Big data analytics: getting the right information to the right people at the right time

It is becoming increasingly clear that an organization’s ability to achieve high performance in today’s shifting, competitive business landscape will be largely dependent on its ability to get the right information to the right person at the right time. With so much competition out there, and so much data being generated, it’s now become vital for enterprises to use big data-derived insights to identify important intelligence like hidden market trends, customer behavior and security breaches to create value and profit. With big data analytics, companies will have a greater degree of intelligence to help them make better-informed decisions, develop more timely strategies, spot disruptive trends, both positive and negative, and create new types of businesses. Whether you’re a large enterprise in the manufacturing industry or a non-profit organization in the public health sector, one message is coming through loud and clear: big data and big data analytics are going to transform the way businesses work.

So where is all this big data coming from?

Governments, businesses, individuals, and even machines are all contributing to the massive accumulation of data. Companies maintain vast amounts of transactional data, gathering information about their customers, suppliers, and operations. And the same is true for the public sector. Most countries in the world manage enormous datasets containing census data, health indicators, and tax and expenditure information. If you then add into that online and mobile financial transactions, social media traffic, and GPS coordinates, in other words, the kinds of activities that most of us do several times a day on our smartphones, we are currently amassing over 2.5 quintillion bytes of global big data daily.

It isn’t just humans who are contributing to the mass of information either: increasingly machine-to-machine communication is also creating huge amounts of data. Digital sensors are installed in shipping crates to track movement along a route and send the information to transportation companies; sensors in electrical meters measure energy consumption at regular intervals and report the information to utilities companies. The gathering of such information is becoming increasingly common. It’s estimated that are more than 30 million networked sensor nodes present in the transportation, automotive, industrial, utilities, and retail sectors today, and the number of these sensors is increasing at a rate of more than 30 percent per year.

How will we know if big data analytics actually adds value and efficiency to enterprise?

While big data may be big news right, it’s worth bearing in mind that it’s been around some time. It may now have come into mainstream consciousness, but some organizations have been using it for a while now and have been benefiting from the analysis of big data and data mining. Amazon is a prime example. The online retailer has been using data in this way for years and has utilised customer information, purchase history, and other data to power its recommendation system: that’s why the recommendations are so spookily accurate. Similarly online dating services have analysed big data to determine potential matches among their users, and sports teams put digital information to use in their recruitment strategies. Studies by bodies like the McKinsey Global Institute show that those companies which have been employing data-driven decision-making, achieve productivity gains that are 5 percent to 6 percent higher than other factors could explain.

Even in the public sector, big data analytics have been used to better identify needs, provide services, and predict and prevent crises among low-income populations. A new initiative by the United Nations, for example, is using natural-language processing software to predict job losses and spending reductions in the regions that are considered to be at risk. They will then be ahead of the game and able to help and agencies deal with any potential issues. During the cholera outbreak in Haiti in 2010 and 2011, researchers tracked the movement of people from the affected zones to new areas via data generated by SIM cards. This information helped aid organizations prepare for new outbreaks.