Unlocking the value of the networked economy

April 13, 2015
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Pfungwa Serima - CEO - SAP Africa
Pfungwa Serima – CEO – SAP Africa

, Big Data? That’s so last decade. What we live in today is an era of Massive Data – and it’s growing by the second, as we connect everything from our businesses to our coffee pots to create a giant networked economy. The real challenge that companies are facing is how to make sense of this data, and to use this newfound network to create connections that make a real difference.

They won’t necessarily admit it, but most companies are sitting on a pile of data that can reach halfway to the moon. Problem is, they’re not necessarily doing much with it. It’s called “dark data” – terabyte upon terabyte of information that nobody really knows what to do with, but they don’t want to get rid of it because it might prove useful at some point.

Worse than dark, it’s often unstructured, which means it’s disorganised and raw. In fact, research house Gartner estimates that roughly 80 percent of all corporate data is unstructured. And it keeps pouring in from everywhere: customers, suppliers and partners.

The good news is that if analysed and understood, this avalanche of information can deliver a keenly insightful picture of your business at any given time. If you are able to quickly respond to what your markets are telling you – like market fluctuations or an increase in demand – then you’re ahead of the game. To do this, though, you’ll need some business intelligence solutions that turn this deluge of data into understandable, actionable insights.

Welcome to the world of predictive analytics. It’s not as arcane as it sounds. We come across predictive analytics every day without even knowing it: weather forecasts, insurance premiums, credit analyses are all based on this core ‘enabler’ of big data. In a business, it gives you the opportunity to spot trends, anticipate customer needs, forecast wider market trends and manage risk.

Generally, businesses tell us they want to better understand their customers, make more accurate financial predictions and improve their sales forecasting. But beyond these obvious uses, companies are starting to think more strategically about how they can further use the information they gather to drive revenues and grow their businesses.

Here’s an example. During the holiday seasons, retailers will be looking at ways of gaining an advantage using predictive analysis. So if a customer bought a cooker last month, chances are they will need their gas refilled in the next couple of weeks. But what else can you sell them when they come in? How often do they come into the shop? What specific deals can you offer them to make them come in? If you can answer these questions, chances are your bottom line will be looking healthy come January.

Predictive analytics is very much a fledgling market, but it’s on the rise as data volumes grow. In fact, 2013 research from SAP found that for 60 percent of businesses, predictive analytics is already an investment priority. Additionally, more than two-thirds of companies think that predictive analytics will be an investment priority for them within the next five years.

The use of this technology is putting data firmly at the heart of organizational decision-making, across all sectors and industries. And it doesn’t take rocket scientists to operate it, either: the technology in increasingly intuitive, with easy-to-use interfaces that reflect the realization that data should not be the exclusive responsibility of one individual or department; it should be front of mind of everyone. Make data visual, current and actionable, and suddenly analytics starts developing the potential to drive real value.

Ultimately, though, what will really see predictive analytics coming into its own is the ability to affect a cultural shift to one of greater collaboration. By avoiding information silos, and encouraging integration across the business and its networks, we will start to see the real power of analytics. It’s going to be a wild ride. Be sure you don’t get left behind.

READ: Is big data the solution to Africa’s big issues?

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