Forecasting financial data is an important process because it allows management to review an organization’s current financial state through the fiscal year’s actual and projected financial data. In this process, financial planning gathers the current fiscal year’s actual data, analyzes the outcomes, and forecasts the remaining fiscal year. Therefore, the resulting forecast is only as reliable as the actual data gathered and the quality of analysis.
Gathering the actual data and analyzing variances is often burdensome and shifts focus away from financial planning’s primary role: forecasting. To streamline these phases of the forecasting process, organizations should begin with the ERP system. Organizations can design an ERP that aligns data forecasting and recording, configure the actuals to flow seamlessly into the financial planning model, and provide financial planning ERP training for variance explanations. These steps further improve the forecasting process by shifting financial planning’s focus back to forecasting.
System Design and Reporting Requirements
An ERP system is an invaluable tool to many functions within an organization. Other functions, like financial planning, may view the ERP as inadequate because the accounting data extracted doesn’t meet forecasting requirements. Whether the financial data is too detailed or not detailed enough, both scenarios require financial planning to dedicate time to manipulating data rather than analyzing and forecasting financials.
The ERP may not meet the needs of financial planning because financial planning’s requirements were never expressed during the ERP design. The design phase is a critical phase in an ERP implementation wherein future-state data and reporting requirements are documented. Including the needs of financial planning streamlines the process for retrieving historical data and determines the level of detail that should be recorded in the first place, unless GAAP requirements specify otherwise.
The means by which financial planning receives historical financial data can also cause problems in the forecasting process. Manually retrieving and uploading data into the financial planning tool can lead to errors or outdated data in the forecast model. By investing in an Extract, Transfer, Load (ETL) tool, financial data automatically flows from the ERP system to the financial planning tool. A translation can bridge the gap if the ERP design was not tailored to financial planning’s requirements but can be translated logically.
This allows financial planning to receive and utilize up-to-date and accurate information for forecasting without having to manually touch the data. This significantly decreases the risk of invalid data in forecasting models and allows financial planning to shift their focus from validating manually manipulated data to forecasting financial data.
If the organization does not have a financial planning tool, ensure the ERP data extracts are set up to financial planning’s exact specifications so they can flow seamlessly through the financial model.
Knowledge and Training
Part of the financial planning process is analyzing and explaining variances between forecast and actual data. Usually, financial planning must search the organization for the appropriate resource to explain the variances. However, if financial planning has access to the ERP system and receives training on the overall layout and reporting capabilities, variances can first be researched in the source system. If further explanation is required for some account variances, financial planning can use the ERP to identify specifically which transactions need explanation and who is responsible for these transactions.
On the other hand, some financial variances occur due to coding or roll-up changes that accounting enforced for their reporting needs. With training on the ERP layout, financial planning can articulate how ERP changes will adversely affect the forecasting process and reporting requirements. Conversely, if management requests changes in the forecasting layout, financial planning can work with accounting to realign how data is recorded with how management requests analyses and forecasts.
Align actuals and forecast through ERP design, integrate the ERP and financial planning tool, and train financial planning on the ERP layout to streamline the financial planning process. These steps prevent financial planning from dedicating resources to manipulate data to align with the forecast, reformat data extracts to flow into the forecast model, and search blindly for variance explanations. By streamlining the first two phases of the forecasting process, financial planning can concentrate on projecting a more reliable forecast with quality data and strong analysis.
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