It has been established beyond doubt that data and its analysis can have a huge impact on an organization’s top line and bottom line. Business Analytics helps organizations deliver better business performance in two ways – by optimizing business processes and by helping to innovate. Optimization helps organizations be efficient and effective by taking inefficiencies out of the business processes and focusing on the high impact opportunities. Innovation on the other hand helps organizations by uncovering new customer segments, new product categories, new markets, new business models etc.
The styles of analyzing data are many fold from answering questions like “what is going on?” to “why are the things the way they are?” to “what will happen if I do X or Y?” to “what does the future look like?” Broadly speaking the styles of analytics can be classified into three categories:
· Exploratory Analysis: The objective of exploratory or investigative analysis is exploration and analysis of complex and varied data – whether structured or unstructured for information discovery. This style of analysis is particularly useful when the questions aren’t well formed or the value and shape of the data isn’t well understood.
· Descriptive Analytics: The objective of this style of analysis is to answer historical or current questions like what is going on. why are the things the way they are?. This is the most common style of analysis and here the questions as well as the value and shape of data are well understood.
· Predictive Analysis: Predictive analysis aims at painting a picture of the future with some reasonable certainty.
So, what’s art of possible with business analytics? It’s the application of the above three styles of analytics to a business scenario for better insights, decisions and results. Let’s try and explain this with an example. Consider this scenario:
You are a Financial Services firm e.g. a large bank and are trying to improve profitability. You read Larry Seldon’s book titled “Angel Customers and Demon Customers” and agree with the findings that 20% of your top customers bring in 80% of the profits and would like to manage you business as a portfolio of customers as opposed to portfolio of products. So, how do you do that? The answer is business analytics.
You can start by using descriptive analytics techniques like operational reports, ad-hoc query, dashboards etc. on data collected from different sources like sales, customer service etc. to determine the profitability of each customer. You can then use predictive analysis techniques like data mining, statistical analysis to further enrich your customer data into profitability segments like high, medium, low and loss making customers. Finally, you can choose different customer service channels like personal banker, phone or ATM to cost effectively serve you customers e.g. a high profitability customer can be served by a personal banker free of charge but if the loss making customer wants a personal banker there will be a charge. Once you have implemented such programs you can use exploratory analysis to gauge the sentiment across social media channels like Facebook and Twitter to see if the programs are working as desired. Better yet you may come up with new innovative business models like mobile banking or online only banking to improve profitability.
That’s the art of possible powered by business analytics. Stay tuned, I intend to publish more examples from different industries to show the art of possible with business analytics.