Advanced Methods in Rolling Forecasts

By Juan Porter
November 10th, 2011

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In previous posts, we covered transitioning from traditional budgeting and forecasting to rolling forecasts and implementing rolling forecasts. Now it’s time to turn our attention to what to do once you have this new approach in place. And to do this, I’ll spend the next two posts discussing advanced methods in rolling forecasts.

Making Rolling Forecasts Effective

Once you’ve decided to implement a rolling forecasts, you need to determine how you can make the process efficient and valuable to company. Before we talk some of the ways how, it’s good to review the keys to overall success with this innovative approach to managing the forecasting process.

Throughout the implementation, the role of the executive sponsor remains critical and this is especially true as you approach go-live. This is the time when the new process is undergoing adoption; and to make sure everyone embraces rolling forecasts, the executive sponsor must be continue to operate as the “change sponsor.” Remember change takes time to adopt, so not only does patience need to be exercised but it also needs to be visibly included in the first few cycles to ensure people have time to perform and understand the new process.

Another thing you’ll want to review is this new process. This was defined at the start of the project but now the process meets reality. In addition, a regular review of any process is always a good idea so adjustments can be made as the needs of the business change. Make sure who, what, and how still lines up with the same departments, groups, and/or people.

The “how” and “what” is what will determine the effectiveness of and ultimately value to your organization. It is not reasonable or feasible for most to perform a true zero-based or bottoms-up rolling forecast in a few days. So it’s important to determine what information a manager can directly control/influence and how/what data that can then drive. This is where efficiencies and value is gained by using driver-based models.

Driver-based Models

Driver-based models allow you to minimize the amount of data input and focus on key drivers. Using driver-based forecasts facilitates collaboration and business modeling, which in turn raises the quality of the outcomes while at the same time providing more control. Moreover, a driver-based approach lets you standardize with a single methodology and align key assumptions across the organization. Driver-based models also offer the ability to model different scenarios (Best/Worst case).

Simplicity Through Drivers

The key to creating a driver-based model is to understand the relationships and dependencies in your data. From this you can the drivers that will improve the accuracy and flexibility or your forecast.

At a high level, driver-based models are basically calculations where:

• Users can enter a single base element of a calculation and results are driven from that
• Certain elements are centrally defined/controlled
  • Unit price/cost, discount rates, etc
  • Salary mid-points, benefits, taxes, etc
  • Depreciation
  • Simple example:  Unit x Rate = Amount
    • Unit is input by user and is their focus
    • Rate is centrally supplied/controlled
    • Amount is derived result

Some specific examples of this are outlined below.

Revenue/Cost Based Drivers

• Drivers set by Corporate or LoB
  • Unit Price and Cost
  • Discounts, Returns, DiF, etc
  • Currency dependencies
  • Units sold are input by users
  • Improves Customer and Supplier relationships
    • More focused on strategic relationships
    • Total units sold may impact cost basis

 

 

Employee Based Drivers

• Drivers set by Corporate or LoB
  • Salary levels by grade or position
  • Benefits and Payroll Tax rates
  • Currency dependencies
  • New Hires are input by users
  • Focus on type of resource and when to hire
    • Improves modeling of different hiring plans

 

 

Employee Based Advanced Drivers

 

 

The last post in this series – Understanding Your Forecast– will take you beyond the numbers, discussing the less obvious aspects of rolling forecasts.

This is Part III of a four-part blog series on rolling forecasts:

Part I – Transition Traditional Forecasting to Rolling Forecasts

Part II – Implementing Rolling Forecasts

Part III – Advanced Methods in Rolling Forecasts

Part IV –  Understanding Your Forecast

Check back next week for Part IV – Understanding Your Forecast

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