This document provides guidance on assessing failing, struggling, or underperforming association programs through a thorough review process. It outlines key steps, including: defining goals for the review by getting input from stakeholders; exploring the original program goals and how it has changed over time; researching through historical documents, opinions, and behavior data; measuring outputs, outcomes, and impacts; assessing efficiency and finances; determining who to involve in the implementation; and clearly communicating the results and recommendations. The overall lessons are to seek to understand the program's purpose and evolution, make decisions based on comprehensive data collection, and plan for changes resulting from the review.

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FixFix it or Flee itit or Flee it??
Proven approaches for dealing withProven approaches for dealing with
failing, flagging and floundering association programsfailing, flagging and floundering association programs
Greg Melia, CAE @gmeliacae
Photo credit: hebedesign on flickr
ProgramAssessment is a lot of GRIEF
ProgramAssessment is a lot of GRIEF
• Goals
• Research
• Impact
• Efficiency
• Finances Credit: Angie Torres on Flickr

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Defining the Goal of the Review
– Work with key stakeholders and decision-
makers
– Solicit their key questions:
• What do they want to know?
• What information will help their decision-making?
• What do they think needs to be evaluated?
– Refine questions to be measurable and defined
Exploring Program Goals
Investigate the Key “Whys”:
•Why was the program originally established?
•Why has it continued to be offered?
•Why has it change over time?
Review the Original Intended Approach:
•Who, what, when, where, why and how?
•What was implemented?
•What was not?
Lessons Learned
• Verbalizing goals of the review are an important part of
preparing for change
• Seek superordinate goals
• Some agreements are easier reached upfront

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Research
3 kinds of data:
Corpus Inscriptionum
Opinions and Descriptions
Imponderabilia of behavior
Bronislaw Malinowski
Credit: Photographie et Ethnologie:
Les photographes français au XXème siècle
devant d’autres formes de cultures.
Lessons Learned
• Historical minutes and documents can be VERY
informative
• Seek to understand program mutations
• Good decisions based on bad data usually give bad
results
• Remember they may have been involved
Impact Measure
• Outputs = Immediate
I attended
• Outcomes = Short-term
I gained knowledge
• Impacts = Long-term
I served more members as a result

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Efficiency
Staff and Volunteer Time
Complaints and Comments
Marketing/Communication
Registration/Orders
Technology Photo credit: mansikka on Flickr
Lessons Learned
• How do people feel about it? Do they have
suggestions to increase efficiency?
• What are the trends in terms of level of effort?
• What is cost/benefit of doing it the same way versus
trying a new approach?
• Can improved efficiency save it?
Finances
• Direct fixed expenses
– Incurred regardless of how many people participate,
buy, or are served (e.g., office rent)
• Variable expenses
– Incurred per each additional unit or person that is
serviced (e.g., per person meal charge)
• Mixed expenses
– Incurred per each additional set of units or persons
serviced (e.g., room rental, temporary help)

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Key Calculations
• Revenue – Expense = Margin
– Margin per attendee/unit
– Margin per staff hour
– Margin per impact
Lessons Learned
• One full flight is more profitable than two half full ones.
• Most do not realize the true full cost.
• Understanding costs helps determine price.
• Price increases (and closing programs) take time.
Implementation
• Who to involve
– Consultant?
– Stakeholders
– Staff
– Non-users
• Who to interview
–Former volunteers
–Former staff
–Vendors
Photo credit:
kierenmccarthy.co.uk

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Communication of Results
• Review purpose of review
• Review what was done
• Arrange key findings in logical order,
highlighting interpretations where
appropriate
• Close with recommendations or issues to
be addressed
Credit:
EE.UTD.Events
on Flickr
Lessons Learned
• Equivocal recommendations get equivocal results
• Decision-makers need synthesized data, not the
opportunity for data analysis
• Survey data is important, but the proof is in historical
performance
• Plan and communicate transitions
Thank You!Thank You!
Greg Melia, CAE
gmelia@asaecenter.org
@gmeliacae