Successfully managing cost volatility has a material impact on customer satisfaction, sales team satisfaction, and profitability. That’s why it’s imperative to solve this challenge in a way that effectively serves all constituents, as the author explains. Dallas Crawford is an Advanced Analytics enthusiast and executive at SKYSHEEP with over 15 years of experience helping companies leverage data-driven insights to empower their teams and maximize operational results. Prior to Co-founding SKYSHEEP, he spent several years gathering the uniquely diversified experience of leading Sales, Consulting, and Product Development teams through periods of substantial growth and client execution.  He can be reached at dallas@skysheepdata.com.

The Pricing Advisor, August 2022

Distributors across a multitude of industries have faced cost volatility challenges for decades. A prime example is the Food Service industry, which often experiences daily cost fluctuations driven by a myriad of issues associated with underlying commodities. Sometimes yield suffers due to weather or climate changes, natural disasters, spikes in transportation costs, or emerging labor shortages. The pandemic and current inflationary environment have certainly exacerbated the management challenge for distributors, but this is an issue that will persist as commodities continue to shift.

Successfully managing this volatility has a material impact on customer satisfaction, sales team satisfaction, and profitability. That’s why it’s imperative to solve this challenge in a way that effectively serves all constituents. This requires:

• An approach that will not frustrate your sales force, who lives on the front lines ensuring customers are happy with your services,
• A system that provides customers with stable pricing in line with existing market conditions,
• And, equally important, a method that will deliver substantial improvements to top-line revenue and bottom-line margin.

Aligning pricing to market expectations

Food Service is a people business.  Most sales reps in the industry maintain tight relationships with their customers and have a high sense of account ownership and pricing accountability.  This is especially true for specialty distributors, given the narrower portfolio they often carry and the higher level of effort to penetrate vs. broadliners.  Presenting credible prices is critically important to them, regardless of any macro or micro issues faced by the company.  This requires pricing to be hyper-relevant to several attributes including but not limited to customer size, buying behavior, purchase frequency, and geographic location.

While working to achieve internal growth objectives, reps must manage customer sensitivity and market volatility on a product-by-product basis to ensure customer satisfaction.

With an average salesperson responsible for hundreds of customers that cover potentially tens of thousands of products, it is virtually impossible for each customer/product relationship to be adequately considered.  There are simply too many variables and nuances for even the most diligent salesperson. Amidst external pricing pressure, this balancing act can become unbearable, forcing them to overmanage their portfolio or underprice their products.

Enabling the sales force with insight and automation 

Traditionally, Food Service distributors have attempted to help their sales teams by providing price guidance in the form of margin/bracket recommendations, volume guidance, or “average price” figures. As the following survey responses demonstrate, this kind of high-level guidance has not been firmly embraced by sales teams (only 6% feel “completely confident” in current company-provided price guidance):

Sales team responses to a survey on confidence in existing pricing methodology:

Given the abundance of factors that must be considered to provide meaningful pricing, it is crucial to augment the sales team’s detailed account-level insight with a data-driven system that considers all key purchase decision factors in a trusted manner.

Utilizing sophisticated Artificial Intelligence (AI) and Machine Learning against existing data (typically gleaned from several disparate data sources), predictive pricing can be developed to provide overwhelmed reps with customer/item-specific recommendations. These predictive systems learn from detailed historical customer/item buying behaviors and apply them at scale to recommend the optimal price point for any item by customer.

Accounting for current costs and market conditions in conjunction with this granular sales history enables hyper-targeted price recommendations to be delivered.  Effectively treating millions of individual product/customer intersections with the same level of interest that is normally applied to only the most visible combinations.

These systems also deliver a level of automation that allows this process to run on a schedule at any frequency. For example, many distributors reprice weekly, while having flexibility to adjust some customers twice weekly and others that are limited to contracted agreement periods. Automated schedules specific to each subset or grouping is critical to executing at this scale and inherent in these systems.

Impact of data-driven price guidance

In addition to delivering smarter and more relevant pricing, price guidance systems also automate administrative tasks that help busy teams reclaim substantial time. This allows salespeople to focus on what they do best: managing relationships, placing new items, and growing their overall base.