Self-service platforms with a simple interface can empower non-technical users to derive insights. Basic training or built-in tutorials can be helpful here and can enable employees to feel more confident while working with this data.
Dedicated specialist in product teams
A great strategy as deployed by VanMoof is empowering teams with specialists dedicated to enabling access to centralized data. Whether you have Scrum squads, chapters, or tribes, adding a dedicated data specialist to each team or having a dedicated lead from the data team assigned to you, will help ensure your teams can access your data and configure it to their needs. “Alignment and processes aren’t an afterthought. They both need time and attention. That’s why there must be a dedicated team member who continuously monitors the process,” Hazelaar advises other fast-growing companies and people in similar positions.
As you enable access to data, various teams will view and interpret this data through a unique lens. So, how do we align teams on the meaning and interpretation of this data?
3. Create a data dictionary
With so many teams and stakeholders assigning and interpreting data in their own way, it becomes a real necessity to establish universally agreed-upon meanings to the data. This can be achieved by creating a data dictionary. IBM Dictionary of Computing describes a data dictionary as a “centralized repository of information about data such as meaning, relationships to other data, origin, usage, and format”. Invest time in understanding how your team interprets data, creating a catalog of all terms and how they assign meaning and definitions to them. This can be facilitated through a workshop for grouping, identifying similarities or conflicts, and finally arriving at standardized terms and definitions.
Read our interview with Duco Berghuis , Product Team Lead at Just Eat Takeaway.com about, among other things, the need for a data dictionary as you scale up.
The upkeep and maintenance of your data dictionary is as important as the creation of it. As new streams of data are plugged into your system and new changes are introduced by the product or business team around the parameters of your product/service, maintenance and upkeep of your data dictionary are paramount to ensure there are no redundancies, duplications, and/ or omitted meanings.
4. Enable flexibility in the data system architecture
As Hazelaar mentioned, VanMoof has many digital products that generate huge volumes of data from various sources in various formats. Traditional IT infrastructures tend to contain data silos that are complex and time-consuming to integrate. As a result, information is often inaccessible to users outside a certain department, causing reporting gaps or bottlenecks. These environments conceal the end-to-end visibility businesses and teams require to derive accurate insights from their data and use it strategically.
When thinking of a data strategy as a tool for strategic alignment, it’s important to also evaluate the technical vision and map out if your current systems and architecture support that vision. Taking advantage of cloud economics for storage, rapid provisioning, and near-infinite scalability from the get-go will enable your organization to meet unknown future data demands and always have the capability to reassess your data strategy without restrictions of rigid architectures and archaic systems. The infrastructure and technology you choose should go hand-in-hand with your corporate culture and reflect your organizational goals. As mentioned earlier, most teams and employees look at data through a unique lens, and the tools or technology you deploy to enable access to this data should reflect this diversity.