Change Management is at least as important as your latest AI algorithm!

Of late, I had the opportunity to interact with several supply chain top executives, who are beginning the journey of machine learning for process improvement. The biggest concern they voice is neither algorithm nor technology but people, process and culture. As a career-long AI professional, I’m not surprised! But the tone of those top executives and the gravity of the issues lingered with me. 

What happened so far? 

While technology and infrastructure changed rapidly in the last two decades, innovation on ‘change management’ lagged far behind. Digital has become the buzzword for corporate success - ‘people’ are driven to the periphery and often threatened by the so called ‘4th wave of industrial revolution’. The Man vs Machine paradigm has moved from factories to white-collar jobs where low to medium complexity decission making is being replaced by AI and Intelligent Automation. The black-box nature and possibility of biases in AI - didn’t help the case either! 

The background:

Let me take you back to my discussion with supply chain executives from a global organization with 100 years of glorious tradition in serving consumers. The demand planning team, responsible for ensuring the availability of the products whenever and wherever the customers want, has grown large. But due to product proliferation, channel expansion and business volatility the organization wanted to reduce inventory and improve agility in the demand planning process. They zeroed down a suitable technology but holding short due to the uncertainty of future changes. 

Are cliched triad (people-process-culture) still important?

Yes, it is - if not more important than ever. For proof, during my entire discussion on new technology implementation with top executives - we never discussed technology. Ironic - isn’t it? But this reflects their priority and mindshare, which revolved around how the uncharted path of transformation looks like! How will team members react to this sudden change when a system will replace part of their activity? Will the process and cultural change going to be smooth? How one assures them the positive impact of automation and incentivise to adopt change? This clearly shows while the algorithm and deployment of AI improved rapidly, the science of change management to implement the technology couldn’t keep pace! The solution for cultural change and process disruption is not generalised and is still restricted to a few ‘consultant’ - let aside making it widely available.  

Who should we look up to?

With the hindsight of several transformational projects, without any doubt, the buck stops at the top management and analytics professionals. Top management must have the ‘vision’ where AI should take the organization, the ‘action plan’ to ensure continuity, the ‘incentive’ to take along employees and the ‘resources’ such as budget, infrastructure & training to resolve the changes at hand. 

The analytics community must pay attention to literature to simplify the jargon, evolve an AI project change management charter, draw upskill-path for existing employees and above all standardized for industries and business functions. To me, for AI to become an agent of positive change, we must adopt the path of ‘AI-Empathy’, a humane approach for mass AI adoption. More about that in my upcoming blog.