How to maximize the value of your dairy production assets with demand hunting

Dairy Demand Hunting with Austin Data Labs

It’s one thing to identify the opportunities for higher returns across your dairy supply chain but then the challenge becomes how to operationalize that across your business to capture these higher returns. This idea builds on my colleague Robbie Turner’s recent white paper on dairy optimization and his recent blog post about the impact of breakeven and scenario analysis on the diary supply chain. Demand hunting can help solve this.

When you find your dairy company in the frustrating position where you can see that certain products are returning higher than your current product mix, and you have the production capacity and available milk solids but lack additional demand to sell this product into, you need a process in place for demand hunting. 

There are a number of factors that limit your business’s ability to capture higher returns:

  • Insufficient demand over and above regular sales
  • Lack of clarity by the sales team on what is returning the most
  • Misaligned incentives

The question then becomes: “How  do I overcome these issues to drive the right behavior and capture higher profits for my shareholders?”

Robbie outlined a scenario where whole milk powder (WMP) was returning higher than skim milk power (SMP)/butter stream. In this example, to capture more value you would ideally reduce the production of SMP/butter and reallocate those milk solids to WMP, then sell that WMP. What happens if you don’t have enough WMP demand for this, or demand isn’t at the price at which you are selling the rest of your WMP?

What I have seen work well is a simple report that you send out to the sales team at the end of each planning cycle that outlines the opportunity to sell more of your higher returning products. This report would include:

  • The volume of product available
  • In which months it is available for shipment/sale
  • How much the price could be reduced to facilitate the sale (based on the break even price) 

An example of what this report might look like in figure 1:

Figure 1: what demand hunting might look like in a spreadsheet
(to see what it looks like in our product, ask for a demo)

By doing this you provide the clarity the sales team needs regarding what  can be sold, when, and how much leeway they have to sell these products while still returning higher than the next best alternative. The sales team can then take this information and have conversations with customers that buy these products from other suppliers. It is important to monetize this, as well, to help the wider organization understand the value on the table. For this example the total incremental value ~USD $24M is shown at the bottom of the report 

We have built this functionality into one of our standard dashboards in the Austin Data Labs scAIcloud™ platform, meaning this information can be provided automatically to sales people via login or sent out as scheduled report.

Want to hear more from Robbie and Hamish on the dairy supply chain?

Join their webinar on September 30, 2021! Sign up here to get the link.

Share on linkedin
Share on twitter
Share on whatsapp
Share on reddit
Share on pocket
Share on mix
Share on email
Share on facebook