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Nestlé USA Applies Optimization Models to Save on Transportation and Production Costs

“Using advanced analytics to manage the supply chain and reduce costs has become imperative. FICO Optimization has been critical to supporting the optimization needs at Nestlé USA.” Shan Collins, Vice President of Planning and Center of Excellence with Nestlé USA’s Supply Chain

Nestlé USA has achieved exceptional benefits by applying FICO® Xpress Optimization to production planning and load building:

  • Delivered significant savings by maximizing payload and minimizing transportation costs
  • Reduced production plant costs
  • Increased sales by reducing the number of product shortages in each distribution
  • Increased customer satisfaction scores by consistently meeting service level agreements
  • Reduced losses by avoiding product scrapping 

Client: Nestlé USA Challenge: Reduce production and transportation costs Solution: FICO® Xpress Optimization Results: By developing several optimization models targeted at production planning and load building, Nestlé has delivered significant savings in transportation costs and has significantly reduced production plant costs.

Using advanced technology to gain efficiency and reduce costs

Nestlé USA, is part of Nestlé S.A. in Vevey, Switzerland — the world’s largest food company, which is not only committed to being a successful leader in nutrition, health and wellness, but also in gaining efficiencies. The company is dedicated to adopting more efficient technologies and processes. One of the ways Nestlé USA is doing this is through its Supply Chain Optimization team. This group of analytics experts is applying machine learning, statistical models and prescriptive models to completely change the way the company does business. “Nestlé USA is an innovative and forward-thinking company,” says Bhanu Gummala, Director of Advanced Analytics at Nestlé USA. “Our leadership team has a vision for relying on advanced technology to find ways to reduce the resources we use and to find efficiencies throughout all of our internal processes. The optimization models we have applied have changed the whole paradigm of the supply chain.”

Load building optimization delivers significant savings in transportation costs

Nestlé USA produces food and beverage products in production facilities around the United States with limited or no storage. The items are shipped to six distribution centers around the country to be stored and then delivered to resellers. Supply chain managers must ensure that each distribution center is receiving the right type and amount of product it needs in order to meet service level agreements and maintain high customer satisfaction. 

In addition, the supply chain managers must manage transportation costs. They do this through a payload management process that maximizes load utilization, thereby minimizing the cost of transportation. If a load reaches maximum weight but there is still space available in the trailer, then the payload has not been well managed and the company will need more loads to move the same quantity, resulting in more cost. When a load is close to the maximum cube and the maximum weight, it is considered to have optimal payload. Nestlé USA needed to develop a reliable way to maximize its payloads and minimize transportation costs. The problem is extremely complex. “Nestlé USA has 64 brands with numerous products within each brand. Each product has a unique weight and volume to be considered for shipment and can be sent to one of six distribution centers. Add in demand forecasts and current supply levels and you have a very difficult problem to solve,” says Robert Wang, Principal Supply Chain Optimization at Nestlé USA.

The Supply Chain Optimization team at Nestlé USA used FICO® Xpress Optimization to create a load builder optimization model. From the millions of possibilities, the model calculates the very best shipment combinations to arrive at a set of maximally balanced payloads for each individual load shipping from every plant. “We have had this model in operation for the past seven years and it has been incredibly effective,” says Wang. “Nestlé USA has significantly reduced its transportation costs because of our load building model.”

Taking it further: optimizing redeployment In addition to standard load building, Nestlé USA is also using FICO® Xpress Optimization to optimize redeployment of inventory from one distribution center to another. Even when payload shipments are managed effectively, there are times when inventory needs to be moved around either because it wasn’t deployed correctly the first time or because the demand forecast was off. When there is an imbalance, the supply chain team must redeploy from one distribution center to another. This payload process is even more complex than one coming from the production facility. Nestlé USA has developed a separate algorithm with Xpress to determine what product to move, when and from which distribution center.

Taking it further: engaging customers in the process Nestlé USA used its FICO® Xpress Optimization load building model to develop an application for some of its largest customers to help manage payload. Nestlé USA communicates the load details to the customer, and the customer accesses the application to fill the truck optimally from their perspective. This transparency has led to increased customer engagement, good collaboration and reduced costs for Nestlé USA, its customers and their end customers.

FICO® Xpress Optimization provides power and flexibility

The Supply Chain Optimization team at Nestlé USA is composed of 12 experts focused on business intelligence and analytics. The team uses a variety of optimization tools depending on the preference of the expert and the problem the team is trying to solve. The team turns to FICO Xpress Optimization for:

  • Flexibility to automatically recalibrate parameters. Being able to make changes to models immediately is extremely important, and implementing changes in minutes instead of months can have a big impact on profitability.
  • Sophisticated modeling language, Xpress-Mosel programming language, provides an easy-to-learn, robust way to interact with Xpress solver engines.
  • Powerful solvers help model with greater accuracy and solve highly complex problems. A wide array of sophisticated, robust optimization algorithms can solve large-scale linear problems and mixed integer problems as well as non-linear problems.
  • Scenario planning allows business users to carry out what-if analysis and to understand dependencies and sensitivities within the problem. “FICO Xpress Optimization is very sophisticated. It comes with a wealth of features and functionality,” says Gummala. “For us, it’s a one-stop-shop. The FICO tool has a lot of flexibility and will do everything we need.”

Rethinking your supply chain processes can fundamentally transform your business. Learn more at

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