Academia and Industry Compared

In the beginning of this year I switched careers. I quit my job as assistant professor and became lead data intelligence in Obvion, a mortgage provider in the Netherlands. Just before making the switch I wrote a piece on how I felt about making that switch. About four months in I wrote a piece on why I think an academic career was not for me (tldr: I might not be resilient enough and it is too solitary of a job). And now I’m reflecting (following three quotes) on some differences I’ve come to realize exist between academia and industry.

In my previous role my work consisted of doing research (both applied/with industry and fundamental), teaching and applying for funding. To summarize it, I spent quarter of my time doing research by myself or colleagues in university, quarter of my time doing research with industry partners and about half of my time teaching (courses and thesis supervision). Whatever was left I spent on writing grant proposals.

In my current role things are different. Like numerous before us, at Obvion we have realized that we should leverage data in order to serve our customers and the advisors that help them. There is quite a transition to be made, that I like to describe as the switch from conventional business intelligence to more contemporary data science. In the current situation our business intelligence is done mainly through SQL and Excel (basically spreadsheets) and we are transitioning towards using dashboarding and predictive analytics/machine learning. I do this with my Data Intelligence Team within the department of Data Management and to really summarize it, my current activities are three-fold:

1. I am reshaping our team of data analysts to become competent with the required tools and methods
2. My team is helping with designing our data warehouse, and
3. Our department is taking the rest of the organisation along the next steps in terms of data-driven maturity

A lot of words, but it all boils down to providing input at meetings with our tech partners (e.g. the organisations helping us out with our Data Warehouse and CRM solutions), making sure that our current reporting activities remain consistent and collaborating with different departments in data science use cases. And while there is quite a lot on my plate, that I am not even sure I am trained for, I feel that three aspects of my current role make it way more manageable than my previous role. I’ll go through those aspects along three quotes:

If you want to go fast, go alone. If you want to go far, go together

African proverb

One of the biggest differences is the number of colleagues you work with. In my previous career I can count the number of actual collaborations on two hands. For my research I interacted mainly with two professors, one post-doctoral researcher and a PhD student. In terms of education I interacted with a small group of faculty teaching in the same program, with our examination board and of course my students. And then in the context of the BISS Institute there were another dozen people. But in my current job there are many more people I interact with. My team has a nice number of people, both on Obvion’s payroll and external hires. On top of that there are almost always internship students. Apart from that, I interact almost daily with the two other leads of our Data Management department and our manager. And aside from my colleagues/peers, I have regular interactions throughout the organisation with people working in the different departments we service. 

And (to me) this is really invaluable! The collaborations are more intensive than what I am used to. The contacts are more frequent, but also there is less fragmentation, if that makes sense. Previously, the group of colleagues I was teaching with, was quite disjoint from the group of colleagues I did research with. But now, whenever you talk to a colleague, they have the same activities and goals. So there is a constant feedback on how things are going so there is no time to ruminate about things you did. You made a mistake? You’ll know within a couple of hours when people impacted by your decision come knocking on your door. It will not take 6 months until you’ve written about your decision in your paper, your paper gets reviewed and your reviews make you aware that you made a mistake. But this also goes for the positive feedback. But this also works the other way: Do something cool? Within a couple of hours you receive the praise on what you do.

Having the critics praise you is like having the hangman say you’ve got a pretty neck.

Eli Wallach

The high standard you need to reach to publish your research means that every decision is scrutinized and should be taken carefully. If there is a decision to be made with regards to the design of your experiment, or the positioning of your work in a stream of literature, you best make sure you have at least three arguments to justify your decision, preferably in the form of published results. One wrong decision can make the difference between publishing a paper, or having to redo your research.

This also results in academics being super critical. Let aside whether it is constructive or less constructive, we are kind of trained in identifying inconsistencies or weaknesses or fallacies in reasoning or justification. So there is this focus on the things are wrong, that quite often overshadows the attention for things that are good.

In my current job there is less criticism. The mindset is more along the lines “if it works, it works”. One major reason for this, I reckon, is that everyone is working for the same goal. Like if your colleague is successful, that’s good for the organisation, which in turn is good for yourself. This is not really the case in academia, where maybe your colleague’s success is different. But especially when doing peer reviews, there is no real motivation to focus on the positive. That doesn’t mean that the feedback is not fair or honest, it is just that the emphasis is more on what could be improved than on what is good. All in all, I do feel that feedback in industry is not necessarily more honest, but it is more balanced.

Responsibilities fall heaviest on those willing to take the load.

Heather Day Gilbert

I remember when I was stressing about teaching a course for the first time, my head of department told me “of course you want to do a good job, but in the end teaching is not a life-or-death situation, students won’t die if you do poorly”. And that’s true. In the end the responsibilities as faculty are relatively small. Even the highest ranked academic has marginal responsibilities. I have the feeling decisions in industry have more impact and bigger risks. If you make a (wrong) decision in academia worst case: you have to start over and you’ve wasted your time and some resources for data collection. In industry you might be involved in decisions that could cost the organisation millions if made poorly. And because of this, the responsibility of making decisions is shared by a whole chain of command. Decisions that only affect your work, you can make yourself. Decisions affecting your team you make with the team. Decisions that affect departments or budgets, you run past a manager. Decisions that affect other departments or the organisation as a whole, members of a management board have to argue.

And this is nice, no decision you make is going to reflect on only you. So gone is the anxiety at the beginning of your project when you decide for a certain research design or methodology, because you are forced to run it past multiple people that evaluate the decision from multiple perspectives. At the same time, the flip-side of that coin is that the power with regards to making decisions is a lot less in industry than in academic research. You work in industry and you have a research question that needs answering? Everything goes! Just choose and use the tools that are suited for the job. Decide today, implement your research tomorrow. In industry however, things are a bit different. Sadly (or maybe luckily) you’re bound to stick either with decisions that have been made in the past and have already gone to the process, or go through a whole decision making process where anyone is involved from the procurement/purchasing side of things, to the legal side of things, to the budget/financial side of things. All of a sudden you’re in the situation that you can decide something today, but your decision is only approved weeks or even months later.

Reflection

So personally, I am quite happy where I am now. Looking at the number of self-help books that I have with regards to anxiety and anxiety-related issues such as procrastination and imposter syndrome, anxiety plays quite a big role in my personality. And being able to work together in a team, get balanced feedback and share the burden of decision making really makes my work a lot more enjoyable. All in all, I do not think I worked harder in my previous role than I am doing now, as a matter of fact think I might work even harder in my current role. But there are way less opportunities for me to start doubting myself and have my crippling anxiety setting in, so in the end my work now costs me way less energy. And who knows, maybe this experience will even create the self-confidence that would allow me to pick up some academic activities again at some point in the future…