The impact of machine learning is likely to be rapid for those who have their technology house in order. It is a truism of the technology industry – first identified by Bill Gates the Microsoft founder – we often underestimate how long a new technology needs to take hold, and then we underestimate the impact it will have over time.

On one hand, machine learning seems be testing the limits of that rule. It feels like it has burst upon the world only recently, yet in truth the work has been decades in the making.

And much of the early success of machine learning is actually built off the significant investments companies have already made getting their core systems in order.

According to Rebbecca Kerr, the general manager technology at mining company Roy Hill, “From a technology perspective, my view is if you’re not investing in the enabling technologies, you’re never going to leverage the value from the newest innovations.”

She noted that Roy Hill spent three or four years building the right technology foundations for its digital mining operations.

Intelligent enterprises effectively use their data assets to achieve their desired outcomes faster – and with less risk.

For companies like Roy Hill who have established these enabling technologies, now that machine learning is is available, uptake is likely to be rapid and its impact is potentially dramatic.

At the recent SAP Real World Transformation Summit, we asked Deloitte’s Brad Burt and SAP’s Stephen Moore whether they believed machine learning and AI is truly on an accelerated development path.

“Absolutely,” says Burt. “I think if you look at all sort of transformational technologies we are discussing today — machine learning, IOT, the data analytics and blockchain — I think machine learning certainly has the most immediate application.”

According to Burt, it is also accelerating faster than the others.

“Today when you jump onto a retail site it knows what you bought last time and it makes predictions about what you might want. I think a lot of this also comes back to the big data question as well. It really is dependent on data.”

He described machine learning as an advance from the big data technologies of the past and echoing the view of Kerr, who said it is important to get the enabling technologies in place, Burt said the success of big data has accelerated machine learning to be where it is now.

SAP director Stephen Moore said companies are moving from predictive analytics into predictive insight.

“I think if the retailer and the customer have a shared insight, the retailer knows what you bought, so they can then be insightful about what you may want to buy next.”

Retailers can then provide the same insight back to their suppliers in terms of what’s selling and what isn’t.

For companies, all these extra insights provide an important opportunity. “It’s allowing companies to rethink the process, the actual work process, and not just the interaction. For each one of those transactions that we’ve described, if you apply those to a complete workflow then AI can actually simplify the process and shorten the process time.”

Moore said, “To Rebbecca Kerr’s point, if you’re limited in how efficient you are at producing an ore body, if you’re limited with how much you can ship, the only game in town is to reduce the cost per tonne aboard because you can’t ship anymore volume.”

He said the win for companies could come from reducing the number of processes, the complexity of the processes and the cost of the process. “And you can do that most effectively by the application of these new technologies, that’s the winning formula.”

About the author

Andrew Birmingham is the director of the Which-50 Digital Intelligence Unit of which SAP is a member. Members provide their insights and expertise for the benefits of our readers. Membership fees apply.


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