“Most people use statistics the way a drunkard uses a lamp post, more for support than illumination.”
_ Mark Twain
Everybody knows that clothes sell more during weekends and holidays than during weekdays. Stocks, hiring temporary salesmen and even parking are based on this understanding. Unfortunately for the stores, this isn’t the whole truth. An analysis of sales data reveals that the demand for baby clothes is much higher during weekdays.
This single insight helped a popular retail chain make changes that led its revenue to grow by over 2 per cent. This was also huge for their bottom line because infant wear usually carried the highest margins and almost no discounts.
Making the right decision is hard. You have to frame the question properly, find the right data to support the analysis and do all this in a way that is transparent and repeatable. But without the right up-to-date information, leaders are often forced to rely too heavily on intuition, experience, and gut feel to make decisions. Getting decision-makers the right information is what enterprise intelligence is about. Utilising our driver-based approach and aligned to strategic goals, enterprise intelligence provides answers to the right questions, getting immediate answers based on real-time information from every corner of the company’s operations and enabling accelerated, strategic decision-making that is efficient and cost-effective.
Enterprise intelligence
One of the areas where enterprise intelligence is used extensively is in understanding customers better. In these cases, the data can play a pivotal role to understand the behavioural pattern of customers. The goal of this analysis would be to improve the top line and / or bottom line. Customer analytics is a blend of hard facts, common sense and business rules combined with behavioural economics and technology that can be used in everyday business to identify opportunities, seek actionable customer insights and derive intelligence.
Some common customer analytics solutions are predictive modelling like churn analysis, cross-sell – up-sell, customer segmentation and sentiment analysis. Customer analytics is being leveraged across most of the sectors. Retail, financial services, insurance, aviation, technology, consumer goods, telecom, pharmaceuticals and automotive businesses use data extensively.
A drug manufacturer used point-of-sale data collected from the pharmacies across a country to help understand the products that can be bucketed together. One of the analyses showed that patients buying calcium supplements have 92 per cent probability to buy Vitamin D also. The patients who buy medicines for lung diseases display 73 per cent probability to buy medicines for bacterial infection. Understanding these patterns helps the company identify target products and eventually gain market share.
The popular story of vehicle insurance companies analysing the colour of cars being insured and also charging a higher premium for certain colours is true too. Analysis of claims data reveals that black cars have a higher probability of an accident and a claim.
Similarly a telecom company improved cross-sell of its value-added services to its existing customer by more than 47 per cent by understanding the customer profile analytically and targeting the right customer sub-groups.
Targeted telemarketing has helped an insurance company hike its sales from 1.5 per 100 calls to 2.7 per 100 calls in a six- month period. This is an 80 per cent increase in sales for the same efforts. This became possible by studying the demographic profile of the existing buyers and targeting similar prospective buyers.
There are many similar success stories. In today’s environment with tremendous volumes of data and intense competition, there is no way any business can succeed without having the capability to use the underlying information within the data in the right context to enable business decisions.
There are more benefits to using an analytics-driven approach. This enables better informed decision-making. It is important that we understand the root cause and develop insights and intelligence by analysing in a rapid and iterative framework that brings insights / intelligence to our toughest business problems in days and weeks versus months and years.
It is also very important to build analytic capabilities that lead to an analytics-driven continuous improvement culture within the entity. This will make our decisions more objective. The analytics and the analytical tools are more an aid to the business decisions. The onus of the decisions still is on the managers.
Customer analytics are the key to the vault with hidden treasures which can help your organisation leap to active and proactive decision-making. Is your company there yet?
“Get the habit of analysis - analysis will in time enable synthesis to become your habit of mind.”
- Frank Lloyd Wright
N. Balaji is Enterprise Intelligence & Data Analytics Leader, Advisory Services, Ernst & Young. Views are personal.