Petabytes, exabytes or zettabytes. It’s not all about size
We’re in the midst of a data revolution, with 4,400 exabytes stored in the digital universe in 2013, a number expected to grow to 44 zettabytes by 2020 (the equivalent of 9.4 trillion DVDs).
This explosion of data is often termed ‘Big Data’.
Big Data is not what you store on your personal computer, rather it is enormous data sets that can combine, cross match and provide insights that would otherwise be invisible. It is gleaned from multiple sources from mobile phones to travel cards and used well, can give organisations unique insights into their business.
So, when talking about Big Data, the question should not be “how much?” but rather “how useful?”
The industry rhetoric is that with huge amounts of data available we should be asking novel questions and solving new problems. Unfortunately, this leads to organisations getting hung up on accumulating masses of data and asking a myriad of hypothetical questions without any immediate business benefit.
The key to making better decisions today is using this data to answer the questions we’ve always been asking, aided by more information to deliver better, more accurate answers. When you visit a doctor you’re asked to provide information in order to help her understand your health. The questions a doctor asks are rapidly changing as our available data changes. So she may ask, “how many steps did your Fitbit register?” Or, “can I see the report from your internet enabled fridge?”
But some core questions haven’t and won’t change with time. How old are you? What do you weigh? What is your blood pressure?
Despite the new questions, the doctor will be better informed by having access to more available data for questions they’ve always asked.
In a corporate setting, when executives want to check if their company is healthy they also have a set of core questions. How many customers do we have? What is our quarterly revenue? What is our average product margin? How does our profit calibrate to this information?
Applying Big Data to address these questions will deliver more immediate benefit than asking something new that has no direct relevance to your company’s business.
Our experience is that businesses have a sophisticated understanding of how to ask these questions, but haven’t had the analytics or data to answer them. We’re helping them to embark on a technology journey that lets businesses ask ‘old’ questions in new ways which are not limited by data analytics constraints.
Let’s look at revenue assurance using Big Data. Previously, to track revenue leakage we would take data from an ordering system and check to see if the customer has the same product in the billing system, but in an ad hoc but tactical way by requesting data extracts and running reconciliations as one offs to find missing revenue.
Now, using Big Data and the associated analytical tools we can plug our same reconciliations into the Big Data environment and run scheduled, automated daily checks to find missing revenue.
The same data sources let us connect billions of rows of customer data across dozens of sources and touch points to paint a rich picture of interactions. To ask customer experience questions to identify specific root causes of frustration with opportunities to turn detractors into advocates.
Same questions but much more sophisticated and timely results.