Businesses are slow-moving creatures that operate on established processes to keep them going. They don’t generally have much awareness of what is going on around them, or have the ability to react to the changes they do perceive.
The landscape that businesses are operating is changing so that this mechanical approach to the market is no longer workable.
The scale of commercial enterprise has grown so that many organisations operate at a global level. At the same time, local markets have become more fluid with customers’ demands changing rapidly.
Communications technology has allowed individuals to interact with each other and for corporate networks to extend far beyond the boundaries they were designed to operate within. They reach mobile employees in the field and in some cases customers directly all over the world.
Customers converse with each other online about their suppliers and this sentiment is available to suppliers if they have the ability to pick it out of the rest of the world’s digital chatter.
Cheap computing devices have allowed IT to become pervasive and the numbers of objects, from phones to vehicles that are traceable and able to communicate their states to each other is expected to increase exponentially in the next few years.
On one side is a mountain of information that is now at the organisation’s fingertips and on the other is a powerful drive to use that data to move with the swiftly changing winds of the market.
Big Data, the term coined to describe this wealth of information, is abundant and easily collectable, but it is very difficult to winnow out the relevant from the rubbish. Much of it is in forms that conventional data management systems cannot cope with.
Much of this data is unstructured or human-friendly – it comes in the form of emails, text, video, phone calls or tweets. It’s very difficult for instance to analyse all of the calls from a call centre to find out customer satisfaction, even though every call can be digitally recorded and stored.
Data analytics is a form of IT service that has been designed to shape corporate data into understandable forms, so that business leaders can make informed decisions on customer behaviour or predict shifts in the market in time to turn them to their advantage.
For instance, a UK retailer that is able to understand the shift in consumer demand from red shirts to blue shirts a couple of months before the summer season, will be able to bulk order cheap blue shirt stock from its Chinese supplier and have it in the stores when consumer demand is high, not weeks after the trend has moved on.
The traditional database vendors have recognised the need for more sophisticated data analytics systems and big names like IBM, HP and Oracle have all rushed to acquire or develop offerings that process big volumes of unstructured data. But, internally organisations still lack employees with the skills to be able to process and interpret the data, and turn it into meaningful guidance for business users.
Business-line managers themselves also can be distrustful of analytics systems because they have learned to trust their own gut instinct when it comes to on-the-spot decision making and see the introduction of such systems as undermining their value to the business.
Cultural changes have to take place on many levels for an organisation to make use of Big Data, but as always, knowledge is power and no organisation can afford to ignore the sea of information washing up on their doorstep if their competitors are using it to steal a lead on them.