Location Analytics in Supply Chain: Network Optimization and Design

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Due to a rise in consumer demand, national supply chain shortages are becoming more prevalent across a wide range of industries. What do organizations need to do to meet unexpected changes in consumer demand? They need to invest in location analytics for supply chain network optimization.

Site Selection Analytics for Supply Chain Networks

Site selection for factories, manufacturing plants, and distribution centers can be challenging, especially with the current shifts within the commercial real estate market. Consumer behavior patterns, population, and transportability are some factors to consider when organizations are in the middle of site selection.

With location analytics, organizations can determine the best site for a warehouse or distribution center based on consumer behavior and business activity in locations of interest. It can also help determine if there is enough activity to be able to hire the right number of employees.

For example, a distributor is trying to find the right location for their primary distribution center and has narrowed their search down to two locations.

  • One location has easy access to major highways but is located on the outskirts of a relatively small town.
  • The other location is in the middle of a heavily populated urban area but transport access is more difficult.

After comparing foot traffic data for their areas of interest, the distributor decides to move forward with the first location. Although the town is small, the people who live there are newer transplants and more likely to be on the market for a job, an important factor, given recent staffing shortages. Foot traffic analytics shows less congestion in the small town. The urban area’s foot traffic revealed more congestion and less opportunity to easily reach customers.wed more congestion and less opportunity to easily reach target customers.

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Predicting Surges in Consumer Demand

Organizations can use insights from enterprise location intelligence to understand consumer behavior in the real world. Because of this, predicting surges in consumer demand becomes much easier. Using Starbucks as an example, let’s consider how location analytics could be used to improve the efficiency of its supply chain network.

In 2021, Starbucks experienced an oat milk shortage as well as a shortage of other items like coffee syrup and plasticware. With location analytics, Starbucks would be able to get visibility into their supplier’s activities related to employee and truck traffic at warehouses. This information along with identifying changes in trade areas over time can help Starbucks revisit its supply chain network. The Seattle-based coffee chain can then allocate resources to the suppliers that need to prepare for shifts in consumer demand and fluctuations in inventory.

Starbucks would be able to predict expected surges in demand before they happen and adjust its supply chain strategy when a particular ingredient isn’t available. As a result, they can better prepare their suppliers for demand related to upcoming seasonal drinks.

Supply Chain Network Optimization with Location Analytics

Location analytics can provide companies with information on which facilities will work best for an effective supply chain. Imagine being able to map out all of the facets of the warehouses, distribution centers, and deliveries according to supply and demand, or being able to predict constraints within a supply chain network design before implementing it.

These insights can also help organizations optimize their supply chain network designs. With the right data solution in place, organizations can prepare partners for increased demand and ensure that they are ready to address anomalies within their supply chains. To learn more, book a meeting with us today.


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