What is prescriptive analytics?

Prescriptive analytics tools like Gurobi equip you to make optimal business decisions in the midst of extreme complexity. For example, you can decide exactly which products to produce, in which quantities, in which order, and in which facilities, while taking into consideration production minimums, manufacturing time and costs, raw material inventory, and inventory capacity, in order to minimize total product costs.

Prescriptive analytics is one of the three main types of data analytics, as show below:

Three Primary Types of Analytics

What is predictive analytics?

Predictive analytics tools—like machine learning, statistical models, and simulations—seek to find patterns in data, in order to predict what might happen in the future. For example, you can estimate industry growth, raw material pricing, revenue or profit growth, or changes in demand by product line.

How can prescriptive analytics be used with predictive analytics?

Predictive analytics looks for patterns in historical data and uses those patterns to make predictions about the future. Prescriptive analytics can help you find the optimal way to achieve your business goals, given those predictions.

For example, if you were planning a trip, machine learning can predict what you may encounter along your journey (weather, traffic, engine trouble). But with mathematical optimization, you can take those predictions into consideration, as well as your goals (fastest, cheapest, safest route) and constraints (time, budget, speed limits), and identify the single best road you should take.

 

What is an example of prescriptive analytics?

One popular prescriptive analytics use case is marketing campaign optimization—enabling you to offer the right product to the right person at the right time, so you can maximize your marketing ROI while satisfying your business constraints.

Another example is production planning:

Your goals/objectives:

  • Minimize product costs

Your constraints:

  • Minimum production of a given product
  • Required manufacturing time and cost of a particular machine
  • Raw material inventory
  • Finished goods inventory capacity

Your decision variables (the questions you need answered):

  • In which order should we produce which products?
  • In which manufacturing facilities?
  • On what product lines?
  • In what quantities?

Other examples include inventory optimization, location planning, portfolio management, vehicle routing, workforce scheduling, and more.

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