Interview: Change management for digitisation and agentic AI
We speak to Thomas Bodé, chief digital transformation officer at European energy company Met Group, about delivering successful digital initiatives
People often talk about going digital and digitisation initiatives, but technology is only half the story. As Thomas Bodé, chief digital transformation officer at European energy company Met Group, points out, it’s quite easy to get people excited about technology.
“Technology is also quite tangible,” he says. “People are moving from something which was sometimes suboptimal.”
Perhaps the IT infrastructure was not sufficient, or there were missing pieces of functionalities, akin to getting a new car. “If I replace your old car with a shiny, good-looking, new car, usually the resistance is not going to be very high,” says Bodé, but the challenge is in the transformation, in terms of changing the way the people work.
Headquartered in Switzerland, Met Group’s activities include natural gas and power, where it is focused on multi-commodity wholesale, trading and sales, as well as energy infrastructure and industrial assets.
Bodé has been working there since 2022, and is responsible for establishing Met Group’s digitisation strategy. “Bringing in technology will not solve the issues that you are facing alone,” he says. “The problem that we started to solve at Met Group is basically a problem which includes people, process, data and technology.”
The goal, says Bodé, is to enable the business to operate at lower risk and higher efficiency so it can cope with new market opportunities.
“The company has already reached a size where there is a very high complexity, and it wants to keep growing, so we need to remain lean, avoid growing our costs and ensure we can manage our risks properly,” he adds.
Millennium company complexity
Met Group is a company of the millennium, founded in 2007, the year the iPhone was launched. One would assume it has not had to suffer the technical debt and brittle business processes often associated with energy companies that have been operating for decades, but in spite of being a relatively young company that has had the opportunity to learn from best practices of well-established businesses, Bodé says Met Group is a very entrepreneurial company, which has meant the complexity of the business has increased as it has grown.
While it started out in the digital era, and people had computers and access to digitised information, what Met Group really needed was an enterprise IT architecture that could scale as the business grew.
“If you don’t have this big strategy with an enterprise architecture, it becomes very complex to achieve true agility, which allows you to embrace new opportunities safely and quickly, without the cost of building further complexity,” he says.
In his work life, during meetings concerning business strategy, Bodé urges the people making decisions to consider the intangible liability that occurs due to complexity, which can slow down the business or have an adverse effect later.
This is something he experienced previously when he worked at jewellery retailer Swarovski, which wanted to link its complex supply chain. “There was a very long supply chain,” says Bodé. “We tried to connect the entire supply chain from base production through manufacturing, distribution and, ultimately, to retail, but what we saw was that while people were talking about products and customers, they were not using the same terms.”
This, he says, was a major issue both in terms of the transmission of supply chain data, and in how people spoke about their data. Without a common language for the data, it is impossible to connect business processes together to build IT systems that enable the business to produce exactly what its customers want to buy and what products it needs to put into its retail stores.
For Bodé, this was a significant lesson. “I realised that connecting business processes together actually starts by connecting the people and then defining the data,” he says.
These are prerequisites for driving this agility. “This, for me, is true digital transformation,” says Bodé.
Consolidating reports
As an example of a similar problem Met Group faces, Bodé describes the journey the company is taking with business intelligence (BI) and artificial intelligence (AI) to avoid scalability issues and reduce the risk of failing.
He says Met Group has massively grown the use of BI, which means there are around 10,000 reports circulating. While it is great to have everything on one platform, Bodé says: “If there is no logical organisation and no rationalisation, you lose the value that you have created in the first place.”
This is because people do not know where to look to find the information relevant to their decision-making. “You no longer understand what [data is relevant] for me, what is for someone else, and how we connect the information together to make decisions,” he adds.
The problem is one of scalability and accessibility, and these are the main focus areas that have shaped much of Bodé’s strategy at Met Group. The effectiveness of making data-driven decisions is correlated directly to the quality of the metadata and the architecture.
But even as a single version of the truth is established from a data source and reporting perspective, his previous experience at Swarovski demonstrates the significance of robust change management. “At Swarowski, we massively invested to create a single point of truth, which resulted in high-quality reporting with reliable data,” says Bodé.
But while the processes and IT applications had been standardised, in his experience, it takes years to bring people to change their habits. Metadata and people changing their working practices are prerequisites for a sound artificial intelligence (AI) strategy. The evolution of a full agentic AI ecosystem is achieved when decisions can be made almost totally without human intervention, via AI agents connected by a metadata layer working alongside people who are able to understand where and when to delegate certain decisions to the AI.
To achieve true agentic AI requires change management to facilitate seamless human-AI workflows. This returns to Bodé’s point that while people will generally accept shiny new technology, such as an agentic AI workflow, how they adapt and change their own working practices to this innovation is key to success.
