Insight brokerage digital information and machines - The future of big data
Ian West, VP, analytics and information management, Cognizant, explores the evolution of big data and its potential in the future
Much has been said about Big Data in recent years. From data lakes and geographical locations to analytics and technology tools, the opportunity for businesses to take advantage of better understanding their customers through the data their actions and behaviour produces is the Holy Grail. Many organisations are working to sort and secure their own data in order to start gleaning insights from it but, in my view, Big Data as we know it has evolved.
Instead, there are three specific areas I think offer the biggest opportunity for businesses to start making the most of data.
1. Gathering the right information
The first area of interest is insight brokerage - the idea of pulling different data sets together from differing sources, outside the remit of one particular or single business. This could be from various organisations offering, for example, their data for purchase, open source data or personal data from social media accounts. Companies increasingly want to construct a stronger, ongoing dialogue with customers, and therefore need to have a clear picture of who they are and what they like in order to build brand loyalty, what we call “Code Halos” - the data surrounding people, place and things. Historically this has focused on observing and analysing buying behaviour, acquisition patterns and product adjacencies that then led to up-selling, cross-selling and future purchase recommendations. But increasingly, embedded technology and real-time analytics will focus on point of acquisition behaviour and influence customers with hyper-personalised offers, to incentivise a certain type of behaviour at a particular point in time depending on where the person happens to be, time of day, weather conditions and a plethora of real-time metrics.
With Big Data and machine learning colliding, there is even more of an opportunity for businesses as they can pre-empt the way customers will behave and act accordingly. One key element to note is that the vast majority of people who want a social media presence, already have one. The challenge is to use these pools of immensely valuable information to truly understand customers, and predict what they will like, based on previous purchasing decisions for example and how they might behave in certain scenarios.
2. Smart data
The second area of interest is digital information. This is the ability to listen to what customers are saying across multiple sources and adapt to what is important to them in real-time using technological advances. This is a big task, but an essential one.
The Internet of Things (IoT) means that this information is particularly useful for any organisation that can embed sensors into their client interactions such as utilities and energy companies. They can monitor individual customer behaviours and preferences to offer micro-personalisation and rewards. For example, British Gas’ Hive allows the company to understand its customers’ behavioural patterns such as what time they get home from work, turn on the oven or do their washing, which in turn gives British Gas a real-time view of the consumer’s lifestyle leading to things like providing customised offers based on these insights.
3. Rise of the machines
Businesses need to access these pools of information to underpin their digital transformations and many organisations are seeing data as the critical foundation for building their transformation strategy. Machine learning is a key piece of a digital information strategy; however, businesses need to go one step further and embrace data economics - securing real monetary value from that data.
With data offering so much value, there is a growing demand among businesses to harness it and make the most of the opportunities it offers. This is set to lead to the emergence of Information-as-a-Service. It will mean harvesting the right data quickly from multiple different sources and having the answers ready in seconds, to address pressing business challenges that may not be immediately visible.
Looking to the future
Gartner recently said that the future will be machine learning. While Big Data is evolving and machine learning is playing an increasingly prominent role, the future of Big Data is more than machine learning alone. By harnessing the opportunities presented by machine learning and insight brokerage, and to compete in the market, businesses of the future will need to embrace a fully information-enabled digital strategy.