The Economist Intelligence Unit report, “The Deciding Factor :Big Data & Decision making,” commissioned by Capgemini, reveals that nine out of ten business leaders believe data is now the fourth factor of production, as fundamental to business as land, labor, and capital. The study, which surveyed more than 600 C-level executives and senior management and IT leaders worldwide, indicates that the use of Big Data has improved businesses’ performance, on average, by 26 percent and that the impact will grow to 41 percent over the next three years. The majority of companies (58 percent) claim they will make a bigger investment in Big Data over the next three years.
Data analysis tools used by banks to determine if you are likely to default on loan repayment, could soon help nab criminals.The National Crime Records Bureau decided to deploy data analytics to not only track criminals but also to predict incidence of crime in a region on the basis of past incidents.
Banks are teaming-up with retailers to target customers by analysing the customer data they collect more closely.
A bank can’t make a customer spend £1,000 that they were not planning to spend. However, if the customer is planning to buy a new TV for £1,000, for example, then there might be ways to encourage the customer to use that bank’s credit card, or to take out a loan.
The use of data to drive management decisions and product design is well known in the financial sector. Today, most commercial banks utilize data analysis to support their decision-making. Grameen Foundation’sMicrosavings Initiative uses these same techniques to help advance the mission of our partner microfinance institutions (MFIs) to effectively bring savings products and services to their poor clients.
Sears (A major retailer in North America) is using big data to help set prices – nearly in real time — and move inventory by giving loyalty shoppers customized coupons.
Sears is using the software to correlate huge quantities of information about everything from product availability in specific stores to competitor prices on specific products to information about local economic conditions in order to set prices.
There’s great opportunity for new business models to emerge. One example is a 9-person firm in Israel that manages an online site that uses analytics to aggregate thousands of social media feeds to provide their audience with a single view of information, research and opinions on various medications on the market. They do not promote one drug or treatment over another. They simply provide a single view of related data for consumers to read what other patients have experienced – in their own words – so they can make their own decision.
No matter the staff size, annual revenue or number of offices, Big Data can be a big advantage for small, medium and large businesses – if they have access to the tools that can help them link relevant information sources while finding useful insights that are buried deep within.
CIO Journal has spotted billboards for Big Data along the side of the road — in Times Square and on Highway 101.
Big Data itself isn’t a competitive differentiator, but your ability to find creative ways of using it very well may be. For instance, at eBay, Big Data is used to identify potential fraud, according to its CTO Mark Carges; at retailers Gilt Groupe and Sears, it’s used to improve product recommendations – but even there, the two companies use different types of Big Data software and have different hardware set-ups to run it.Commonwealth Bank of Australia’s CIO, Michael Harte, tells CIO Journal the bank is using Big Data for real-time pricing and risk assessment, allowing its reps to make credit decisions instantaneously.
Here are top 3 reasons why marketers should let themselves fall in love with data scientists:
1)Drowning in data = bad time management.
Marketer’s time belongs in marketing … not stuck in a spreadsheet with numbers they can’t begin to understand. This critical task is best done by Data scientist.
2)The C-suite craves structure around new marketing methods.
Now, more than ever before, the C-suite demands accountability, and data scientists are best hope for understanding big data, interpreting results and providing solid insights to act on and report.
3)They’re not just machines—they’re part-magician!
Data scientists aren’t robots or computers (though their ability to process information may outstrip your laptop some days). Data scientists know how to deal with facts and ideas, with “definitely” and “maybe.” They pull the big picture from the big data mosaic, and make it make sense.
If you’re a marketer trying to dig your way out of big data, it’s time to admit that you can’t do It alone. Let a data scientist sweep you—and your marketing goals and plans—off your feet.