Supply Chain Trends and Issues : Our Weekly Feature Article on Important Trends and Developments in Supply Chain Strategy, Research, Best Practices, Technology and Other Supply Chain and Logistics Issues  
 
 
  - July 22, 2008 -  

Supply Chain News: Improved Internal and External Collaboration Key to Improved Forecasting Results

 
 

Getting There Doesn’t Just Happen – Seven Tips for Making it Work

 
 

 

SCDigest Editorial Staff

SCDigest Says:
Some companies spend too much time trying to improve forecast accuracy on products that aren’t big drivers of sales and profits.

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Across the globe, companies are working hard to improve forecasting processes. But progress is often slow, because so many factors are working today to make demand planning more challenging than ever. Those challenges include SKU proliferation, shorter product lifecycles, global market coverage, reduced customer loyalty, channel complexity, etc.

In a recent column for the Wall Street Journal, Dr. Chaman Jain of St John’s University and Mark Covas of Procter & Gamble offer seven keys to achieving improved forecasting results, with a big focus on collaboration, as we summarize below.

1. Get Senior Executives Involved: No surprise here, as this tops every list of key success factors for everything. One smart idea, however, is to quantify the financial impact of even a 1 percent point increase in forecasting accuracy – or a 10-point improvement.  That can quickly get CEO, COO or CFO attention.

2. Explain the Mutual Benefits: True internal or external collaboration will almost always be impossible unless the other parties can also see what’s in it for them, which forecasting managers too often forget. Ocean Spray managers, for example, obtained much greater input from Sales in the forecasting process after they explained how that effort would result in improved inventory planning and fewer stocks outs – which cost the sales people commission and could put an entire account at risk.

3. Clearly Define Goals and Agreements: Efforts to improve forecasting will falter if the better demand plans can’t be translated into clear bottom line benefits. Procter & Gamble, for example, focuses on inventory management, both within the company and at the store level in terms of stock outs. It is important to get input on these metrics and the targeted goals from multiple areas of the company, Jain and Covas say, both obtain a 360-degree view of the issues and to ensure expectations of what improved forecasting can achieve are realistically set.

Setting those metrics and goals can be even harder with trading partners – meaning the effort to define those plans is even more important. Jones Apparel, for example, has several different levels of “collaboration” with retailers, which involve distinct levels of collaboration and information sharing.

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  4. Use the Best Technology: “Companies should use state-of-the-art technology and standardized data if they're going to get the most out of collaborative forecasting,” Jain and Covas say. While many companies have already invested in such tools, many others have not on the demand or supply side. Jain and Covas also expect even more smarts to come to market from demand planning technology providers in terms of “what if” scenario analysis.

5. Focus where Revenue and Profit are Greatest: Some companies spend too much time trying to improve forecast accuracy on products that aren’t big drivers of sales and profits. An “ABC” type categorization of SKUs is critical, with the preponderance of time and effort targeted towards the A’s. This is the approach chemical maker BASF took, with outstanding results.

6. Link Incentives to Company Wide Goals: Metrics can often unintentionally sabotage forecasting improvement efforts. Jain and Covas say it is often smart to use company wide goals, such as revenue and profit, rather than localized ones, to drive behavior.

7. Aim for Continuous Improvement: In some cases, initial success in improved forecasting can later stall. It’s important to track actual results against the forecast in each forecast period and look for issues and problems – as well as the opportunity to improve. Importantly, well document any changes to the process that occur over time, and see whether they improve forecast accuracy – or make it worse.

“Many companies pursue collaborative forecasting in ways that limit its effectiveness, if they pursue it at all. In some cases, not enough departments are involved, while in others, planning meetings aren't held regularly, or support from management is lukewarm at best,” Jain and Covas say.

What would you add to this list of tips for improved forecasting success, especially in terms of getting more internal and external collaboration in the process? Let us know your thoughts at the Feedback button below.

 
     
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