Data-Driven Decision-making: Developing a Long-term Police Staffing Plan
Data-Driven Decision-making: Developing a Long-term Police Staffing Plan
Event Type: eLearning Course
Dates and Times
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May 1, 2026 Noon - 1:30 p.m. ET
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May 15, 2026 Noon - 1:30 p.m. ET
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May 29, 2026 Noon - 1:30 p.m. ET
Speakers
Event Details
Field of Study: Finance
Level: Basic
Credits: 3
Prerequisite: None
Details
When it comes to budgeting for law enforcement personnel, the gold standard is to align staffing with identified workload. This is different from traditional approaches based on per capita data, prescribed staffing minimums, or historical precedent. Determining the “right” number of staff must be grounded in data-driven workload analyses, incorporate community needs, expectations, and goals, and occur within the context of what a jurisdiction can afford. I as well as conversations about what the jurisdiction can afford. In addition to setting a baseline for existing staffing needs, a workload-based approach also helps illustrate the most fiscally and operationally efficient way to deploy existing staff (e.g., temporally and spatially) to meet performance goals.
In this three-part webinar series, experts in police staffing and budgeting will walk through what it takes to develop a multi-year police staffing plan, put the plan into action, and assess your progress.
Each webinar will feature 60 minutes of presentation followed by up to 30 minutes for questions and answers. The webinars will be recorded, so if you miss one, you can watch the recording before the next one to get caught up. You cannot earn CPE credit if you do not join the live session.
Who Will Benefit
- Budget, police, and city leaders seeking data‑driven, affordable staffing plans.
Learning Objectives
After completing the webinar series, attendees should be able to:
- Explain the importance of aligning police staffing with identified workload
- Outline the steps involved in developing a multi-year police staffing plan
- Discuss how to implement and monitor the staffing plan
Member Price: $150.00
Non-Member Price: $300.00