CBRS - Continuous Benchmark Rate Setting

CBRS: Continuous Benchmark Rate Setting. Business problem: how are the different metrics/ technologies/ operating models/ layout impacting the productivity? Output of the project: develop a model which defines Site-specific Benchmark Rates based on Site’s characteristics. This document will describe (from initial shaping to final deployment) a new methodology for benchmarking AMZL sites’ performance in terms of costs and productivity. The IB CBRS model, Continuous Benchmark Rate Setting model for Inbound, will introduce a quarterly-refreshed benchmark rate for the Inbound core processes in AMZL Delivery Stations (Last Mile Logistics sites). This model is built upon the K-means clustering approach, and it is based on Stations’ layout peculiarities, available technologies, existing processes, and seasonality. The final goal is to ensure global parity when setting rate expectations among the network. To generate BM expectations aligned with stations' characteristics, the CBRS model creates groups of similar stations for benchmarking. To produce the output, we will feed to the algorithm a number of factors: station’s attributes, characteristics and situations that may influence the performance (considered as Non-Controllable by the Operations Managers on site), and numeric KPIs that track the actual performance of the DS (Controllable by OPS). Therefore, sites with similar characteristics, technology and operating models will be clustered together to form a base set of stations for benchmarking, and every cluster of Delivery Stations will have different benchmark goals, which highlight the drivers of regional variances and leverage these differences to continuously improve the network’s operational performance. Additionally, benchmark rates will be refreshed quarterly to continually capture Best-in-Class performances and promote a prescriptive approach towards improvement opportunities, while guiding every DS to collect best practices from similar peers globally. Expected Benefits: • Ensure global parity when setting rate expectations; • Ensure usability of BM rates for operational activities such as labor planning, while meeting global standards of performance; • Enable Operations to improve their productivity by sharing best practices and standard work with peers of the same cluster (with the same operating model, level of automation, package profile...); • Capture improvements through a quarterly refresh of the BM. In order to preserve the company’s confidentiality, in this document we will refer to every AMZL metric by using a different code name, and we will represent data only after concealing it by a corrective factor that will not be disclosed.