Location Analytics in Supply Chain: Network Optimization and Design
August 10, 2021
The return of shopping and dining in 2021 comes with an unprecedented hurdle: national supply shortages. The recent changes in the supply chain have National supply chain shortages are emerging across many different industries due to an increase in consumer demand. What do organizations need to do to meet this unexpected increase in consumer demand? They’ll 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 real estate market. Consumer behavior patterns, population, and transportability are some factors to consider when organizations 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.
Predict Surges in Consumer Demand
Organizations can use insights from location intelligence to understand consumer behavior in the real world. Because of this, predicting surges in consumer demand becomes much easier. Let’s take a look at an example: how Starbucks could use location analytics to optimize its supply chain network.
Starbucks is currently experiencing an oat milk shortage as well as a shortage of other items like coffee syrup and plasticware. With location intelligence, 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.
Using Analytics for Supply Chain Network Optimization
No one can accurately predict the weather or when there will be an unexpected event that disrupts the supply chain, but using the right data can help. There are external and internal factors that impact supply chain design.
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.
Location intelligence can 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 react to anomalies in their supply chains.