by Ryan Champlin
Across the SAP community, we’ve been talking a lot about the intelligent enterprise and the urgent imperative for organizations across industries to begin their digital transformation journeys to get there – especially if they haven’t started already. What’s clear is that everyone is on the same page when it comes to the strategic need to evolve toward the intelligent enterprise. What’s not so clear (and still largely unfolding) is the tactical roadmap to make it a reality.
Innovation in the Intelligent Enterprise
Organizations that are making the transformation to the intelligent enterprise are in fact establishing a foundation for intelligent innovation. After all, the ability of organizations to meet virtually any innovation goal quickly and cost-effectively is a core benefit of the intelligent enterprise. But what makes intelligent innovation possible at any given organization? Well, it’s actually several factors, starting with the skill, creativity, and dedication of the people in the organization, supported by the right technology infrastructure. In that regard, we’ve identified two key ingredients.
Machine Learning and Data Science Platforms
A thought-leadership study by Forrester Consulting, commissioned by SAP, highlights the importance of predictive analytics and machine learning (PAML) in building the intelligent enterprise. The study surveyed over 300 decision-makers in large enterprises from different regions around the world and found that 93% believe that PAML is “integral to the ongoing success of their business.” In fact, 88% agreed that the next generation of enterprise applications will be enriched with machine learning and other AI technologies.
But the Forrester study highlighted a key challenge these same companies face in implementing these next-generation applications. Of those surveyed, 64% acknowledge that their internal teams – particularly their data science teams – are struggling to meet the huge demand for PAML models. What’s more, 42% acknowledge that the lack the skilled personnel “has both caused and compounded the issue.”
The Machine Learning Knowledge Gap
Because of this critical skills gap, the Forrester study recommended that companies adopt solutions from technology partners to deploy PAML-enriched applications and processes. These solutions constitute the second ingredient for intelligent innovation: the data science (DS) platform.
But what is a DS platform? SAP recently sponsored research by Eckerson Group to take a deeper look. The resulting report clearly defines a DS platform not as data science tools, workbenches, applications, or product suites, but instead as a set of “features” including rapid scalability, open collaboration, and accessibility.
With a true DS platform, organizations can establish a production pipeline to “democratize” analytical models, making them available to every person, process, or thing that needs them. Providing this level of access to IT and business users alike not only relieves overburdened data-science teams; it is critical to an organization’s ability to expand its innovation opportunities.
From Data to Innovation
At SAP, our customers are expressing considerable interest in a DS platform, both to improve outcomes for their customers and for their internal teams, as well. That’s why they’re looking to simplify the creation and sharing of business insight for every one of their business users – enabling them to exercise their skills and creativity to deliver intelligent innovation without process limitations or reliance on IT.
From achieving new efficiencies with automation to developing new revenue streams with process transformation, robust DS platforms are generating the analysis and algorithms organizations need to bring machine learning to life.
So where does your organization stand in terms of DS platform maturity? Ask your data-science team. Are they overloaded with too much demand? Are they having trouble collaborating with business teams or with other IT groups? Are they detached from business deliverables? If yours is like most organizations, the answer to all three questions is probably yes.
The good news? Solutions and expertise are readily available to help virtually any organization create a productive DS platform.