How Change Management Professionals Help Enterprises Pivot and Adopt AI
For the world’s largest and most successful enterprises, constant change remains a fact of life. Mergers and acquisitions, pressure from competitors, organizational restructuring and shifts in customer demand all conspire to keep corporate priorities, org charts and product offerings in flux.
The process of adapting to shifting business conditions — whether it’s a new external competitor or the integration of a new team — is known (funnily enough) as change management. And one of the more common drivers of change in recent years is technological disruption. How does an enormous enterprise organization incorporate a game-changer like artificial intelligence at scale?
Some companies, like New York-based Dataiku, have made this tech-driven change management their business. The startup works with enterprises in the “Forbes Global 2000” — the world’s 2,000 largest public businesses — to help them adopt artificial intelligence and other data science-driven technologies. Dataiku’s technology underpins business operations like fraud detection, predictive maintenance, supply chain optimization and fraud detection for businesses across industries like healthcare, finance and manufacturing.
“These companies are not traditionally digital native organizations,” Chief Customer Officer Kurt Muehmel said. “And the process of implementing a new technology or business process is a transition in their effort to modernize.”
In an interview with Built In, Muehmel explained the mindset that change management professionals must bring when helping an enterprise adopt new technology.
Kurt Muehmel, Chief Customer Officer at Dataiku
What are the biggest challenges for change management professionals when integrating new teams and products?
For our customer engagement and change management roles, working from the “old way” to build a new process is undoubtedly the biggest challenge. This exercise and implementation work with customers is also often a cultural shift for the company as it involves setting up entirely new capabilities. In the past, analysis and forecasting may have lived with a specific individual or specialized team. Now, through AI models, it can reach more teams in an organization.
To start tackling this transition, our teams work with our customers to first identify and understand their business problem. From there, we can understand what the organization is trying to accomplish and where we can help them apply more modern, automated techniques through data science and machine learning.
Tools of the Trade
How do you define success when undergoing a large change?
The best engagements stem from strong alignment and partnership with our customers. From there, success starts with a clear rollout plan with milestones that everyone involved can map progress against. As part of this plan, there must be an initiative to provide education on how to best use and deploy your technology. For us, this works best when we put the education in the context of the customer’s perspective, communicating how Dataiku will become ingrained in their day-to-day work.
As part of our implementation and change management process, we want to empower customers with the understanding of how Dataiku is making predictions and decisions based on their data. This becomes even more important as the technology gets integrated into their business processes. Everyone involved needs a clear picture of what data is used to develop models and be reassured that the model is serving the intended purpose. For us, this is what we call responsible AI, and it allows our customers to build these models with the confidence that it is serving their business.
“These types of roles must also balance having a technical background with clear communication and management skills.”
What are the most important skills for change management professionals?
Change management and customer success roles are all about understanding your customer needs, your product, your technology and the market. The main goal is to combine these areas of expertise to find a solution for the customer that solves their business challenge. These types of roles must also balance having a technical background with clear communication and management skills to take care of the customer’s business considerations, while making the new technology and process work for the organization.