Shared Service Factor Considerations
- Public perception of duplicative efforts in local governments
- Tight budgets that require service re-evaluation and re-engineering efforts
- Political pressure to make government more efficient
- Professional staff who see opportunities for make government service delivery more efficient and better for the customer
- Changes in key leadership positions (e.g. two or three police chief or HR Director positions open simultaneously in adjacent organizations)
- Past successes in shared services efforts which have fostered a climate of collaboration
- Legislative mandates
- Witnessing the success of others and deciding to try it at home (competitive forces)
Principles for Service Sharing
- Recognizing Complexity
- Building Trust
- Understanding the Amount of Time and Effort that will be Needed
- Managing Expectations
- Ensuring Ongoing Leadership
- Maintaining Healthy Relationships
- Celebrate Small Victories
Assuring Unsuccessful Partnership Efforts
- MANDATE them
- Be INCONSISTENT in keeping up the PRESSURE NEEDED TO ACHIEVE
- RESULTS
- EXPECT quick results in a SHORT TIME
- IGNORE the need for MUTUAL BENEFIT
- Go QUICKLY with the OBVIOUS choice
- EXPECT to save money AND get better service
- DON’T WORRY about who will LEAD the effort
- COPY what others are doing and expect the results to be EXACTLY transferable
- PUNISH all false starts
- Don’t worry about DIFFERING MISSIONS
- SKIP right past the “BUILDING A GOOD RELATIONSHIP” and the “BUILDING TRUST” phases
Fundamental Questions
- Does it have the potential to save money?
- Does it have the potential to provide an equal to or better service level?
- Is it a sustainable solution over the long-term?
Necessities for Successful Collaborations
- Political will
- Administrative leadership
- Foresight and vision
- Have a “champion” for the cause
- Persistence
- Go beyond the study
- Trust & Honesty
- Open and inclusive process
- Creativity and flexibility
- Equitable and consensus based solutions
- Timing
- Adoption of appropriate governance model
- There is no one size fits all approach
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