Data Team

How can we increase efficiency and service quality with data driven decisions?

A Nextwit case study showcasing the leading Hungarian back office service provider’s journey to become data driven

employees working on reports

The leading Hungarian utility back office service provider started a new initiative to improve their bottom line through data driven decisions while improving their service quality. As they grow with large client acquisitions by taking over their back office services (i.e.: invoicing,payments, customer care), the data architecture 1 have became fragmented with different organizational siloes handling separate data requests. As a consequence overall decision making time and quality worsened and resource needs to support crucial decisions increased. As pressure on the IT architecture grew, decision support have been flooded with office tools (mainly custom queries loaded into Excel files) which further deteriorated trust in data quality and exposing security challenges.

The Challenge

Understand the current reporting landscape and requirements while exploring what is handled under the radar in office tools.
Select strategically important key performance indicators and position them in a future reporting system. Show what is needed to ease the pressure on IT, which kind of tools and competencies are missing. Focus further efforts on selected KPIs and must have competencies / tools with an actionable program and project plan.

The approach


We interviewed 15 teams handling the majority of the reporting requests and gathered all current reports in a structured report catalogue with sample files. We mapped the IT infrastructure and put it into our best practice landscape to show what’s missing. We also identified related projects in progress to be able to plan the next steps without interfering with other business priorities.


We designed the future state of decision making with user personas, a fitting reporting pyramid and key performance indicators to be included in it. We designed a streamlined a streamlined enterprise data model to have everybody on the same page when thinking about data. 3 We also showed what kind of tech tools needed to ease the pressure on IT.


We compiled a strategic program with enabler projects focusing on the data management process, skills and technology tools and also on supporting business initiatives with the introduction of thematic data marts. We also delivered a detail project plan for each initiative for the next year with scope definition, budget, responsibles and a proposed schedule.

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