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, expertise 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 loads concerning the connections between control systems and technology management.
The secure, dependable efficiency of airplanes and spacecraft, automobiles and vans, houses and buildings, chemical vegetation and manufacturing services, communication and monetary networks, and lots of different complicated methods 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 expertise administration.
Whether or not in engineering or administration, uncertainties are pervasive. Within the case of the latter area, we will 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 likely to be tempted to decide by flipping a coin.
However most selections should not made randomly, and management engineering gives insights for managerial decision-making underneath uncertainty.
Psychological fashions and uncertainty
We depend on psychological fashions—our information, beliefs, assumptions, experiences, observations, and reasoning. However fashions of any selection should not actuality. They’re correct approximations at finest, they usually’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 a wide range of inputs, equivalent to deflections of flight control surfaces, and measuring how the airplane reacts to them.
Based mostly on that knowledge, fashions of the required accuracy will 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 workforce, managing a mission, allocating assets, 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 corporation or a mission probably wouldn’t present data of a excessive sufficient signal-to-noise ratio for psychological fashions to be reliably up to date.
As an alternative, particular duties and conditions will be instrumental in attaining the purpose. For instance, a supervisor might give a difficult process to a workforce member primarily to enhance the supervisor’s psychological mannequin of the worker, slightly than to deal with a urgent organizational want. The improved psychological mannequin can assist the chief decide the perfect function for the worker when an precise difficult scenario arises.
No matter effort, psychological fashions won’t ever be good. There’ll all the time be uncertainty. So, one essential lesson for decision-makers to remember is that no matter you realize, you solely assume you realize. 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 surroundings. However additionally they embody your self-model. It’s essential to have a transparent understanding of your personal capabilities, preferences, and circumstances. Examples embody your workload, the tempo at which you’re employed finest, your flexibility in mild of different priorities, and what motivates you. And, in fact, you might want to respect that your self-models are unsure, too.
Individuals usually 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 replicate. Doing so can strengthen your understanding of your self.
Dynamics and decision-making
Typically the consequences of a choice aren’t instantly obvious. It could possibly take days and even years for that to occur. Within the meantime, observations can present a sign of the consequences, however they is also mistaken. In management concept, 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 growth funding. For the following few quarters, earnings probably 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 pattern and cuts R&D assets can worsen slightly than enhance issues by sacrificing the long-term vitality of the corporate. Such short-sighted selections occur all too usually.
Selections are hardly ever one-and-done affairs. Main a workforce, managing a mission, allocating assets, and enterprise a design all require common interactions with others, with preliminary selections adjusted repeatedly over time.
These dynamics have to be thought-about in complicated decision-making conditions. The changes are primarily based on monitoring the exercise, thereby closing the suggestions loop.
Time delays will be particularly tough to handle. As famous, selections made about tasks 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 problems 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 potential, to scale back them—is a priceless 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 occasions of excessive uncertainty. This perception is the idea of the “no free lunch” theorem in optimization, that means that no decision-making strategy will 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 an alternative, it’s best to reply by making gradual modifications and ready for suggestions alerts. To paraphrase, the extra unsure the scenario, the extra one ought to hedge one’s bets.
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