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Friday, April 20, 2018

SAP Study Reveals Key Traits of Machine Learning Leaders

Nearly half (48 percent) of the companies who say they have already benefited from machine learning cite increased profitability as the top benefit they have realized, according to a new study from SAP SE.

A similar share of companies who are already benefiting from machine learning also expect revenue growth of more than 6 percent for the two-year period of 2018-2019, the study showed. The study was conducted by the Economist Intelligence Unit (EIU) and written in discussion with SAP.

“Making the Most of Machine Learning: 5 Lessons from Fast Learners” is based on survey results from 360 senior executives across four geographic regions: North America, Europe, Asia Pacific and Latin America. The study identifies the opportunities, value and implications for companies that look at machine learning in a holistic way. The results also reveal leading companies — called Fast Learners — that are already seeing substantial benefits from machine learning. These benefits span the entire organization and include increased profitability and revenues, greater competitive differentiation, and faster, more accurate and more cost-efficient processes.

Traits of Machine Learning Leaders

Fast Learners hold five key traits. They:

  • Make machine learning a C-level strategic priority: Fast Learners have senior management who understand the strategic value of machine learning and are more open to embracing change. Seventy-five percent of Fast Learners plan to retrain employees displaced by machine learning to perform more interesting and higher-value tasks that keep them within their organization.
  • Drive competitive differentiation and innovation: Fast Learners see machine learning as a way to stand apart from the competition. Thirty-one percent say machine learning has already resulted in business model or business process innovation. For example, UK-based Ocado, an online grocery retailer, created its own machine learning–based logistics platform for automated warehouses that it plans to license to other retailers.
  • Recognize potential for new revenues and profitability: Fast Learners have realized that machine learning can increase profitability and impact new revenue streams, due in part to faster, more accurate and more cost-efficient processes — including the ability to identify revenue opportunities more accurately.
  • Keep key processes close to home: Fast Learners are spending more today on business functions — such as finance and HR — sourced locally (58 percent) than they are in low-cost regions (22 percent) — and they expect that trend to continue. Business relevance and customer value will increasingly take precedence over cost in important decisions on sourcing priorities.
  • Implement an enterprise-wide strategy: Fast Learners are implementing machine learning enterprise-wide, rather than within individual business units or functions. They have also done more to integrate machine learning into key customer-facing and product development functions. Forty-one percent say machine learning is translating into higher customer satisfaction.

“Machine learning is creating results for businesses — both on their income statement and with their customers,” said Mike Flannagan, senior vice president, SAP Leonardo and Analytics. “Executives need to view machine learning not as a quick fix but as an integral part of a larger strategy to give their business a competitive edge. This requires looking past the initial investment and focusing on the potential for long-term business value.”

About the Study
The survey underlying ​“Making the Most of Machine Learning: 5 Lessons from Fast Learners” was conducted by the Economist Intelligence Unit​ from September to October 2017. The survey included 360 senior executives from four geographic regions: North America, Europe, Asia Pacific and Latin America. Half of the respondents came from organizations with $500 million or more in annual revenue.  Read the full study: https://www.sap.com/ml-study.

To view the original press release, please click here.

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