"Doctoral research" v/s "Product research"
One may already have a good measure of research techniques gained over that PhD / doctoral research, but would that suffice as a transferable skill for product roles?
DISCLAIMER:
This article is in no way intended to belittle the efforts & activities that form an integral part of the scholarly research work carried out as a part of one’s doctoral research / academics. The very fact that PhDs ought to identify a niche problem over their respective streams & work towards proposing something that could be a workable solution to making even a wee bit of progress with earning that degree is an absolutely commendable effort.
Also, looking at the world one'd realize how doctoral research has formed the basis providing more than enough context to fueling product innovation.
Over the course of mentoring product managers in the last 2 years, I have had the good fortune & opportunity to work with many PhDs from the Americas hailing from really multivariate streams of study. When some have managed to land leadership roles in product, some have made it to senior management roles at non-product orgs. But as a part of my initial exploratory call I do make it a point to shoot a few questions at my mentee-to-be so as to help me gauge their motivations, aspirations, behavior & also contribute to something of a SWOT analysis. And one question I pop mandatorily is:
Why product management?
I was amazed at how many PhDs mentioned how they had actively participated & were also able to cover the nuances of conducting research, like:
basic need for research work
art of formulating hypotheses
framing the problem via a problem statement
what data to look for & put an emphasis on
awareness of the wide room for biases to sneak in
methodical way of breaking information down & making it usable
proving (/ disproving) it by employing data craftily
arriving at a state that could lead to progress thereof
When most of that does have a parallel with product research (research work undertaken by product managers / teams over the PLC) there are subtle differences between the two, which is what I shall cover over this article.
Yes, product work starts off with research & that’s what leads to a bankable discovery as well. But here are some subtle differences between the two.
NOTE: Being a PhD & carrying a certain degree of exposure to the research work could put you in a comfort zone over the types of research activities you / your teams ought to undertake provided you understand the ulterior motive & uphold the purpose at all times.
But just as any product mentor would tell you, the most important part of bagging a product role is about how you work towards elevating / improving those transferable skills to tick off those A-level skills deemed absolutely essential for PMs.
So, here’s a list of skills PhDs may have built over their doctoral research & should focus on to help them elevate their chances of bagging product roles.
1. Information search / Building references
Going on an indefinite search in looking for all the information needed, enlisting those biblical references & nested references thereof is a crucial step every research activity could start off with, which almost every PhD would be pretty strong in given an extensive slice of time they have spent on it.
Information searching is a skill that associates with product management as well. Given the way one is bound to set the ball rolling & dive into primary / secondary research activities for a host of stuff to help reemphasize the idea itself is also a crucial step every PM does spend time on during the Ideation stage of the PLC.
2. Problem formulation
Look at the world from the lens of a strategist & one’d find that there are tons of gaps that obviously convert to problems, both major & minor. But having said that, a doctoral candidate ought to know how to brush away all the clout & zero-in on a problem, understand it at a granular level & see if it aligns with their cause.
Coming up with a crisply drafted problem statement is often perceived as half the job done in the product world given how that is the starting point & also the foundation that determines the direction / future course of the product. Being able to drop all the ambiguity from this exercise is a great skill to possess for PMs.
3. Building hypothesis
When the problem statement could point to a broader area of study, the need to dig in deeper so as to identify those problem layers & building a hypothesis over each of them is essentially what doctoral research usually involves.
Zeroing in on a problem, being able to individually strip it down to a level of granularity, proposing a few odd hypotheses over given a user group of a market segment in trying to establish a validation for it is often considered as a precursor to every feature out there that was ever built.
4. Data collation
As an academic researcher hitting that reference list obtained in the previous step & individually extracting exactly that part deemed useful to further the research activity happens to be a mandatory step everyone ought to pass through. There’s obviously a need to collate / sort / rank all the data that is required to prove / disprove a hypothesis based on the relevance.
When all of that collation is majorly done online, the disruption in Tech has induced a bout of innovation in the way data is gathered / collated today, making it ridiculously easy & also cost-effective for anyone who is looking to do so. Many CDPs (Customer Data Platforms) are employing LLMs (Large Language Models) to extract just the required data slice that could help them decipher the problem to even a hyperlocal level. The only thing one ought to be aware of is “where to look for what”.
5. Data slicing
Usually the data collected may cease to be any use in its raw form & may need multiple cycles of skimming & slicing so as to make it readily usable for decision making / analysis. Although doctoral research is not direct as for the impact to the market, it could still involve a lot of cleaning which could subjectively change based on the area of research.
The hypergrowth of Chatbots & GPTs (Generative Pretrained Transformers) over the recent past has made it super-simple to extract a slice of data & the AI-based tech could also help with interpreting it. When the world has moved towards Tech, it could become very difficult if one doesn’t have any knowledge of these.
6. Data analysis
When there’s no scarcity of data in the world today, the whole focus for PhDs at most times isn’t to get their hands on it, but to find innovative ways to use it / employ it towards effective decision making so as to facilitate / aid their cause.
Understanding exactly what questions to ask & where to look for answers, what qualifies as a valid answer & what doesn’t is obviously a great skill to possess as a PM, for even an entry-level PM is often found getting their hands dirty with data, analyzing it & so is a product leader as well. Just that their purpose / perspectives may be different over the data points.
7. Inference / Decision making
When being able to interpret & infer from the data on hand, make those decisions of pursue / pass is a common trait across the board, the impact is more direct here for PhDs given how they are bound to tread on newer paths, exploring routes nobody has ever been on before.
Decision making also happens to be a crucial skill for product people across the board as one is usually found dabbling with tons of data, requesting / collaborating with the respective teams to get their hands on the slices that may have gone amiss, getting them to an usable stage & make them bankable.
8. Solution fitment
Coming up with list of alternative solutions to the proposed problem statement, using & applying the knowledge of the world (which is where a mentor could come in), trying to dig deeper into identifying patterns in the data already collected & trying to understand if the solution proposed would fit the targeted space is a mandatory & pre-final step over doctoral research.
Speculating over the positives / negatives of the situation / problem / solution is closely associated with the product workflow. And that is one quintessential skill every product manager / leader ought to posses given how one may also be expected to get skin deep into it at a regular cadence.
9. Proposal writing
Given that most of them who have PhDs often carry enough work experience already prior to their doctoral degrees would make leadership positions a default target, writing proposals could double up to RFIs, RFQs & RFPs.
Writing proposals based on the findings (data & inference) from the research, coming up with best ways to convey ideas via reports, working on those presentation skills is a great skill to have as a product manager.