The other benefits

AI and machine learning will also propel strategy and management practices – not just operations – at winning companies.

By Lars Fæste*

Forward-thinking business leaders we work with are keenly aware that most of the well-honed change management and transformation practices of the past few years probably won’t hold up to the demands of the future. In other words, they won’t provide what it takes to “win in the ‘20s.”

What will? Our work relating to the large-scale changes companies will need to make suggests they’ll have to up the ante – significantly – on putting rigor into the “science of change”: Winners will have found ways to apply AI and machine learning beyond product innovation and development, operations, marketing and other operations and functions – and focus it on strategy and developing and enacting management practices.

Essentially, companies will need to strive to become hybrid “learning enterprises” that combine technology, analytics and human elements in ways that have rarely been applied to culture, resilience and change.

We see a number of ways that companies can become such learning organizations. They may…

Use science to get the right talent in the right places and fine tune the capacity to develop and bring on the right capabilities: Neuroscience and artificial intelligence – deployed through tools like digital games – can reliably predict success in various scenarios and identify the right people for the right new roles. (Neuroscience and AI can also determine which capabilities can be developed internally and which ones need to be hired.)
Leverage the intersection of behavioral science and data analytics to “nudge” employee behavior in powerful ways. Effective leaders will focus on identifying small interventions that may shift employees into different, more productive behaviors – ones better suited for heightened uncertainty and complexity.
Similarly, use data analytics to improve companies’ ability to detect early warnings – e.g., that a business’ current growth engines are running out of steam.
Deploy crowd-sourcing platforms that “gamify” change initiatives internally and get real-time feedback about what works and what doesn’t.
Deploy machine learning to potentially identify disruptions in the business environment and diagnose organizational health, real time.

Check out our article on this subject. The imperative to meet the future of large scale change management and transformation is certainly challenging – and also full of immense possibility.