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Budget staff outlines peer-city benchmarks and a budget-evaluation matrix to guide council review

Chattanooga City Budget Working Group · March 31, 2026
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Summary

Staff described a data-driven peer-city identification tool and proposed a budget-evaluation matrix; council asked for separate peer lists for budgetary comparisons and aspirational goals and requested departmental input on peer choices.

City staff presented a two-part proposal to help the council benchmark performance and inform budget decisions: (1) a budget-evaluation matrix (short and long versions) that staff will circulate for council use, and (2) a peer-city identification process combining census, finance and employment measures with geographic and boundary-stability filters.

Dr. Acuff and Chris explained the methodology: the peer identification uses population bands, regional proximity, government finance metrics, employment and boundary stability over a 10-year window. The tool produced an initial candidate list; staff recommended removing consolidated or metro governments (for example, Columbus, Ga.) because their structures distort comparability. "So that's the starting point of what you're currently using," Dr. Acuff said, and he invited council input on which metrics (budget size, headcount, poverty, education, etc.) matter most for departmental and budgetary use.

Council members requested two separate lists: one focused strictly on budgetary peers with comparable municipal budgets and government size, and another aspirational list identifying cities with higher incomes or education outcomes that Chattanooga might study. Several departments were asked to share their peer lists so the council can harmonize criteria across uses.

Why it matters: A consistent set of peers tied to explicit metrics helps departments compare service levels, staffing and spending, and allows the council to set measurable benchmarks across multiple years.

What’s next: Staff will return with refined peer lists, spreadsheets of underlying data, and a plan for departmental input to finalize benchmarks and application of the matrix.