Big Data

SAP invests in machine learning to simplify customer transition to cloud

SAP believes it has the capabilities to deliver machine learning solutions to help customers improve their end-customer journey and tackle issues that were previously too costly.

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As SAP continues to makes its own transition into the cloud, the company is also focused on delivering applications that will help customers make that same change simpler.

At this year's recently held SAP Sapphire Now conference in Orlando, Florida, a key theme for the company was introducing machine learning to its HANA cloud platform.

CEO Bill McDermott predicted that over the next five to 10 years the hype will be around machine learning, artificial intelligence, and augmented reality.

"I think very strongly that intelligent applications will fundamentally change the way you do work in the enterprise and the way you collaborate with your trading partners outside of the enterprise," McDermott said.

He went on to say that machine learning has the capabilities to help businesses make more informed decisions around how they can better serve their end-customer.

"We need the system to tell us what to do," McDermott said. "Based on algorithms of that data and inputs that are in that data bank, we need to be able to advise you on the next step for your sales cycle, who you should meet with, and what the expected outcomes are, and what the level of probability would be on you striking a deal."

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At the same time, McDermott said the appeal of using machine learning as part of business processes is that it will "liberate workers."

"The difficult, tedious tasks will get essentially helped out a lot by the technology. For example, if you're matching a job candidate and profile in the human capital management department, or you're selling a product as a retailer and on social media you're getting a lot of feedback, the machine will learn what that feedback is and make a decision on what the response should be, based on what is going on," McDermott said.

Bernd Leukert, a member of the SAP executive board, vouched SAP's "significantly improved platforms" that now have the capability to run algorithms "at the speed where businesses can get value of them."

"The algorithms themselves have existed 20, 30, 40 years. When I was going to university 30 years ago, I was attending university lectures on AI in operation research. However, at that point in time, the computers, the hardware, and the related memory was far too expensive in order to provide at scale business advantage," Leukert said.

"These algorithms can match this and can give you a significantly higher match rate. What 10 people did is probably what one person can do now," Leukert said.

One industry SAP plans to apply machine learning to is healthcare, with McDermott saying it will help solve some of the difficult challenges that the industry is currently facing.

"I don't understand why we can have great first responders, nurses, doctors, surgeons; but we still have an archaic medical record system," McDermott said.

"The patient needs something digital, they need somebody to know them...I can't understand why we can't put an electronic record in a secure cloud that is aligned to one individual, and if they provide the authorisation for people to see their history, and they can go from one person to another seamlessly ...I believe they should do that," McDermott said.

Co-founder and chairman Hasso Plattner made similar remarks despite acknowledging there are still complexities around legislation, particularly in the European Union, to work through.

"It's what we really need...but it's a totally difficult marketplace. There are different regulations in different countries, different regions in the world, but they need next generation software systems. Countries like Germany have to rethink whether privacy laws are hindering us from doing a personalised medicine, or are making it so complicated that nobody goes there," Plattner said.

Plattner continued: "If we can use how we do history maintenance for machines, how we do root cause analysis for machines, and yes the human body is much more complicated, but the same principles apply there."

SAP said it also plans to use machine learning to help tackle gender bias. Using capabilities within its SAP SuccessFactors HCM Suite, SAP plans to help companies identify and track where bias exists in talent acquisition and management processes, with hope it will address any workplace biases.

Despite these plans, it's still the early days for SAP when it comes to machine learning and combining it with data, said Leukert, who believes it's a "completely new business" that requires new business models, and one that will receive dedicated investments going forward.

The 3 big takeaways for TechRepublic readers

  1. SAP plans to use machine learning to help customers stay competitive by personalising the end-customer journey.
  2. Specific focus areas in which SAP plans to use machine learning include in the boardroom, to tackle gender bias, and to develop new applications.
  3. SAP is taking its analytics business a step further with machine learning, which further signifies another phase of the company's transformation process into the cloud.

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Disclosure: Aimee Chanthadavong travelled to 2016 SAP Sapphire Now courtesy of SAP.

About Aimee Chanthadavong

Since completing a degree in journalism, Aimee has had her fair share of covering various topics, including business, retail, manufacturing, and travel. She continues to expand her repertoire as a tech journalist with ZDNet.

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