Big data seems like a buzzword around tech and business circles at the moment, but it’s for good reason. The deluge of data – or more importantly, how insights are drawn from it – can have a profound effect on the way we do business.
While handling data is complicated, it can be put to work to simplify business planning and forecasting, helping executives make smarter, more informed decisions, and helping companies become more agile and responsive to today’s dynamic business environment.
“When it comes to big data, it’s not the existence or storage of the data that is really important, but the information and knowledge we can extract from it,” says Professor Sally Wood, Discipline of Business Analytics at the Sydney University Business School.
“The existence of big data has really led to the awareness of the value of evidence-based decision making using rigorous analytics.
“It’s the use of rigorous analytics with real-time experiments that offer companies a competitive advantage.”
The key is to pick difficult problems and draw insights from the right kind of data around those issues. With the right analytics tools the result, in many cases, is a real-time view of what’s going on, spotting hidden trends and patterns.
Here are some examples of how big data, despite it seeming like a complicated topic, can actually introduce clarity to business decisions and planning.
Better understand the types of people you need to recruit
Taking on a new employee is a huge investment for a company. Instead of making a decision to hire a candidate on face-value, data can put some quantitative metrics behind the recruitment process.
One company which does this is office equipment manufacturer Xerox. The company monitored staff performance in its call centres to figure out what the characteristics of an ideal candidate were. What it found was past experience in a call centre was not an indicator of success and that candidates with a criminal record often outperformed those with a clean slate. The experiment reduced staff attrition rates by 20%.
“There is a view [in business] that it’s all about gut instinct and ‘I don’t need data to tell me,’ ” Wood said. “Then I say, ‘Let’s see how well you can predict the future. Let’s have a data-driven model and let’s pit it against your instinct. Let’s see which one wins.’ Nine times out of 10 it’s the data-driven model [that wins].”
Understand precisely the mix of demand for your product or service
Often businesses hold stock and offer services which are either taken up ridiculously quickly or go unused or left sitting on the shelf. By analysing purchasing data and customer search queries or activity, a business can figure out whether, for example, they should be stocking more black t-shirts in a size medium and less blue ones in a size small.
Knowing you when – and where – to raise and lower prices
By analysing transactional data you can figure out where your customers are, what they’re buying, and determine their needs from that information. Finding hidden correlations that provide insights is one of the major areas where data can unlock new value for businesses.
One of the famous stories told about data – supposedly stumbled upon by Walmart through transaction analysis – is the discovery that young men like buying beer and baby nappies at the same time on a Friday evening, because they are staying home for the evening rather than going out for a drink. The myth goes that baby nappies and beer go on sale at the same time, or end up being placed together conveniently for young dads at that time of the week. The point of the story is surprising correlations, which reveal new truths about customers, can be hiding everywhere in the data a business collects.
Direct your resources more precisely.
There’s no point opening a store and wearing all the costs which go with that without customers. Looking at customer activity can provide insights into your busiest times, and assist with scheduling the right staff on at the optimal time.
Wood says, “One of the insights that big data gives is us is the realisation that it’s not ‘one size fits all’. It enables us to drill down and understand our business processes at a very micro-level.”
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