Strategic Decision Making. The model we’ve developed for choosing decision support tools is dependent on managers’ being able to accurately determine the level of ambiguity and uncertainty they face. The plan also includes determining business rules to improve and measure supply chain efficiency. Careful readers will have noticed that the decision tree has one set of tools we have not covered: information aggregation tools. The SCOR model has proven to benefit companies that use it to identify supply chain problems. Managers’ biased assessments of the level of uncertainty they face might lead some to conclude that our diagnostic tool is of limited practical use and might point them toward the wrong approach. Combining vast amounts of data and increasingly sophisticated algorithms, modeling has opened up new pathways for improving corporate performance. A PowerPoint presentation that describes the entire SCOR process can also be downloaded. However, the tool we advocate using most, case-based decision analysis, is not yet widely used, partly because the more formal, rigorous versions of it are relatively new and partly because executives typically underestimate the degree of uncertainty they face. It’s impossible to eliminate risk from strategic decision making, of course. The trees could be used to calculate the expected value, variance, and range of financial outcomes that McDonald’s might face if it introduced the sandwich. Stay connected with the alumni network and benefit from a range of online resources. More than 1,000 MBA students and 150+ Executive MBA participants every year to meet your talent acquisition and retention needs. Get inspired by their latest stories and INSEAD news and developments. This step involves management of finished inventories, assets, transportation, product life cycles, and importing and exporting requirements (3). First, it knows the variables that matter for success: local demographics, traffic patterns, real estate availability and prices, and locations of competitive outlets. Is the manufacturing process make-to-order, make-to-stock, or engineer-to-order? These similarity ratings are then aggregated across individuals using simple statistical procedures to generate forecasts (for revenues, completion times, or costs) depending on the goal. (See the sidebar “Developing Rigorous Analogies.”). The authors bring their framework to life using decisions that executives at McDonald’s might need to make—from the very clear-cut (choosing a site for a new store in the United States) to the highly uncertain (changing the business in response to the obesity epidemic). Develop critical thinking skills, sharpening your intuition in the face of risk and uncertainty, Learn ways to discover, manage, mitigate and avoid decision-making traps, Learn to leverage the power of ‘nudges’ – a light-touch way to influence human behaviour and improve decision-making, Boost your ability to build high-performing teams by understanding what conditions enable teams to make better decisions than individuals, Become a more strategic leader and decision-maker by understanding the long-term impact your decisions can have on your organisation, Senior executives and key decision-makers, Managers responsible for building high-performing teams, Managers who frequently lead projects and want to improve their ability to make smart, sound decisions. (This will require process and culture change in many organizations.). Manufacturing and production are the emphasis of this step. If it’s decentralized, can you tap the experts you need and aggregate their knowledge? This may be problematic, because decision makers—like all human beings—are subject to cognitive limitations and behavioral biases. Make more rigorous use of historical analogies to inform your most ambiguous and uncertain—and usually most important—decisions. Rather than make an expensive, high-risk decision now, many colleges are undertaking small-scale experiments to test the waters and learn more about what “success” in this space will look like. A newer approach to gathering dispersed information is to use information markets (also known as prediction markets) to capture the collective wisdom of informed crowds regarding key variables such as likely macroeconomic performance in the next year or how a proposed product will be received. We make a strong case for increased use of case-based decision analysis (which relies on multiple analogies) and qualitative scenario analysis under conditions of uncertainty. For example, any decision maker who assumes that she has a firm understanding of the economics underlying a big decision should be challenged with questions such as, Is there reason to believe that the relationship between critical success factors and outcomes has changed over time, making our historical models no longer valid? The company has or can get all the information it needs to be reasonably certain how a given location will perform. It’s not possible to design all of the perverse incentives out of a system, but some commonsense protocols can make a big difference. These methods require decision makers to collect a sample of analogous cases, determine the results achieved in those cases, and assess how similar each case is to the decision at hand. What assumptions are you making when estimating probabilities? Decision makers may then consult with the group again until a consensus is reached. It discusses how to handle supplier payments and when to receive, verify, and transfer product (3). Join the conversations on the latest global topics. Valuable supply chain research and the latest industry news, delivered free to your inbox. More often, decision makers can identify a range of possible outcomes, both for specific success factors and for the decision as a whole. Don’t misunderstand. From manager to mentor - career development tips to go. Here how you can do it: http://enable-javascript.com, © 2020 INSEAD Institut privé d'enseignement supérieur. There is a clear disconnect between the tools that are being used and those that should be used most often. A robust analysis of analogous situations forces decision makers to look at their particular situation more objectively and tends to uncover any wishful thinking built into their return projections. Although business leaders frequently use analogies to inform their decisions, many don’t do so in a rigorous, systematic way. This article provides a model for matching the decision-making tool to the decision being made, on the basis of three factors: how well you understand the variables that will determine success, how well you can predict the range of possible outcomes, and how centralized the relevant information is. Leading Business Transformation in Asia - NEW! Prediction or information markets are designed to gather “the wisdom of the crowd” by creating financial markets where investors can trade securities with payoffs linked to uncertain future outcomes (for example, the winner of an election or the release date of a new product). Why are these traditional tools used so often even though their limitations are widely acknowledged? Strategic Decision Making for Leaders is aimed at executives who make important decisions in their organisations and are responsible for establishing decision-making processes. Yet every business leader we have worked with over the past 20 years acknowledges that more and more decisions involve judgments that must be made with incomplete and uncertain information. INSEAD is committed to developing the next generation of global leaders who will change the world. This made no sense at all. (Here it’s essential to use structured frameworks for comparison.) Learn how to successfully navigate the decision making process with this 5 step method. Corporate Venturing and Innovation - NEW! Leveraging the power of INSEAD GO-Live, our next-generation and real-time learning technology allows you to connect from anywhere in the world and engage live with faculty and peers just like you would in an INSEAD classroom. All rights reserved. Let’s now assume that McDonald’s is entering an emerging market for the first time. We start by defining strategy and SDM in order to set the expectations for the rest of the paper. Decision makers can feed the information about traffic and other variables into standard discounted cash flow models to accurately predict (to a close-enough approximation) how the proposed location will perform and make a clear go/no-go decision. Demand and supply planning and management are included in this first step. Make more rigorous use of historical analogies to inform your most ambiguous and uncertain—and usually most important—decisions. (For more on case-based analysis, see the sidebar “Developing Rigorous Analogies: An Underutilized Tool.”). On the supply side, scenarios might focus on uncertainties in the emerging market supply chain and regulatory structure that could cause wide variation in supplier costs and reliability. As you ponder which tools are appropriate for a given context, you need to ask yourself two fundamental questions: You need to know whether you have a causal model—that is, a strong understanding of what critical success factors and economic conditions, in what combination, will lead to a successful outcome.
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