Why everyone needs data- but only some get it right!

Businesses small and big are waking up to the fact that data, used the right way, really amounts to much more than facts and numbers

big data

Author

Tirumala Rao Bokka is the Founder-Director and CTO of Spoors

“In God We Trust. Everyone else must bring data.”

This quote by one of the most eminent statisticians of the world really summarizes what all the world should ideally rely on. The question is:

How much do we leverage the opportunity that data presents. And, do we really strive for the right data?

Today, terms like Big Data have taken ubiquitous status among business priorities. Businesses small and big are waking up to the fact that data, used the right way, really amounts to much more than facts and numbers. Yet, there are umpteen examples of data being misused.

Data should ideally be used to guide your decisions and not the other way around. Recently, we heard of a company as big as Microsoft using data the wrong way. Executives at the company hired researchers to only support what they had already concluded.

Every researcher and marketer worth his salt knows the importance of data, yet, we find a dearth of data that lends meaning to everyday business.

What exactly are the challenges involved?

1. There is no authentic way to collect data

Too many times, there is misplaced emphasis on the metrics that matter to the bottomline of the company. To understand the deeper data story, managers should not only be willing to track and measure, but cull out the important metrics to drive the business forward. Data integrity is also an issue because managers often do not deploy the right tools for data measurement.

2. Data collection is expensive and/or inconvenient

Data collection is a long-drawn and expensive process. Traditionally, companies employ manpower to collect and trawl through heaps of data. To be able to find the right catchment areas for your data requires a deep understanding of the market- which, in turn requires more data handling. How and where to spend money to kickstart the collection process and keep making sense from it takes money, effort and dedicated resources to produce meaningful data.

3. Challenges in data consolidation

While there are many several benefits to data analytics, the data collected must first be consolidated and normalized to make sense of the reporting and analytics ( to be be able to get the real picture about your numbers). Actionable decision making that stems from this kind of deep dive data consolidation are likely to be sound decisions that bear the company’s long-term interests in mind.

Like most things, technology is usually the simplest answer to all the data woes- big and small. Data collection, integration, consolidation and analytics are all ongoing projects which do not have end dates, and the earlier we start the better.

Using the right tools is about taking away the pressure from these tasks and making room for something far more important- informed decision making.

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