Case Studies McKesson: Building a People Analytics Center of Excellence

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	McKesson: Building a People Analytics Center of Excellence

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
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. Read More
About 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. Read More
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. Read More Log in to view content
Contents

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

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 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.

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.

Impact #1	The COE has become a place where people can come for business-relevant analysis and insights. The center can triage requests (using a prioritization matrix) and help stakeholders understand what might be (and not be) an analytic question. For the first time, the analysts can talk together across the groups.
Impact #2	Analytics efforts are now more strategic. There are synergies in this new shared services model and service levels are beginning to improve.
Impact #3	Through the COE, McKesson discovered there were sometimes differences in data definitions between groups. The collaboration—and close business partnership— of the COE is enabling McKesson to align around common definitions and develop a clear and consistent understanding of the use cases when different approaches might be appropriate.

Impact #1

The COE has become a place where people can come for business-relevant analysis and insights. The center can triage requests (using a prioritization matrix) and help stakeholders understand what might be (and not be) an analytic question. For the first time, the analysts can talk together across the groups.

Impact #2

Analytics efforts are now more strategic. There are synergies in this new shared services model and service levels are beginning to improve.

Impact #3

Through the COE, McKesson discovered there were sometimes differences in data definitions between groups. The collaboration—and close business partnership— of the COE is enabling McKesson to align around common definitions and develop a clear and consistent understanding of the use cases when different approaches might be appropriate.

Benefit #1	Removal of redundant activities, eliminating about 1,000 hours of extraction, reporting, and analytics work in the first six months.
Benefit #2	Data that used to take 40 hours to bring together now takes less than a day.
Benefit #3	They have been able to double Visier utilization since they can concentrate on a core set of tools and communicate in one voice, in an advisory capacity.

Benefit #1

Removal of redundant activities, eliminating about 1,000 hours of extraction, reporting, and analytics work in the first six months.

Benefit #2

Data that used to take 40 hours to bring together now takes less than a day.

Benefit #3

They have been able to double Visier utilization since they can concentrate on a core set of tools and communicate in one voice, in an advisory capacity.

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Overview

McKesson: Building a People Analytics Center of Excellence

Operational Impact

Quantitative Benefit