The Impact of Forecasting Improvement on Return on Shareholder Value
John T. Mentzer; Journal of Business Forecasting

Improving Salesforce Forecasting
Mark A. Moon and John T. Mentzer; Journal of Business Forecasting

Benchmarking Sales Forecasting Management
John T. Mentzer, Carol C. Bienstock, and Kenneth B. Kahn; Business Horizons

Conference: The Dynamic Supply Chain--Strategies for Implementing Sustainable Competitive Advantage,
Nov 17-18, NY
Hear Glen Margolis, Founder & EVP Steelwedge Software, Carol Ptak, Former APICS CEO and Author, Others
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Forecasting and Consensus Planning in a Rapidly Changing Environment
June 15, 2005, 1pm Eastern, 10am Pacific
Principal Speaker -
Christine Pfefferle, Director of Global Demand & Order Management, Tellabs  
Click here to view recording

Extending SAP for Global, Integrated S&OP ,
May 25, 2005
Stu Reekie, Air Products
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By Anders Gjerde, Senior Manager and Business Analyst at Steelwedge Software

Most business plans and forecasts give you a snapshot of where you are right now, and what is expected for the future. If your plans never changed, then all would be well - your planning needs are met. But the reality for many managers and executives can best be described as a planning process that is in a state of constant change, with too much information to track and too little time to make sense of it. It's critical to know-- What changed? How much? When?

This is where waterfall analysis can help, providing a vehicle for answering the above questions. Waterfall Analysis is a term used by professionals in planning and performance management, but, surprisingly many are confused about what it means, how it is used, and/or how to interpret results. This article seeks to clarify some of this confusion by first describing what waterfall analysis is, then providing some examples of how waterfall analysis can be effectively used, and finally, what is needed to be able to do waterfall analysis.

What is Waterfall Analysis?

Waterfall analysis can be defined as taking snapshots of forecasts or plans at different points in time and compare them in order to gain visibility into changes over time - what changed, how much, and when? To illustrate, let us look at a simple example:

In the beginning of May, a regional manager is reviewing her sales plan for the next three months. The plan is her primary management tool to help steer and monitor her sales staff's activities. She vaguely recalls that the sales plans looked different when they were reviewed in March and April. The total plan for the next 3 months does not look very different, but something has changed. She proceeds to develop a waterfall table, taking a snapshot of future sales plans as they were in prior months:

Looking at this table, she finds that for the snapshot in March
(Time of snapshot = March), a spike was expected in May of 120 (Planning Period = May). One month later -- in April -- this spike was pushed out to June. Now -- in May - the spike is pushed out yet another month; to July. Armed with this knowledge, the manager can create waterfall tables for each of her sales people to see who is pushing their sales plan out, and make more informed inquiries as to how real this spike is, what to do about it, etc.

As the above example shows, waterfall analysis is about taking snapshots in time and comparing them to look for changes and trends as time moves on. In other words, waterfall analysis tells you what your plan is versus what you thought your plan would be.

Practical Applications of Waterfall Analysis

The above example illustrates how a manger analyzed changes in sales plans over time. A more realistic example would probably include a break-down of product lines, regions, etc. Although useful, many people find it difficult to make sense of information in this tabular format.

An alternate, more graphic way to view waterfall information is to compare 2 snapshot periods at a time, as in the following example:

In this example, we are comparing expected value forecasts and total sales pipeline for snapshot (as-of) date 11/1/2004 and snapshot date 1/1/2005 . We can see that for snapshot date 11/1/2004 , we expect a sales peak in June 2005. However, as of 1/1/2005 , that peak appears to have shifted to July 2005.

Below is another example of a waterfall analysis - it shows how much sales leads were generated in different periods:

In this example we can see that September 2004 and February 2005 were particularly productive months, whereas August 2004, November 2004 and January 2005 were ditto unproductive with regards to lead generation.

Below is yet another example of a waterfall analysis, showing how sales generation proceeds through the sales pipeline, by showing how many days it takes to convert leads from "initial contact" to actual "deals":

This example shows that once initial contact with a prospective customer is established, it takes over a month to convert the opportunity into a qualified lead. Once this is done, negotiations about features and functionality do not take long, but the contract takes over 45 days - suggesting a bottleneck in the contract department.

Requirements for Waterfall Analysis

Creating waterfall analysis requires a Plan of Record.

That is, it requires a data processing system that can take snapshots of the forecasts or plans at different points in time, and put a date-stamp on the data when they are snap-shot.

Upon creating of waterfall analyses, the system must be able to query and display data by snapshot dates.

Conclusions

Waterfall analysis can be used - and displayed - in a number of ways, answering the ever-present planning and performance management questions;" What changed, how much, and when? " Waterfall analysis requires a data processing system that is able to take snapshots at different points in time, time-stamp these snapshots, and store them for later use.

Below are some planning processes that can benefit tremendously from waterfall analysis:

• Sales funnel or sales pipeline management
• Sales force effectiveness
• Forecasting and planning
• Forecast accuracy measurements

Anders Gjerde is a Senior Manager and Business Analyst at Steelwedge Software. Since joining Steelwedge in 2002, he has worked with customers to implement innovative solutions to help them solve a wide range of planning and performance management problems. Prior to joining Steelwedge, Anders was Director of Global Client Solutions at Decision Focus/Talus Solutions (acquired by Manugistics, Inc in 2001). Anders holds an MBA from the Norwegian School of Economics and Business Administration.