Data is now the critical tool for managing many corporate functions, including marketing, pricing, supply chain, operations, and more. This movement is being further fueled by the promise of artificial intelligence and machine learning, and by the ease of collecting and storing data about every facet of our daily lives.
The Best Approach to Decision Making Combines Data and Managers’ Expertise
Data-driven management has risen sharply from a decade ago, when Thomas Davenport wrote Competing on Analytics. Data is now the critical tool for managing many corporate functions, including marketing, pricing, supply chain, operations, and more. This movement is being further fueled by the promise of AI and machine learning, and by the ease of collecting and storing data about every facet of our daily lives. But has the pendulum swung too far? Are managers relying excessively on data to guide their decisions, abdicating their own knowledge and experience?
One possible solution may be found in Agent-Based Simulation (ABS), a novel approach to solving complex business problems through computer simulations. One of the most appealing aspects of ABS is that it combines domain expertise and data. The domain expertise is used to define the structure of the simulation, which is unique to each business problem. The data is used partly to refine the details of the simulation, and partly to ensure that as the simulation runs, the resulting outcomes match real-world results. With this approach, the manager’s expertise regains the primary role, and the results of the simulation can be analyzed by the manager and data scientist together.