Machine Learning, in particular, is one of the most closely watched technologies, which the world’s largest and most innovation-intensive companies are already embedding at the core of their systems. This could revolutionise processes and businesses, and SAP has already developed a Machine Learning strategy to harness this new technology.
For SAP, the centre of gravity for its execution of this key strategy is located in SAP’s Innovation Centre Network (ICN) in Singapore, where a team that works on machine learning solutions for sales and service, the finance and HR areas as well as cross-industries, is based.
The facility includes data scientists who are already part of SAP’s team, as well as a pool of Machine Learning PhD students in excellent university programmes who could potentially be a great fit for SAP’s new facility. The lab currently has about 95 people.
One of the teams at SAP’s Innovation Center Network (ICN) location in Singapore works on machine learning solutions for sales and service. One of these is SAP Service Ticket Intelligence, which categorizes customer service tickets automatically, routes them to the right agent, and provides the agent with recommendations for solving the issue at hand. The more tickets the solution processes and the more user feedback it receives, the more efficient it becomes. In short, it learns as it goes along. It’s in processing this unstructured data in customer tickets that the strengths of machine learning really come into their own, and thanks to built-in machine learning algorithms, the model understands the semantics of the tickets, is able to recognize similarities, and improves over time.
SAP Service Ticket Intelligence is offered as a discrete business or web service and as part of SAP Hybris Cloud for Service. And it’s a prime example of SAP’s strategy of making all of its solutions smart ‒ a strategy that describes the machine learning team’s vision.
SAP usually automates business processes. Its developers do that by programming (simple) rules to create a basic payroll or MRP process, for example. But where a problem is more complex because, say, the data involved is both highly unstructured and extensive – as in the service ticket intelligence solution – or what it calls the sweet spot for machine learning.
Additionally, Singapore hosts several of SAP’s other R&D facilities, including SAP’s co-innovation lab which opened in 2013 to offer its partners the space and infrastructure to experiment with hardware and software combinations.
