Enhance Decision-Making With Control Systems

This text is a part of our unique career advice collection in partnership with the IEEE Technology and Engineering Management Society.

A lot of engineering is decision-making. Engineers make selections about product design, program administration, know-how street maps, analysis instructions, management of technical groups, and extra.

As a previous president of the IEEE Control Systems Society and now the 2026 president-elect of the IEEE Technology and Engineering Management Society, in addition to holding management positions in trade and academia, I’ve thought lots in regards to the connections between control systems and technology management.

The protected, dependable efficiency of airplanes and spacecraft, automobiles and vehicles, houses and buildings, chemical vegetation and manufacturing amenities, communication and monetary networks, and lots of different complicated programs depends on automation and control systems. However, as I focus on right here, the ideas of management engineering are additionally related to human decision-making in know-how administration.

Whether or not in engineering or administration, uncertainties are pervasive. Within the case of the latter area, we are able to by no means make sure about innovation processes, market projections, and other people’s personalities and capabilities. Certainly, the uncertainties could seem so overwhelming that some could be tempted to decide by flipping a coin.

However most selections usually are not made randomly, and management engineering provides insights for managerial decision-making below uncertainty.

Psychological fashions and uncertainty

We depend on psychological fashions—our data, beliefs, assumptions, experiences, observations, and reasoning. However fashions of any selection usually are not actuality. They’re correct approximations at greatest, and so they’re utterly mistaken at worst. It’s important that every one decision-makers acknowledge the discrepancies between their psychological fashions and actuality, after which take motion to scale back the mismatch.

Let me draw an analogy from management engineering. To develop a management system for an plane, for instance, mathematical fashions—not the psychological selection—are developed of the aircraft’s airframe. For numerical accuracy, the fashions require “adequate excitation,” which suggests offering quite a lot of inputs, comparable to deflections of flight control surfaces, and measuring how the airplane reacts to them.

Primarily based on that knowledge, fashions of the required accuracy may be created and included into the flight controller design. The info should be wealthy sufficient in order that related alerts can rise above irrelevant noise.

Selections are hardly ever one-and-done affairs. Main a workforce, managing a challenge, allocating sources, and enterprise a design all require common interactions with others, with preliminary selections adjusted repeatedly over time.

The identical applies to psychological fashions for human decision-making. Monitoring regular day-to-day operations of a company or a challenge doubtless wouldn’t present info of a excessive sufficient signal-to-noise ratio for psychological fashions to be reliably up to date.

As a substitute, particular duties and conditions may be instrumental in reaching the objective. For instance, a supervisor may give a difficult job to a workforce member primarily to enhance the supervisor’s psychological mannequin of the worker, relatively than to handle a urgent organizational want. The improved psychological mannequin can assist the chief decide the perfect function for the worker when an precise difficult state of affairs arises.

No matter effort, psychological fashions won’t ever be good. There’ll at all times be uncertainty. So, one essential lesson for decision-makers to remember is that no matter you already know, you solely assume you already know. Resist the temptation to imagine you actually know the reality.

As a decision-maker, the objects of your psychological fashions embrace your group, different stakeholders, and the exterior surroundings. However additionally they embrace your self-model. You’ll want to have a transparent understanding of your individual capabilities, preferences, and circumstances. Examples embrace your workload, the tempo at which you’re employed greatest, your flexibility in gentle of different priorities, and what motivates you. And, after all, it is advisable admire that your self-models are unsure, too.

Individuals typically don’t know themselves in addition to they assume they do. Be trustworthy with your self, and ask for feedback from trusted colleagues and friends. Don’t react defensively; take heed to the suggestions, then mirror. Doing so can strengthen your understanding of your self.

Dynamics and decision-making

Generally the results of a call aren’t instantly obvious. It may possibly take days and even years for that to occur. Within the meantime, observations can present a sign of the results, however they may be mistaken. In management idea, for instance, we educate the idea of inverse response, the place the preliminary response to a call is the other of the ultimate impact.

A easy instance is what occurs to an organization’s earnings if it considerably will increase its analysis and growth funding. For the subsequent few quarters, earnings doubtless might be decrease due to the R&D bills. As soon as new merchandise roll out, profitability most likely will improve.

A supervisor who doesn’t acknowledge the momentary inverse response development and cuts R&D sources can worsen relatively than enhance issues by sacrificing the long-term vitality of the corporate. Such short-sighted selections occur all too typically.

Selections are hardly ever one-and-done affairs. Main a workforce, managing a challenge, allocating sources, and enterprise a design all require common interactions with others, with preliminary selections adjusted repeatedly over time.

These dynamics should be thought of in complicated decision-making conditions. The changes are based mostly on monitoring the exercise, thereby closing the suggestions loop.

Time delays may be particularly tough to handle. As famous, selections made about initiatives and processes take time to have an effect. Delays may end up from numerous sources together with communication points, new insurance policies, staffing issues, procurement instances, and reporting processes.

To be an efficient decision-maker, your psychological mannequin ought to embrace estimates of delays. The issues arising from unanticipated setbacks in suggestions processes are well-known, each in management engineering and systems engineering. The flexibility to anticipate delays—and, the place doable, to scale back them—is a useful ability for decision-makers.

Connecting the dots

The interconnections among the many ideas of psychological fashions, uncertainty, dynamics, and suggestions are deep and interesting. The insights they provide for decision-making are quite a few.

One instance is the robustness-performance tradeoff in management engineering. The tradeoff refers to the truth that the very best ranges of efficiency can’t be attained whereas concurrently being sturdy throughout instances of excessive uncertainty. This perception is the premise of the “no free lunch” theorem in optimization, that means that no decision-making method may be optimum in all conditions.

When uncertainty ranges improve from a mismatch between a psychological mannequin and actuality, the presence of noisy knowledge, or exterior disturbances, decision-making needs to be much less aggressive. As a substitute, it’s best to reply by making gradual modifications and ready for suggestions alerts. To paraphrase, the extra unsure the state of affairs, the extra one ought to hedge one’s bets.