Blum Group: Effective organizational structures for successful digitalization

Anyone who owns IKEA furniture is also familiar with the products of the Blum Group. Now in its third generation, the family-owned company from Vorarlberg, Austria, produces high-quality hinge, flap, and box systems. Today, the Swedish furniture giant is one of its largest customers.

Blum is one of the world’s leading manufacturers of furniture fittings. To manage its global business, the company increasingly relies on data-driven decisions. But until recently, neither the technologies nor the organizational structures kept pace with its rapid growth.
“We were struggling with a growing backlog of requests from the specialist departments in our central IT department,” explains Alicia Manglano, Lead Business Analytics Strategy. “At the same time, management wanted key performance indicators for corporate management. So we had to act urgently.”

Realignment with decentralized structures

The large-scale digitalization initiative focused not only on technology but also on the organization of data analysis.
“Our challenges were not only technical in nature,” says Alicia Manglano. “Many were related to processes and the distribution of responsibilities. It makes no sense for business users to go through IT every time they need something new.”
One of the core objectives was therefore decentralization: specialist departments should be able to design reports and dashboards independently and take more responsibility for their data.

To achieve this, Blum brought in external support. ORAYLIS GmbH, already selected to build the new data platform, was also tasked with helping set up the necessary organizational structures.
“This was a recommendation from our neighbors at ALPLA,” recalls Alicia Manglano. “ORAYLIS had been very successful in helping them revamp their company-wide data analysis. It was a great advantage for us to receive all consulting services for our transformation from a single source.”

Data mesh as an organizational concept

The collaboration began with a Data Strategy Assessment (DSA), covering both technological and organizational aspects.
On the technology side, the result was a cloud platform in Microsoft Azure, designed as a hybrid data mesh. This supports controlled decentralization: individual analysis teams – primarily specialist departments – access the same consolidated data set. Created reports, tables, and models are published as data products on a shared platform.

Meanwhile, the organizational stream addressed processes, roles, and responsibilities.
“These principles are essential in a data mesh,” stresses Simon Esser, project manager and strategy expert at ORAYLIS. “Without clear standards, there’s a risk of everyone doing their own thing – at the expense of data quality. That would jeopardize the entire project.”

The starting point for the further work of the organizational project was two exemplary use cases that were intended to reflect the two typical characteristics of the desired mesh construct: a more user-oriented “standard analytics product” in the form of order-to-cash reporting, and a complex case for visualizing quality data, which served as an example of “advanced analytics products.”

Processes and roles for different data products

“Blum’s standard and advanced products differ greatly,” explains Simon Esser. “That’s why we defined separate lifecycles for each. From initial data research to the finished product, we mapped out all tasks, assigned them to roles, and defined the required skills and responsibilities.”

With this foundation, the organization team set up specific work packages and began step-by-step implementation. The close cooperation between organizational and technical teams, supported by ORAYLIS, created a stable foundation for becoming a data-driven company.

Departments are very satisfied

“The collaboration with ORAYLIS worked really well. Our processes have accelerated massively,” says Alicia Manglano. “Thanks to the roles we defined together, each department now has its own data product team that independently creates dashboards and is the first point of contact for user concerns. If IT support is needed, our new template ensures fast, efficient processing. Our users are very satisfied – today, they get what they need much faster.”

Employees now also have direct access to the company’s central database. Relevant data can be used in daily work without relying on IT. As a result, the data mesh construct is growing dynamically, with more and more departments acting as independent analysis teams.

Blum is already planning further development:
“We are currently working on a certification to ensure the quality of our data products,” says Alicia Manglano. “We also plan to introduce monitoring to track their costs. Once these steps are complete, we will be ready to roll out the concept globally across our subsidiaries.”

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