Volunteer Scheduling Coverage Planner
Plan volunteer rosters, identify coverage gaps, and prevent burnout. Enter values for instant results with step-by-step formulas.
Formula
Gap = (Volunteers × AvgAvailability) - (Shifts × PeoplePerShift)
The Gap represents the difference between Supply (Total Available Volunteer-Slots) and Demand (Total Required Shift-Slots). A negative gap indicates a shortage, requiring either more recruitment or increased commitment from existing volunteers.
Worked Examples
Example 1: Food Bank
Problem: Need 4 people/shift, 3 shifts/day, 7 days. Have 20 volunteers doing 2 shifts/week.
Solution: Demand: 4 * 3 * 7 = 84 slots. Supply: 20 * 2 = 40 slots. Gap: -44 slots.
Result: Shortage (52% Coverage)
Frequently Asked Questions
What is a safe 'Coverage Ratio'?
Aim for 120-130%. If you need 10 people, book 12 or 13. Life happens, and volunteers don't have the same obligation to show up as paid staff. Excess volunteers can spend time connecting with beneficiaries.
What is the 'Volunteer Value'?
Independent Sector estimates the value of a volunteer hour at ~$30. Use this to report 'In-Kind Contributions' to donors and the board.
Can I fire a volunteer?
Yes. If they are disruptive or unreliable, they cost more than they contribute. Document issues and have a respectful conversation.
What are the main types of insurance coverage?
Major types include health insurance (medical costs), auto insurance (liability, collision, comprehensive), homeowners/renters (property and liability), life insurance (term or whole life), disability insurance (income replacement), and umbrella insurance (excess liability). Each has specific coverage limits, exclusions, and deductibles.
Is my data stored or sent to a server?
No. All calculations run entirely in your browser using JavaScript. No data you enter is ever transmitted to any server or stored anywhere. Your inputs remain completely private.
How do I interpret the result?
Results are displayed with a label and unit to help you understand the output. Many calculators include a short explanation or classification below the result (for example, a BMI category or risk level). Refer to the worked examples section on this page for real-world context.