In the 1970s, a small vineyard in the Napa Valley was facing a tough decision. Freemark Abbey Winery had a crop of Riesling grapes that were close to ripening. Taking them from the vine at the point of maturity would yield a perfectly reasonable, if perhaps mediocre, wine. But there were reports of a storm heading toward the winery a little later, and if the grapes were exposed to just the right amount of rain, they might develop a type of “noble rot,” which would produce a far superior, sweeter wine. This wine could be sold to wholesalers for a far greater price.
The dilemma for Freemark Abbey: Should they harvest now and cash in on a sure thing or take their chances and wait?
The Freemark Abbey story caught the attention of business scholars and was converted into a case study. Over time, the case has become a hallmark in business education because it shines a clear light on so many of the dynamics at play in decision-making — dynamics that might seem both complex and mysterious.
Making business decisions can feel daunting either because the associated stakes can be very high or because they integrate both quantitative and intangible dimensions — oftentimes all of the above.
But if the Freemark Abbey case demonstrates anything clearly, it’s this: All of these variables can be broken down, understood and assessed, taking something of the complexity and mystery out of the process of making the optimal decision for leaders and organizations. So says Darden Professor Yael Grushka-Cockayne, who serves as both the Altec Styslinger Foundation Bicentennial Chair and senior associate dean for professional degree programs.
Grushka-Cockayne teaches the Freemark Abbey Winery case as a core part of Darden Executive Education and Lifelong Learning’s Women in Leadership Program. And not only does it illuminate what’s involved in robust decision-making, it reflects the kinds of choices leaders have to grapple with every day, and how they can face the element of risk that accompanies choosing the best course of action. Of note, research indicates that women more than men can be prone to risk aversion.1
The Quality of Data
“The case is a typical, fairly common binary choice that elicits a yes or no answer: Harvest now or wait until later? And it gets people talking about their attitudes to risk from the get-go,” Grushka-Cockayne notes. “Some want the sure thing, and others will try to avoid the risk because of the potential damage to reputation. In leadership, we often struggle to integrate quantitative data and hard numbers with more intangible things, like reputation.”
In reality, says Grushka-Cockayne, even intangibles can be assigned a dollar value, though leaders typically tend to separate them or even use them “like a wand” as an excuse to ignore numbers. What the Freemark Abbey Winery story elucidates, however, is the value in “pausing, laying everything out and searching for the bigger picture.”
“With Freemark Abbey, the probability of rain is given as 50-50, and that leads to discussions about the reliability of meteorology itself,” she says. “This tends to open up an important conversation about the quality of data and the need for more and more of it.”
The Value of Good Questions
But a fuller analysis of every factor at play, including the winery’s financial history and robustness, its existing stock, the market, prices, and all of the potential outcomes attached to different scenarios and decisions, reveals something compelling: Even if the probability of rain were to fall to an absolute zero percent, all things considered, the winemakers would still in fact be better off — both financially and in reputational terms — by delaying the harvest of the crop.
In other words, having more data — perfect data, even — around the probability of rain still doesn’t change the final and best decision. And this highlights something absolutely critical. In the organizational setting, leaders routinely feel like they don’t have enough data to make a decision. Yet all too often, we forget to ask good questions about the actual value of data — and whether more of it would change our choices, says Grushka-Cockayne.
“Leaders often pause to collect more data ahead of a big decision, without really questioning what bearing that data has,” she says. “We set such a high premium on information that without great quantities of it, we might at times delay decisions for no really good reason. Or we pay money for market surveys, and the like, that in the end have no effect on our decision-making.”
How to Mitigate Doubt
For leaders, the Freemark Abbey Winery story holds a number of critical insights, says Grushka-Cockayne. These insights can help mitigate some of the complexity and diminish doubt or risk-aversion that can lead to hesitancy in decision-making.
- Consider potential outcomes. Smart business decisions happen not when you prioritize an abundance of data, but when you combine probability and outcomes. Typically, we conflate risk with uncertainty about things: If I have an 80 percent chance of success, I’ll do it; if it’s a 20 percent chance, I won’t. But the probability of success on its own isn’t enough. To make a good decision, we need to also understand all the potential outcomes across a range of scenarios and weigh up all the implications.
- Build a common language. Leaders have a clear responsibility to bring their teams together to integrate probability and outcomes in a way that is coherent and built around a common language. Everyone with a stake in the decision needs to be in the same place in this respect, and it’s down to leaders to step up and make this happen.
- Debate the alternatives. There is clear value in soliciting multiple and diverse perspectives. When the case is taught in class, says Grushka-Cockayne, the best decisions emerge when scenarios are subject to brainstorming, when alternatives are laid out, and the pros and cons of each are debated openly. Sometimes we feel we need to be guarded and show up with the “right answer,” she notes. But one of the greatest skills in leadership is to lay down a process, present a full set of scenarios, and then have the group come together to provide advice and insight.
“Women are still more prone to risk-aversion and at times self-doubt in their decision-making than men,” Grushka-Cockayne says. “In programs such as ours, and through the work we do using cases like this, there is so much that we can do to bolster confidence by demystifying these processes. The tools and frameworks that we can deploy as leaders are absolutely game-changing.”
The preceding is drawn from Women in Leadership, a white paper featuring evidence-backed techniques and tools that leaders can leverage to reconfigure the playing field — for themselves and others.
- 1For example: Catherine C. Eckel and Philip J. Grossman, “Men, Women and Risk Aversion: Experimental Evidence,” in Handbook of Experimental Economics Results, Vol.1, ed. Charles Plott and Vernon Smith (New York: Elsevier, 2008), 1061–1073. Elke U. Weber, Ann-Renee Blais and Nancy E. Betz, “A Domain-Specific Risk-Attitude Scale: Measuring Risk Perceptions and Risk Behaviors,” Journal of Behavioral Decision Making 15 (2002): 263–290, https://doi.org/10.1002/bdm.414.