Many years ago I had the chance to observe a local shop keeper chat up his customers at his store. His friendly demeanour, open ended questions and proactive approach to make sure you get what you want got him some clear responses. He would also meticulously note down some select information every now and then. This shopkeeper was one of the limited sources of household material for the local community and as the community grew I saw his store grow. Eventually, the store grew into a small mart that had one of the most effective layouts of household products. There was a plan in the design of the store. So some 20 years ago, how was it that a simple uneducated man with limited resources, no computers and technological resources get to create a best laid plan for his store. It boiled down to the information he collected from people over a period of time and observing the buying trends of people in the community.
Years later while working with a major investment bank and leading a legion of eager sales professionals on the investment advisory side, we had one thing to tell them –TALK TO CLIENTS. But more importantly, at a very basic level, the idea was to know them personally, their needs preferences and individual requirements. On the upper end of the information gathering spectrum, a dedicated team of quantitative and technical professionals were working on collating massive amount of information going back a number of years. All this data, as unrelated as they were, had significant bits of information sitting within that could give critical insight into multiple avenues such as customer segmentation, personalized product offering, risk and compliance and much more.
What we were able to achieve, over a period of time and with the limited technological tools available then, was a clear understanding of individual investment requirements/ patterns of some of our most critical clients and plan on how to service them most effectively. It came to a point that by the time the client came into office for a meeting a simple spreadsheet told the sales team what were the last few interactions on and how to plan the discussion for the meeting at hand. Most of the time, the sales call or a new product pitch was successful.
What we did and what the shop keeper did was nothing but gather information on consumers, clients and effectively analyse them to best service the same consumers and clients. This was basic information that could be tracked and analysed easily. This data – in a larger sense is now called Big Data.
Today we all hear this term Big Data being used frequently across industries and IT platforms and how it will change the way we see sales and client service. Imagine every swipe of your card or online transaction creating a data point that tells the bank what kind of products you are shopping, how much fuel you are using, what is your expense on an insurance policy and so on. Imagine then walking into a bank and getting the best deal on a product that best suits your purse.
So what can be the most basic understanding of Big Data?
In its most basic form Big Data is making sense of an enormous amount of information collected over a period of time. In a practical situation, this data cannot be analysed effectively with the normal data analysis tools available but needs to be broken down into smaller sets of data for effective processing and analysis.
How will it be of help to a service provider?
Consider having more than a bird’s eye view of a consumer’s requirement, lets’ call it intuitive foresight. Imagine being miles ahead of your nearest competitor in the understanding of a consumer’s pattern of requirement. To be able to service a consumer better, increase customer loyalty, have better production planning based on market needs, reduce wastage and most importantly increase revenue and profits.
From a retailer’s perspective, think about managing supplies to multiple point of sale locations based on purchases in a particular region by a variety of demographic groups, at certain points in time, driven by various unconnected events such as inclement weather, or a book/movie-release. Effective gathering and analysis of massive data originating from disparate sources in unstructured formats forms the essence of Big Data. Timely, accurate and insightful analysis of this information by retailers can support a cost effective plan on purchasing, production, warehousing, logistics and store presentation leading up to effective sales and market-share build up.
Effective utilization of the digital footprint of today as a data point
The digital footprint of today is one of the most non-invasive tools of data collection for any organization. Everything from looking up baby food online to shopping for furniture gives an insight into customer behaviour and preferences. The source of data collection has grown from direct internal resources to external data collection resources. As the most basic explanation, the effective mapping of this data from multiple sources is the key to practical intelligence gathering for innovative business solutions.
As with any new concept, Big Data has its own scary points. Giving access to information is a touchy subject, even though none of think twice when we click “accept all requirements” when we install applications on our smart phones or sign up for any online agreement. The availability of this information to national and international government bodies has become an even more controversial topic.
While the subject of Big Data will have its naysayers, it is a concept that organizations will eventually embrace for a benefit in the long run. It is upon individual companies what effective insights they want to draw from the data available and how effectively to use it. Responsible organizations are also putting together governance protocols on how this collated insight will be used and shared internally and externally. Consumer insights derived can enable organizations to compete innovatively, improve customer service, market visibility and revenue streams. Big Data will have an impact on most consumer (B2C) and many business-to-business (B2B) organizations including financial services, pharma, retail, CPG, logistics, energy, natural resources, healthcare, telecom and others.
Over a long term the cost involved to implement Big Data seems sensible enough to get the edge in the market. More to follow on soon on Big Data, Business Intelligence and Data Analytics.