The field of analytics has brought new and varied opportunities at a time of disruption and severe professional tension. It has emerged kind of as a silver lining for those who were worried about the security of their careers. In the light of this, it is important to say that these opportunities are not reserved for a select few from certain technical fields; they are for every person who is enthusiastic and prepared to put the hours in.
Business analytics in layman terms
If I said business analytics involves the use of conceptual layer in business logic in order to resolve problems, I would be right but it would not explain it too well. In fact it is one of the major responsibilities of the business analytics professionals to explain complex stuff in layman’s terms; ergo we make an attempt at it.
Let us say Mr. S has a chain of restaurants. One in Bangalore, two in Delhi and two more in Kolkata. Now just as you read this article Mr. S is counting his profits for the month of January 2020. And he finds that the profit margin has significantly dropped in the Bangalore joint. So, he has got a business problem. Now, if he pulls out every piece of information on the buying and selling at the joint and compares it to the data from the other joints in order to find out what went wrong, he would be performing a form of business analytics.
The first step : Describe
Mr. S looks at all the spreadsheets kept by the employees at the different branches of his restaurant chain. He has the data in front of him. He can see what offers had been run; how many plates of poha were sold; how many new customers visited the joints (they keep the phone numbers of customers); how many old customers did not make a visit; every thing.
The point is that Mr. S can now describe what has been happening at the restaurants for the last month.
We call this descriptive analysis. It is the first component of business analytics as well as data analytics. When the amount of data increases as significantly as to be qualified as big data and acquires the variety and velocity suited to big data, we need certain tools and skills to tackle it. Mr. S appoints a business analytics professional who learnt from the premium business analytics learning materials
Step 2 : Diagnosis
It often occurs that you know something in your body hurts but you cannot really put your finger on it. A similar situation is observable in the field of business. You keep losing money without realizing where exactly the problem lies. Diagnostic analysis helps the analysts find the lacuna – the gap in your otherwise full proof business strategy.
Business analysts do not only look at the business data but also a variety of structured and unstructured data from various sources.
They could look up what people are saying about Mr. S’s food joint on different social media platforms. Now, you must realize that this is easier said than done. Textual data is unstructured, unclean and often deceptive so, these are perilous waters. However, after a fair bit of deliberations and pondering the analyst point fingers at a number of variables that might be the cause of the losses.
The game called Prediction
By this time the analysts have delved deep into the buying patterns of the customers. They know which snack gets around the tables the most at what part of the day or the week. And they know what’s rotting in the inventory. Based on the data they can make predictions that can help stock up the inventories with stuff that may actually have some demand. Predictive analytics is often the most ambitious step taken by a business analyst until she decides to step up the game.
Getting ambitious with prescriptive analytics
The analyst Mr. S had hired now knows what is happening in the company. She has identified the problem and made some predictions. The next step would be to think of a situation where certain positive changes can help sky-rocket the profits.
Based on the analysis it can be anything. She can suggest a change of pricing, a change of menu or even a change of venue in order to drive more profit.
In the end Mr. S’s problem might be solved, it might take some more time but what matters the most is that he did the right thing by prioritizing data and maths over intuition and gut feelings.
