The Transformation Conundrum: Are You Innovating, Inventing, Or Improving?

Paul Kurchina

So much has changed in our digital landscape in recent years. In what started as a quest to capture data and get a view of how the business is performing has become a platform for continuous learning. People and machines now can work together to continuously uncover new – and hopefully better – ways to get things done.

But I often wonder: Is this new world order really about innovation? Or are we really just inventing or improving?  According to Bob Parker, group vice president of IDC, and Yaad Oren, vice president of corporate strategy at SAP, machine learning may be one of the latest technologies to help decipher this mystery.

“Businesses have traditionally invested in point solutions to solve particular challenges, such as fraud detection for a credit card process,” Parker observed during the Americas’ SAP Users’ Group (ASUG) Webcast “Learning to Innovate by Innovating from Learning. “Now with machine learning, they are moving away from a point-solution view of the world to create a decisioning environment.”

Machine learning: Turning small departmental projects into enterprise-wide transformation

3M Corporation, as one of the most respected innovators of the old and new economy, has famously maintained a reputation for churning out successful innovations after another. This track record is mainly dependent on its distinction between invention and innovation. The company describes “invention” as that eureka moment of sudden discovery when the proverbial light bulb over the head turns on, while “innovation” is considered as the continuous improvement that comes from learning.

If we accept the 3M assertion, we also have to agree that a process can benefit from a system. This is where machine learning fits in so well. “Things are moving so quickly that we can’t rely on our internal experts to wade through data on their own to make a decision,” advised Parker. “We have to augment – and in some cases, automate – that process through the application of machine learning.”

One of the most significant challenges to leveraging machine learning is scaling innovation from a small departmental project to an enterprise-wide digital transformation. Oren suggested, “Business should never stop learning how to innovate. A variety of skills and services are needed to capitalize on the latest technologies and the models to open the door to capabilities that offer differentiating value.”

Considering the current fervor around data science, people who are experts in the recent crop of digital technologies and best practices are in high demand. However, unfortunately, there is still a shortage of this valuable talent. With machine learning, businesses can overcome that common challenge by accessing the algorithms and capacity for handling large volumes of data to support innovation processes and drive significant competitive advantage.

Cutting through the hype reveals the true definition of innovation

The idea of data-driven decision-making may have been around for years, but rapid innovation in machine learning is unleashing tremendous business potential. Thanks to this digital opportunity, decision-makers can gain a better understanding of everything their business touches and impacts while solving complex problems in real time.

Discover how your business can leverage data to automate sustainable innovation that will ignite success for years to come. Consider about the technologies and best practices from the Americas’ SAP Users’ Group (ASUG) Webcast replay “Learning to Innovate by Innovating from Learning,” featuring Bob Parker, group vice president of IDC, and Yaad Oren, vice president of Corporate Strategy at SAP.

Paul Kurchina

About Paul Kurchina

Paul Kurchina is a community builder and evangelist with the Americas’ SAP Users Group (ASUG), responsible for developing a change management program for ASUG members.