Fill in the blanks: Which X is Most Likely to X?

May 21, 2009
67 Views

Business analytics allows organizations to make decisions and take actions they could not do (or do well) without the analytics capabilities.

INCREASED EMPLOYEE RETENTION
Which of our employees will be the next most likely to resign and take a job with another company? By examining the traits and characteristics of employees who have voluntarily left (e.g., age, time period between salary raises, percent wage raise, years with the organization, etc.), business analytics can layer these patterns on the existing work force. The result is a rank order listing of employees most likely to leave and the reasons why. This allows managements’ selective intervention.

INCREASED CUSTOMER PROFITABILITY
Which customer will generate the most profit from our least effort? By understanding various types of customers with segmentation analysis based on data about them (and others like them), business analytics can answer how much can optimally be spent retaining, growing, winning back and acquiring the attractive micro-segment types of customers that are desired.

INCREASED PRODUCT SHELF OPPORTUNITY
Which product in a retail store chain can generate the most profit without carrying excess


Business analytics allows organizations to make decisions and take actions they could not do (or do well) without the analytics capabilities.

INCREASED EMPLOYEE RETENTION
Which of our employees will be the next most likely to resign and take a job with another company? By examining the traits and characteristics of employees who have voluntarily left (e.g., age, time period between salary raises, percent wage raise, years with the organization, etc.), business analytics can layer these patterns on the existing work force. The result is a rank order listing of employees most likely to leave and the reasons why. This allows managements’ selective intervention.

INCREASED CUSTOMER PROFITABILITY
Which customer will generate the most profit from our least effort? By understanding various types of customers with segmentation analysis based on data about them (and others like them), business analytics can answer how much can optimally be spent retaining, growing, winning back and acquiring the attractive micro-segment types of customers that are desired.

INCREASED PRODUCT SHELF OPPORTUNITY
Which product in a retail store chain can generate the most profit without carrying excess inventory but also not having periods of stock outs? By integrating sales forecasts with actual near real time point-of-sale checkout register data, business analytics can optimize distribution cost economics with dynamic pricing to optimize product availability with accelerated sales throughput to maximize profit margins.

These are three examples of the contribution that business analytics can provide – solutions such as offered by my employer SAS. This blog’s title is “fill in the blanks.” One can think of hundreds of other examples where the goal is to maximize or optimize something. With business analytics, the best and correct decisions can be made and organizational performance can be tightly controlled and continuously improved. Without business analytics, an organization operates on gut feel and intuition; and optimization cannot even be in that organization’s vocabulary.

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