# Is Center-of-Gravity Analysis an Appropriate Method When Designing Distribution Networks?

**Distribution network design** was initially conducted on Lotus 1-2-3, the spreadsheets of that time, as there were relatively low processor capabilities and no supply chain-focused modeling software available in the early 1990s when it first started being done digitally. Over time, spreadsheets evolved to become more sophisticated, like Excel, but those wishing to address network design with more sophisticated analytical methods turned to Center-of-Gravity Analysis when deciding where to locate distribution centers.

*Finding the pivot point to balance weights on a seesaw is a center of gravity calculation.*

Center-of-Gravity (COG) analysis, developed based on mathematical formulas, involves a simple method we learned in high school physics. If you want to balance a stick on your index finger, you try to find the point where the stick’s weight is evenly distributed to the two ends of your finger. This point is called the “center of gravity” and can be calculated with simple algebraic operations.

So what does this physics principle mean for **distribution network design**? While the answer varies depending on your network design, we can use the same mathematical equations to find the center of gravity of demand, for example, distances (in kilometers) from the points of origin of demand and the magnitude of the demand (such as the quantity of boxes, pallets, or packages). It’s no different from balancing a seesaw. This approach might seem very competent as it is based on a familiar physics rule and formulas. Let’s explore when it is competent and when it falls short together.

**Instances where Center-of-Gravity (COG) analysis is beneficial for Distribution Network Design:**

In Direct Store Delivery Networks, with multi-stop routes delivering to many customers in the same region, you can use the center of gravity to minimize distances to delivery points by accepting a small margin of error when finding a warehouse location, as the last-mile delivery cost is the largest component of the supply chain in this structure.

When optimizing a network spread across a broad geography (e.g., a national distribution network) and the system requires additional warehouses, potential candidate locations are pre-determined for new facilities. A center of gravity study can be conducted to identify these candidate locations. Subsequent optimization work will identify the distribution centers that need to be opened by choosing among these candidate locations.

For distribution operations with a single warehouse, there is no need to invest in sophisticated optimization software or set up an analyst team for such work. In other words, if a quick Center-of-Gravity Analysis suggests a location in Sancaktepe while a sophisticated software suggests Gebze, the difference might not be significant.

**The Pitfalls of Relying Solely on Center-of-Gravity Analysis When Designing Distribution Networks:**

Center-of-Gravity (COG) analysis only considers the magnitude of demand and distances to the demand points. This means it overlooks cross-hauls between suppliers and warehouses, as well as between facilities. From our experience, the costs of these “in-network flows” can sometimes exceed distribution costs when selecting distribution center locations. While you may have minimized the costs of last-mile logistics with Center-of-Gravity Analysis, if you have a network with intensive initial and intermediate transportation, your solution may not reduce the total supply chain cost; it might even increase it.

Distances are calculated as the crow flies in Center-of-Gravity (COG) calculations. This means the actual road distance, accounting for highways, mountains, or other geographical barriers, is not considered.

Transportation costs vary for each direction due to reasons like regional differences and lack of backhaul. For example, freight rates per kilometer between Istanbul and Izmir may differ from those between Izmir and Konya. Another cost element affecting the results is that the minimum price limit of the carrier cannot be considered in Center-of-Gravity Analysis.

Many logistic constraints commonly encountered in the real world cannot be accounted for in Center-of-Gravity Analysis. However, these constraints are critical components of finding an optimal **distribution network design**. For example, storage and production capacity constraints, storage conditions (ambient and frozen products), and delivery time limits must be considered simultaneously in an optimization study.

Transportation modes are one of the things neglected in Center-of-Gravity Analysis. Therefore, for customers who deliver their shipments using mixed shipping modes such as cargo, LTL (less-than-truckload), and FTL (full truckload), different pricing rules are required. For a mixed-mode **distribution network design**, transportation costs per kilogram or kilometer need to be differentiated and considered by the optimization.

*We design our customers’ networks using the most powerful optimization software and correct methods.*

In summary, Center-of-Gravity (COG) Analysis will provide you with a very narrow perspective when designing a **distribution network**. Since COG analysis is popular due to its simplicity, many supply chain managers still believe it is the only option available for network optimization. However, based on our experience, we can confidently say that relying solely on decisions made through COG analysis for **distribution network design** will likely result in a flawed design. By doing so, you will miss the opportunity to fundamentally reduce your total supply chain costs.

Center-of-Gravity Analysis and Network Optimization are not the same thing. Center-of-Gravity analysis produces much weaker results compared to the gains obtained from a full-fledged network optimization study.