How Two Frozen French Fry Manufacturers Increase Margins Despite Wildly Fluctuating Market Conditions

Last week, I shared about the impact that volatile weather patterns have on the supply chain using this year's potato harvest as an example. I also suggest that in order to respond well to that volatility, commodity based companies need proper tools that enable them to make actionable, data-driven business decisions.

Today, I'd like to share the story of how two frozen french fry manufacturers are doing just that.

Case Study: Two Frozen French Fry Manufacturers

In today's digital economy, commodity-based companies are leveraging the power of AI to stay on top of their wildly fluctuating markets. In my role at PROS, I get to witness these stories each and every day.

Two examples of such companies happen to be two of the largest frozen french fry manufacturers in the world. Despite unpredictable weather changes (like this year's cold and wet harvest), commodity costs, supply, and demand, these two companies are using enhanced data analytics to increase margins. 

Commodity-Based Businesses’ Pricing and Selling Pain Points

Given the complexity of their businesses with manufacturing plants, different input costs, varying freight costs, multiple distribution channels, and many supply chain headaches, these two companies had lost control of their pricing and selling processes.

As is common with agriculture operations, these potato manufacturers predominantly struggled to manage margin and trade spend. They found that all of the money they were spending on rebates, promotions, and lump sum programs had gotten out of hand and was putting major pressure on their margins. Additionally, they found it challenging to adequately equip their sales force. Their sales teams were growing exponentially and did not have the data they needed to make the best business decisions, especially when negotiating with customers and operators that all wanted a personalized, discounted cost.

Commodity-Based Businesses Face the Uncertainties of the Crop Year 

On top of those pricing and selling challenges, these french fry manufacturers faced the uncertainties of the crop year. With the harvest coming around November every year, they store these potatoes while they get processed into French fries. Production planning and inventory planning were difficult, especially as substrate comes in different every year — it could have different water content, varying amounts of solids, varying skin (it could be lighter or tougher), and fluctuating costs.

Given these complexities, sales people couldn't keep up — both businesses found that their sales force was too busy to sell. They thought that analysts would help the sales team free up their load, but those analysts spent most of their time collecting data instead of looking back at it, making sense of it, and using it to develop a strategy.

To enable sales to solely focus on maximizing revenue, these two companies came up with a plan to get into the data, compile the information, make better decisions, and implement better pricing discipline.

The Solution

Such a feat is not possible alone, so both french fry manufacturers looked into new and scalable AI-powered solutions for help.

With these data-driven solutions, they are equipped to tackle the fluctuations of their commodity-based businesses.

Here are 5 of the many improvements they've seen:

• Previously, their sales people had too much flexibility to write sales contracts. Additionally, multiple versions impacted the communications flow. Today, they have a seamless integration that allows them to respond to quotes with an optimal price quickly and without errors.
• Managing price lists and making updates was one of the biggest headaches. Today, they manage all price lists, price updates, and changes to price guidance based on market and competitive conditions in real-time, all within a modern, fully integrated solution. This means that if costs go up because of a shortage in supply, the companies rest assured their prices are adjusted and optimized across all channels, immediately.
• Because of many manual overrides, senior management had to review every single deal. Today, the sales team has 'guard rails' for every negotiation based on the customer's willingness to pay.
• Delivering prices to the field was chaotic and ineffective. Today, they have a strong automated mechanism that delivers pricing guidance (not a mandate) backed up by all the data they need to support those recommendations.
• Because of the complexities of selling commodities, sales did not feel confident about the prices they were offering or the opportunities they were pursuing. Today, they have access to a tool within their CRM that shows them transactional information and sales recommendations. This data builds on their confidence and allows them to grow and understand pricing and selling in a much better way.

Closing Thoughts

Overall, through these AI-powered solutions, these potato product manufacturers now deliver smarter pricing and faster quotations as an iterative and sustainable way to drive value.

Despite wildly fluctuating market conditions, they rest assured they can continue to increase margins and stay on top of the competition.

And now, what about you? How have you seen AI transform the way commodity based businesses do business?

I'd love to learn more.