Part 1 of the three-part series, “Innovating the Intelligent Enterprise“
As the debate over the impact of artificial intelligence technology in the workplace rages on, people often plead their case from one of two perspectives. One side settles on the impending doom of human replacement while the other celebrates the opportunity to increase business productivity.
But like most arguments, there are more than two ways to view the value of such intelligent advancements. When analysts talk about 60% of tasks being automated by 2025, they are not talking about a mass reduction in the workforce. In fact, recent research suggests the possible rise of a third scenario – the unique chance to relieve the workforce from unnecessary stress by redesigning jobs and reengineering business practices in ways that make people’s lives better.
Think about it: no one dreams of a job full of mindless, repetitive work that’s unfulfilling and offers no room for growth. Shouldn’t we use technology like machine learning to help people break free from the mundane and pursue roles that reflect the best of their talents and interests?
Let machines do what they do best so people can do the same
The things that machines are very good at are often dull and predictable. Meanwhile, every person has creativity and emotional intelligence that machines cannot duplicate. When these two sides of the next-generation workplace are linked together, employees can reveal their greatest potential with tremendous intelligence and freedom, regardless of their role.
As machine learning capabilities strengthen alongside continually increasing data volumes, processing speed, and algorithms, people can use a highly intelligent foundation to channel their talents in the most informed and efficient ways.
Take, for example, the sales organization. Feeding data from the CRM system into a machine learning algorithm can generate a propensity-to-close analysis. But don’t be fooled – this approach goes beyond using historical information. The model leverages diverse structured and unstructured data such as optical character recognition; emotion and facial detection; text-feature extraction; and speech-to-text, text-to-speech, and natural-language chatbots.
The resulting insights automatically trigger an update to the CRM record showing which customers are ready to close and which ones require more time to make a decision or will likely choose a competitor. Not only does the business grow revenue, but account representatives also have the confident means to meet their quotas and build strategic customer relationships. Plus, marketing and sales managers can better determine which segments respond well to which message or promotion and where the business should concentrate its efforts to compete profitably.
This sales example is one of many, many business cases that show the potential to improve how people work with machine learning. From product and spare part identification, label reading, and risk detection to accelerated contract processing, updating, and analysis, complex tasks can be streamlined and provide insights that help people act on emerging challenges before the business is disrupted.
In the end, machine learning streamlines business processes into an end-to-end system of focused, strategic capabilities so people can make a difference in their business by resolving emerging exceptions and addressing unexpected events quickly. And, regardless of role, employees can shine and reveal their best selves at work – every day.
Achieve more with less and outmaneuver your competition with advanced machine-learning capabilities built into your business processes. Watch the Americas’ SAP Users’ Group (ASUG) Webcast replay “Build an Intelligent Enterprise by Embedding Machine Learning into Your Business Applications.”