Decision with control systems

This article is part of our exclusive career advice series in partnership IEEE Technology and Engineering Management Society,

Most of the engineering is a decision -making. Engineer make decisions about product design, program management, technology road maps, research instructions, leadership of technical teams, and more.

As the previous president IEEE Control System Society And now 2026 Presidential Eats IEEE Technology and Engineering Management SocietyAlong with having leadership status in industry and academics, I have thought a lot about the relationship between control systems and technology management.

Airplanes and spacecrafts, cars and trucks, homes and buildings, chemical plants and manufacturing facilities, communication and financial networks, reliable performance, and many other complex systems depend on automation and control systems. But, as I discuss here, the concepts of control engineering are also relevant to make human decisions in technology management.

Whether in engineering or management, uncertainty is widespread. In the case of the latter domain, we can never be sure of innovation processes, market estimates and personality and abilities of the people. In fact, uncertainty can look so heavy that some can be wooed to make decisions by blowing a coin.

But most decisions are not made randomly, and control engineering provides insight to make managerial decisions under uncertainty.

Mental models and uncertainty

We rely on mental models – our knowledge, beliefs, perceptions, experience, observation and logic. But models of any diversity are not reality. They are the best accurate estimates, and they are completely incorrect. It is necessary that all decision manufacturers identify discrepancies between their mental models and reality, and then take action to reduce mismatch.

Let me attract an analogy from control engineering. To develop a control system for an aircraft, for example, mathematical models – not mental variety – are not developed by airframes of the aircraft. For numerical accuracy, the model requires “adequate stimulation”, which means providing a variety of inputs, such as the deflections of flight control surfaces, and measuring how the airplane reacts to them.

Depending on that data, the model of the required accuracy can be created and included in the flight controller design. The data should be rich in enough so that the relevant signals can grow above the irrelevant noise.

Decisions are rarely one-and-one cases. Leading a team, managing a project, allocation of resources, and starting a design requires regular interaction with others, regularly adjusted over time with initial decisions.

The same applies to mental models to make human decisions. Monitoring the normal day-to-day operation of an organization or the possibility of a project will not provide a high adequate signal-to-show ratio information for mental models, which will be firmly updated.

Instead, special tasks and conditions can play an important role in achieving the goal. For example, a manager can mainly give a team member a challenging task to improve the mental model of the employee’s manager, instead to address a pressure organizational requirement. A better mental model can help the leader determine the best role for the employee when a real challenging situation arises.

Despite the effort, mental models will never be correct. There will always be uncertainty. Therefore, an important lesson to keep the decision makers in mind is that whatever you know, you only think that you only know. To believe that you oppose the temptation that you really know the truth.

As a decision-maker, the objects of your mental models include your organization, other stakeholders and external environment. But they also include your self-model. You need a clear understanding of your abilities, preferences and circumstances. Your charge in examples, the speed with which you do the best work, it inspires your flexibility and you in the light of other priorities. And, of course, you need to appreciate that your self-model is also uncertain.

People often do not know themselves and at the same time they feel that they do. Be honest by yourself, and ask for response from reliable colleagues and friends. Do not react defensively; Listen to the response, then reflect. By doing this you can strengthen your understanding.

Dynamics

Sometimes the effects of a decision are not immediately clear. This may take day or year for this. Meanwhile, observation can provide a sign of effects, but they can also be wrong. In control theory, for example, we teach the concept of inverse reaction, where the initial response to a decision is contrary to the final effect.

A simple example is what happens to the company’s profits if it greatly increases its research and development investment. For the next few quarters, R&D expenses will be less likely to profit. Once rolling new products, profitability will probably increase.

A manager who does not recognize the temporary inverted response tendency and cuts the R&D resources, may deteriorate rather than improving cases by renouncing the company’s long -term vitality. Such short -sighted decisions are all often.

Decisions are rarely one-and-one cases. Leading a team, managing a project, allocation of resources, and starting a design requires regular interaction with others, regularly adjusted over time with initial decisions.

Those dynamics should be considered in complex decision making conditions. The adjustment is based on monitoring the activity, which closes the feedback loop.

Managing the delay of time can be particularly difficult. As mentioned, the decisions made about projects and procedures take time to have an impact. The delay can occur from various sources including communication issues, new policies, staffing problems, procurement time and reporting procedures.

To be an effective decision-maker, your mental model should include an estimate of delay. Complications arising from unexpected failures in reaction processes are well known, both control engineering and system engineering. The ability to estimate the delay-and, where possible, is a valuable skill for those taking-in-law to reduce them.

Add dots

Mental models are deep and attractive between the concepts of uncertainty, dynamics and reaction. Those who provide insight to make decisions are many.

An example is the strengthening-trading in control engineering. The tradeoff refers to the fact that the highest level cannot be achieved, while stronger is strong together during the time of uncertainty. This is the basis of insight “”no free lunch“Theorem in adaptation, which means that a decision -making approach may not be optimal in all situations.

When a mental model and reality increases the level of uncertainty from a mismatch, the presence of noise data, or external disturbances, decisions should be less aggressive. Instead, you should respond by making gradual changes and waiting for response signals. For paraffrees, the more uncertain the situation, the more one should bet.