Download PDF
McKesson: Building a People Analytics Center of Excellence
Technology Category
- Analytics & Modeling - Data-as-a-Service
- Analytics & Modeling - Predictive Analytics
- Functional Applications - Enterprise Resource Planning Systems (ERP)
Applicable Industries
- Healthcare & Hospitals
- Pharmaceuticals
Applicable Functions
- Business Operation
- Human Resources
Services
- Data Science Services
- Software Design & Engineering Services
- System Integration
The Challenge
McKesson had a need, driven by their CHRO, to make more data-driven people decisions. They had completed an HR transformation several years ago, part of which was designed to further develop HR business partners into true strategic partners for the business. As part of this transformation, they had to inform and arm the business with data they needed to make people and business decisions. McKesson stood up a workforce intelligence group of about five analysts, situated within the corporate Talent Management organization. The group existed as a centralized resource, primarily supporting Corporate HR at first. As a result, McKesson began to go from making decisions about the workforce based on intuition to gaining the ability to come to the table with data, just like other functions such as finance or their major business units. However, these workforce insights were not yet embedded in the business. At McKesson, each business unit had very capable analysts working with business leaders to help them make data-driven decisions. However, they were disconnected. Furthermore, each analyst was focused on their business unit and not necessarily on the enterprise. Each group also had different goals, often with their own dashboards and metrics. This was further complicated by the challenge that there were different approaches, different analytics tools, and different information being used across the groups. While each had good governance, there was a lack of efficiency and an inability to scale analytics efforts. This ultimately meant it was difficult to drive results across the enterprise.
About The Customer
McKesson Corporation employs approximately 78,000 worldwide. Currently ranked 7th on the FORTUNE 500, McKesson is a global leader in healthcare supply chain management solutions, retail pharmacy, community oncology and specialty care, and healthcare information technology. McKesson partners with life sciences companies, manufacturers, providers, pharmacies, governments, and other organizations in healthcare to provide the right medicines, medical products, and healthcare services to the right patients at the right time, safely and cost-effectively.
The Solution
When the Vice President of Workforce Planning and Analytics joined McKesson, one of their first initiatives was to establish a workforce intelligence center of excellence. They saw a need to leverage the business knowledge and different analytics strengths of the distributed analysts to create an effective, scalable, and sustainable people analytics capability across the enterprise. The Vice President of Workforce Planning and Analytics also recognized that while the business units were quite different, with different customers and products, the analytics they needed were actually very alike. By creating a COE, they could create the space for the analysts to be effective yet different where it mattered. McKesson realized an opportunity to drive more standardization where they could, establishing further discipline and a structure for delivering consistent data to support workforce decisions. By building the COE, McKesson would create a community, enhance coordination, and enable information sharing on best practices. McKesson implemented a hub and spoke model to drive standardization where possible, to eliminate redundancy of efforts, and to coordinate the people analytics community and their work. The “hub” became the resident place for those with the deepest people analytics skills and who could be leveraged across the enterprise (i.e. data science, workforce planning, technologists, and data infrastructure, etc.). The “spokes” were analysts solely designated to support specific business units or functions, but are now able to work across groups and collaborate on enterprise-wide projects. McKesson brought the analysts from the business units into the COE from a reporting relationship, creating a stronger community capable of delivering consistency and scale, while keeping them embedded within the business units. By doing so, the COE gained the business contexts from this group of experts while maintaining a conduit back to the business.
Operational Impact
Quantitative Benefit
Related Case Studies.
Case Study
Case Study: Pfizer
Pfizer’s high-performance computing software and systems for worldwide research and development support large-scale data analysis, research projects, clinical analytics, and modeling. Pfizer’s computing services are used across the spectrum of research and development efforts, from the deep biological understanding of disease to the design of safe, efficacious therapeutic agents.
Case Study
Hospital Inventory Management
The hospital supply chain team is responsible for ensuring that the right medical supplies are readily available to clinicians when and where needed, and to do so in the most efficient manner possible. However, many of the systems and processes in use at the cancer center for supply chain management were not best suited to support these goals. Barcoding technology, a commonly used method for inventory management of medical supplies, is labor intensive, time consuming, does not provide real-time visibility into inventory levels and can be prone to error. Consequently, the lack of accurate and real-time visibility into inventory levels across multiple supply rooms in multiple hospital facilities creates additional inefficiency in the system causing over-ordering, hoarding, and wasted supplies. Other sources of waste and cost were also identified as candidates for improvement. Existing systems and processes did not provide adequate security for high-cost inventory within the hospital, which was another driver of cost. A lack of visibility into expiration dates for supplies resulted in supplies being wasted due to past expiry dates. Storage of supplies was also a key consideration given the location of the cancer center’s facilities in a dense urban setting, where space is always at a premium. In order to address the challenges outlined above, the hospital sought a solution that would provide real-time inventory information with high levels of accuracy, reduce the level of manual effort required and enable data driven decision making to ensure that the right supplies were readily available to clinicians in the right location at the right time.
Case Study
Gas Pipeline Monitoring System for Hospitals
This system integrator focuses on providing centralized gas pipeline monitoring systems for hospitals. The service they provide makes it possible for hospitals to reduce both maintenance and labor costs. Since hospitals may not have an existing network suitable for this type of system, GPRS communication provides an easy and ready-to-use solution for remote, distributed monitoring systems System Requirements - GPRS communication - Seamless connection with SCADA software - Simple, front-end control capability - Expandable I/O channels - Combine AI, DI, and DO channels
Case Study
Fusion Middleware Integration on Cloud for Pharma Major
Customer wanted a real-time, seamless, cloud based integration between the existing on premise and cloud based application using SOA technology on Oracle Fusion Middleware Platform, a Contingent Worker Solution to collect, track, manage and report information for on-boarding, maintenance and off-boarding of contingent workers using a streamlined and Integrated business process, and streamlining of integration to the back-end systems and multiple SaaS applications.
Case Study
Driving Digital Transformations for Vitro Diagnostic Medical Devices
Diagnostic devices play a vital role in helping to improve healthcare delivery. In fact, an estimated 60 percent of the world’s medical decisions are made with support from in vitrodiagnostics (IVD) solutions, such as those provided by Roche Diagnostics, an industry leader. As the demand for medical diagnostic services grows rapidly in hospitals and clinics across China, so does the market for IVD solutions. In addition, the typically high cost of these diagnostic devices means that comprehensive post-sales services are needed. Wanteed to improve three portions of thr IVD:1. Remotely monitor and manage IVD devices as fixed assets.2. Optimizing device availability with predictive maintenance.3. Recommending the best IVD solution for a customer’s needs.