Lack of standardization and the manual nature of the cash flow exposure management forecasting process match up well to the guiding principles of the Lean approach and breed an opportunity to maximize value and minimize waste.
Three specific areas of the exposure forecasting process particularly lend themselves to LEAN:
1. A CLEAR WORKFLOW
The Problem: Generally, the exposure forecasting workflow is largely manual and completed in spreadsheets.
A Lean Approach: In order to streamline this process, corporations can implement tech solutions. An automated process that prioritizes forecast initiation through the distribution of a prepopulated forecast baseline eliminates errors from previous forecasts from transferring over and reduces the amount of time needed to begin forecasting.
2. FORECAST CAPTURE & CONSOLIDATION
The Problem: Forecasts submitted from the field in different forms through different mediums at different times can leave room for process error and its associated risk.
A Lean Approach: Automated submission of forecasts through a single platform ensures data is kept in the same place and format, and eliminates wasted time spent collecting and consolidating individual forecasts.
3. CASH FLOW EXPOSURE ANALYSIS
The Problem: Treasury teams without a set data aggregation structure waste time trying to force data into a usable format.
A Lean Approach: Creating a standard format for exposure analysis and review provides time to trap quality issues at their sources, drives collaboration and provides better insight into exposures.
FiREapps for Cash Flow, an end-to-end SAAS solution, implements a measurement-based strategy that focuses on improvement and variation reduction – producing better results with fewer resources and helping processes flow smoothly. Each step of the process adds value to the data by using the right tools and executing a resilient and repeatable workflow where errors are caught early on.
Treasury has the opportunity to take a lean approach to cash flow exposure forecasting where the process is streamlined, wasted time and effort are reduced, and errors are eliminated. By eradicating processes that do not have a direct bearing on the value of the exposure forecast or lead to inaccurate forecasts, a lean approach improves the quality of data and yields a more efficient process allowing for better risk management.