Technology is now playing an increasingly sophisticated role in all of our lives; with more than three billion internet users globally, and more smartphones in the world than people.In a single second we type over 9,000 tweets, 48,000 Google searches, and 2.3 million emails, and UK consumers are expected to spend more than £50 billion online this year. We are all spending more time – and money – online, and businesses must be tech-savvy to survive. Leaders are undoubtedly aware of this changing dynamic; 4,000 C-level executives participating in a recent IBM survey consider technology the single most important external force shaping their business. Lying behind these statistics is a confluence of disruptive technological forces – social, mobile, cloud and analytics – all channelling the current explosion of data. Data-fuelled innovation is taking place right across the commercial landscape; from the smallest local companies to the largest multinational corporations. All businesses are in the business of innovation, and there are endless opportunities available to those using new technologies such as cloud and analytics to build their businesses. What is now key is adapting to the changing market and customer expectations. The dynamic nature of a digital marketplace leaves no room for error, as traditional barriers to entry are being broken down, and agile smaller businesses are seizing the opportunity to deliver a more personal response to clients and customers.
AnalyticsFor any business to lead today, it cannot afford to neglect its data. In the same way that the use of steam, oil, and electricity revolutionised the industrial age, data is a vast new natural resource for the digital age.
This resource is plentiful: last year’s mobile data traffic was nearly 18 times that of the entire global internet in 2000, and monthly global data is expected to surpass 15 exabytes by 2018. But in the same way that we have to refine oil, this deluge of data must be refined by analytic technologies to be put to practical use. In the insurance industry for example, one car insurer reimagined its entire operating model, offering “earned” premiums based on how safely each customer drives. They were able to analyse driver data using an on-board telematics device, and set personalised premiums based on individual customer behaviour. A regional police force went through a similarly landmark transformation, using data to achieve its lowest crime rates in a decade. Through analysing information from police reports they were able to identify incident patterns, predict crime “hot spots”, and allocate their resources accordingly. The aim of this strategy was not to produce a larger, or more forceful police organisation, but a smarter one – and it was strikingly successful in doing so.
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Another prominent example is a major utilities company, which was required to transform its cost base in the face of new regulatory requirements and commit to a $1 billion cost reduction.A large fraction of its costs stemmed from the maintenance of its physical assets: a process that was hugely time-consuming and prone to human error. The complexity of these assets meant even the monitoring process was a challenge, and in the event of any failures the operator was always a few steps behind. However, better consolidation and analysis of the data gathered by the network sensors has allowed the operator to get ahead of the game. This data is now used to forecast more failures in advance, and plan the maintenance strategy accordingly. As a result the utilities company is now on track to meet that reduction in operating expenditure – savings that will ultimately be passed on to the consumer. These are just a few examples of analytics in practice today, but the future of this technology is even more exciting. One of the tools now freely available is IBM Watson Analytics, a cloud-based analytics service based on the Watson cognitive computing platform which made its debut by winning the US general-knowledge game show Jeopardy! In 2011. Watson Analytics brings much-needed analysis to new areas within organisations including marketing, sales, operations, finance and human resources. It is a natural language-based cognitive service that provides businesses with fast access to predictive and visual analytic tools so they can analyse immense new streams of data. Continue reading on the next page to discover where mobile and social fit into the process. Image: Shutterstock
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