Introduction Supply Chain Case Study
A worldwide leader in medical technologies and innovations needed to improve its entire logistical process, to ensure the optimal customer experience and to minimize waste in the delivery services.
The company is present in most countries across the world and needs to send parcels with goods from centralized international manufacturing sites and warehouses. Therefore, the logistics team needs to use many and different carriers. Due to the nature of their business, these deliveries are extremely time-sensitive, and permissible deadlines need to be kept at all costs. However, because of the different systems used by the carriers, the process of gathering data from them was mostly manual and the data was not standardized. As a result, it was hard to optimally assess their performance and calculate losses due to damages and delays. Moreover, the company also was not able to unify the service-level agreement (SLA) that is to be required from carriers, as such analysis was only possible on a regional level.
Use Case:
- Global sales presence
- Using multiple carriers with different data gathering systems
- Inefficient data gathering from the carriers
- Orders and carriers not optimally processed
The Challenges:
- Differences in the CRM interfaces from carrier to carrier
- Inability to collect data from disparate carriers’ systems
- Complexities of the client’s ERP system
- Lacking vital data for assessing the carriers’ service levels
Solution:
- Introducing a unified criteria list to be used by all carriers
- Enabling automatic gathering of carrier information
- Introducing and calculating “On time” and “In full” KPIs
- Calculating the service-level agreement (SLA) delay
The Challenges Before
Us One of the significant challenges of the project was that having many carriers, resulted in many data sources. Furthermore, each of the carriers has a different CRM interface with its specifics on how the information is tracked and provided to their customers, making the gathered data very different in format and analysis potential. Additionally, there was a varying frequency of data export capabilities.
The different carriers’ CRM interfaces had various mismatches between their booking procedures and the client’s ERP interface. The incoherent nature of the systems made the automation of data collection impossible for our client and they had to do it manually, resulting in many man-hours lost. There was also a high possibility of human errors while manually booking in the ERP system. The complexity of our client’s ERP system represented a further challenge from data transfer point of view, all causing delays in reporting of performance analysis.
The lack of reliable data to fully assess the performance of each carrier as well as the end-client experience had provoked the use of the Line Level Fill Rate (LLFR) model, which had a gap in tracking actual customer experience and satisfaction as it omitted several essential variables such as the exact number of items delivered to the end-client.
The Solution
Instrumental to the success of the project was the close work with the client. Our deep understanding of their supply chain process allowed us to suggest a thorough unified checklist of data required from each carrier. Thereafter, we facilitated the communication between business and technical teams, both within the client’s structure and the various carriers to make checklist data provisioning possible. We provided the technical expertise to overcome the challenge with multiple systems with different interfaces to derive the final unified data set. A clear understanding of the business needs allowing us to design it in a way that will lay down the foundation for future more advanced analytics based on the acquired data.
Our team created an automated interface that will continue to feed hourly data, thus eliminating the need for manual data handling and transformations. The data is fed into a reusable data model, which can be seamlessly integrated with other CRM and ERP data and within new complementary applications, drastically reducing future development cycles.
All this allowed our customer to switch to a new model of reporting – On Time and In Full (OTIF), which, unlike the LLFR, considers the delivery time as well as the quality of the received parcel (in full, goods condition, etc.). To keep track of the OTIF metrics, we created an easy-to-use application, which provides the management team with a one-stop source of data for the whole logistical process, to identify areas of improvement and optimization. This, in turn, allows them to conduct far superior analyses of the used delivery services and their providers.
Conclusion
As a result of the proposed innovations, our client has managed to optimize their entire logistical process, making it more precise and efficient. They can quickly collect data from each of their carrier service providers and assess their performance. Furthermore, based on the collected data and the OTIF model, our client can easily perform even more in-depth analyses in the future.
