An elusive calculation
Supply chain teams typically have detailed information about routes, timing and costs but they often struggle to break down the cost at the individual stop level. The cost to serve individual customers is very difficult to determine without advanced mathematics. As a result, most businesses adopt a one-size-fits-all service policy, but this results in high logistics costs.
Nationally Recognized Solution
ORTEC’s Cost to Serve solution was a finalist for Best IT Innovation for 2020 MHI Innovation Award among 155 submissions.
Faster insights, better decisions
ORTEC Cost to Serve uses sophisticated machine learning algorithms (AI) to accurately and efficiently determine cost allocations, taking dozens of customer attributes and extensive historical route data into account. You can consider factors like service window, volume, proximity to market, and distance to depot, among others. Calculations are completed in an instant, helping you understand profits and costs per individual customer and take action quickly. For instance, you can decide to reduce the number of visits per customer, negotiate larger service windows, re-assign customers to different depots, identify the minimum profitable delivery quantity, or increase your sales footprint in a given region.
Save $1 million per year
Sensitivity analyses on an aggregated level (department /region, group of customers or products) enable you to understand how frequency, drop size, distance, duration, and capacity impact costs and profitability. We have seen that these insights result in at least $1 million per year in savings. Companies using ORTEC Cost to Serve see numerous benefits.
Find the right depot, delivery window and volume per customer
Pinpoint areas to extend your customer base or improve SLAs
Visibility and insights that improve collaboration and alignment
Forget time-consuming calculations and gain agility