Maximize Your Data With Performance Measurement Processes

Strategic Planning January 9, 2019

Associations are collecting more and more data on member characteristics and behavior, but they often struggle to analyze it and apply what they learn. ASAE Foundation research identified structured performance measurement processes that support effective data-driven decision making.

Everyone is collecting data these days—web analytics, member profile information, program surveys—and associations employ a growing number of tools that simplify collection processes. But acting on that data presents a different kind of challenge. To measure performance effectively, you need to start with a plan.

According to the ASAE Foundation report, Measuring Performance: Purpose, Process, and Practice, useful metrics may be specific to a particular need or business question, but the process to apply metrics can and should be more universal.

An effective performance measurement strategy starts with a planning document that outlines the organization’s definition of success by stating its goals and the specific outcomes that will indicate success. Examples include a strategic plan, theory of change, or logic model. A planning document increases the likelihood that data will be used. Sixty-seven percent of associations with a planning document reported formally tracking organizational metrics, while only 9 percent of associations without a planning document did the same.

With the foundation set, leaders can build a framework that details which metrics will be used and how they will be applied and can create an implementation guide that takes staff through the steps of the framework.

Performance Measurement Framework

The planning document serves as the basis for a performance measurement framework, which specifies the metrics to be used and how they will be tracked. Associations that used some type of framework, developed externally or internally, were more than three times as likely to track both mission attainment and organizational health metrics as were organizations that had no framework. 

A good performance measurement framework includes process indicators, which measure the execution of activities, and outcome indicators, which evaluate whether results are being achieved. For example, a process indicator would be the number of education programs an association delivered over the course of a year, while an outcome indicator would be the percentage of attendees who demonstrated a certain level of knowledge at the end of a program. A performance measurement framework also includes distinct milestones—points at which association leaders must assess collected data to identify issues or act on patterns.

Performance measurement frameworks are meant to evolve, and they require periodic assessment to ensure that the data collected is meaningful and useful. Leaders are likely to go through multiple iterations before they identify the optimal combination of data points they need to make decisions.

67% Percentage of associations using a planning document that say they formally track organizational metrics

Implementation Guide

A clear implementation guide ensures the success of performance measurement processes by establishing when and how data will be collected and reported. A guide should help staff understand their distinct roles in data collection, analysis, and reporting. Setting clear expectations about roles and activities can keep these important tasks from getting lost among competing priorities.

Researchers stressed the importance of getting staff buy-in on performance measurement processes from the beginning. Staff need to know not only how to collect the data correctly, but also why they are doing it and how it will serve the association’s goals. Staff should also be informed of the results of data collection and the actions undertaken based on those results.

Performance measurement processes create additional tasks, but they help associations gather, analyze, and act on available data systemically and strategically. Association leaders intent on using data effectively should take the time to develop their plans and establish processes—and then be ready to continuously change them based on evolving needs.