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Decision Coaching

A new professional discipline is emerging: decision engineering. Decision engineering shares the same norms and ethics as established engineering fields. However, it is different enough that it deserves the attention of educators, business, and government.

As the publisher at Baker Street, my goal is to help define this discipline. The opinions expressed here are my own. They reflect the thinking of several of my colleagues in and around Stanford University, notably Jim Matheson of SmartOrg. The roots of decision engineering lie in the teachings of Peter Drucker, Edwards Deming, Bill Linvill (Stanford), Ron Howard (Stanford), and Chris Argyris (Harvard.) The field rests on more than half a century of study, teaching, experience, and observation.

My formal education is in systems engineering, decision analysis, and economics. I have always worked across disciplines, especially engineering and economics.  I have worked with corporations, think tanks, and consulting companies. I have started for profit and not-for-profit organizations. I have worked on some of the biggest private and public investment decisions of my generation: nuclear power, coal mining, synthetic fuels, green house gas abatment, rail transportation, forest fire management, multi-billion dollar product investments, automobile and truck design, investments in game-changing new technology, global branding, global components acquisition, new business models, and, most recently, fishery management and electric power markets. I have led strategy teams in Europe, Asia, South America, and the Middle East. With this background as a prelude, let me propose a description of the new discipline.

A decision engineer has a degree in engineering or another technical field like physics. He or she has a profound understanding of systems analysis, applied probability, and decision theory. This training is preparation for dealing with complexity, dynamics, and uncertainty. This knowledge is important for building and understanding models, designing algorithms,  and presenting the results.

A practicing decision engineer will have experience in framing complex problems, designing strategic alternatives, facilitating groups, and managing projects.

Decision engineering is needed on decisions involving large, high-risk capital investments like new plants, new processes, new products, new services, new technology, geographic expansion, or major infrastructure changes. Decision engineering is also needed in developing decision support tools, for example, “apps” to screen loans, detect fraud, and treat diseases. Decision engineering is also needed in the public sector. Our policy decision making is woefully in need of critical thinking and collaborative design, both engineering strengths.

Big decisions require an understanding of a broad range of domains:  technology, markets, supply-chains, economics, and project management. They also involve working with people from a broad range of professions. An experienced decision engineer, like an experienced lawyer or doctor, has the skills needed to go into new situations and work with new groups of people. He is an agile, fast learner.

A decision engineer knows that a good outcome is not the same as a good decision. His focus is on helping people make good decisions.

A decision engineer is guided by norms of logic and behavior. His critical thinking skills enable him to understand the distinction between what is normative and what is descriptive.

A decision engineer is a Bayesian. (If you have to look up the term “Bayesian,” then you are definitely not a decision engineer.)

Decision Engineering.003Engineers know how to exercise judgment when data is not available. (Early in my engineering career I was told that, “Engineering is the art of approximation.”) Decision engineers know how to help other people assign probabilities to uncertain events and overcome cognitive biases. In terms of Daniel Kahneman, engineers know how to “slow think.”

Decision making is about the future. A decision engineer is forward looking. He is comfortable using future-oriented tools like expert assessments, scenarios, and computer-based structural models.

Decision Engineering.002In some situtations decision engineers can be most useful if they remain value neutral. That is, they do not advocate for anything beyond good decision making.  Decision coaches are a special class of decision engineers. They are always value neutral.

A decision engineer is familiar with two fundamental processes: the Decision Analysis process and the Collaborative Design process. The Decision Analysis process is appropriate when there are not many stakeholders involved. The Collaborative Design process is useful when the stakes are high and many people are involved. The Decision Analysis process is at the core of the Collaborative Design process.

The decision engineer is comfortable using a broad range of tools: decision hierarchies, strategy tables, decision diagrams, structural modeling, sensitivity analysis, probability assessment, and decision trees.

There is ample evidence that decision engineers can move smoothly into strategic executive roles. Half of the CEOs in the United States are engineers. Decision engineering is great way to develop the experience and skills required to be a top-level executive.

For more about decision engineering and decision coaching see my recent article in the IEEE Engineering Management Review, “A New Engineering Profession is Emerging: Decision Coach.”

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