Platforms have disrupted industries and made companies like Uber and Airbnb household names. As the concept becomes more entrenched, traditional companies and everyday businesses are looking to capitalize on a platform strategy to innovate new products and services and stay abreast of tough competition. A digital platform is an environment that connects different groups, allowing participants to benefit from the presence of others. Accenture called digital platforms the "most profound and global macroeconomic change since the industrial revolution." Half of companies surveyed by Accenture defined platforms as central to their business strategy, with 40% citing platforms as a critical enabler.

Editor's note: This is the second of two parts about Johnson & Johnson's technology operations. You can find the first part about early cloud adoption and the role of the CIO here. In technology, there is a delicate balance of when to adopt cutting-edge offerings and when to lay in wait, cautiously optimistic about capabilities but hesitant to waste resources. Chief information officers are key in the enterprise to understanding where technology fits, advising where to trial emerging technologies. Successful CIOs balance modernizing the technology core with working on moonshots to drive future business.

Just shy of 60 years old, machine learning has never looked so good. Exponential data growth, advanced algorithms, and powerful computer processing are enabling the technology to fulfill its ultimate destiny: identifying profitable opportunities and avoiding unknown risks by evaluating massive volumes of complex data and delivering accurate results in real time. However, during the Americas' SAP Users' Group (ASUG) Webcast "Guide to the Machine Learning Galaxy: How Your ERP Knowledge Enables Value-Driven Intelligent Processes," Darwin Deano, principal and chief SAP Leonardo officer, and Denise McGuigan, senior manager and Deloitte reimagine platform leader (both from Deloitte Consulting LLP), forewarned that machine learning is only as good as the algorithm. And the algorithm is only as good as the data. Deano advised, "Data evolves over time. Even though ERP systems provide a strong foundation for identifying opportunities and delivering on the promise of machine learning, it does not factor in information outside the core structure, nor does it move with information as it changes."