It starts with the EIM, sometimes referred to as the common information model (CIM). An EIM is a framework for organizing the critical information required to run the business and drive insights. The EIM provides the foundation on which an organization’s business processes and reporting will be built. An EIM can be made up of many domains (e.g., Finance, order management, supply chain, and operations), based on the structure of the business. Each domain has its own data models, but the key data elements that are required to run the business should be common across all domains. At minimum, organizations should have a common definition and an aligned understanding of how it affects reporting and performance metrics.

Defining an EIM is just the first piece of the puzzle. It lays the overall foundation from which to build a reporting strategy, data strategy, and common chart of accounts. It enables an organization to align on what data and level of granularity is needed by what functions, by each leadership level, and for what purpose.

Once a common language and data needs are understood, the next step is to define a data strategy. What are your data sources, where do you want to report, and what tools do you want to use? Does the information you need have to be in the general ledger, or can it be sourced or reported on elsewhere (e.g., subledgers, a data hub, or a data warehouse)? The answer to these questions will influence where the data is captured and how to design the chart of accounts.

Once there’s alignment between the critical data elements needed (assets, locations, etc.) and the functional data models (supply chain model, finance model, etc.), there can be a clearer understanding of how those elements affected performance measures and the relationship between operational and financial performance.

Once the data design is complete, the next step is to assess the global system and reporting tool architecture. This includes assessing the current technology landscape (e.g., ERPs, sales tools) and identifying ways to maximize those tools based on clear data definitions and process discipline. Afterward, Finance can identify the gaps based on desired capabilities (near-real-time data availability, financial modeling, analytics, data visualization, data science, etc.). In looking to activate new capabilities, consider the enablers for all the reporting use cases (operational reporting, management reporting, strategic analysis and insights, external and statutory reporting, etc.) needed as part of an ERP-driven finance transformation.

As with all successful transformations, the desired outcome changes the way activities are performed to generate better results. Reporting is no different. Enabling new reporting capabilities means less time is spent reconciling data and performing shadow finance activities. Therefore, it is important to assess the impact on your people and finance organization.

Finance team members will be asked to generate insights and no longer just keep score based on historical performance. As the role shifts, it often results in new efficiencies and a need for new skills. Finance organizations are being challenged to retool their teams and to help them shift from transactional and operational reporting activities to strategic insight generation and scenario modeling that informs key business decisions.

As the organization adopts new reporting capabilities, it will need to shift to a continuous improvement mindset. The organization will also need a scalable reporting capability to evolve with the business. There should be an emphasis on self-service, and Finance should take on an elevated role beyond being a distributor of reporting. Instead, the focus should be on ensuring reporting capabilities are aligned to the business strategy and reflect a current view of the organization.

No matter how well your EIM is defined, or how advanced your reporting and visualization tools are, they will only be effective and sustainable if the proper governance and controls are in place. Effective governance includes clearly defined roles and responsibilities, strict adherence to data and hierarchy governance, and a scalable security model to manage user access to reports and data. The governance model includes finance data in ERP systems, as well as upstream reporting systems across the enterprise.

Reporting governance also means the organization defines standard reports for key business reviews and eliminates both legacy reports and oversized reporting packages that have grown over the years. Standard reporting packages are essential to the successful implementation of a reporting strategy, as they typically help drive standardization across the enterprise that increases efficiency and aligns business reviews with KPIs linked to the overall business strategy.