Researchers can be regarded as extreme knowledge workers. A fresh research manager will no doubt face some challenges: How do you lead people who know more than you, who are more intelligent than you, who can think more strategically than you? Management ideas that work for Walmart or for Microsoft will not work for research organizations. But what will work then?
I manage a small research team, but I don’t have much formal management education. In the last couple of years I have tried to educate myself by reading some management literature. Some of the management ideas I read about have changed how I see myself as a research manager. These ideas have guided me into making myself a platform for my research team (read below about what I mean by a platform). I try to define my job as 1) making sure my team members are motivated to do their best as researchers, and 2) making sure we don’t forget essential tasks such as fundraising and strategy work. Here in this blog I summarize six management ideas that I have found useful in my own work, and how they fit to managing researchers.
Senek’s golden circle model
Simon Senek’s book “Start with why” is less empirical than that of Collins. Nevertheless, his golden circle model is inspiring and relevant. It simply makes sense. That is probably why Senek’s TED talk about the model is one of the all-time most watched talks at TED.com. Senek uses a number of case studies in his book to illustrate the validity of the model, so the model is not completely un-empirical. Senek’s model fits well with the process of research.
The model is summarized in the form of three questions that you need to answer in order to build a strategy. These questions are illustrated as three circles as shown in Figure 3. The what, the outer circle in the model, is about the tangible results of your research. In most cases these will be academic or other publications but they can also be novel concepts, designs, prototypes, patents, etc. The middle circle , the how, is your research method and paradigm. Do you do qualitative or quantitative research? Do you follow a positivist or interpretative paradigm? What is your favorite data collection tool? The why question –probably the most important one –is about your research questions and how you generate impact. What drives your research? Why do you work in this particular research area? What impact do you want to make through your research? What are the types of problems you wan to solve? For whom? These are all questions that need to be answered by a researcher who wants to stay motivated and relevant. Senek’s model makes these questions explicit, and makes you think and reflect about them. An important part of Senek’s argument is that you should start from inside –first answer the why, then how and then what –and not the other way around. We all know researchers who regard the number of their publications –the what of their research –to be the most important criteria. We also know those researchers with impact who publish a few good articles. Which one do we want to be?
Collins’ hedgehog model
One of the most difficult things you can ask a researcher to do is to prioritize one research project above another. Researchers are curious people by nature. Anything new is exciting and an opportunity to do research! Additionally, we researchers are often in charge of defining our own projects. This puts great demand on our self-management and prioritization skills, so that we don’t commit to do too much, get burned out, and lose strategic focus.
Any model that can help us prioritize is therefore welcome. Jim Collins’ book “Good to great” is a popular management book based on a study of more than 500 extremely successful companies (based on longevity and cash flow). I have found the hedgehog model introduced in this book easy to grasp and applicable to research management (see Figure 2). Researchers do research because of their passion and curiosity, which is one of the three ways to prioritize (Ask yourself:”Am I deeply passionate about this project?”). Additionally, researchers are rewarded for the novelty of their results. Any academic result has to be compared to the state-of-the-art and demonstrated to be novel. Otherwise you cannot publish it in prestigious journals (Ask yourself:”How is my research better than that of all other researchers?”). The third element, economic engine, is also extremely important. No research can be done without funding and availability of resources (time, money etc.). However, this last part is what researchers find boring! No researcher likes to write grant applications, but they have to! (Ask yourself:”What is the long-term economic engine for this research?”).
Ries’ Lean startup
When I first read Eric Ries’ book “The lean startup”, I though “At last, a research-based innovation method!” The model is shown in Figure 4 and is based on experimental and iterative introduction of innovations. It can be adapted to empirical research involving technology or other forms of innovation.
You start with some idea –in research terms: hypothesis or proposition –and create a product –or an intervention in research terms. The intervention can for instance be a new technology to be tested, an experiment involving a new way of working, or anything new you want to test. The intervention will test your hypothesis, and will be used as a vehicle to collect empirical data. The empirical data will help you validate your hypothesis, or throw it away –what Ries calls pivoting. The model is totally based on empirical learning, learning by collecting empirical data from the field, learning by doing experiments. And, as part of the the process, you actually build a business. A central part of the model is to iterate through the idea-product-data cycle, and iterate fast. Iteration is definitely one thing that researchers can learn to do more. Many research projects spend months and some even years, in a single phase e.g. idea generation, before moving to the next –a phenomenon also called analysis paralyses or armchair theorization. By following the lean startup model researchers can plan to verify their hypothesis more frequently and empirically, and adjust the course of their research accordingly. In the same way that the model reduces the risk of investing a lot of money in an startup that is doomed to fail, it can also help researchers avoid spending a lot of time and effort in pursuing research that is not worth doing.
Lencioni’s team dysfunction model
A lonely researcher has limited output. If you want to do important research you need a team of researchers. How do you make a group of researchers produce top results? I found the book “The five dysfunctions of a team” by Patrick Lencioni useful. The book is written in a fiction form and is a highly readable book, which is probably why it is one of the most popular group dynamics books. The book is based on a layered model of group dynamics, as shown in Figure 1. The model, as described in the book, is a bottom up model. The protagonist of the book, a CEO, starts with the lowest dysfunction (absence of trust), and gradually moves up to the highest dysfunction (inattention to results) as she builds builds up her own management team. The elements of this model are not new and are studied by many researchers. Lencioni summarizes this knowledge and tells the story in an entertaining way.
My view is that the model is conceptually good, but for researchers (and probably for a real management team in the real world) it does not work bottom-up. It works from top to bottom. Researchers are not inspired by shallow team/trust building activities. You don’t motivate a team of researchers by taking them to go-cart, if they are not allowed to discuss their latest paper with each other. We researchers think these team-building activities are ridiculous. On the other hand, we think producing results –meaning: writing papers –is motivating. Ask two researchers who don’t know each other to write a paper together, and by the time the paper is written they will have created a high level of trust in each other as colleagues. Therefore, my experience is that the model is good, but only when going from top to bottom. One should create opportunities for producing great results together, and the trust will follow.
Platform business models
I work in a large research institute. I believe that in any research organization the most central organizational unit is the lowest level research group. That is where the knowledge of the market and the research problems lies. Research these days is so specialized that each research group is forced to have a very narrow focus on an area that often only that group in the organization understands. Additionally, the network of partners and relationships are unique for each research group. The role of the larger research organization should therefore be to function as a platform for the research group.
Platform models have been studied intensively at least in the last couple of decades. Henry Chesbrough wrote about them in 2003, using Adobe’s postscript platform as an example. Since then we have seen most companies moving towards platform models, where they focus on a core set of services developed to serve a large number of users. In the area of research management, Ernø-Kjølhede et al. use a model for research management that resembles a platform model. I recommend you to read their article.
Qualitative models of research
Contrary to the five ideas I discussed so far, the qualitative research model is taken directly from research but can be applied to any type of management. Qualitative research is research that helps you make sense of complex and apparently disorganized phenomena. Modern management happens in complex an rapidly changing settings. Qualitative research methods don’t need to be limited to research. They have the potential to help today’s managers make sense of their own organizations. For instance, Svend Brinkmann’s book “Qualitative inquiry in everyday life” shows how you can start thinking in terms of qualitative research in all aspects of your life. I have started to regard my research team as a phenomenon that can be studied and understood using qualitative methods.