The following is a guest post from Swetha Pandiri, manager of FP&A business systems at Kaiser Aluminum. Opinions are the author’s own.
Finance leaders are surrounded by data and often lead some of the most expensive investments in business intelligence tools and data automation initiatives across the firm. Yet in most scenarios, they roll back to offline spreadsheets and manual reconciliations to validate key metrics.
At the root of this problem is a lack of alignment across data sources, key metric definitions and reporting structures. Different business units often operate on separate systems, develop their own performance indicators and interpret results through local logic. As a result, even basic questions around operating expenses, procurement activity or working capital can generate multiple answers depending on who is asked, and which report is referenced. This fragmentation is not only operationally inefficient but also undermines decision-making. Executives are forced to spend time validating data rather than interpreting it, and financial analysts devote hours each month to re-explaining numbers to stakeholders.
While CFOs are expected to revolutionize data innovations in the organization, they often inherit reporting environments and legacy ERP systems shaped by outdated processes and fragmented data ownership. While these challenges are complex, CFOs are well-positioned to lead the solution since they hold a unique view across both financial and operational systems. This broad perspective, combined with finance’s responsibility for the accuracy and timeliness of reporting, makes them the natural leader for enterprise reporting reform.
CFOs who succeed in fixing fragmented reporting often rely on a collaborative approach between IT and finance, where a finance technology leader acts as a liaison who understands both the systems that manage data and the financial context behind the data. This combined perspective helps bridge the technical and functional gaps that frequently hinder transformation efforts.
The following steps offer a structured approach that organizations can use to build sustainable and practical reporting improvements.
1. Diagnose the sources of fragmentation
The first step is to understand the flow of data. Start by focusing on three primary areas: source systems, reporting logic and stakeholders’ usage. This means looking beyond individual reports and focusing instead on where the data comes from, how it is calculated and how it is used across different teams. In many companies, the underlying data may come from the same ERP system, but the problem lies in how different teams consume and interpret it.
This exercise helps uncover such discrepancies in definitions and manual workarounds to adjust the numbers. It also often shows a lack of governance and ownership over the data.
2. Establish governance and accountability
Establishing a reporting governance framework that defines ownership, data standards and review processes would be a crucial next step. This includes setting clear definitions for key metrics, outlining the calculations involved and identifying any customizations required by cross-functional teams. Each report or metric should have a designated owner responsible for maintaining definitions, managing updates and ensuring consistent usage.
This phase helps establish data standards that can improve clarity and collaboration across teams and allows reporting to scale with the business.
3. Invest in building a centralized data foundation
Once reporting gaps are identified and governance is in place, the next step is to ensure that the reporting structure is supported by a reliable data foundation. In most organizations, key financial and operational data is spread across multiple systems like ERP, procurement, budgeting tools and spreadsheets. A centralized data warehouse brings this data together into a structured environment where it can be transformed, standardized and made report-ready. While many pre-built data warehouse solutions are available in today’s market to address these challenges, those solutions are only effective when paired with internal ownership and oversight.
The data warehouse should do more than store raw data. It should be designed with a structured approach —using models such as the medallion architecture, for example — to organize and prepare data for reporting. Business rules such as mappings, calculations and flags must be built directly into the data layer, aligned with definitions agreed upon during the governance process. That logic should exist in one place and be applied consistently across all reports.
A well-structured warehouse provides the foundation for data to flow cleanly from transactional systems into analytical tools. This is essential to keep reporting reliable, repeatable and free from rework.
4. Promote a culture of reuse and data literacy
Once the core metrics are defined, ownership is in place and the data warehouse is structured to reflect that logic, the next step is to ensure these standards are adopted across the organization. CFOs should reinforce the use of approved reports and shared data models, rather than allowing each team to rebuild metrics on their own. This will lead to more consistent outputs and reduce the time spent maintaining disconnected logic.
Data literacy is another big part of this equation. The finance team should lead this effort by helping business users understand what each metric means, how it is calculated and where the data comes from. Taking advantage of features offered by modern data warehouse platforms, such as data cataloging, defined KPI rules and metric documentation, should be the starting point. This becomes especially important as more teams rely on self-service tools to make decisions.
5. Start small, focusing on one domain to build momentum
Once the foundational work is in place, the next step is to apply it in a focused, practical way. Widespread reporting transformation can feel overwhelming. Instead of attempting to fix all reporting at once, finance leaders should select one domain where the fragmentation is both visible and impactful, such as capital expenditures, procurement or operational expenses.
Using the standardized definitions, trusted data sources and governance structure already established, the team can align stakeholders and deliver one complete, consistent reporting solution. While this approach helps validate the framework, it also builds credibility. A well-executed rollout in a single area demonstrates what “good” looks like and helps others see the benefit of adopting the same standards.
Creating a repeatable model
Reporting transformation gains momentum not by scale, but by trust. Starting small allows finance to lead with confidence and bring others along through results, not mandates.
Addressing fragmented reporting requires more than surface-level fixes. It takes a deliberate approach that starts small, focuses on what matters most and scales with clarity. The CFO is in a position to lead this shift not only because finance is accountable for the numbers, but because it sits at the intersection of strategy, operations and systems. The steps outlined form a repeatable model that brings structure to how information flows through the organization. When applied with discipline, this structure supports faster decisions, fewer errors and clearer alignment across teams.
