Visibility into Operations, Profits
The right Cost to Serve solution enables you to understand, compare, and analyze cost and profitability at a detailed customer level - plus get insight into cost per customer.
The Challenge: Determining Cost per Delivery
“Right sizing” or identifying the cost of servicing your customers is a challenge because of the struggle to break down route costs per delivery. If you’re still operating under a one-size-fits-all service policy, you may be under-servicing some customers while over-servicing others – and that drives high logistics costs.
The Solution: Cost to Serve Automates Costs with AI & Data Analytics
The ORTEC Cost to Serve solution uses advanced analytics software to accurately and efficiently determine cost allocation while accounting for dozens of customer attributes and extensive historical route data. The solution achieves these results with machine learning to identify delivery cost per customer.
The technology uses customer attributes that impact costs (such as distance to depot, service window, volume, and proximity to market) to break down route cost and allocate per customer.
Key Analytics Elements of the Solution
- Makes use of all available data (routes, cost, characteristics) to determine individual cost to serve
- Advanced analytics to understand cost impact of individual characteristics (proximity, distance, volume, time windows)
- Allocation algorithm to determine individual cost to serve based on impact of individual characteristics and customer contribution to these characteristics
- Similarity algorithm to compare like customers and identify opportunities
The Results
- Understand Profits and Cost Per Delivery/Volume
- Visibility on Route/Customer Outliers
- Effective Decision Making with Operations & Sales
The results from the Cost to Serve model enable you to understand, compare, and analyze cost and profitability on a detailed customer level. For logistics providers, the solution gives accurate insight into the cost per customer, and the profitability can be right sized. Sensitivity analysis on an aggregated level (department / region, group of customers, products) shows the impact of decisions and supports in understanding the effect of frequency, drop size, distance, duration, and capacity on costs and profitability.
The solution can also be used for new customer pricing with measurements such as expected volume and distance to understand estimated cost per delivery / volume and product.
The Specifics
- Pinpoint the areas your sales team can focus on to extend the customer base.
- Guide sales on the effect of specific agreements as delivery frequency and order volumes.
- Support planning and operations on where and how to improve efficiency.
- Learn ways to be more efficient by analyzing comparable regions, routes and customers
The Features
- Understand the ideal number of visits per customer, which reduces overall transportation costs
- Identify the minimum profitable delivery quantity to keep customers profitable for your operation
- Determine the optimal service window to maintain satisfied customers
- Find the best depot for each customer to reduce miles driven and lower costs for each customers
- Identify sales growth regions to expand your business
Companies Are Saving $1M+ in Year 1
Discover more with the Cost to Serve video on right-sizing customers on price and service.
