Data Champions Online Nordics revealed how the region’s data leaders are mastering stakeholder management, increasing data literacy and managing expectations around emerging technologies
Corinium’s inaugural Data Champions Online Nordics event brought together 200+ executives from the region’s leading brands from June 9-11. Building on the success of the CDAO Nordics conference, this one-of-a-kind event shone a light on the rapidly developing role of data and analytics as an innovation-driver within organizations.
Though it touched on many themes, the consensus across the three-day event was that mastering stakeholder management, increasing data literacy and managing expectations around emerging technologies are key factors when leading data-driven digital transformation projects.
The Time for Digital Transformation is Now
It’s no accident that digital transformation is a top priority for many of Europe’s top enterprises today. As Alteryx Director of Product Management Nick Jewell said, this era of digitization, automation and disruption has been 50 years in the making.
He noted that there’s a fundamental difference between innovation and disruption. Innovation is the improvement of processes within an existing business model. On the other hand, disruption turns business models on their heads. It creates new products, new revenue streams and even new businesses.
“Successful companies often assume they can disrupt the market by adding technology to their stack, rather than addressing the end-to-end analytics process itself,” he claimed. “Technology doesn’t deliver value in the change process alone. It’s the data that provides the actionable insights.”
Market research company IDC reporting that global businesses will have spent USD $2 trillion on digital transformation projects by 2022. As such, Jewell argued that now is the time for data analytics leaders in the Nordics to seize their moment and disrupt their organizations.
Bringing Stakeholders on the Digital Transformation Journey
Perhaps the strongest theme of the week was the importance of effective stakeholder management. For speakers and attendees alike, these relationships are not project-by-project considerations. They are the long-term basis for successful business transformation.
Girish Agarwal, Director of machinery maker Husqvarna’s AI Lab, spoke about this idea. He shared how his team uses an end-to-end approach to digital transformation projects. He argued that the roadmap for transformation must feel like “the stakeholder’s agenda”, rather than that of the data and analytics function.
This sentiment was echoed by Finnair’s Head of Data, Minna Karha. She said “speaking the language of the business unit” is essential for securing buy-in and understanding what matters to key stakeholders.
Such tactics go a long way to establishing trust between business units and their data and analytics functions. This can often be the difference between digital transformation success or failure.
Karha recommended ensuring that all data and analytics activities provide clear value to key stakeholders and taking stock of these relationships regularly to bring them along on the digital transformation journey.
Increasing Data Literacy Through Continuous Learning
Data democratization, data literacy and data-driven culture are regularly discussed topics within data and analytics functions. During her keynote presentation, Nobia’s Eminé Olausson Fourounjieva outlined how her organization is tying all three together.
As the kitchen specialist’s Digital Analytics and Insights Lead, Fourounjieva is responsible for the data and analytics strategies of more than 15 brands. Data democratization is a critical part of the group’s roadmap. But for her, that means more than just giving staff access to the data.
Nobia’s data team regularly runs ‘data bootcamps’ with key stakeholder groups to increase their familiarity with data available to them and improve their ability to read, analyze and create actions using it.
Increasing the organization’s data literacy has fostered a wide-ranging data culture. Crucially, Fourounjieva concluded that these bootcamps are not only improving people’s understanding of data, but also increasing their trust in it. In this way, her team is reducing Nobia’s reliance on ‘gut instinct’ and making intelligent, data-driven decisions the norm.
Avoid the AI Graveyard with Persistence and Realism
Years of hype have created a maelstrom of unrealistic expectations around AI. As Oskar Eriksson, Customer Facing Data Scientist at ML company DataRobot, quipped, some executives think ‘doing AI’ is as simple as hiring some data scientists, giving them an AI tool and locking them in a room with some pizzas.
In reality, the road to AI success is more complex. To get the ball rolling, Eriksson recommended that AI leaders “start small, even boring” to find AI use cases within their organizations. In doing so, they can sharpen their tools before seeking higher risk, higher reward projects in the future.
Eriksson added that AI projects rarely follow a straight line. People, culture, process or technology typically create “fracture points” along the way. The critical thing is to expect, identify and address these challenges. He recommended implementing a robust process to judge an AI product’s strengths, weaknesses and areas for further development post-deployment.
Not every AI project will be a home run. But committing to experimentation with persistence will ensure that AI will be become a critical tool in an organization’s digital transformation.