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 choices 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 business and academia, I’ve thought quite a bit concerning the connections between control systems and technology management.
The secure, dependable efficiency of airplanes and spacecraft, automobiles and vans, properties and buildings, chemical vegetation and manufacturing services, communication and monetary networks, and lots of different complicated techniques depends on automation and control systems. However, as I talk about 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 folks’s personalities and capabilities. Certainly, the uncertainties could appear so overwhelming that some is perhaps tempted to decide by flipping a coin.
However most choices are usually 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 are usually not actuality. They’re correct approximations at greatest, they usually’re utterly unsuitable at worst. It’s important that every one decision-makers acknowledge the discrepancies between their psychological fashions and actuality, after which take motion to cut 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 airplane’s airframe. For numerical accuracy, the fashions require “enough excitation,” which suggests offering a wide range of inputs, reminiscent of deflections of flight control surfaces, and measuring how the airplane reacts to them.
Based mostly on that knowledge, fashions of the required accuracy could be created and integrated into the flight controller design. The information have to be wealthy sufficient in order that related alerts can rise above irrelevant noise.
Selections are hardly ever one-and-done affairs. Main a crew, managing a mission, allocating assets, and endeavor a design all require common interactions with others, with preliminary choices adjusted often over time.
The identical applies to psychological fashions for human decision-making. Monitoring regular day-to-day operations of a corporation or a mission possible wouldn’t present data of a excessive sufficient signal-to-noise ratio for psychological fashions to be reliably up to date.
As a substitute, particular duties and conditions could be instrumental in attaining the objective. For instance, a supervisor may give a difficult process to a crew member primarily to enhance the supervisor’s psychological mannequin of the worker, fairly than to handle a urgent organizational want. The improved psychological mannequin can assist the chief decide one of the best position for the worker when an precise difficult state of affairs arises.
No matter effort, psychological fashions won’t ever be excellent. There’ll all the time be uncertainty. So, one essential lesson for decision-makers to bear in mind is that no matter you understand, you solely suppose you understand. Resist the temptation to imagine you actually know the reality.
As a decision-maker, the objects of your psychological fashions embody your group, different stakeholders, and the exterior atmosphere. However additionally they embody your self-model. You must have a transparent understanding of your personal capabilities, preferences, and circumstances. Examples embody your workload, the tempo at which you’re employed greatest, your flexibility in gentle of different priorities, and what motivates you. And, in fact, it’s good to recognize that your self-models are unsure, too.
Folks usually don’t know themselves in addition to they suppose they do. Be trustworthy with your self, and ask for feedback from trusted colleagues and friends. Don’t react defensively; hearken to the suggestions, then replicate. Doing so can strengthen your understanding of your self.
Dynamics and decision-making
Typically the results of a choice aren’t instantly obvious. It will probably take days and even years for that to occur. Within the meantime, observations can present a sign of the results, however they is also unsuitable. In management idea, for instance, we educate the idea of inverse response, the place the preliminary response to a choice 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 improvement funding. For the subsequent few quarters, earnings possible can be decrease due to the R&D bills. As soon as new merchandise roll out, profitability most likely will enhance.
A supervisor who doesn’t acknowledge the non permanent inverse response development and cuts R&D assets can worsen fairly than enhance issues by sacrificing the long-term vitality of the corporate. Such short-sighted choices occur all too usually.
Selections are hardly ever one-and-done affairs. Main a crew, managing a mission, allocating assets, and endeavor a design all require common interactions with others, with preliminary choices adjusted often over time.
These dynamics have to be thought of in complicated decision-making conditions. The changes are primarily based on monitoring the exercise, thereby closing the suggestions loop.
Time delays could be particularly tough to handle. As famous, choices made about initiatives and processes take time to have an effect. Delays may result from varied sources together with communication points, new insurance policies, staffing issues, procurement occasions, and reporting processes.
To be an efficient decision-maker, your psychological mannequin ought to embody estimates of delays. The issues arising from unanticipated setbacks in suggestions processes are well-known, each in management engineering and systems engineering. The power to anticipate delays—and, the place attainable, to cut back them—is a invaluable ability for decision-makers.
Connecting the dots
The interconnections among the many ideas of psychological fashions, uncertainty, dynamics, and suggestions are deep and engaging. 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 best ranges of efficiency can’t be attained whereas concurrently being sturdy throughout occasions of excessive uncertainty. This perception is the premise of the “no free lunch” theorem in optimization, which means that no decision-making method could be optimum in all conditions.
When uncertainty ranges enhance from a mismatch between a psychological mannequin and actuality, the presence of noisy knowledge, or exterior disturbances, decision-making ought to be much less aggressive. As a substitute, you must 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.
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