Data has increased in volume but has also gained richness and diversity - here's how businesses can benefit.
The exponential growth of data can’t be disputed, and new tools are constantly being developed to turn the swathes of raw data into insight. Fuelled by the Internet of Things and connected devices, data has not only increased in volume but has also gained richness and diversity. It’s generated by everything from connected vehicles and traffic sensors, to wearable devices and social media. In a single day, five billion internet searches are made, 294 billion emails are sent, 4PB of data is created on Facebook, and 4TB of data is produced by only a single connected car.
And that’s only set to increase: by 2025, 463 extrabytes (EB) – each made up of one million TBs – of data will be created every day, with much of it made available via a vast and interwoven network of words, clicks, images and signals, mostly transmitted by devices. Successful global businesses know the power of tapping into the network of data available to them – and underpinning it all with the cloud – in making better-informed business decisions, refining their offering and ultimately pleasing their customers.
First, what’s driving data analytics?
According to McKinsey, machine learning – a term that encompasses a range of algorithmic approaches – has rapidly advanced to the forefront of analytics. Combine that with increased investment in massive computing clusters, often accessed as cloud services, and underpin it all with a steady improvement in computational power, and the stage is set for strategic and creative upheaval in data analytics.
How can data analytics transform businesses?
A study by SAS found that 72 per cent of organisations said data analytics helps them generate valuable insight, while six in ten said their analytics resources make them more innovative. McKinsey, meanwhile, found huge disparities in performance between a small group of leading companies and the average company. Analytics is shifting the competitive landscape as industry leaders are using it to grow revenue, enter new markets, change the nature of their relationship with customers, and increase efficiency.
Digitising customer interactions also provides reams of information for marketing, sales and product development, and digitally native ‘unicorn’ companies know it. The likes of Uber, Airbnb and Spotify are thriving because their business models predicated on data and analytics – and it’s far easier to design new systems from scratch than it is to overhaul existing ones.
Global digital leaders have also harnessed the capabilities of data analytics to improve their core operations, or launch entirely new business models. T Mobile US, for example, halved customer defections in a single quarter by merging information gleaned from social media with its own transaction data, while Netflix has used customer data to refine its recommendation engine and roll it out to global customers.
In Raconteur’s Future of Data publication, Nick Bouch, data and analytics in assurance leader and partner at PwC, explains that C-suite directors have realised “just how important data is to the business, including the risks of not securing it correctly, the implications of getting regulatory and statutory reporting incorrect, the ability to apply advanced analytics and machine-learning to improve the supply chain, and its role in developing new products, and driving customer insights and engagement.”
Looking at return on investment alone, the benefits of data and analytics capabilities are profound. McKinsey found that on average, those who invest can expect productivity gains of 6-8 per cent, which translates as roughly double the organisations’ investment within a decade. That rate of return surpasses even the computer investment cycle in the 1980s, according to Jacques Bughin in the Journal of Applied Marketing Analytics.
How can companies start harnessing its power?
Starting small, failing fast and proving value are key for those successfully making the transition to being data-enabled, according to Bouch: “They have to be able to exploit and bring together their data faster and with greater agility, but they know they can’t change overnight. They adopt an evidence-based approach to data and prioritise where to spend their efforts.”
As is the case with most organisational overhauls, it all starts with developing a solid strategy. Working out the most important problems and opportunities within the organisation, and establishing KPIs for each of them, will help to hone in on exactly what needs to be achieved – and how data analytics can help to achieve it.
Once data and analytics is incorporated into a core strategic vision, the emphasis lies in fostering a data-driven culture within the organisation. Speaking to Forbes, Murli Buluswar, chief science officer at AIG, explains: “The biggest challenge of making the evolution from a knowing culture to a learning culture – from a culture that largely depends on heuristics in decision making to a culture that is much more objective and data driven and embraces the power of data and technology – is really not the cost.”
Data infrastructure and developing the right talent are equally important. Incumbents in particular should remember that the answer isn’t to layer powerful technology over existing operations, rather, it lies in digital transformation from the ground up.
Cloud-based data technology infrastructures allow organisations to capture their customer’s data across a plethora of digital touchpoints. While this level of digital transformation may be relatively slow and involve multiple steps, when it’s combined with strategic vision and a data-first culture, it enables an organisation to unleash the full potential of data analytics. And when it comes to employees, talent is critical in any data analytics journey, as Zoher Karu, speaking to Forbes, explains: “The way I build out my organisation is I look for people with a major and a minor. You can major in analytics, but you can minor in marketing strategy. Because if you don’t have a minor, how are you going to communicate with other parts of the organisation?”
Data-savvy companies like Netflix, Google and Spotify – who have seriously invested in cloud data analytics, shifted their culture accordingly, and remain agile to AI technology as it develops – are the ones at the bleeding edge of customer insight and experience. They’re also the ones proving that investment in data analytics is now near-enough non-negotiable.
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