Month Prior Year (MPY)

YAML type: mpy | Category: Periodic

Compares the current month to the same month in the prior year.

Description

MPY isolates seasonal month patterns while comparing YoY growth.

Month Prior Year (MPY) illustration

Month Prior Year compares the current month aggregate to the same month last year, with the same aggregation and direction controls as MoM.

Prefer MPY over MoM when strong seasonality makes consecutive months hard to compare (for example retail peak months).

Requires multi-year history for stable interpretation.

Configure detectors on the data view Analysis tab or in YAML. Validate with Data Preview before enabling production schedules.

Parameter	Default	Description
`percentualChange`	`50`	Minimum absolute % change
`mode`	`both`	Direction -- see Allowed values
`aggregateMode`	`sum`	Period aggregation -- see Allowed values

Value	Meaning
`above`	Flag increases / values above the comparison (or high side of a band)
`below`	Flag decreases / values below the comparison (or low side of a band)
`both`	Flag either direction

Used when the detector compares period totals (week / month / quarter), not raw daily points.

Value	Meaning
`sum`	Compare sums of daily values in the period (default)
`average`	Compare averages of daily values in the period

Most detectors also accept optional series filters in params:

Parameter	Purpose
`maxGapAmount`	Skip series when gap amount is too high (`null` = no limit). Catalog create-default is often `5`.
`minValue`	Skip series whose average value is below this (`null` = no limit). Catalog create-default is often `1000`.
`maxValue`	Skip series whose average value is above this (optional; omit/`null` = no limit)
`useSpecialDates`	When `true`, suppress anomalies that overlap special dates

When a filter skips a series, Data Preview shows the reason.

analysis:
  detectors:
    - type: mpy
      params:
        percentualChange: 30.0
        mode: both
        aggregateMode: sum

Prefer over MoM when seasonality is strong.