Very good use of advanced analytics.
Many business decisions need to be made with incomplete information, and require managers to plan for uncertain outcomes. If implementing a new inventory policy has the promise of reducing holding costs across the enterprise by $10 million over the next 2 years, what’s the chance the savings will be exactly $10 million? Well, it’s about zero. Would a manager’s decision to move forward with the initiative change if they were told there’s an 80 percent chance of saving more than $10 million? What about only a 50 percent chance? How about 10 percent? Incorporating measures of uncertainty can be tremendously helpful for decision makers. Unfortunately, many analytic techniques produce very deterministic, or single point, estimates (e.g., “Our model predicts exactly $10 million in savings!”).