Adopt Rolling Forecasts to Replace Annual Budgets
Contributed by Narsimha Rao Garlapati, Ramya Durga
Rolling forecasts can help organizations react more effectively to increasing competition and a changing economic environment.
In today's volatile business environment, organizations need to anticipate change and react to it nimbly. In this environment, they can ill afford to rely only on annual budgeting and forecasting. By embracing continuous planning or rolling forecasts, companies can remain agile, focused and flexible enough to meet changing business needs.
Implementing Rolling Forecasts
A rolling forecast continually predicts performance against key business drivers. This allows an organization to better foresee risks and opportunities, revisit strategy in the light of new business scenarios and frequently align resources/activities for competitive advantage. Rolling forecasts are not simply periodic updates against the annual budget and are not associated with a specific financial year.
Three critical steps in implementing rolling forecasts are:
Driver-based forecasting: Forecasting should focus on specific metrics by identifying business drivers that are relevant for analysis and decision-making. This will eliminate data overload and provide organization-wide alignment and control over forecasting.
Linking the forecast to strategic and operational decisions: Risks and opportunities identified during a rolling forecast should trigger “what-if” analyses and scenario planning. Resources for capital projects and operational expenses can then be reallocated and new performance targets set.
Ensure direct ownership and involvement of budget owners: For a rolling forecast to succeed as a reality check, budget owners should be directly involved and provide unbiased data.
Appropriate change management: Rolling forecasts are radically different from fixed forecasts, where projections are adjusted to fill gaps. Many participants will therefore need to jettison their monthly budgeting and target negotiating mindset. Organizations should create a change management policy that explains the objective of rolling forecasts, as well as the new communication practices, knowledge sharing and training programs they require. They should also identify the key metrics for the success of the change management policy.
Data and Analytics Essentials
Just as important for the success of a change management initiative is the focus on data. Organizations should consider:
Focusing on relevant data and data-related processes: Rolling forecasts should focus on a small set of metrics and drivers that are essential for tracking changes in the environment. This should include external market and demand information, along with internal business details. Since rolling forecasts happen at smaller intervals and are expected to produce current and future state views of business within a shorter period of time, rapid integration and aggregation of data are critical.
Processes around data generation, consistency, maintenance and integration should be well supported by data policies and technologies. Rolling forecast corporate performance management (CPM) applications should be able to create and manage different scenarios to facilitate scenario planning, and integrate with actual information for analyzing trends and extrapolating the future.
A CPM application for generating rolling forecasts should be evaluated for specific business fit and strategic features. These features include the ability to forecast across months and years, driver-based planning and scenario management, integration of sales, revenue and cost rolling forecasts and the ability to integrate projected information and compare it with the user-created forecast.
Technical features should include customizability, scalability and automated data input and different user interface options.
Apply proven statistical techniques and predictive models: Rather than relying only on historical data to understand what has happened, rolling forecasts anticipate the future by visualizing patterns found in historical and transactional data. Predictive models can be created for “scoring” data and simulating scenarios using statistical techniques to identify risks and opportunities and make meaningful decisions.
Role of a Framework
Using a proven framework can help assure rolling forecasts help organizations react proactively to business changes. One example is our FAST framework whose steps include:
- Identifying and tracking all financial and non-financial metrics;
- Conducting a detailed risk/opportunity analysis using the appropriate technique for each industry.
- Performing a “what-if” analysis and scenario planning to identify alternative strategies to adapt to wider opportunities and risks, and
- For the newly identified strategy, redefining priorities for the operative processes and proposing adaptation measures and activities.
The benefits of such a framework include vertical integration of strategy with the continuous planning/rolling forecast, horizontal integration across different functions in forecasting, greater visibility and monitoring, driver-based functional process outcomes consolidated and integrated at corporate levels, and enhanced “what-if” analysis and simulation.
If implemented properly, rolling forecasts provide forward-looking insights that help organizations proactively change course to avoid risks and exploit opportunities. For more insights, read Replacing the Annual Budget with Rolling Forecasts (PDF) and learn more about Cognizant's Performance Management services, and its Data Warehousing and Business Intelligence solutions.