Research management: How to manage knowledge workers

Management is a well-known term that everybody has heard before. All aspects of our lives require management, from managing our home, and our study to our work or business.

Research management: How to manage knowledge workers

Management is a well-known term that everybody has heard before. All aspects of our lives require management, from managing our home, and our studies to our work or business.

Similarly, management is instrumental for research. Without good management, research cannot be successful.

In this post, we will discuss research management focusing on how we can effectively and efficiently manage knowledge workers (that is, the researchers!).

By the end of this post, we can understand key factors to manage and how to manage these factors for our successful research.

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Modern management theory

This post is based on the management theory or concept proposed by Peter Drucker [1,2] with some modifications tailored for research activity and researcher.

Peter Drucker is the father of modern management. He has formulated essential management concepts that shape current modern management science.

His key management concepts are, such as the concept of decentralisation, workforce development, knowledge worker, corporate social responsibility (CSR), organisational culture and customer experience.

Especially for this post, we will look at the concept of managing knowledge workers, that are the researchers themselves. The consideration is that researchers themselves are the main component of all research activities.

Managing knowledge workers has a special management concept as explained by Peter Drucker as the concept of managing oneself [2,3].

That is, we need to manage ourselves first!

We focus on managing individual researchers (ourselves as a researcher) and a group of researchers. Since this discussion focuses on individuals or a group of some individuals, the concept may not be directly applied to an entity of a large group or large research organisation.

Researchers or knowledge workers operate as if they are the CEOs themselves. We cannot micro-manage these types of workers.

Each of them has their ego, value and goal. It is very important to understand this aspect so that a coherent research activity and collaboration can be performed to achieve both individual’s and group’s research goals.

In a research group, all researchers should work and collaborate (within and across other groups) together toward the research goal of the group and their researcher. A research group leader should define research visions and topics and delegate each topic to their researchers with complying research knowledge, skills and experiences.

The process can be briefly explained as follows: The group leader and the researchers set their research goals together, each researcher details his/her research plans following their expertise and objective, the group leader and researcher together monitor research progress and take necessary corrective actions, the group leader and researchers periodically evaluate their progress and results and the group leader and researchers received feedback based on the research results (such as paper publications and funding acquisition) and, then, reward/recognition awarded.

Key management concepts for knowledge workers (including researchers) are discussed as follows.

Manage our strengths

The first thing that we need to manage is our strength!

Because our strength is the thing that we need to focus on and improve continuously.

Only by operating on our strengths, we will become effective and productive and can produce excellent research.

All performer workers and researchers operate on their strengths.

Remember though, strength and expertise may not always be the same. Instead, very often they are different.

Expertise is something that we know much or deeply, but strength is more than expertise, it is something from our side that gives us competitive advantages, for example, our strength is in mathematical modeling. This strength can be in various expertise, such as optimisations, statistics or numerical modeling or physical modeling.

To manage our strengths, we need to know what our strengths are. After knowing our strengths, then we can consistently develop, improve, practice, perfect our strengths and execute research plans to achieve excellent results.

Unfortunately, many of us do not know (or have a false impression about) what our strength is.

To find our real strength, Peter Drucker proposed a feedback analysis. In this analysis, it is suggested that we write down any of our decisions and evaluate the results (positive/negative) after some time, e.g., after a year or so. By doing this, our strength is the one that gives positive feedback and otherwise [2,3].

Yes, it takes some processes and time to understand what our strengths are.

Once we already know our strengths, for example, in designing a 3D model or designing an experiment, we then need to focus on working on our strengths to achieve excellent results.

We should ask for help for something that we are not good at or is not in our expertise. For example, we can use software to perform a complex statistical analysis rather than doing it ourselves in MATLAB when we do not have as strong programming and linear algebra skills to calculate the statistical analysis by ourselves.

That is, we need to and do not hesitate to ethically ask for help. Because, if we focus on our weaknesses, instead of our strengths, we will waste a lot of resources (time, energy and cost) and will only achieve “so-so” or mediocre results.

Do not be arrogant!

It is very tempting that those who are experts in one field tend to be arrogant and overlook other disciplines.

Avoid being trapped in intellectual arrogance!

Successful research or work requires a combination of different knowledge, disciplines and skills. Also, we need to understand how to work with people and should not only think about our activity.

Keep learning new things, even though they are not from our disciplines. The more knowledge we seek outside our expertise, the more wisdom we will get.

READ MORE: Is research expensive?

Manage our attitudes (manners)

In any work, including research, we need to manage our attitude or manner. we need to interact and/or collaborate with other people in our research. These people have a different mindset, culture and way of thinking.

Hence, a good attitude or manner can be the “lubrication” to reduce or avoid friction in people's interactions. This is a law of nature that two bodies that are in contact with each other will create friction.

Small things can be used to increase “manner” when we interact with other people. For example, saying “thank you”, “please”, “asking about their weekend” and mentioning “the name” of our co-worker can be a great manner to boost collaborations.

By having good manners, two people can work with each other efficiently and effectively even if they do not like each other [2].

If we observe a great researcher failing in a collaboration or multidiscipline research project, there may be an indication that there is a lack of manner from that individual.

Manage our values

Values or ethics are one of the most important principles that we should have in our lives.

Our values are something that is considered standard and important in life, such as honesty, humanity, freedom, accuracy, trustworthiness, etc.

We can explore our value by asking, for example, what is the main purpose of our research? Why do we perform research?

We should have a correct value and ethics to be able to perform successful research. If our main purpose in doing research is only to get rich (only for money purpose) instead of to contribute to the knowledge in our disciplines or to solve problems, we may fail in our research as the “getting rich” purpose is not the correct main purpose of doing research.

Also, to create harmony in research collaborations and to boost a collaboration performances, we should select partners that have similar value to us.

If our value of doing research is to, for example, find a solution to solve society's problems and our partner's value is to get money as fast as possible, then we may have a conflict during the research collaboration.

This conflict can then cause a failure in the research collaboration.

All research activities should align with our values. For example, if our research is to find a new medicine to help people, then we will work hard and perform many experiments carefully to achieve the best results.

READ MORE: Five fundamental rules for scientific writing that are applicable for all fields

Manage our resources

Resources, including for example our time, energy and capability, are limited. Since we know that we have limited resources, it is important to best use of these resources for our research and work.

We should focus our resources to maximise what we are good at, that is our strengths.

It is known that we will need a greater resource to improve ourselves from zero to a mediocre level than to improve ourselves from competency to excellence.

That is, it is much better to use our resources to improve our strengths or what we are good at to a level of excellence rather than use the resources to improve our weaknesses up to a mediocre level.

An extreme example is as follows. If we are good at chemistry, we should focus our time and energy on improving our expertise in chemistry instead of learning another field, that we do not good at, from zero.

Of course, very often, we need to learn also some supporting knowledge for us to be able to master, in this example, chemistry, such as reading skills, some computer skills and statistical skills. But we need to learn these skills just enough to support our main expertise to learn chemistry instead of learning these skills to be the expert in each one of them.

Manage our battles

Understanding where we belong is very important. We know that our resources are limited.

Not only do we need to focus on our strengths, but also, we need to select our “own battle”.

We need to understand what our capability is and how many resources we have. That is, we cannot do everything and say “yes” to everything.

If somebody wants to ask us to collaborate with him/her, we need to be honest with ourselves, whether we have the capability and the resources. If we do not have both of them, it is fine to say “No” to the offer.

Sometimes, we can work on a big research project. Or maybe, we work best in a small research project. We need to understand our specific research preferences where we can thrive.

In research, especially nowadays collaborations are encouraged, it is very easy to accept or offer a research collaboration with other research groups or researchers. Very often, we write many research proposals with different groups to get funding.

However, although the research topics of the proposals or collaborations are within our expertise, too many research activities beyond our resources, such as time to manage or the number of researchers to do the research will backfire on us.

For example, we may miss many deadlines, cannot deliver results in time or even brunt out. In addition, our research members can also get the negative impact of all the activities that are beyond the capability of our research group.

So, we need to really focus on research activities that we have the capabilities and resources, such as equipment and laboratory. By focusing on our expertise and resource, we can achieve research excellence in our disciplines.

READ MORE: Research is a broad ecosystem: All results are important!

Manage our learnings

Learning is a life-long activity. No matter how expert we are in our field, we still need to keep learning to find new knowledge and skills related to our field as well as learn new things outside of our field that can be used to support our research.

Remember, we do not want to change ourselves by learning something. Instead, we want to improve ourselves.

For example, we use a specific machine learning method to learn our data. over time, more and more new machine learning methods have been developed that can learn from our data faster and give high-accuracy predictions.

By learning these new machine learning methods, we can improve the use of our data.

In addition, we can try to learn something that is outside our current expertise or discipline. We may find something interesting or new ideas that we can bring to our disciplines. Very often, viewing the same problem from different angles will give us new ideas for new solutions that can be much better (more effective and efficient) than current solutions.

Remember strength and expertise may not be the same! Focus on our strengths does not mean focusing only on our expertise.

After learning something, we need to ack on the learned knowledge. For example, after learning a new statistical analysis method on data, we can apply that method to our future research data.

Manage our contributions

Contribution is the most important aspect to be looked at when we perform research and work. We should make sure that our contribution to the research or work is significant and obvious. If not, we should rethink the research. Maybe, we need to re-plan or re-do the research.

The formula is that the harder we can get results from our research, most likely, the more significant and visible the results will be.

Basically, there are three main types of contribution to research:

  • Contribute to a new method or model or solution applied to a new problem.
  • Contribute to a new method or model or solution applied to an old problem.
  • Apply an established method or model applied to a new problem.

The first one of course has the largest contribution compared to the later two.

A new method or model or solution can be an old one but significantly improved. For example, an improved model that considers non-linear effects compared to a previous model that only considers linear effects.

READ MORE: Calculus and linear algebra as tools for statistics

Manage our responsibilities

We have to understand that a researcher or knowledge worker is an individual who has his/her own values, way of thinking and strength. That is, we need to accept other researchers as an individual.

We need to define clearly what is our responsibility in a research project, whether as data analysts, experiment engineers or technicians, data collectors or other responsibilities. Also, we need to understand what the responsibility of other people is.

By managing our and others' responsibilities, we will automatically manage the relationship among the researchers.

Managing responsibility requires us to make good communication among researchers. This good communication will help in assigning clear responsibility for each researcher.

Data analysts may be able to work remotely, but technicians or engineers who set up experiments need to work offline in the lab or workplace.

Nowadays, hybrid working or even full remote working is common. Hence, clear responsibilities should be defined for different researchers who work offline or remotely. We need to understand the strengths and behaviour of each researcher so that we can maximise all resources toward our goal.

Manage trusts

Trust is a well-known aspect that all people respect. Remember, it is difficult to get trust, but it is very easy to lose trust!

People can work and collaborate because of trust among them, not necessarily because they like each other [2,3].

To build trust, we need to show our responsibility, real contribution, performance and real results. That is, we need to show that we can consistently deliver the results of tasks given to us.

For example, if our task is to implement an algorithm for data analysis, then we need to deliver the software as requested within the timeline. If can do this delivery consistently, people will trust us with our capability and will be willing to work with us (they do not necessarily like us though).

That is, we need to build credibility to get trust!

Manage our excitements

Research is a marathon. That is, research is a long process that requires resources and time.

Therefore, we need to manage our excitement in research. By managing our excitement, we can avoid boredom. If we get bored, we will not become productive and then will not achieve our research goal.

One way of keeping excitement is to Look at other or alternative research fields outside our core expertise. For example, if our core expertise is in manufacturing processes, we can start to work around our expertise, for example, working on something related to material science or even computer science.

Learning new trends in our field and other related fields can also give us excitement. For example, following what the trends in the manufacturing industry in the next 5-10 years in different countries will be or following what the trends of new deep learning models that have been applied by various industries will be.

Another way is to find other meaningful and rewarding activities other than our core expertise. For example, we can be involved in a community voluntary program to help old people in our city.

This activity can be considered as a “second career” that can also give us some sense of achievement and finally avoid boredom.

READ MORE: Demystifying p-value in analysis of variance (ANOVA)


In this post, we have discussed research management focusing on the management of knowledge workers based on the concept proposed by Peter Drucker.

A researcher is considered as knowledge worker. This type of worker is special as they operate as if they are their own CEO and cannot be micro-managed.

Essential concepts to manage researchers have also been discussed. Several important concepts are, such as, managing our strength, managing our manner, managing our value, managing our resource and team, managing our responsibility, managing our learning process, managing our contribution and managing our excitement in research (avoid boredom).                                                                                                          


[1] Drucker, P., 1999. Management Challenges for 21st Century New York: Harper Business. Rosabeth Moss Kanter (2001) Evolve, pp.192-196.

[2] Drucker, P.F., 2008. Managing oneself. Harvard Business Review Press.

[3] Drucker, P.F., 2020. The essential Drucker. Routledge.

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