I recently sat down with Yael Grushka-Cockayne, one of ten leading professors who teach on the MiniMBA in Management. But Yael’s professional repertoire spans further than our virtual classrooms.
Most recently, she was appointed Dean at the University of Virginia Darden School of Business; the first time this position has been held by a woman in Darden’s 70-year history.
After joining the faculty in 2009, Yael has become a published scholar and decorated teacher, winning the Darden Outstanding Faculty Award, the University of Virginia's All University Teaching Award and the Transformational Faculty Award.
In her newest position, Yael is responsible for the Darden’s academic mission, program quality and student experience, though she plans to continue her teaching and research.
In our conversation, we spoke about Yael’s early career, where her fascination with decision analysis came from, and the common mistakes and winning habits she often encounters when it comes to making good decisions.
Early career
Before Yael moved into academia, she worked in industrial engineering and information systems in Silicon Valley. But she was increasingly aware of the disparity between how decisions should be made, and how people actually make them.
“Industrial engineering taught me to see systems, while operational research gave me rigorous ways to model choice and uncertainty. I became fascinated by the gap between how people should make decisions and how they actually make them.”
It was this, combined with her natural draw to teaching and research, which Yael thinks was influenced by her dad who was also a professor, that led her into the academic world.
A lot of Yael’s work as a decision analyst aims to bridge the disparity she noticed early in her career. Normative theory tells you how decisions should be made, and descriptive research shows how people make them. Yael's work lives in between the two. Given the gap between theory and actual, what should we actually tell decision-makers to do?
Her earlier career in marketing left a mark too, one she still leans on today. “Marketing taught me to begin outside myself: Who is the customer, and what problem are they trying to solve?”
What is decision analysis?
When asked to explain decision analysis to someone who has never heard of it, Yael keeps it reassuringly light. A skill that is not to be overlooked given it’s an MBA-level subject.
“It is a disciplined way to make choices amid uncertainty. You clarify the decision and objectives, identify real alternatives, separate what you control from what you do not, then assess consequences and trade-offs.”
Yael stresses that decision analysis isn’t simply about eliminating uncertainty or guaranteeing a good outcome, it’s about being explicit about your assumptions and making every option visible.
The words ‘alternatives’, ‘assumptions’ and ‘trade-offs’ came up a lot in my conversation with Yael, all of which translate to a similar meaning. Making all possible options known.
Great decision-makers, she says, slow down at the start so they can move fast later. They frame the right question, build out genuine alternatives, and interrogate what would actually have to be true for an idea to work. They hold their conclusions with confidence, not certainty, and actively look for someone who disagrees with them.
Average decision-makers do the opposite. They land on the answer they want, then go hunting for evidence to support it.
This is also the most common mistake Yael sees senior leaders make. “Experience helps leaders recognise patterns quickly, but it can also make the first pattern feel inevitable. Then analysis becomes justification.”
Instead, Yael proposes that leaders should actively assign someone the job of providing counterarguments and asking “what could go wrong?”
Another decision-making red flag Yael mentioned was ‘the illusion of precision’. “If a leader provides exact numbers about an unknown future, you should challenge and doubt them.”
In a professional setting, we often avoid using number ranges for fear of being labelled inaccurate, but Yael argues that using ranges is more honest and “prepares us for the potential downside that exists with the risk profile of most opportunities.”
A common crossroads in decision analysis happens between data and judgement. Should we rely on information, or trust our intuition? Unsurprisingly, we need both.
“We almost never have enough information. The useful question is whether more information would change the choice and whether it is worth the cost of waiting.”
Judgment is a permanent part of the job because no dataset can tell you what your objectives should be, or which trade-offs you're willing to live with. "Good analysis doesn't replace judgment; it disciplines judgment and makes it visible."
On the topic of human judgement, our conversation moved towards AI and its role in modern day decision analysis. Yael agrees that AI can help us process information, generate alternatives and identify patterns, but she is wary of its use as an echo chamber.
“Using it [AI] to validate what you already believe risks confirmation bias at machine speed.”
Instead, she encourages decision makers to use AI to stress-test assumptions, argue the opposite case or imagine how alternative choices fail.
“AI can generate an answer, but leaders must decide what deserves trust, whether the choice is ethical and who bears the consequences. Responsibility cannot be delegated to a tool.”
Instead of a piece of software or framework, the one thing Yael would install in every rising leader is keeping a decision journal. In her experience, organisations are good at keeping records of what happened but not why, which means the same reasoning mistakes get repeated.
Before any big decision, write down what you’re deciding, what you’re trying to achieve, the alternatives on the table and the assumptions you’re making, along with what evidence would change your mind and when you revisit the choice.
The MiniMBA in Management
I asked Yael her favourite decision-making theory or framework, to which she replied, “asking a decision analyst to choose a favourite is slightly dangerous, but I return to the decision tree.”
It’s a simple tool that lays out a decision step-by-step and encourages the decision maker to answer three key questions: What can I choose now? What remains uncertain? What might I learn before the next choice?
The decision tree forms the backbone of Decision Analysis in the MiniMBA in Management, the module designed and taught by Yael. In the module, learners build and use a decision tree to navigate two real-life business decisions.
When I asked Yael what learners could expect from her MiniMBA module, she said this: “They should expect to participate. The aim is a practical process learners can use immediately and explain to a colleague, team or board.”
Whilst the MiniMBA in Management is designed to give senior marketers fundamental business management skills to continue progressing in their career, Yael’s module provides essential learning for anyone whose decisions affect other people.
“It is especially useful for functional experts moving into broader leadership, when strong instincts must become testable and communicable across the business. The module prepares people for the question, 'What do you recommend, and why?'”
We concluded our conversation looking to the future. Stepping into a new academic year as Dean, Yael will be helping shape Darden’s next chapter while continuing important work in AI, the student experience and faculty impact.
“I want Darden to be more visible, connected and useful without changing what makes it special: rigorous, student-centred learning and research that helps people lead in practice.”
The MiniMBA in Management starts this week. Meet Yael and the nine other leading professors who will guide you through MBA-level research, case studies and frameworks to help you master the language of the boardroom and take the next big step in your career.