Prescriptive analytics tools help you make decisions based on your real-world goals (“objectives”) and limitations (“constraints.”) This can be especially useful when you’re facing a business problem with multiple, conflicting goals (such as cutting spending while increasing production) and multiple constraints (such as time, distance, product availability).
Predictive analytics tools seek to find patterns in data, in order to predict what might happen in the future. For example, predictive analytics can predict who will launch which cyberattack, which experiments are more likely to prove the hypothesis, imminent machine failure, supply chain issues, infrastructure maintenance needs, and price movements—all before they happen.
Although there are countless ways to use prescriptive analytics, here are some real-world examples, with links to their stories:
Prescriptive analytics tools provide a detailed set of recommendations for how you can best achieve your goals, given your limitations. Although you can use it to automate decision-making, you can use it to inform your traditional decision-making processes. Its ability to explore what-if scenarios can be particularly helpful.
Say you were planning a trip. Predictive analytics can predict what you may encounter along your journey (weather, traffic, engine trouble), and prescriptive analytics can, given those predictions, identify the route that best helps you achieve your goals (fastest, cheapest, safest route), given your constraints (time, budget, speed limits).
Here are some additional examples:
Prescriptive analytics doesn’t rely on historical data—which means you can make decisions for the future, even when it doesn’t look like your past. To use prescriptive analytics, you need to know three things:
With this information, the prescriptive analytics tool can generate a detailed action plan for achieving your goals, given your limitations.
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