Supply Chain Planning Trade-Offs: A Success Story in the Snack Food Industry

     

A River Logic customer was unable to meet demand for their most profitable product because they were working with constrained capacity. They had no visibility into their supply chain planning trade-offs, were wrangling 20+ spreadsheets to create plans, and missing out on major profit opportunities. Since adopting River Logic, hundreds of thousands in cost savings per week have been uncovered.

A Customer Success Story

We all know that tough trade-off decisions exist across supply chains. At River Logic, we see this all the time. One of our customers, a U.S. snack food-giant, was meeting less than 90% of demand for one of its most profitable product portfolio categories — let’s call it Product Family A. To produce products within product family A, two of the steps in their manufacturing process had limitations:

  1. They could only ever get 35% of their raw material into the appropriate shape to produce the products in Family A
  2. They also had to slow down one of the steps in their manufacturing process to further process Family A  

With over 20 plants and several hundred processing and packaging lines, the company was doing what most other manufacturers do: using gut feel and 20+ spreadsheets to determine where to produce which products, with no visibility into the forward-looking financial impacts of their decisions. In addition to spreadsheets, they used a solution suite from a major ERP vendor, a point optimization solution, and a well-known network design tool. Their assumption was that transportation costs would outweigh producing only certain products at certain plants. Therefore, the company had decided to make every product at every plant in order to try and meet demand for Product Family A.

Like more than 50% of companies today, the problem with this approach is that corporations have limited or no ability to measure cross-functional trade-offs. For complex supply chains operating in a dynamic market, the inability to access intelligent data impedes insights to the best courses of action. Even more so, actions aren’t tied to financial impacts and companies end up under-performing in the long run. In the case of our snack-food giant, they were driving up costs, unable to relieve constrained capacity, and failing to meet demand; thus, they were missing out on major profits.

Using Spreadsheets to Balance Supply Chain Planning Trade-offs

With over 20 plants and roughly 20+ spreadsheets that contain data from sourcing, production, finance, sales, and transportation, it’s easy to see that finding where to make certain trade-offs in order to meet demand was impossible for them. According to Ventana Research, this snack food company is not alone in its planning dilemma. In Ventana’s recent report, Supply Chain Planning with Prescriptive Analytics, it states that almost 80% of companies use spreadsheets for supply chain planning. For one-off scenarios and prototyping, spreadsheets work well. However, when it comes to everyday dynamics, spreadsheets are error-prone, difficult to validate, and inflexible to use for collaboration. The research also shows that over 50% of supply chain planners say spreadsheets make their jobs more difficult!

Furthermore, spreadsheets enforce silos and are unable to respect cross-functional trade-offs, as we saw in our snack-food guru. To understand how and where to make which products, they needed two things:

  1. They needed to understand, on a per product level, the impact of everything from raw material to distribution
  2. They needed to see forward-looking financial impacts of their operational decisions, i.e., they needed an integrated financial and operational model of supply chain. 

An Intelligent Model Powered by Prescriptive Analytics for Supply Chain Planning Trade-offs

Supply chain companies acknowledge that spreadsheets make it too difficult to detect the trade-offs needed to meet objectives. It is why Ventana’s research states, “A dedicated planning application that uses prescriptive analytics can give managers and executives the ability to assess trade-offs with greater insight and precision, especially if the analysis incorporates financial data.” 

This is exactly the advice that our snack-food giant decided to take, and they finally found what they were looking for in our prescriptive analytics solution. With an end-to-end (supplier to distribution) Intelligent model fed data from their existing spreadsheets, ERP, etc., they could finally see the financial and operational impacts of trade-offs across their value chain.

With a fully validated financial and operational model, they could balance:

  • Production capability complexity
  • Demand complexity
  • Cost of goods complexity
  • Transportation variations
  • And more…

The Value of Prescriptive Analytics in Making Tough Trade-off Decisions

With their Intelligent Model, powered by prescriptive analytics, our snack-food giant was able to allocate the right demand to the right location at fewer overall hours than before! It ended up being more profitable to reduce material and transportation costs while increasing the number of changeovers across their nationwide network. They found hundreds of thousands in cost savings per week, in addition to huge opportunity costs due to freed up inventory. The hard savings were unmatched by any other tool they had been using:

  • Transportation costs were also reduced because the Intelligent Model chose to make certain products closer to the point of sale.
  • Throughput rates were increased, thus leading to more demand being filled because the Intelligent Model found that increasing the number of changeovers across the entire network was more profitable.
  • The model reduced overall labor costs by reducing production hours.
  • Through collaborative planning and insights from the model, the company was able to produce to demand rather than keep inventory. The model could then help them determine how to best utilize the free inventory.
  • The overall raw material purchase and variable costs also went down because the Intelligent Model was able to account for the variation of these costs across different plants.

Closing Remarks

Although our customer is a major, globally known supply chain manufacturer, they suffered from the same challenges that companies of all sizes and complexities suffer. Supply chains don’t need to be global giants in order to take advantage of this type of technology. In fact, sometimes it’s easier if a company is less advanced because they have fewer systems to wrangle. The fact is, companies won’t know until they ask. For this reason, River Logic offers FREE assessments that can help determine if your company is ready to take the next step in its planning journey.

Don’t wait until all your competitors have already started — request your free assessment today.

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