From Ivory Tower to Corporate Tower: 9 Learnings from My Transition to the Corporate World

Academia and the corporate world can vary significantly across various dimensions such as project execution, cultural dynamics, and task management approaches.

In this article I want to share my personal learnings from my transition from academia to the corporate world.

Photo by Erol Ahmed on Unsplash

Two Towers: Two Worlds

I won’t keep you hanging with a never-ending tale of my career journey, but a quick sneak peek is crucial to set the stage for what comes next. If you’re itching to dive into the juicy learnings, feel free to skip ahead. However, for the curious minds hungry for the backstory of my leap from academia to the corporate world, drop a comment. If there is interest, I’m all in for crafting a detailed article to spill the beans on that transition.

The Ivory Tower: Academia and Applied Science

If you can’t explain it simply, you don’t understand it well enough. - Albert Einstein

This quote nails it. And it is not only Einstein who sees it that way. Richard Feynman was also famous for focussing on a deep understanding - in research and in teaching.

Personally, I’ve also always believed that explaining a topic to someone else greatly enhances my own understanding. This was one of the reasons for me to start working as a part-time tutor for mechanical engineering during my master program.

But it was not only the teaching-part that interested me. I’ve consistently been drawn to the scientific facet of university life as well. Writing scientific articles, in particular, intrigued me. However, I found pure scientific pursuits, devoid of any attempts to apply the results to the “real” world, less appealing. Hence, a solely scientific career was not a consideration for me.

Upon completing my studies, I had the chance to write my master’s thesis as part of an applied research project in collaboration with an industrial partner.

I really liked it. Working at the intersection of theory and practical value has both: scientific curiosity & practical applicability.

Therefore, I decided to start my first full-time job in applied science.

I worked in a highly specialized research team in the realm of Industrial Engineering and Digitalization. My colleagues all had at least completed a master program and were (junior) experts in their fields. I learned a lot.

All together, my time in applied science was great: I was working on research projects and industrial projects on a broad variety of topics ranging from value stream mapping to Data Science and AI topics. I even had the opportunity to pursue my PhD while maintaining a full-time job, thanks to the project securing funding.

I really liked the fact that I was learning so much. I was learning new methods, applying methods by developing software and I also learned soft-skills: we had to present the results of our projects to our industrial and research partners. Furthermore, I learned a lot about how to manage and steer projects.

However, working in academia always had a goal: finishing my PhD. To me it was clear from the start that I would move on once I completed my studied.

I did that.

Once I finished my PhD, I made the transition into the corporate world.

The Corporate World

I am working in the corporate world for four years now where I serve as the manager of a department dedicated to Digitalization and IT.

My tasks are managing a portfolio of projects in the realm of digitalization, automation and IT. Even though I am still working on some innovative topics, my altitude has changed: it’s more about keeping the overview of the portfolio and delegating tasks.

Furthermore, I am responsible for solutions (mostly IT systems) used in production running smoothly - I manage a team of systemadimistrators. Some of the solutions need to perform 24/7/365.

Most of the time I enjoy my job. However, it is very different when compared to the tasks I had in applied science. Where I would brainstorm complex, novel ideas at the edge of practical feasibility with a highly specialized research-team, I now find myself responsible for the operation of legacy systems. Oftentimes I have to argue with a broad variety of users about how new features could potentially crash an existing solution. Curiosity is not the main factor anymore, but business value is.

Operation has its own charm. Knowing that the solutions we offer are actively applied in real-world scenarios, easing the workload for numerous colleagues in our cooperations is very motivating. Back in academia this was different: the topics were very novel, but it was not sure that the solutions would ever be used in practice.

There’s a certain appeal to projects in the corporate world as well: they are more about short lead-times and generating value quickly than about innovating radically - sometimes just for innovation’s own sake.

9 differences I observed between the two towers

1. Cultural Dynamics: Motivation

In academia, a key motivator is “learning.” In applied science, the emphasis shifts slightly toward creating value and “making the world a better place.” Within the corporate environment, this focus leans even more towards business value, which becomes the central factor.

These distinct goals also extend to shaping employee motivation.

In academia, individuals concentrate on exploring innovative topics, occasionally even without a clear practical application. The objective is to generate something new that can contribute to a scientific paper, with motivation deeply rooted in intrinsic factors. In the corporate world, motivation is oriented more towards extrinsic values like financial rewards and prestige, directly stemming from the emphasis on business value.

2. Specialization vs. Generalization

Expertise in the academic realm is highly specialized, a necessity for generating innovative solutions within a specific research area. In contrast, the corporate world, particularly for managers, demands a broader understanding across various domains. While each company maintains specialized knowledge to uphold its unique selling proposition, running a business effectively requires a broad spectrum of knowledge.

I noticed this myself.

In my role in applied science, I honed my specialization in crafting algorithms for production planning and plant maintenance. My expertise spanned both the development and implementation of algorithms as software tools, coupled with a deep understanding of industrial processes.

Fast forward to my current position as a manager in the corporate realm, and the landscape has expanded considerably. Now, my responsibilities encompass a diverse range of areas, including budgeting, employee management, project portfolio management, and more. It’s a shift from the intricacies of algorithm development to a broader scope of overseeing various facets of corporate operations.

3. Task Management: Number of tasks

Task management takes on a different dimension in the corporate world, where tasks demand a broader perspective. In the realm of research projects, tasks are often specialized, and the next steps are clearly defined (such as enhancing an algorithm’s accuracy to X in the next three days).

Transitioning to the corporate landscape brings a tidal wave of tasks. Without an effective notetaking system, the potential for feeling overwhelmed is imminent. While pen and paper sufficed in academia, I found it necessary to construct a tailored productivity system to effectively handle the multitude of tasks on my plate in my current role (cf. My Productivity Journey).

4. Innovation vs. Reliability

In the corporate world the operation of solutions has a much higher priority than the development of new solutions. Systems must be reliable and they must be reliable 24/7.

Innovation is present in the corporate world, but does not soley exist for innovation’s own sake. Radical innovation, however, is often met with skepticism as it often replaces established, traditional solutions.

When developing new solutions, it is important to think pragmatically: it is better to have solution components that work reliably than the latest, most sophisticated ones.

This is different in academia: you strive for the most novel solutions on the brink of usability or sometimes even beyond. This can be odd: in scientific papers, the introduction often integrates the state-of-the-art, yet frequently, the referenced sources are not practically utilized, despite being considered the current best practices.

5. Learning and Exploiting

To innovate does not merely mean to develop something new; it embodies a journey of continuous learning.

What I experienced in academia was e.g. absorbing methodologies from one field and applying them to illuminate another. The academic sphere’s approach to learning operates on a heightened meta-level, distinct from the corporate landscape.

However, corporations, too, engage in the art of learning, albeit with a distinctive flavor. Here, learning often involves the application of pre-existing, battle-tested solutions tailored to the their business context. While the term “exploiting” may carry a certain weight, it captures the essence: corporations progress by harnessing and evolving existing solutions within the unique panorama of their business perspectives.

Full-scale exploitation is a rare occurrence in academia. Once a new method is developed, the project concluded, papers are written, the exploitation phase is considered as complete. While the results may be referenced in subsequent initiatives, the practical implementation often becomes someone else’s responsibility.

6. Bureaucracy

Let’s dive into the bureaucratic maze for a moment. Now, don’t get me wrong – bureaucracy isn’t inherently evil, but it does have a knack for slowing things down. Picture this: You’re steering the ship of a mammoth corporation, and suddenly, decisions start taking the scenic route.

It’s frustrating, to say the least.

Imagine having to hit the brakes on a project that’s humming along smoothly, all because you’re stuck in the waiting room of a decision-making marathon. In academia, bureaucracy tends to flex its muscles right at the project’s kickoff. Before the wheels start turning, your project draft goes through the bureaucratic obstacle course. However, once your project takes off, interruptions caused by bureaucracy become the unicorns of academia – rarely seen.

7. Project management

At my job in applied science I learned a lot about project management. As the projects we did were close to industry we had shorter lead-times (when compared to basic research in academia).

I learned that a project has a clear start and a clear end (obviously).

In the corporate world, the dynamics can be quite different, especially when projects are conducted internally. Often, projects start with a brief timeline but tend to diverge from the initial plan. This shift can happen as different stakeholders have to adapt their expectations and requirements due to market changes after the project‘s kick-off. Projects in academia have the clear advantage of not being so closely linked to the market.

Additionally, the technology readiness level varies. The projects I undertook in academia weren’t prepared for production. They still needed to be integrated into existing systems.

In the corporate realm, I discovered that this final stage of application can be exceptionally challenging, as unforeseen issues often emerge only in this final stage.

8. Funding of projects and initiatives

Securing funding in academia can pose a significant challenge, particularly when dealing with nascent topics where the potential for immediate applicability is uncertain.

This is different in the corporate world. Funding for projects can be hard, however, it is by far not the hardest part. It is much more difficult to get the appropriate resources for a project. Working on multiple projects simultaneously is a common practice, and the question of whether the project team has sufficient capacity is rarely raised.

9. Knowledge management

In academia, where learning is a cornerstone, knowledge management plays an equally pivotal role. Research findings are distilled and shared within the scientific community through publications. Other scholars then incorporate these insights into their own knowledge base.

Diligent researchers typically employ various tools for knowledge management, including software to organize literature references.

Contrastingly, in the corporate world, managing knowledge can be a challenge. With a heavier project workload, there’s often limited time for reflecting on initiatives’ outcomes and documenting key learnings. Project teams must swiftly transition to the next task at hand.

Despite the challenges, there’s much the corporate world can learn from academia’s approach to knowledge management. Drawing from my experience in applied science, I’ve introduced some of these practices at my department. While we’re still making strides, I believe we’re headed in the right direction!