Probability - exact model and decision record

Poisson Event Expected Value Calculator

Scale an observed event rate to future exposure, estimate expected count and impact, and reconcile the budget calculation.

Live model

Turn an observed event history into a future exposure and budget plan

Fit a simple events-per-exposure rate, scale it to a planned period, and translate the expected count into a linear impact budget. The model keeps expected count, count uncertainty, chance of any event, variable impact, and fixed readiness cost distinct.

Fitted rate / exposure-
Expected future events-
Count standard deviation-
Expected variable impact-
Expected total impact-
Chance of >=1 event-

Editorial illustration of a maintenance planner extending an incident-rate ruler from historical records to a future calendar and budget envelope
Historical exposure sets the rate; future exposure sets the expected count; cost assumptions translate that count into a planning budget.
Exposure and expected-impact bridge - live current inputs
StageExposure / quantityEvents or unit valueDerived valueRole

Current calculation process

Formula, substitution, intermediate quantities, and check

r = c/T; lambda_future = rE; E[C] = lambda_future; E[impact] = lambda_future v + F; P(C>=1)=1-e^(-lambda_future)

This page estimates one constant rate from observed count divided by observed exposure. It then scales, rather than re-fits, that rate to future exposure. Variable impact is linear in expected count; fixed readiness cost is added once.

    Use the calculator

    Five planning steps

    1. Audit the historical count. Apply one incident definition and remove duplicates before entering events.
    2. Match its exposure denominator. Enter only the time, assets, transactions, or distance during which those events could occur.
    3. Translate the future plan into the same unit. Convert years to months or fleets to machine-hours before entry.
    4. Separate variable and fixed impacts. Unit impact scales with events; readiness cost is incurred once in this model.
    5. Read expectation with uncertainty. Use expected count for average load, SD for natural count spread, and P(>=1) for event-free planning.

    Five foundations

    Expected value for an exposure-scaled count

    1. A rate needs a denominator

    Eighteen events alone do not define risk. Eighteen in twelve machine-months produces 1.5 events per machine-month.

    2. Scaling assumes comparability

    Multiplying by future exposure assumes comparable operating conditions, event definitions, and observation quality.

    3. Expected count is not a forecasted integer

    lambda=13.5 is a valid average across many comparable plans even though one period cannot realize half an event.

    4. Linear impact is an assumption

    The page assumes each additional event contributes the same average impact and does not model caps, queues, or economies of scale.

    5. Fixed cost changes the reverse check

    Subtract fixed readiness cost before dividing total impact by unit impact to recover expected event count.

    Calculation anatomy

    Symbols and the default bridge

    SymbolMeaningUnit
    cObserved event countwhole events
    TObserved exposurechosen exposure units
    rFitted event rate c/Tevents per exposure
    EFuture exposuresame units as T
    vAverage impact per eventcurrency/event
    FFixed readiness costcurrency/plan

    Default substitution: r=18/12=1.5, lambda=1.5x9=13.5, variable impact 13.5x$275, then add $900 once. No annualization occurs unless the entered exposures are already annual.

    Deep analysis

    Three decisions around the same expected count

    Workload staffing

    Expected count supports average throughput. Add the count SD and a chosen service quantile before turning that mean into a capacity commitment.

    Event-free probability

    When readiness cost depends on any event occurring, P(C>=1) is more decision-relevant than a fractional expected count alone.

    Budget decomposition

    Keep variable and fixed components visible. Otherwise a policy change in readiness cost can be mistaken for a change in event frequency.

    Decision cases

    Routine and boundary planning

    Maintenance callouts

    Eighteen callouts across twelve machine-months are scaled to nine future machine-months. The manager uses expected variable impact for budget and retains the readiness contract as a separate fixed line.

    Zero future exposure

    If a line is shut down and future exposure is zero, expected events and variable impact are zero, while an entered fixed readiness cost remains. That boundary confirms the cost definitions are separated correctly.

    Terms

    Expected-value vocabulary

    Observed exposure
    Opportunity base that produced the historical count.
    Fitted rate
    Observed count divided by observed exposure.
    Future lambda
    Rate multiplied by planned exposure.
    Expected count
    Long-run average realized count across comparable periods.
    Variable impact
    Expected count multiplied by average per-event impact.
    Readiness cost
    Fixed amount added once regardless of realized count.

    FAQ

    Questions for event-rate budgeting

    Why can expected events be fractional?

    Expectation is an average across repeated periods; realized counts remain whole.

    How is future exposure handled?

    The fitted rate is multiplied by future exposure in the same unit.

    Is rate-estimation uncertainty included?

    No. Use the confidence calculator or a predictive model when sparse-data uncertainty matters.

    Is fixed cost charged with zero events?

    Yes. Enter zero if that does not match the contract.

    Can impacts vary?

    This model uses one average linear impact; variable severity needs a richer model.

    Why also show P(>=1)?

    It answers whether the plan remains event-free, a different question from average load.

    Limits and evidence

    Planning boundaries

    • The historical rate is treated as fixed; no confidence or trend adjustment is included.
    • Observed and future exposures must be comparable and use the same units.
    • Impact per event is linear and constant; no frequency-severity dependence is modeled.
    • Fixed cost is incurred once regardless of event realization.
    • The Poisson process assumes independent occurrences and constant intensity within exposure.
    Evidence record: retain the raw event register, exposure source, inclusion rule, unit conversion, future activity plan, unit-impact basis, fixed-cost contract, export, scenario owner, and review date.

    Sources and related tools

    Rate basis and uncertainty follow-up