Decision Analysis for Electrical Engineers

The Pillars of Decision Analysis for Electrical Engineers

All technical occupations have important decisions to be made. In electrical engineering and related practices, these decisions often center around the safest and most efficient way to deliver needed resources across a device or structure. Even choices that seem simple inevitably lead to other choices demanding complex decision-making skills.

When they are evaluating a problem, engineers have many ways to gather the data they need to make the right choices. However, a relatively smaller number of engineers delve deeply into the details of decision science, the formal, collaborative, and interdisciplinary science of making optimal decisions to reach particular goals.

Decision science includes many different components:

  • Mathematics, including the math inherent to electrical components and systems.
  • Business resources, strategies, and constraints that may be external to the issue.
  • Available technology, including the whole infrastructure around the problem.
  • Behavioral sciences and the ways that human factors influence the decision.

Not all engineers will have an equal background or aptitude in every one of these factors. However, by understanding the structure of decision-making from a holistic viewpoint, it is possible to clarify decisions and partner with other stakeholders in areas that remain ambiguous. This makes teams stronger and produces better project results.

What is a Decision?

People make decisions every day, but they rarely think about what a decision is. Many decisions are small, and have noticeable, measurable impacts in the short term. Others are large and complex, and most of their results may not be obvious until well into the future. In the context of electrical engineering, all decisions are important and influence all future ones.

A decision has been described as as “a choice among alternatives that will yield uncertain futures, for which we have a preference.” Looking more closely at the elements of this definition will help facilitate deeper understanding of the whole.

Decisions consist of:

  • Choices: An old adage states that not making a choice is a choice. In formal decision science, this is absolutely true. A decision does not exist unless someone has the agency to make a choice between the available options. Prior to this, there is only potential.
  • Alternatives: Decisions become exponentially more complex as more alternatives become available. If used injudiciously, analysis will reveal many additional alternatives without clarifying the differences among their likely results.
  • Uncertainty: As alternatives increase, uncertainty grows. However, whether there are two alternatives or two hundred, there is still uncertainty in the final outcome. If there wasn’t, it would be easy to select the optimal answer even in an ocean of alternatives.
  • Preferences: All decisions involve preferences – even those that are difficult to analyze formally. When choosing between different dining options, for example, one would probably like the meal to be “enjoyable,” whether or not any analysis defines that term. In electrical engineering, preferences are somewhat easier to define.

From any perspective, making a decision requires adequate information. The specific details that matter most vary from one decision to another, but a close interrogation of the factors above can yield some general themes that all decision-making processes have in common.

To make a decision, all decision-makers require:

  • Information about the actions that are possible.
  • Information about possible outcomes of choices.
  • Information about one’s preference for outcomes.

If any of these elements are missing, either a decision does not exist, or the differences between one choice and another are impossible to evaluate. Luckily, electrical engineers will typically make decisions from within a robust framework of knowledge about a project and its potential outcomes.

How can engineers improve the actual decision-making process?

Methods of Clarifying and Improving Decisions

There are many different approaches to improving the results of a decision such that the optimal results are more likely to occur. In the case of major, strategic decisions, it is important to apply a rigorous form of analysis that takes into account all of the available data.

Some approaches electrical engineers should be familiar with include:

Systems Analysis

Systems analysis is an approach to dynamic, large-scale systems aimed at synthesizing better decisions using information about the system’s various parts. By understanding the parts, a decision-maker has the opportunity to understand interactions between them that might otherwise go unnoticed and have unanticipated future consequences.

Decision Analysis for Electrical Engineers

Many technical systems can be seen in terms of the following parts:

  • State Variables: In a dynamic system, a state variable describes the state of the system at any given moment. In electrical systems, state variables can be tested, monitored, and understood in terms of voltage, amperage, impedance, and so on.
  • Feedback: Feedback is data about the performance of a system. In the context of an electrical or mechanical system, there are usually central systems for gathering and providing performance feedback to engineers and end users.
  • Stability: A “stable” system is one whose performance remains predictable and constant until acted upon by some external force. When the force is removed, highly stable systems return to their initial state.
  • Sensitivity Analysis: Sensitivity analysis consists of testing a system by changing one variable at a time, thereby yielding quantitative performance data about its ability to respond appropriately to stressors.

A formal systems analysis approach is appropriate in situations where core engineering decisions can be made in isolation from business drivers or “human factors.” It can also be combined with decision theory, below, to create a more complete strategic picture in which quantitative and qualitative forms of analysis must be combined.

Decision Theory

Decision theory consists of four key elements:

  • Acts: Acts are the specific actions the decision-maker can take. For most purposes, they are the functional equivalent of the concept of alternatives discussed above – the range of potential actions considered according to their effect on outcomes.
  • Events: Events take place outside the scope of the decision-maker’s control and have varying effects that interface with the choices that agent has made. Although they cannot be caused or prevented, they can be anticipated and prepared for.
  • Outcomes: Outcomes are the ultimate result of the interplay between acts and events. If a decision-maker chooses not to take an umbrella when going out (act), he or she is subject to different outcomes based on whether or not it rains (event).
  • Payoffs: Payoffs can be both positive or negative from the perspective of the decision-maker, though all decisions are framed with the pursuit of positive payoffs in mind. In the example of rain, staying dry or ending up wet are both potential payoffs.

Electrical engineers can use conventional decision theory to help them think about unintended consequences on many levels. Virtually anything can be analyzed from this perspective, from trade-offs on efficiency versus performance to unexpected end user behavior.

Electrical Engineers Should Constantly Refine Decision-Making Skills

Engineering decisions are not strictly limited to the performance of electrical, electronic, and mechanical systems. Engineers are called upon to provide business justifications for decisions and to partner cross-functionally for a more holistic approach to achieving the goals of all stakeholders – the engineering team, end users, marketing team, and senior executives.

Formal decision-making skills may not be necessary for the most basic decisions, but are valuable for major decisions with far-reaching implications. Engineers who aspire to be strategic leaders should explore decision science and apply it to their work.


Sources

The Foundations of Decision Analysis Revisited citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.411.9840&rep=rep1&type=pdf

What is Systems Analysis? www.iiasa.ac.at/web/home/about/whatisiiasa/whatissystemsanalysis/what_is_systems_analysis.html

The Idea of a Dynamical System mathinsight.org/dynamical_system_idea

An Introduction to Control Systems www.facstaff.bucknell.edu/mastascu/econtrolhtml/Intro/Intro1.html

Using Decision Support in Business: An Overview onlinecampus.bu.edu/bbcswebdav/pid-843933-dt-content-rid-2221759_1/courses/13sprgmetad715_ol/module_03a/metad715_m03l02t03_usingsupport.html

A Very Fast Intro to Decision Theory www.siue.edu/~evailat/decision.htm

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