Ditching dashboards for scalable analytics

We talked to Magnus Dahlbäck, Senior Director of Data and Platform at Voi, who leads a team of 13 data professionals. He explains how implementing Steep transformed analytics at Voi—from a dashboard-heavy approach to a scalable, metrics-first strategy.

Background

Like many companies, Voi's data team was the only resource with comprehensive access to company data. Business users would turn to the data team with specific data requests, and analysts would create dashboards in their BI tool to provide answers. Commonly, delivering a dashboard led to follow-up questions, which meant building more dashboards and adding endless ad-hoc work for the data team. This cycle led Magnus to ask two questions:

1. How can we be smarter about our data team's time?
2. How can we make it easy for more people to find and use data independently?

Challenges Dashboard overload

Magnus stated that the challenges Voi's data team faced were threefold and highly connected to the reliance on analysts for data insights, causing bottlenecks for both the data team and the company's business users.

1. Inefficient use of analysts' time: Highly skilled analysts spent the bulk of their time designing, building, and editing dashboards.
2. Lack of engagement with data: Most business users had view-only licenses in Voi's BI tool, which didn't allow for exploring data, and upgrading licenses for all users was too expensive. It made it impossible to give everyone the tools to explore data and build content, making users dependent on the data team for insights.
3. Dashboard chaos: Business users struggled to find the right visualizations with the latest numbers amongst hundreds of dashboards. KPI numbers and names often varied due to evolving definitions or creator differences. The lack of a systemized way to ensure reliable dashboards made it hard for business users to trust the data, creating a cognitive overload.

Solution Mission to replace dashboards with metrics

Magnus realized relying on dashboards limited his team's ability to scale analytics. He identified that organizing data into metrics could foster scalability, free the data team from inefficient admin work and dashboard building, and empower business users to explore data.

How Steep enables scalability with metrics

Steep is built on a semantic layer, enabling a consistent, metric-based way of working with data. KPIs are defined centrally in metrics, ensuring a single source of truth for all data. Combined with an intuitive interface, Steep enables all employees to easily access and explore data freely without inconsistencies.

Magnus shares that a small but powerful benefit of defining metrics centrally is that Voi can use the business language familiar to everyone in the company to name metrics, making them easy to find, recognizable, and relatable for everyone. For example, an important KPI and a key metric for Voi is vehicle rides per day, centrally defined and available to all users in Steep with the same name used daily in the company.

Using Steep Giving business users access to data

The data team at Voi is responsible for building the metric catalog in Steep, which is then accessed by all other teams.

Business users can explore individual metrics in the metric catalog or build reports to view and compare several metrics. The flexibility and consistency of a metric-based approach eliminate the need to create and save new content to answer every question, saving everyone’s time and lowering the cognitive burden that dashboard overload formerly caused.

Introducing Steep allowed Voi to adopt a new way of working with data, not only in the data team but across the entire organization. Voi uses its own business language when naming metrics, making them easy for all employees to grasp and find.

With Steep, Voi achieves:

• Consistency across all company data with metrics as building blocks.
• An accessible tool for all non-data specialists.
• A powerful, modern tool adapted to Voi's high data demands.

Impact High productivity and curiosity for data

The productivity gain in Voi's data team has been game-changing after implementing Steep. Metrics are now the core data asset and can be used by anyone in the organization. Magnus has noticed a visibly stronger curiosity for data across non-data users and an increase in employees using data in their daily work.

Core benefits of using Steep:

1. Improved data quality: Centrally defined metrics guarantee data consistency at all times. Steep has enabled Voi to implement clear ownership of data; metrics are defined centrally and have clear owners, making it easy for everyone to know who to turn to with questions and ensuring all metrics are someone’s responsibility.
2. Increased data consumption: Anyone from analysts to office workers and warehouse staff can create content with Steep. Easy access to data enables employees to analyze metrics crucial to their team’s success, helping Voi as a whole to become more data-driven. Employees use Steep daily to help themselves instead of turning to analysts with ad-hoc requests.
3. Reduced data requests: By giving business users the tools to access their own data, the data team has cut the bulk of inbound requests and eliminated dashboard building. Magnus estimates his team saved the equivalent of one full-time employee's time, allowing skilled analysts to spend their time solving more advanced problems that have a strategic impact on the company.

Finally, Magnus states that the internal reception of Steep has exceeded his expectations in both time to implement and adoption. Business users highly value the intuitive user interface, the modern feel of Steep, and the connection to Voi's business language, making it simple for everyone to access the right data. The weekly and monthly active users of data have significantly increased, since employees can now independently use data to make informed decisions.

Want to say goodbye to dashboards? Book a demo with Steep today and discover how our intuitive BI tool can transform how you work with data.

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