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.
