There’s a segment of the tech services sector who are now and forever breathing sighs of relief – and probably slapping one another on the back down at the bar on a Friday night.

They are the companies who (since around 2010) have been yelling at other companies about their data; the companies who built giant, sleek businesses around the data promise, who could demonstrate the value of big data, could project visions of world dominion from that big data, but who really didn’t produce the goods in the final analysis.

Big data was a bit of a grey area for a decade or so. Business Intelligence got a boost from analytics to some extent, but it often seemed that neither party really had a clear idea of what to do about sorting the (often majority) data that was left out, nor even what sorted, interpreted data’s true value might be – and how they’d apply it afterwards.

If everyone can now be honest, we can acknowledge that there was (too often) a large gap between the promised value of “sorting your data” and what came out of the other side.

Also, there were needed practice runs on how to collate irregularly formatted data, or work across platforms in so doing. The sheer volume was intimidating, and the level of analytical (read: artificial) intelligence in play at the time was limited. Data companies got big and wealthy while everyone – customers included – went through the learning curve.

Today’s specialist analytics companies have redeemed that erstwhile faith in their abilities and, no matter the previous silent moments when analytics was a fledgling field, it’s has become an essential business tool now that its intelligence is greater, its application wider, and the results amazingly accurate and informative.

In fact, London-based firms servicing startups have seen a shift towards analytics being a now-default inclusion into companies’ Business Intelligence, marketing strategies, and overall digital reality. Analytics always was the answer to big data.

Now that it’s found its feet, the adoption of its insightful, strategy-enabling, and fraud prevention abilities has been swift and wholesale. Few things have jumped into the global commercial toolbox as a ‘must-have’ as easily as analytics. It just needed to walk its talk, and the results were inevitable.

The fundamental shift that analytics enables

To truly appreciate just how analytics as a field has transformed business agility, dexterity, and overall fitness, it’s useful to put it this way:

Thanks to analytics, companies are now able to shift from simply analysing historical data to improve performance to monitoring what’s happening right now to enable proactive performance.

In other words, analytics has shifted from presenting historical data in a legible fashion, to – after having collated and learned from historical data – tailing and flagging issues in the here and now.

That might seem like ‘no big deal’ to people not leaning heavily on analytics, but it is in fact a massive shift.

Hugely enabling when it comes to business dynamism (as business at large faces a still relatively unknown future), it’s a small wonder analytics has found such widespread uptake. It’s like being able to see the global markets, in your head, every day as you conduct your affairs, seeing every possible input that might impact your profitability.

Previously, that took a lot of reading on the ‘tube before you arrived at the office! Plus a whole slew of data analysis, information gathering, and liaison that staff had to wade through, quite apart from the in-house record-keeping that would enable a storehouse of historical data in the first place. Unfortunately, the results would be limited at best anyway. Sufficient, but limited, and they’re no longer sufficient on a quickening globe.

Analytics gradual approach to the finish line of real-time, exquisitely relevant data is nearing completion. The obvious next step is having analytics encroach upon Business Intelligence even more, sorting and interpreting the data, and having a hand in formulating strategy based on that data.

Right now, that decision-making is predominantly a human privilege – but this will change.

It’s interesting to note that Nike, for instance, has hired John Donahoe as its new CEO. Donahoe is a veteran executive from the technology sector, not apparel or footwear, or anything else consumers might associate the brand with.

A former president of eBay Marketplaces and a former CEO of ServiceNow – a cloud computing outfit – Donahoe’s appointment serves as a flagship example of how businesses are becoming dependent on analytics, today capably boosted by very impressive AI, with the IoT thrown into that commercial mix for good measure. Management has become far more (artificially) intelligent, and far more demanding of those with technical savvy.

Analytics is both symptomatic and causal of the tech reality today, and the future we’re heading towards. As a recent Forbes article noted – every company is a data and analytics company – they might just not put it that way… yet.

If the future is a robot, analytics is its blood

Set a trajectory, fiddle with it on the way there, and you won’t end up where you thought you would. That’s obvious. And it largely remains – in this incredibly fast-paced and disruptive business environment – a persistent source of angst for executives.

Business Intelligence informed company strategy, and the way forward was broadly set at regular intervals. With the phenomenal advances and sheer volume of analytical intelligence now available through applied analytics, “regular intervals” can now be daily updates, and “optimum strategies” can change overnight.

That’s not as scary as it sounds, as those “overnight changes” are more a tweaking of the company strategy en route towards success, and not a wholesale abandonment of such strategies.

That angst aspect of execution has diminished. The race towards real-time, comprehensive Business Intelligence is almost over, but it’s geared towards the same goals – successful strategies that will enable profitability now and in the near future.

Rather than applied analytics being a threat to consistent strategy deployment and business success, it’s an aid. Analytics allows executives to fine-tune strategy from a base of vastly improved, comprehensive Business Intelligence, making a more effective beast of strategy, not dissolving it on the back of daily whims.

Now, marketing is more targeted and powerful than ever. Fraud detection and prevention are making life extremely difficult for the crooked among us. Companies can shepherd their strategy not with dated reports, but rather in real-time, as proactive analytics enables them to be more current on any management aspect at the drop of a hat.

Business Intelligence itself might very well become peopled with data centre staff whose role it is to flag any anomaly that might predict a profitable swing in strategy. New “Business Intelligence centres” may be looming, but it’s hard to avoid the fact that AI could do the job better already. In fact, it is doing it, and any needed detailed analysis and management of the enhanced data that analytics enables on a daily basis will likely be best served by analytics itself as part of the process.

From being broadly reactive entities, formulating strategies based on historical data, companies are now able to become proactive centres of business dynamism, forging forward and defining markets, rather than trying to catch up with market leaders. Analytics is beginning to form the core of all companies’ business model.

Admittedly, analytics can’t quite tell the future yet, but just wait – that’s coming, too.

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