Mitigating Challenges in Developing Analytics & Reporting for Big Corporate Companies

In today’s data-driven companies, analytics & reporting – through dashboards are expected to deliver fast, actionable insights that support critical business decisions. Yet, according to a 2022 Forrester study, 60% of analytics initiatives fail to meet expectations because often the data feeding those dashboards is unreliable, incomplete, or misaligned (Forrester, 2022).

Two major challenges consistently stand in the way: data fragmentation across siloed teams and systems, and misalignment in data logic and KPI definitions. These issues can often go unseen but have a profound impact on the success of any dashboarding initiative.

In this article, we unpack these challenges through a real-world case study, highlighting how fragmented data and inconsistent logic drive the bulk of effort in BI projects. We’ll explore the hidden backend work required, the roadblocks encountered, and the strategies we used to deliver a scalable solution for a global automotive company.

Two of the biggest obstacles in building enterprise dashboards aren’t technological, but structural: fragmented data systems and misaligned business logic.

Large corporations are often structured in a way that encourages independent operation across departments, business units, or geographical markets. While this may provide flexibility at the local level, it creates major challenges when trying to build centralized reporting that spans the entire organization.

According to the 2021 Accenture and MIT CDOIQ survey, 37% of Chief Data Officers cited siloed infrastructure as the greatest challenge in delivering their data vision (Accenture, 2021). Before any reporting can happen, teams must first determine where the data lives, who owns it, how it’s structured, and whether it’s reliable. In many cases, just locating the right dataset can involve weeks of back-and-forth between departments.

Even once the data is secured, deeper alignment issues often emerge. Different teams or regions often use slightly different definitions for the same KPI. One team might measure weekly conversions based on user actions, and another might track it using product orders. Without alignment on definitions, it becomes difficult to create dashboards that stakeholders trust. The result is often a lack of confidence in the numbers and a reluctance to rely on the dashboard for decision-making.

This fragmented landscape also makes data preparation a heavy lift, long before any visualisation begins. A substantial amount of time goes into cleaning, joining, standardizing, and transforming raw data into a usable state. This isn’t just a technical task. It often requires multiple teams to agree on the logic behind the metrics and the definitions they’re working with. Without this foundational work, no dashboard can provide reliable insights. But when done right, it enables scalable, trustworthy reporting that multiple teams can confidently build on.

OVERVIEW:

For a global automotive manufacturer, Artefact was tasked with building centralized dashboards to improve reporting across regions. While the goal seemed clear to streamline analytics and provide real-time insights, the reality of implementing it across a decentralized organization quickly proved to be more challenging than initially expected.

CHALLENGE: 

The company’s business was organized by regions and sub-divided into local markets, each of which operated with a high degree of autonomy. This led to inconsistencies not only in the systems used but in the very definitions of key metrics. One striking example: while one market defined an “online sale” as the moment an order was placed on the website, a neighboring market only considered it a sale once payment was received. These subtle differences created major reporting gaps, especially when leadership required consolidated views at the regional level. Which definition was correct? How could the data be aggregated without misrepresenting performance?

SOLUTION:
To resolve this, we implemented a centralized data platform that ensured all markets and regions aligned on shared definitions and data logic. This required tracing each KPI back to its original data source and working with local teams to unify methodologies. The outcome wasn’t just a dashboard—it was a foundational shift in how the company treated and trusted its data, enabling scalable, accurate reporting across teams and regions.

Through the challenges, several key success factors emerged that helped drive the project to completion:

• Automation of data collection: Eliminated manual effort previously spent on handling Excel files and pivot tables, ensuring real-time data availability.
• Centralized analytics: Consolidated data in a single dashboard, enabling seamless cross-functional insights.
• Accelerated reporting capabilities: Report generation time was reduced from one day to one hour.

Lessons learned:

• Backend and frontend alignment is crucial: Technical requirements often evolved during the project, underscoring the need for early coordination between data engineering and dashboard design.
• Tool limitations can shape your solution: The third-party BI platform had customization constraints, which required creative workarounds and managing stakeholder expectations.
• Change management is part of the job: Many employees were reluctant to move away from Excel, highlighting the need for proactive training, support, and clear communication to drive adoption.

At Artefact, we specialize in overcoming these challenges by fostering collaboration, ensuring data consistency, and delivering impactful BI solutions. In this project, our team successfully aligned multiple departments to:

• Standardize KPI Definitions: We facilitated discussions between teams to create a universally accepted set of performance indicators.
• Unify Data Formatting: Our experts streamlined data structures across different regions, eliminating inconsistencies that previously hindered analysis.
• Break Down Silos: By integrating data sources into a centralized platform, we enabled real-time insights and transparency across teams.
• Deliver a Scalable Solution: We built a single source of truth platform featuring over 20 dynamic dashboards, providing stakeholders with intuitive, real-time reporting tools.
• Adoption & Training: Once the reporting capabilities were set, we organised a series of training to ensure the tools were adopted and incorporated in the day-to-day activities of the stakeholders. 

By leveraging Artefact’s expertise, we transformed the company’s approach to data, helping them move beyond fragmented reporting toward a truly integrated analytics ecosystem.

In large organizations, the biggest blockers to effective dashboards are rarely visual or technical, they’re structural. Fragmented systems, inconsistent KPI definitions, and siloed teams create a level of complexity that no front-end tool can solve on its own.

As this project showed, solving these challenges requires more than just tooling. It demands alignment across departments, a shared understanding of data logic, and a commitment to building strong data foundations before a single chart is built. The bulk of the effort lies in the backend, but that effort pays dividends as it enables scalable dashboards that teams trust, adopt, and use to make real decisions.

For companies looking to mature their analytics capabilities, the message is clear: invest in the hard work of unifying and preparing your data. Once that’s done, the dashboards become the easy part.