Augmented analytics is freeing-up analysts and harnessing their human input

Boredom is a fundamental human condition. According to Dr Irving Biederman, a neuroscientist at the University of Southern California, the brain is hardwired to seek out stimulation. The human eye fixates on two points a second, looking for anything interesting, inspiring or entertaining and anything less is boring.

Apply this thinking to your most talented data analysts and it’s easy to see why most organisations have struggled to retain and attract key data skills. The data skills gap across most global regions is well documented. In Europe, for example, there could be as many as 756,000 unfilled jobs in the European ICT sector this year, according to the EU. The problem organisations face is how to retain skills they have already acquired because once they have gone, they will be extremely difficult to replace.

As businesses have evolved, embraced digitisation and re-shaped their working patterns and processes, they will have done so in a piecemeal fashion. It is almost inevitable that this change has led to increased complexity and in many cases, a run before you can walk mentality. The upshot is that, at least from a business intelligence point of view, businesses will have developed a patchwork BI tools and solutions to rapidly changing organisational problems.

These analytics tools will inevitably be a mixed bag of outdated applications, plug-ins and third-party add-ons, aimed at solving specific issues or delivering specific insights. Data analysts will almost certainly be using their time to cleaning and organising data to then run reports and visualisations for business decision makers. It’s a bit like asking a racing driver to be in charge of a car’s oil.

Embed and augment

As the data increases – which of course we know it will – so the role of those data analysts will become more pressured. Organisations will face a cliff edge where bored data analysts will leave for more stimulation in other companies or industries and there will be a vacuum, as those roles will be almost impossible to replace.

The simple answer to this is; don’t let it happen. Make sure your data analysts don’t get bored but work on high level analytics that can make a strategic difference to the business. Freeing them from the shackles of data cleansing and organising and reporting is key, and only through embedded analytics, and more specifically augmented analytics, is this going to be possible.

According to Gartner, augmented analytics becomes crucial for presenting only what’s important for users across the business in their specific context so they can act in the moment. The result is less biased decisions and more impartial contextual awareness -transforming how business users interact with data and make decisions.

By automating the analytics process, business decision makers can easily and quickly access data to inform their departmental decisions. They do not need to wait for data analysts, go backwards and forwards on visualising various scenarios before reaching a critical point. They can do it themselves, with little or no technical knowledge, freeing up in-demand analysts to work their magic at a higher level.

So why bother? Well, we know for a fact that data science has a significant role to play in modern, growing and dynamic businesses. According to McKinsey’s Catch them if you can… report, 47 percent of organisations surveyed say that data and analytics have significantly changed the nature of competition in their industries in the past three years. 

The message is clear. Data and analytics are now fundamental to business growth. Data analysts are critical to this success. This group of valuable talent must be engaged at a level where they can work strategically and do what they do best – adding significant value and leave the grunt work to augmented analytics tools. It’s either that or boredom and we know where that leads.