The Customer
McKesson is a leading healthcare services company that distributes pharmaceuticals, provides health information technology, and offers medical supplies, playing a pivotal role in advancing healthcare outcomes globally.ShareExportRewrite
The Project
McKesson Case Study: Deployment Automation and Confluent Setup
Overview
Improving embarked on a successful project with McKesson. With the aim of deploying an automated solution for McKesson's Drug Serialization Repository (DSR) system across 29 distribution centers, the Improving team leveraged technologies like GitHub, Kubernetes, Confluent Kafka, and MongoDB to significantly reduce deployment time.
The Business Problem
McKesson was faced with the challenge of complying with the Drug Supply Chain Security Act (DSCSA), which mandates full tracking of drug shipments from reception to destination. McKesson’s initial manual deployment process for their DSR system was time-consuming and inefficient, taking between four and six hours per location. This made it difficult to meet the DSCSA regulatory compliance deadline.
The Solution
Improving brought to the table an expertise in automation, collaborating with Tata Consulting Services, VMware, MongoDB, and Confluent. We worked closely with the McKesson team to understand the intricacies of the DSR application and its dependencies, including MongoDB and Confluent Kafka. Utilizing various tools such as GitHub actions, batch scripts, helm charts, and Kubernetes automation tools, we automated the deployment process of the solution for each of the distribution centers.
Technologies Used
GitHub: Utilized for deployment repository and GitHub actions for automation.
Kubernetes: Used for automating deployment, scaling, and management of applications.
Confluent Kafka: Facilitated the real-time movement of data within the systems.
MongoDB: Chosen for its scalable database capabilities and was configured to work best with the DSR application.
VMware Tanzu: Used as the platform for the Kubernetes on-prem servers.
The Business Benefits
Efficiency: The deployment time was reduced from hours to approximately 33 minutes.
Scalability: The automated deployment process could be efficiently replicated across all 29 distribution centers.
Regulatory Compliance: The automated deployment process helped McKesson meet the DSCSA regulatory compliance deadline.
Business Continuity: The solution assured uninterrupted services at McKesson's distribution centers.
Partnerships
Improving collaborated with Tata Consulting Services, McKesson's corporate business unit for pharma, the executive team for the McKesson distribution centers, MongoDB for database configuration, Confluent Kafka for real-time data movement, and the VMware Broadcom team for Kubernetes cluster deployment.
Lessons Learned
Business Decisions Influence Technical Choices: McKesson's decision to deploy physical clusters at each location influenced the choice of tools and technologies.
Automation Efficiency: Significant efficiency gains can be made through process automation, reducing time and potential for errors.
Collaboration is Key: Successful execution of the project required close collaboration with several teams and partners.
Conclusion
This case study illustrates Improving's commitment to providing efficient and effective solutions to complex business problems. Our collaborative approach, technological expertise, and commitment to understanding our client's needs enabled us to deliver a scalable, automated solution that helped McKesson meet critical regulatory deadlines. Our ability to adapt to the client's chosen technologies and effectively utilize these tools underscores our versatility and dedication to client success.
