Everyone wants a piece of ‘big data’ but most people are not
really sure how to go about it. It is generally thought of as a large
investment involving big companies who can help set up the infrastructure to
collect all the data they will ever touch, generate or consume. The thought is
that this investment will enable them to visualize the data in various fancy
ways or give them ability to slice and dice the data as they could imagine. These
are all great capabilities and will be useful for an organization who is mature
in such data based decision system, but most companies are not even looking at
the data they already have which could be very useful in providing them with
insights before they start to venture into the World Wild Web of outside data.
For SMBs and even for some of the large companies, just collecting
and using the in-house data itself can help them with better understanding and
taking various decisions. For example, a retailer can make actionable decision
in various parts of a business lifecycle; buyers making the right buying
choices based on the data on pricing, demographics, seasonality and
competition; merchandiser can reach the customer at the right price point with
the right promotions as well as bring in
new customers and provide up-sell and cross-sell; fulfillment can be an exact
science as supposed failed promises and disappointed customers; and technology infrastructure
can plan accordingly for promotions and seasons.
One of the challenges for the SMBs is that they generally do
not operate their own technology which is maintained and hosted by other
companies. And in many cases, they do not even have access to their own data. For
them, the first step would be to bring their own data under their control so
they can start to assess it and drive value from it.
Some of the forward-thinking companies are changing this
culture and moving from gut-feel to fact-based when it comes to decision
making. A clear example is the product pricing on Amazon.com where the prices
can change within minutes and there is no manual person involved. It probably
took many years and few mistakes before the merchandisers were comfortable with
a system making such decision, but nonetheless this is the only model which
would have scaled for Amazon without leaving any penny on the table. So the companies
which collect this data and apply various predictive and optimization modeling algorithms
to it are going to get a lot better and efficient than the ones who don’t.
The term ‘Big Data’ could be intimidating as it seems to
suggest that everything about it is big; commitment, investment, and so is the
value. That’s why I prefer to think of it as ‘Smart Data’. In the end, it’s
just data and all of a sudden it’s sexy again.
