A Data Science Central Community
Author: Rahul Nawab, Co- founder, IQR Analytics and Promoter, ADSA (Academy for Decision Science and Analytics).
Educating savvy and business-minded Amdavadis on the importance of numbers and analytics in your business is like teaching the properties of sand to someone in the desert, but here is my effort anyway.
The simplest definition of analytics is "the science of analysis." However, a practical definition would be how an entity, e.g., a business, arrives at an optimal or realistic decision based on existing data. Business managers may choose to make decisions based on past experiences or rules of thumb, or there might be other qualitative aspects to decision making, but unless data is considered, it would not be an analytical decision-making process.
Analytics have been used in business since the time management exercises that were initiated by Frederick Winslow Taylor in the late 19th century. Henry Ford measured pacing of the assembly line, thus revolutionizing manufacturing. But analytics began to command more attention in the late 1960s when computers were used in decision support systems. Since then, analytics have evolved with the development of enterprise resource planning (ERP) systems, data warehouses, and a wide variety of other hardware and software tools and applications
Today, businesses of all sizes use analytics. For example, if you ask my fruit vendor why he stopped servicing our road he will tell you that we try to bargain a lot and hence he loses money, but on the street next to mine he has some great customers for whom he provides excellent service. This is the heart of analytics. Our fruit vendor TESTED servicing my street and realized that he is losing money – within one month he stopped servicing us, and even if we ask him, he will not show up. How many businesses today know who their MOST PROFITABLE CUSTOMERS are? Do they know who their MOST COST GENERATING customers are? And given the knowledge of most profitable customers, how should you target your efforts to ACQUIRE the MOST PROFITABLE customers?
Large business uses analytics to drive the entire organizational strategy. Some examples include:
· A credit card company in the U.S., uses analytics to differentiate customers based on credit risk and they match customer characteristics with appropriate product offerings.
· A Casino in the U.S., identified that against popular belief, their most profitable customers are the ones playing slots. To leverage this insight, they have created marketing programs to attract and retain their MOST PROFITABLE CUSTOMERS.
· An online movie service company, identifies the most logical movies to recommend based on past behaviour. This model has increased their sales because the movie choices are based on customers’ preferences and therefore the experience is customized to each individual.
Common applications of analytics include the study of business data using statistical analysis to discover and understand historical patterns with an eye to predicting and improving future business performance. Also, some people use the term to denote the use of mathematics in business. Others hold that the field of analytics includes the use of operations research, statistics and probability, however it would be erroneous to limit the field of analytics to only statistics and mathematics.
While the concept is simple and the notion is intuitive, the common leverage of analytics to drive business is just in its infancy. Please join me next time as I talk about the SCIENCE OF ANALYTICS.