Predictive Analytics Attains Strategic Objectives across Business Functions - Objective-Compete

To compete is one of the vital reasons for the necessity of predictive analytics. Predictive Analytics enables unique and powerful competition in business.

Wrong business decisions in the tough global economy can make things worse. For this reason large companies are taking the help of predictive analytics to flourish and compete. In order to increase profits companies are making use of data, analysis , reducing risk etc. Previously more emphasis was given on maintaining inventory , hiring talents etc.

Analytics deals with the use of quantitative methods for deriving insights from data, after which it is used to make business decisions for improvement of performance. It can thus be termed as game changer. Predictive Analytics makes it possible to look forward, instead of analyzing what happened earlier it analyzes what will be the next scenario and how will we handle it.

Customer behavior can be measured with the help of business analysis. This is done by taking into account the past records. However, a vital and imperative approach is to compete on predictive analytics.

• The future needs of customers is met by making the correct decisions, which can be done by taking the help of predictive analytics that enables business to look forward. With it, problems can be solved by considering the combination of known and critical things ,and so a number of objectives can be achieved. The objectives include business objectives, the objective of uncovering hidden patterns in the behavior of customers, and thus help in business performance.


• From a report it was visible that most of the companies employed predictive analytics instead of traditional analytics. The median ROI was 145 percent in case of projects based on predictive analytics, while for projects incorporating traditional analytics the median RIO was 89 percent only.


• For executing and measuring predictive analytics scheme it speaks more than crunching numbers. Analytics function nowadays is based on retention group and customer insights.


• It serves both the enterprise's and customer's long term needs ,thus building a trusting and strong relationship. An example can be cited in this regard: Sub-prime mortgage crisis occurred because companies didn't paid attention to the needs. A great trouble occurred for this in the financial markets. It had been different if companies used predictive analytics.


• Higher ROI for predictive analytics can be achieved if business goals are well defined. This is because if goals are well defined the scope will be focused and measurement can be made more accurate. Retailer for example has a goal for increasing his sales. The target and actionable goal is to make sales from high value customers. When the goal becomes more specific there arise more measurable and distinct sale strategies.

There are new approaches for numerous customer segments. This has happened because of predictive analytics. Customer behavior can be predicted over a certain period of time that is dependent on both goals and asset profile.