Insights from data economy super week in Finland

As data becomes a central driver of business success, organizations are rethinking their approach to data assetization, trust, and leadership. Three key events in Finland - Meet VTT-event series, Business Finland’s Data Economy Playbooks publishing event and the inaugural Nordics edition of CDOIQ - brought together experts to discuss the evolving role of Chief Data Officers (CDOs) and the challenges of data management. 

The first-ever Nordic edition of CDOIQ was held in Finland. Originally launched by MIT two decades ago, this CDO/CIO-focused gathering plays a key role in strengthening the community of data decision-makers - now also in this part of the world. A big thank you to Aalto EE for facilitating and organizing this event. 

At CDOIQ an eminent panelist was asked: if you had to choose between tech guy and business guy to get the hardest data transformation done, which one would it be? The answer: humble business guy. The reason behind the answer was interestingly touched upon in many conversations throughout the events.

Technology in data management is increasingly part of the problem, less so of the solution. To address this situation there’s the emergence of a growing number of companies profiting from untangling the complexity caused by having too many overlapping, and incompatible cloud, analytics and data management solutions that organisations are paying dearly for. 

They have invested to simplify and speed-up data management, but the uneven data quality, lack of well-designed and dedicated data pipelines and accountabilities have only led to further complication and lose of data lifecycle transparency. The discussions largely reflected the notion that at the end of this road, the focus moves gradually from tech via business to reshape organizations and to establish new roles. 

As companies adopt agentic AI, they will need Board’s full mandate to begin the required  change of processes. This shift will also require redefining roles and functions to create new units such as a data treasury to manage data assets for the agentic use. 

Another major challenge is trust –mandatory in all inter-organisational data exchange. The more people use AI to generate data, the more polluted and off-track it gets due to lack of effective mechanisms to detect inaccuracies, latent errors, epistemic uncertainty, and so on. Lot of the conversations evolved on Can you trust your data? Can you trust on the game rules on data sharing? Can you trust your stakeholders to use the data correctly. The more we examine reliability and trust in the data exchange and AI context, the more issues there seems to be. 

At the Business Finland event, Finnish company Reima stood out as a prime example of how long-term dedication and strategic focus on data-driven decision-making can drive exceptional digital growth. One key success factor was particularly noteworthy: a strong emphasis on teamwork.  Management focusing solely on their own unit’s or team’s targets – rather than the company’s shared goals - were let to go. 

The common nominator to all above is to have data leaders who can involve, motivate and allocate ownership to people to take on the new roles and requirements that the data focus requires. The difference to business-as-usual, “this is anyway every leader’s task” is twofold: 

• To succeed with data and information assets you need to know who are in possession of them as primary assets and exactly where within the organization. This is no longer about the process experts and product specialists but whole new expertise area’s that is typically hidden. In other words, the demand is for persons who understand e.g. what the data is saying, does it contain inaccuracies and what is the right interpretation context. 
• The second change logically follows; the winning team composition is now different. Organizations will now need data experts, data designers, pipeline management, data scientists, architects for all layers, team ontologists, data and AI lifecycle managers, and data product managers, among the new roles. 

CDO’s new right hand is that humble business manager as an orchestrator to coordinate the various approaches and technologies into a cohesive strategy. This role of business-technology-lex translator to bridge the gaps between data management and rest of the or-ganisation is becoming critical. The profile is probably one of a generalist with excellent people skills. 

• Find the individuals within the organisation who are willing and capable to identify and understand what the business-critical data is factually about 
• Bridge data product owners and product management, with a focus on data consolidation and data-asset management 
• Carry out research on team topologies and accountabilities, with an emphasis to understand data pipelines, value creation and data asset management
• Emphasise accountability and responsibility for data operations, accuracy in data intensive reporting as well as its continuous validation – this is going to be a large amount of people so make it lean and explicit 
• Set up sounding-boards to support teams and individuals to stay agile, accountable, and engaged in the everyday, ground-level data management - because data is everyone’s business

Riina Luoma, Head of Data Intensive Economy R&D&I at VTT, has 25 years of experience from ICT sector, Professional services and data infrastructures in platform and cloud-based businesses through various corporate roles. A recipient of both the Nokia Quality Award and the Nokia Innovation Award, Riina has also steered analytics solutions from R&D to go-to-market (G2M) as well as data strategy for a Nokia Global Services unit. Riina was recently selected to Nordic 100 in Data, Analytics and AI list.