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Smart Analytics the Heart of the Digital Economy

June 8, 2017 by SAP News 1

New forms of systems of intelligence are emerging with embedding AI, machine learning (ML), big data, analytics, IOT and blockchain.

So said Waldemar Adams, SVP analytics and insights EMEA, SAP, speaking this week at the Saphila 2017 Conference at the Sun City Resort in the North West province.

Discussing the value of AI and ML, Adams explained how big data first gained traction when it became the new buzzword, this was later followed by digital transformation and now AI and ML have become the latest fascination among innovative organisations.

“But what does it all really means, what is the difference between predictive analytics, machine learning and AI?” he asked.

Adams believes going digital entails a process of smart collaboration of running business processes combined with intelligence reporting, which provides insight on what is happening in the organisation and predicts what is likely to happen in future.

“These new data driven systems of intelligence enable us to reap unprecedented value from data, unlock new business models and re-imagine business process – across supply chains, customer interactions, work force experiences and many more. Relating to IOT, there’s a two-step process: collecting data and making use of it.”

In SA, he explained, the sectors leading in AI and ML are those with a strong consumer credit focus.

“Leading retailers in SA have been talking of AI and ‘neural networks’ for many years now. Banks, telcos, and retailers are industries which have, in the past lead the way with consumer related in-depth analytics. Use of scorecards, sophisticated consumer accusation, retention, exit systems and strategies have always been prevalent in this area,” he pointed out.

The sectors lagging are those which have not embraced the full spectrum of IOT in their industries, such as mining and manufacturing industries, he noted.

“Historically these industries have never had the need to do the level of statistical analytics that other industries have. The ability now to place sensors on equipment and capture this vast level of data insight is available today, the early adopters of this technology will benefit from AI and ML for new business models, contract management, and maintenance as a few examples.”

He quoted Joe Kaeser, CEO of industrial manufacturing company, Siemens: “Once I have data, how do I make meaningful analytics out of that data, so my customer has an advantage? My customer would pay me for information that makes life easier, better, less costly, or more valuable.”

That is the idea of turning dark data, which consumes space, into meaningful information, which allows organisations to get insights, thus helping them make more informed decisions, Adams asserted.

“ML and the ability now to better understand and act in the consumer space allows organisations to improve areas like customer marketing, loyalty and manage or predict delinquencies,” he concluded.

 

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