Reconstructing Business processes with Predictive Analytics

By CIOReview | Friday, November 23, 2018

Having a good data science team is a must for all the organizations as it helps in improving the company’s business processes. These newly available tools allow enterprises to do things which were not possible initially like recommending customized products to online buyers and many more.

The process of Business Process Reengineering (BPR) was introduced in the 1990s, and it focuses on the process of analyzing the business and challenging everything about it.

Predictive Analytics and BPR

Data science and big data analytics are the game changers for BPR. There are numerous areas where data science can add value to the BPR efforts, though the most compelling one is predictive analytics. This analytics blows up the existing assumptions regarding the business processes and gives a new direction for business to evolve.

Predictive analytics digs out information from data sets to unearth complex relationships, recognize unknown patterns, forecasting trends and also helps in finding an association. This enables organizations to anticipate the future and make the right decision, and therefore the application of predictive analytics in business intelligence is uncountable. It is recommendable to hire business experts to help in identifying areas which require predictions.

Business process re-engineering is the process of creating a core business process with the aim of improving product output, quality, or reducing costs. It involves the analysis of company workflow, finding methods that are inefficient, and figuring it out ways to get rid of them or change them.

How is BPR affecting business experts?

A common challenge faced by all the leading organizations is engaging the business experts who will eventually play the role of developing the business. BPR efforts are fueled by the expectation that the technological advancements will replace the work which is currently done by human beings.

While the organizations are revamping their businesses and are still able to retain their business experts the next step is to consider how predictive analytics will be used. The people in the prediction business of an organization are the best ones to know what to do after the prediction is made. The customer service representatives can best predict what customers prefer therefore letting them go, can turn out to be a considerable loss; they can spend time servicing the customers and building a healthy relationship with them.

Conclusion

Predictive analytics is a powerful weapon which kills assumptions and discovers efficiencies which are required to accomplish the corporate mission and strategy. By predicting what will happen, partnering with a business expert to identify possible opportunities, BPR can be exciting, rewarding and extremely productive with the use of predictive analytics.