SALES FORECASTING MANAGEMENT FORUM
EXECUTIVE ROUNDTABLE
When: September 6-8, 2006
Preliminary Schedule
Where: Knoxville Marriott

A SPONSOR ONLY EVENT
Collage - The Roundtable in Review

7th Annual World Class
Sales Forecasting Management Conference
When: May 15-17, 2007
Where: Knoxville Marriott Hotel

VIEW 2006 CONFERENCE SCHEDULE

Previous Webcast--
Sales Forecasting—
How To Improve Collaboration
Tuesday, July 25, 2006
1pm Eastern, 12noon Central,
10am Pacific
Dr. Tom Mentzer,
Ph.D. Marketing & Logistics
Dr. Mark Moon,
Ph. D, Marketing & Logistics
University of Tennessee
Click here to view recording

Previous Webcast--
Selling Beyond the
Sales Force--
Leveraging Technology
to Improve Sales Effectiveness
Tuesday, July 11, 2006
1pm Eastern, 12noon Central, 10am Pacific
Dr. Jag Sheth, Marketing Professor Emory University
Click here to view recording

Guidelines for S&OP in the Multi-site Enterprise
Wednesday, January 11, 2006, 2pm Eastern, 11am Pacific
Principal Speakers
Share Green, Director,
Program Management,
Teledyne Technologies EMS ,
Glen Margolis, SVP Services, Steelwedge Software
Click here to view recording

TMC.net
June 2006
Steelwedge Offers Tellabs Sales, CRM Help
By David Sims

BusinessWeek Online
June 2006
The Real Disaster: Inadequate Preparation
By Kevin O'Marah

Chief Supply Chain Officer June2006
S&OP Customers Go Cross-Functional and Show Results
By Jacqueline Emigh

Manufacturing Business Technology (MBT) November 2005
Cover Story: Balancing Supply & Demand
By Sidney Hill, Jr.

Baseline Magazine (11/08/05)
Air Products in the Pipeline
By Mel Duval, 11/08/05

START Magazine July-August 2005
Looking Forward: Forecasting and Consensus Planning
By Christine Pfefferle, Director of Global Demand and
Order Management

Turbo Charging Your Sales Forecasting Process
By Anil Gupta, The Applications Marketing Group

The Sales Funnel - a Critical Part of the Demand Planning Process
By EJ Tavella, Senior Director
of Business Development, Steelwedge Software

When is a Next-Generation Forecasting and Planning System Required?

By Dr. J. Thomas Mentzer, Distinguished Professor of Marketing and Logistics at the University of Tennessee.

It is a sad fact of life, but most Demand Forecasting and Planning [1] systems cannot do everything you would like them to do. The question then becomes - does the current planning system effectively address your most important business issues? This article discusses some of those important business issues, including the cost of ignoring or over-simplifying them and puts them into real-world context.

Realizing there are short-comings in existing demand forecasting and planning system(s), executives have to choose one of the following options:

• Ignore the issues
• Perform analysis outside of existing systems, e.g.,
  offline analysis in Excel
• Upgrade existing planning systems
• Invest in a next-generation Demand Forecasting and Planning System designed to address your specific requirements

Which option a user should choose depends on the issue – its business complexity and perceived business value. 

Business Complexity, in this context, is about the amount and intricacy of the underlying data, the sophistication of the analytics, how often the analysis is performed, and the degree of cross-functional collaboration needed. 

Business Value is the impact on operational performance - vaguely defined as anything that helps improve the bottom line, shorten time-cycles, or present greater opportunities to do things better in the future. 

The following diagram compares the options in a decision framework:

If the perceived impact on the operational performance is low and there is little complexity in the planning process for the business process, i.e., it does not require complex data collection, and/or the analysis can be done infrequently, then doing the analysis in Excel may suffice. However, if the business complexity is high, then a more thorough cost/benefit analysis can be undertaken to see if it makes sense to do this analysis using Microsoft Excel or other spreadsheet tools with simplified assumptions.

If the perceived business value is high, then using a more sophisticated planning system is warranted. With low business complexity – particularly with regards to simple analytics – upgrading an existing system may do the job. However, with increasing business complexity, a more specialized tool, like a next-generation Demand Forecasting and Planning System can be a good investment. The next section outlines symptoms that point toward the need for a more advanced planning system.

The Case for a Next-generation Planning System

Next-generation Planning Systems are advanced planning tools built to solve specific business problems. Traditionally viewed as exceedingly expensive and difficult to implement, a new generation of Advanced Forecasting and Planning Systems have emerged that are very price competitive and do not impose more implementation risk than upgrading existing systems.

A next-generation Demand Forecasting and Planning System:

• Incorporates and manages key inputs from all relevant data sources such as a sales pipeline, a new product introduction plan, a financial business plan etc.
• Enables users in various business functions to see the data within a plan from their perspective (e.g., sales sees the information within the plan by customers and region in units, finance sees the same plan by business unit in dollars and operations sees the same plan by manufacturing site in units, etc.)
• Provides transparency across functional silos for assumptions used in creating the plan,
• Uses Enterprise Enabled Excel which combines the flexibility of Excel with the power of an Enterprise Application,
• Enables management by exception,
• Enables users to do ad-hoc analysis or create scenarios, and
• Is designed to support any business process - instead of building business processes around the system.
  

The following table can help you diagnose whether or not your company may benefit from a next-generation Demand Forecasting and Planning System:

If the answer to two or more of the above questions is 'Yes' and the following problems are experienced, then a next-generation planning system should be considered:

• Continually missed revenue projections
• Exceedingly high forecast errors
• Too much inventory
• Too low fill rates
  
  

Case Study 1

When the IT downturn hit in 2001, a large networking equipment company realized that they needed to improve the accuracy of their demand planning and forecasting process.  In the past, planners had created forecast from multiple sources including spreadsheets, manual processes spanning multiple departments, and only a minimal amount of analysis. The resulting forecasts were often inaccurate. A flexible and accurate plan would be critical to stabilizing company’s operations.

The company used contract manufacturers to make all their products and then used its in-house resources for system-builds. Under this business model, they had hundreds of items whose demand needed to be forecasted across many customers around the globe.  These products were configurable and many of these configurations had a very short lifecycle—all creating an immense forecasting complexity.  In addition, many departments within the company did their own planning.  The sales department created their sales forecasts, the finance organization created revenue targets and business plans and the operations department created an operations plan--all with different perspectives and assumptions.  As a result, the plans could not easily reconcile with each other.  Most of these departmental plans were managed on a spreadsheet - hence it was difficult to maintain any consistency and data integrity. 

The planning group within the company had to create consensus demands plans for hundreds of configurable products for ongoing operations planning, while enabling the management team to make more strategic decisions. What would the demand ramp look like in each market? What impact would new market entries have on product mix and profitability? What effect would canceling or delaying a new product have on revenue streams and customer satisfaction?   This situation was clearly a case of high business-value and high complexity in the quadrant chart above.  The company decided to move to a next generation system and selected an Enterprise Performance and Planning system from Steelwedge.

Today with Steelwedge, the company enjoys a number of strategic benefits – as a result of unprecedented market demand visibility they decided to cancel several internal projects and refocus their R&D budget on high growth/high margin market opportunities.  The net result has been a significant improvement in company’s business.  In addition, the company has seen a number of operational benefits including:

• They have cut forecast cycle times and allowed staff to focus more time on analysis and planning.
• They have been able to leverage actual demand forecast (sales pipeline) from their CRM system and incorporate it into their planning process.
• They have gained greater visibility and predictability in their business.
  
  

Case Study 2

A Fortune 500 company in the high tech industry came battered out of the dot com boom. Sales dropped sharply, and demand patterns shifted between product lines. As a result, their mix was off, with excessive inventory for some product lines, and low fill-rates for other lines. Customers were unhappy, revenue projections were off, and profits tumbled, as did their stock price. The company needed change, and fast. Existing spreadsheet-based planning environment that operated in silos was not working. Management realized that in order to turn things around, one of the first things they needed was a better planning system that could tackle these complex business issues:

• Shorter planning cycles – moving from quarterly to monthly planning cycles.
• More agile planning process that would allow for frequent updates and quick turnaround time.
• Improve forecast system to incorporate (1) sales funnel data and (2) dynamically changing product configurations.
• Better visibility into the planning process – at all levels including executive management.
• Exception alerts triggered when forecasts, sales opportunities, actual shipments or backlogs change.
• Effectively include sales and finance in the planning process.
• Better performance measurement.

Based on these requirements, the company needed to migrate to a next generation planning system that quickly created a consensus plan using various inputs from various departments – upgrading to a traditional operations-oriented planning solution was not the right approach.

The company has two major product lines, A and B, with annual revenues of $500 million. Profit margin is 10%, or $50 million. Prior to implementing a next-generation Forecasting and Planning system the two product lines had the following performance:

Product A was over-forecast, and Product B had a low fill-rate and was (consequently) under-forecast. The company had, overall, a planning error (MAPE) of 17-18%.

After 4 months of implementing a next-generation Forecasting and Planning system, the company’s MAPE improved by 2%. This improvement in planning accuracy produced the following results:

• Happier customers.
• Over $500K in reduced annual inventory costs – of which all went to the bottom line.
• Over $5 million per year in increased revenue, of which 10% went to the bottom line.

As a result the company recorded an additional $1 million in increased profits, or a 2% increase in profit margin. Their investment in a next-generation Forecasting and Planning system paid for itself within a few months.

Conclusions

The decision of whether or not to invest in a next-generation Demand Forecasting and Planning System boils down to the following considerations:

• Can the company dramatically improve performance through organizational alignment?
• Would improvements in fill rates bring competitive advantages?
• Do excess inventory costs have a significant impact on the bottom line?
• Is current staffing level required to support manual spreadsheet manipulations and processing too high?
• In comparing different solutions, what issues do different solutions address, and how do they solve them?
• What are the perceived risks and costs of new system
  implementation versus upgrading?

Armed with the above information corporate decision makers should be able to make an informed decision about how to improve Demand Forecasting and Planning.

Footnotes

[1] Demand Forecasting and Planning constitutes all tasks and processes
to collect demand data, project future demand, enable user-interaction with forecasts and plans, perform analysis, measure performance, and publish results to stake-holders – including executive management, sales management, operations management, product management, marketing management, and finance management.

[2] The company, any numbers, and product lines have been altered,
but the general discussion and conclusions remain valid.

About the author:

Dr. J. Thomas Mentzer, Distinguished Professor of Marketing and Logistics at the University of Tennessee is the former President of the Council of Logistics Management (CLM) – a 15,000 member industry organization whose members are primarily executives in the manufacturing and distribution industries.

He is also the author of Sales Forecasting Management, the leading textbook on forecasting, as well as hundreds of papers on the topic of Enterprise Planning. Dr. Mentzer also founded the UTK Sales Forecasting Management Forum, which includes over 100 executives from Fortune 1000 companies such as P&G, Coke, Tellabs, Lucent, Eastman Chemical, and Michelin.