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Research Report

Track shared services efficiency and service metrics during and beyond implementation

October 23, 2019

In the private sector, end-user resistance to shared services is typically counterbalanced by several methods: gainsharing incentives, “sin taxes” for maintaining local processes or shadow systems, and dashboard metrics that broadcast cost and quality gains. Although financial penalties are rare within higher education, more institutions are looking to run shared services “like a business” by vigorously monitoring transactional metrics and pursuing opportunities for continuous improvement.

More on this topic

This resource is part of the Ease the Transition to Shared Services with a Plan for Change Management Hurdles Roadmap. Access the Roadmap for stepwise guidance with additional tools and research.

Solution: Continually tracking and sharing performance metrics
Institutions should select a handful of relevant key performance indicators (KPIs) for the activities performed by shared services. Tracking and sharing them via a simple dashboard and annual reports keeps campus informed about the center’s operations and commitment to ongoing efficiency and service enhancements.

Using metrics to celebrate success, manage operations, and assess service quality

Investing in capabilities to track and report shared services metrics advances both internal and external objectives. These objectives include:

Benefits of tracking and reporting shared services metrics

Data about year-over-year transaction processing speeds and volume of work completed can be incorporated into regular reports. This information can help justify to stakeholders the investment in a shared services organization and mitigate faculty pushback. This data also proves the benefits of partnering with the shared services center to potential customers.

Using productivity metrics and transaction data, shared services leaders can track trends in work volumes and their relationship to processing time and error rates. This data can also be used to set quotas and identify staff who may need additional support or training to fulfill their duties.

Customer satisfaction surveys are designed to gauge campus opinion and solicit feedback on shared services operations. Results can help shared services leaders prioritize efforts to boost customer engagement or redesign business processes. Further, responding to quality concerns can help build trust that shared services is designed with the customer in mind.

Collectively, tracking performance allows shared services leaders to both celebrate “wins” and address areas in need of improvement.

You can’t manage what you don’t measure

Despite ambitions to track operational data, campuses often struggle to document the financial savings, cost avoidance, and efficiency gains associated with shared services. One of the biggest challenges is narrowing in on the best range of quality, productivity, and customer satisfaction metrics to track.

Common Types of Metrics for Evaluating Shared Services


Tracks how well employees are performing the task

Sample Metrics:

  • Error rate
  • Frequency of rework
  • Average turnaround time
  • Number of code violations

Tracks how quickly work is completed

Sample Metrics:

  • Average turnaround time
  • Processes completed per FTE
  • Time spent per process
  • Cost savings

Customer Satisfaction
Reveals whether customers are pleased

Sample Metrics:

  • Satisfaction with service center staff and level of service
  • Number of complaints
  • Improvement in customer satisfaction after service center implementation

Metrics are most useful when leaders compare them to baseline measures of efficiency and service. Even institutions that are not yet ready to undertake organizational change can begin tracking baseline metrics now to build a data-driven mindset and enable analysis later. In some cases, manual tracking or collection of data may be necessary to capture current-state performance.

The specific metrics that an institution should track depend on the processes that have been consolidated. Consider the following principles for selecting effective metrics.As shared services leaders begin to track these metrics, they can use dashboards to help visualize trends in the volume of work, labor intensity, and time to resolve transactions. While reporting tools can grow more complex with greater organizational maturity, start with tracking current performance against targets to enable at-a-glance assessments of current trajectories.

Metric FiltersDescriptionRationale
Accessibility of DataInformation system
should be able to
readily generate
metric data
Unrealistic to expect extensive manual
data collection and
analysis in timely
manner for each
Frequency of
Metric monitoring
should be conducted at regular intervals (quarterly or less)
Infrequent (annual) updates hamper
ability to impact
performance in real
Reliability of DataData should be accurate, consistently
defined, and
measured over time
Absence of
trustworthy data
results in suspicion
toward performance, often yielding
Communicability of ConceptDefinition and
rationale for metric
should be easy to
follow and replicate, suggest appropriate action
Lack of
understanding about metric drivers and
relevance hinders
managers’ ability to
inflect performance
Span of ControlMetric should
components solely
within shared
services center
Not reasonable or
prudent to track
performance against measures shared
services center is
unable to directly

Interested in more on this topic?

Shared services is a tried-and-true method for increasing the efficiency and quality of administrative service delivery, but shared services initiatives tend to evoke fears of layoffs, increased administrative burdens for faculty, and expensive consulting engagements with questionable returns. Use this resource to better understand shared services, take the readiness diagnostic, and look at example maturity models.

Shared services centers absorb administrative work from campus units to realize efficiency and quality improvements. Rather than adopting a one-size-fits-all model, institutions should create a shared services structure that strikes a balance between two factors: the efficiency of process standardization and responsiveness to units’ service expectations.