Small Businesses Need Data Not Big Data

08 Jan,2020


By Sanjeev Kotnala


‘Big Data’ and ‘Data Analytics’ is everywhere. It is the current buzzword, just like Machine Learning, Artificial Intelligence and BlockChain. It seems unless you are not working with Big Data, you are not in business. However, not every organisation has the capability, resources or a mindset to walk the Big Data and Data Analytics road. Then what do they do?

It reminds me of a question in IIM Ahmedabad first year. The problem was simple. How many Puri Bhaji packets must the vendor in Platform-II at Ahmedabad railway station make? He should neither waste and nor miss an opportunity to sell. It has sheets of probability tables of trains arriving, on time, probability of trains being late,  number of passengers alighting, passengers going to Ahmedabad, transit passangers, the likelihood of passengers being hungry and ordering Poori Bhaaij. Now that was real Big Data in 1985.

We all had varied answer ranging from 28 to 169 packets. And we had our logic and rationale for the process we adapted to get to the solution.

I asked this question to a business owner client of mine. His answer was straightforward. He said ‘forget the consultants and the data you are talking about.  If the vendor is enterprising, he will observe other vendors for two days, maybe err for the next 2-3 days. But, by Day 7, he will have his algorithm of deciding how many Poori Bhaaji packets to make.



I have the fortune of interacting with Chalak Malak, highly engaged owner of small- to medium-sized businesses. They are not capturing Big Data. Yet, they have all the relevant patterns at their fingertips.

The Chalak Malak’s insight is based on his observations and an uncanny ability to connects the dots. The level of understanding is unbelievable. And, yes, most of these observations are ratified and endorsed by the excel-PowerPoint spewing MBAs and researchers in the company. These owners are not seeking data supported confidence.

These owners work purely on observations. Their interactions with sales and market are their most valuable data point. At time hugely disjointed data. They do not encourage the interlinking of a multitude of variables. They focus on detailed microdata with limited variables that are essential to predict and control their business.

They work with data that is easily accessible in the business and informative. Something that the organisation can make sense and understand the use of complex systems. It is just data; some data. Neither Big nor Small. Every data capture, recording and discussion are objective-driven and aiming at actionable insight. There is democratic discussion and ultimately a dictatorial approach which facilitate time-bound decisions and implementation.


Unstructured Data.

The Chalak Malaks in these small businesses are happy with such scarce data. They understand business is not all science. There is luck involved. They keep variables that are not in their influence and control outside the preview of discussion. Without Big Data and Data Analytics, they draw upon the predictive and prescriptive impact of their focussed data.

The individual owners’ unstructured data mining ability is enormous. They can observe and analyse reams of data and come to a conclusion fast.

They are not the CMOs looking for extension and a case study to create. They understand the need to act. They take the risk of acknowledging that failure is part of the process. They give themselves the time to Pause, reflect, absorb and move on with life.

There is some sort of a black box in their brain. It uses acquired or genetically downloaded powers to analyse data, draw conclusions, unveil hidden patterns, with an undefined internal algorithm, define market trends and examine overt or covert customer preferences.

Having made sense of the possibilities, they are only interested in actionable. They are least interested in ‘Gyan’ on background, opportunities, business environment and risk mitigation.

We may interpret such decisions as gut-feel or biased. However, they are well informed and evaluated choices.


Big Data Is Understood.

They know of the existence of Big Data and data analytics. They know it requires a budget, resources allocation and talent for it to be leveraged. However, they understand their organisational culture and talent structure. They feel in the current stage, the internally generated data across minimal but crucial variables is what the business needs!


Small Data Used In Big Way.

If not, they are aware of the tools and inputs they could borrow from. They use their eCommerce partner for insights. Google Analytics tells them what the visitors are wanting. Social media acts as a listening post. The blogs and articles are trend analyser. E-mails on skeletally managed customer complaints and appreciation are their warning mechanism on quality and service. The everyday sales and cost reports are their health indicators. Market share is approximation through real groundwork on estimation validated by the sales staff figures. The healthy networked conversation with competitors and well-wishers help business environment understanding. They bank on their grassroots connect and relationship with vendors (mostly non-exclusive) to get early warning signals.


Hate Grey Areas.

There are rarely grey areas. They are comfortable in taking a polarised view, And that is more than enough.

Segmentation is simplified. The consumer is a small, large, medium buyer, a repeat buyer or single user, a customer and/or a user. The data is not micro drilled but most likely aggregated. The regional and religion biases, taste and culture, form a different kind of filters while taking decisions.

They are more dependent and sensitive to the Velocity; speed at which they can get data and Truth-fullness; how much they can trust the data. They are less concerned about the volume; quantity and size of the sample, And the Variety; depth and width of probe or multiplicity of parameters.


Change Of Guard. Not Of Approach.

The new generation taking over is all for robust non-challenged data. However, a few things do not change. Focus on crucial impact variables, eye on ROI, the confidence in gut feeling, willingness to learn and tweak and the speed of action.



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