Over the past year I have had an increasing number of professional conversations about data and analytics, spanning concerns from the strategic to the technological, touching on subjects that might be mistaken for a discipline within natural sciences - i.e. the cloud, lakes and reservoirs. On the main, these conversations have been with senior executives in major global financial institutions, predominantly tier one banks. I will mention some of the items on the veritable smorgasbord of factors contributing to the rise in these conversations, as they go beyond the phenomenon of FOMO wreaking havoc in what is notoriously competitive industry. But I will also go beyond this; beyond my professional dealings, I have become acutely aware how the trend of interest in the subject is beginning to play-out in my day-to-day life and I am fascinated by where this is taking us (nod to Yuval Noah Harari for his bestselling works: 'Sapiens: A Brief History of Humankind' and 'Homo Deus: A Brief History of Tomorrow', both of which I thoroughly recommend).
Having been a headhunter in financial services since the crisis of 2008, I am no stranger to the industry's imposed obsession with compliance, risk and regulation, which has been a major factor in the increased interest in data. Financial institutions accumulate vast swathes of data on a daily basis and there is now a number of regulatory requirements associated with their stewardship and management of this data - and rightly so. However, a heightened interest in data also affords benefits and opportunities beyond a response to scrutiny alone: improved data about customers enables optimisation of business offerings across new and existing markets, which is an advantage only just being tapped into; the application of analytics technologies, tools and techniques can transform facts and figures into strategic insights that reshape business models and drive profitable growth; and better quality data and cutting-edge tools can help these organisations to protect customers from harm, such as fraud and cyber crime (see, McKinsey's article on the subject, for example).
The bank providing my current account recently made such capabilities known as I ventured deeper into this digital era through the purchase of cryptocurrencies - these were initially stopped by my bank before I verified them as legitimate through a mobile bot. That same week, I noticed how much I was being targeted by numerous online retailers punting various women's items, which was (I hope) a result of the research I was conducting for my wife's upcoming birthday. These are just two amongst many recent anecdotes of data and analytics visibly at work in my day-to-day life.
The impact of advancements in data and analytics will continue to be felt in a tangible way by Joe Bloggs and Jane Doe, perhaps increasingly so. The prediction of demand is a clear front-runner for service providers and retailers alike; the bane of Uber's surge pricing, shared by any, is a good negative analogy but the flip-side of this coin will be benefits such as the ability to purchase high-demand items from retailers who have almost prophetically predicted the correct balance of supply and demand at pressured times of the year for consumers, such as Christmas. Improved pricing will come hand-in-hand with this; targeted discounts, promotions and segment-based pricing are experiments already being conducted and benefiting consumers. What is less felt by consumers, however, is the area of maintenance as a service; it is conceivable that our homes will be serviced before we would normally be aware of the need as IoT diagnostics tell our insurers, for example, that out boiler is on the brink of collapse. This points towards other possible uses of IoT by insurers, who might request IoT-deduced data from life insurance policy holders for actuarial purposes. In turn, this points towards uses in the medical field, which is already seeing beneficial practical uses of wearable devices.
Data volumes will undoubtably grow, especially as the number of handheld and mobile devices (noting the evolution of the IoT phenomenon) continues to grow. Data technologies and analytics tools are evolving in favour of user-friendly capabilities that enable the relative layman to extract expert results. With this, however, comes issues around privacy, especially with the imposition of new privacy regulations. In light of this, the evolution of autonomous agents, including robots, may become a preferable option, especially if there is a shortage of subject matter expert personnel in the field. But herein lies a call for caution (Elon Musk on the subject is fascinating).