The Perks of Integrated Business Planning

By  Alliston Ackerman — 05/09/2014

Within the highly competitive branded coffee category, approximately 70 percent to 75 percent of volume is sold on promotion. This is the story of how Massimo Zanetti Beverage USA (MZB) came to effectively use a unified system for trade promotion management (TPM) and predictive forecasting to capitalize on this huge opportunity and further its mission to be the most sought after coffee partner in America.

Promotion-Driven Profitability
Sales of the company’s nationally recognized retail brands, including Chock full o’Nuts, Hills Bros., Segafredo Zanetti, MJB and Chase & Sanborn, secure MZB’s position as one of the top manufacturers of coffee in the United States. However, when on promotion at competitive price points, the company’s brands have been known to hit No. 1 status in New York (Chock full o’Nuts) and Chicago (Hills Bros.).

The company also produces proprietary and private label coffee, tea, and drink mixes for customers in retail and food service channels throughout North America and around the world.

MZB’s competitive position in the consumer market is impressive to say the least when you understand that, for a long while, the company was managing trade promotions using a homegrown system and had no disciplined process for forecasting.  

“During any given month we typically have 250 to 300 promotions running,” says Ron Tieskoetter, vice president Sales Operations Planning & Analysis, MZB. “Due to dynamic market conditions, it is sometimes difficult to accurately predict the amount of cases a retailer may scan for a promotion, which leads to over or under accrual positions. Since trade spend is the second highest liability on our P&L, the resulting reconciliation between actual and accrued spend could swing our overall profitability dramatically.”

Under Tieskoetter’s direction, the implementation of packaged TPM software provided the visibility that MZB needed into its trade spend, at the account and promotion level. In addition, MZB gained the ability to apply deductions at the promotion and account level, and to reconcile accruals. “This enabled us to measure the accuracy of our promotions at the account level,” says Tieskoetter.

The solution appealed to MZB’s Sales and Finance departments based upon its ability to provide visibility to trade spend, as well as forecasting future period trade spend.

Focusing on the Forecast
Forecast accuracy is imperative for a business such as MZB’s wherein 75 percent of its cost of goods sold is dependent upon green coffee commodity pricing.

“Once we had a well-defined trade promotion process, we soon realized we needed a new tool to help us provide better, more accurate long-range forecasts, which would enhance our abilities to take advantage of advantageous commodity market conditions,” says Tieskoetter.

The desired end state — integrated promotion and demand planning — was a tall order that would require process reform, a single, scalable technology platform and rigorous change management.

After evaluating competitive TPM solution offerings in 2011, MZB chose Oracle Demantra Predictive Trade Planning and Deduction Settlement Management modules primarily for the forecast engine capabilities and integration with the company’s ERP system, JDE Enterprise One. Essentially, it would consolidate three critical functions — promotion planning and management, deduction management and an integrated forecast engine — into one system.

At the tail end of the seven-month-long technology implementation came the necessary formation of a Demand Planning department, which began the process of creating metrics for forecast accuracy, coefficient of variance, and an ABC item stratification to coincide with managing inventory and production planning. This department used Oracle Demantra Demand Management, which is directly integrated to the predictive trade planning module to view both the sales forecast of base and lift against the demand planning forecast inclusive of safety stock, lead times, etc., in order to meet the demand driven by the sales organization and trade promotions.

Tieskoetter explains, “Forecast accuracy helped us determine our current base line forecast accuracy and then helped us measure our success moving forward. We used the coefficient of variance metric to determine whether a demand pattern is stable, staying close to its average, or if it is highly erratic. We also used an item ABC stratification, which helped us categorize items into buckets; this allowed us to focus on those ‘A’ items that would have the biggest impact on forecast accuracy first. Utilizing this disciplined approach focusing on the ‘A’ items, in the short term, we were able to increase forecast accuracy quickly and then develop a process to review the ‘B’ and ‘C’ items with the sales team to further improve the overall forecast.”
 
Technology Impacts Process
Armed with actionable data, the S&OP process was improved because MZB could now create forecasts and predictive trade spend plans for the fiscal year to help with financial projections and production planning. During this time, MZB also implemented monthly forecast reviews between the Demand Planning and Sales teams.  

“This allowed Demand Planning to provide key metrics such as forecast accuracy, coefficient of variance and monthly historical trend information to the sales team,” says Tieskoetter. “Through this collaboration we were able to provide guidance and insights, regarding the forecast, to help us improve overall forecast accuracy.”

In order to drive adoption and change in behavior among MZB’s sales force — post training — both forecast accuracy and trade promotion accuracy were adopted as metrics in performance reviews. MZB also measures its brokers utilizing a monthly scorecard that rates their performance related to trade promotion setup and predictive accuracy. These process changes helped to drive acceptance and ownership of the new software and led to improvements in overall forecast and trade promotion forecasted sales and accrual accuracy. For example, trade promotion inaccuracies that lead to imprecise trade accruals and deduction issues were minimized. Thus, the organization changed from a deduction-clearing house to one fully capable of matching deductions to trade promotions and analyzing the deductions.  

Moving forward, MZB’s goal is to create a platform that would contain internal trade promotion information combined with external point-of-sale competitive pricing, promotions and volume data. This, combined with internal marketing programs, would give the organization one place to go for all their needs.

“Having all data sources in one location would allow for easy manipulation and analysis, which would enhance the company’s ability to provide a better, more stable long-term forecast,” predicts Tieskoetter. “Competitive activity could be utilized as a data point to help the forecast algorithms, in Demantra Predictive Trade Planning, to more accurately plan the business.”

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