first modestly understand that they have some underlying assumptions, honestly identify them, curiously phrase the hypothesis and openly and bravely seek the truth by evaluating the outcomes and then flexibly adjust based on the learnings.
For example, phrasing the expected business outcome as a hypothesis could be as follows:
We hypothesize that Feature A will generate 30% more transactions (or will cause users to do things 20% faster or to make 15% fewer mistakes, whatever the expected outcome).
It can be much simpler to have this approach as a startup, after all, you typically have to prove yourself quite quickly or the money will run out. In a larger more traditional enterprise, it’s often more difficult to adopt this mindset for various reasons such as the long lead time until reaching the customer to test the hypothesis, on-premise B2B environments, high customization as in professional services, etc. Nevertheless, as a POPM, one must always strive to make the desired impact, regardless of the organization’s size. In fact, the importance of having the right mindset in an enterprise is incredibly important to minimize the waste of developing too many (wrong) features. In large organizations, this is true for both Product Owners and Product Managers.
Once the hypothesis has earned its place of respect, as Konrad Lorenz once said:
“It is a good morning exercise for a research scientist to discard a pet hypothesis every day before breakfast. It keeps them young.”
So, to openly and bravely receive the truth, the POPM must evaluate the measured outcomes and decide whether they must show flexibility and discard their hypothesis or keep it. The Lean Startup movement introduced the terms for this as to pivot (change direction) or to persevere (keep on with the direction).
Applying pivot might feel difficult to the POPM, as it means that we have disproved our hypothesis. On the other hand, we will have learned something and hopefully avoid an “OMG” headline, and as Lorenz said, pivots keep us “young” 😉
