Pleo logo

    Rittman Analytics and Pleo work hand-in-hand to design and deliver a modern, scalable and user-centric data foundation

    Priscilla Nagashima

    Priscilla Nagashima

    VP of Data, Analytics & AI, Pleo

    "Working with Rittman Analytics has been great. They have been a very helpful extension of our own Data team, rolling up their sleeves and building with us. That partnership was key to leveling-up our data foundations, which lets our team focus on what they do best: using data to drive innovation faster."
    Pleo mobile app interface showing business spending platform

    Vital Stats

    Website

    https://www.pleo.io/

    Industry

    FinTech

    Company Size

    501-1,000 employees

    Headquarters

    Copenhagen, Denmark

    Rittman Analytics Services

    • Data Centralisation

    • Data Team Enablement

    • Data Team Modernisation

    • dbt Consulting & Support

    Technologies Used

    • Looker

    • Google BigQuery

    • dbt

    The Download

    Pleo is a trailblazer in the FinTech world, fundamentally changing how businesses think about spending. From real-time financial tracking to advanced treasury tools, Pleo has become one of Europe's leading holistic business spend platforms, at the forefront of empowering businesses to manage their finances more effectively. This isn't just about efficiency; it's about building a culture of trust and autonomy to free up finance teams to focus on strategic work. This powerful, forward-thinking vision has fuelled their unicorn growth and positioned them as a true leader in the future of work.

    The Challenge

    Pleo's remarkable success and hyper-growth created a new challenge: the data infrastructure that had served them well during their start-up phase needed to evolve to match their future ambitions.

    To continue innovating and scaling their trust-based platform, Pleo needed to supercharge its data platform and so they sought a partner to help them build this next-generation platform, choosing Rittman Analytics to help turn their data capabilities into a new engine for growth.

    The Solution

    At Rittman Analytics, we believe that true data transformation and modernisation of your data function is more than a technical project; it's a fundamental change in your "data operating system".

    Our approach to transforming and modernising data teams and their platforms is built on a proven, three-step methodology that goes beyond surface-level fixes and delivers lasting, sustainable value.

    This structured approach ensures we not only build the right solutions but also embed the processes and culture required for them to succeed.

    1. Confront the Hard Truth
    2. Create the Change
    3. Manage the Change

    Step 1: Confronting Hard Truths Through Discovery

    Over an intensive four-week discovery sprint, we embedded ourselves within Pleo and:

    • conducted in-depth interviews with leadership, domain data leads and engineers.
    • attended daily stand-ups for both infrastructure and data services teams to observe real-time dynamics.
    • performed a deep analysis of all existing documentation, from high-level strategy documents to project plans and team-specific notes.

    Our discovery revealed a central data team navigating a period of change—deeply committed to maintaining core infrastructure, but in-need of support for fast business growth. This highlighted an opportunity to redefine its role as a more visible and influential partner to the business.

    Step 2: Create the Change

    Following the discovery phase and a shared understanding of the challenges, Rittman Analytics and Pleo worked hand-in-hand to design and deliver a modern, scalable and user-centric data foundation.

    Change #1: Co-Creating the Pleo Analytics Warehouse (PAW)

    Together, we designed and implemented a new Pleo Analytics Warehouse (PAW) - a structured, multi-layered architecture that moved data from raw ingestion to reliable, business-ready insights. We also introduced a formal five-phase analytics development lifecycle with clear sign-off points, enabling a more consistent, accountable and collaborative approach to building data products.

    Change #2: Streamlining with a Unified dbt-Looker Monorepo

    To reduce friction and improve delivery speed, we collaborated on the creation of a unified "monorepo" that brought dbt models and Looker assets into a single development environment. This allowed Pleo's data team to work more efficiently across tools, improved the accuracy of releases and introduced a shared QA and testing process that made iteration faster and more reliable.

    Change #3: Expanding Self-Service Through Shared Governance

    With the new architecture in place, we extended the workflow to include Looker development - enabling domain analysts to build and test their own content with confidence.

    Step 3: Manage the Change

    Even the most advanced data platform and technically capable team will fall short without the structures and support needed to sustain meaningful change. Our goal was to ensure that new ways of working didn't just take hold, but became embedded in Pleo's culture and operating model.

    Over time, our role shifted to support and coaching, as Pleo's team grew in confidence and took the lead.

    Business Benefits Delivered

    Through our engagement with Pleo's data and analytics team, Rittman Analytics delivered a range of impactful business benefits, including:

    • Accelerated delivery of Pleo's new analytics warehouse, integrating critical data modeling, orchestration and business intelligence capabilities
    • Increased capabilities of Pleo's internal data team through targeted training and knowledge sharing
    • Fostered improved collaboration and trust between Pleo's central and distributed data teams, ensuring data outputs were well-aligned with the company's evolving business needs
    • Provided a more robust, scalable data platform to support Pleo's continued growth

    Together, the outputs of this engagement will contribute to Pleo's ability to leverage data more effectively to support their business goals.