What is Prescriptive Analytics?
In general, the data analysis techniques help us improve a business management. Firstly, Descriptive Analytics helps us understand the current state of the business more carefully, and secondly, Predictive Analytics contributes to estimate what we do not know.Finally, there is a third level of analytics that works as an extension of these processes: Prescriptive Analytics, which aims to be fully integrated with the business.
Prescription is based on the recommendations made by the analysis system itself on the actions that must be followed in order to reduce costs or improve benefits and increase ROI. Here are some examples of using Prescriptive Analytics to:
Make a planning
Make a planning to create transport organizers for retailers or distribution systems so that costs generated by trips and storage are minimised, maintaining guarantees on the levels of service at the sales points and allowing for external factors affecting the demand expected.
Set a pricing strategy
Make recommendations on the most suitable price for each room in hotel chains to maximise benefits, considering demand foresight and key factors such as national holidays and weather forecast.
Consider public attendance in stores
Estimate the number of customers who will attend a sales point every day, and calculate the staff needed to guarantee the service and keep costs under control.
Perform predictive maintenance
Perform predictive maintenance of transport fleets or street furniture from cities, replacing periodical service or repairs in case of failure with a system that gives recommendations on the right time to do the service for each component, thus reducing costs incurred by breakdowns and repairs.
Prescriptive Analytics contemplates not only the business data, but also how decisions impact on the costs and benefits, and which restrictions and considerations must be accounted for in the actions to be performed. This allows generating automatically realist action policies, impacting directly the ROI of the business.
How does it work?
The Prescriptive Analytics discipline uses as a base the whole knowledge and techniques from Descriptive and Predictive Analytics (classification, prediction and segmentation), and also relies upon fields such as operations research and numerical optimization. Roughly speaking, a prescriptive system compiles business information and predicts on the basis of this information the impact that future policies or actions will have, finally choosing the policy showing the highest return on inversion by means of an optimization process.
Every business is different and, consequently, there is not only one general Prescriptive Analytics solution that works for everyone. Therefore, designing any prescriptive system implies a consultancy work in which the IIC experts cooperate with the client to codify the costs and rules of the business in the system, then designing a customised optimization system that finds the best policy for every moment.
In addition, it is also possible to include several restrictions or limits in the system to balance risks against benefits and choose the best decision.
Once it is displayed, the prescriptive system is constantly loaded with business data (sales, stock levels, performance measures…) to recalculate the planning and execute it automatically or under the supervision of an expert.
All in all, the system allows improving the ROI of the business directly through informed decisions, and indirectly due to costs reduction on the planning process.
Benefits and value of IIC Prescriptive Analytics solutions
Prescriptive Analytics offers:
Automatic adjustment
Automatic adjustment of sales prices, with the aim of maximizing benefits.
Reduction of management costs
Reduction of management costs by means of generating automatically policies that minimise costs, keeping the service levels.
Direct and measurable impact
Direct and measurable impact on the ROI, unlike other data analysis techniques.
Guaranteed efficiency of IIC Prescriptive Analytics solutions
According to a Gartner report, in 2015 only 3% of surveyed companies are using Prescriptive Analytics to improve their business management, despite the high value involved. In parallel, there are few Big Data companies with the capacity to accomplish the development of a prescriptive system.
IIC has a team of highly qualified professionals both in machine learning and numerical optimization, a combination of skills and expertise that are particularly appropriate to design prescriptive systems that fulfil the response times and efficiency required for each individual project.
Prescriptive Analytics makes recommendations on the most suitable price for each product, so benefits are improved.