DEFINE
    MEASURE Sales[Prev Year Sales] =
        CALCULATE (
            [Sales Amount],
            OFFSET (
                -1,
                ORDERBY ( 'Date'[Year], ASC )
            )
        )
EVALUATE
SUMMARIZECOLUMNS (
    'Date'[Year],
    TREATAS ( { 2019, 2020 }, 'Date'[Year] ),
    "Sales Amount", [Sales Amount],
    "Prev Year Sales", [Prev Year Sales]
)

DEFINE
    TABLE ProcessData =
        -- Create a table with index column and "process" values from the DAX Guide db
        SELECTCOLUMNS (
            SUMMARIZECOLUMNS (
                'Date'[Calendar Year Month Number],
                FILTER (
                    ALL ( 'Date'[Calendar Year Month Number] ),
                    'Date'[Calendar Year Month Number] < 200804
                ),
                "Amt", [Sales Amount]
            ),
            "Index", [Calendar Year Month Number],
            "Value", [Amt]
        )
    -- Basic sum measure of the value column
    MEASURE ProcessData[SumValue] =
        SUM ( ProcessData[Value] )
    -- Average value of the data
    VAR MeanValue =
        AVERAGE ( ProcessData[Value] )
    -- Use the OFFSET function to first calculate the absolute differences 
    -- between two consequent values (a.k.a. Moving Range) 
    -- https://en.wikipedia.org/wiki/Shewhart_individuals_control_chart
    MEASURE ProcessData[MovingRange] =
        VAR PreviousValue =
            CALCULATE (
                [SumValue],
                OFFSET (
                    -1,
                    ORDERBY ( ProcessData[Index] )
                )
            )
        RETURN
            IF (
                NOT ISBLANK ( PreviousValue ),
                ABS ( [SumValue] - PreviousValue )
            )
    -- Derive process standard deviation or "sigma" based on the Moving Range
    VAR Sigma =
        VAR MeanMovingRange =
            CALCULATE (
                AVERAGEX (
                    ALL ( ProcessData[Index] ),
                    [MovingRange]
                )
            )
        RETURN
            MeanMovingRange
                * SQRTPI ( 1 ) / 2
    -- Use the WINDOW function to implement the WE Rule 2 for process instability detection:
    -- "Two out of three consecutive points fall beyond the 2σ-limit (in zone A or beyond), 
    -- on the same side of the centerline"
    -- https://en.wikipedia.org/wiki/Western_Electric_rules
    MEASURE ProcessData[Rule2Test] =
        VAR ZoneARowsPositive =
            CALCULATE (
                COUNTROWS ( ProcessData ),
                FILTER (
                    WINDOW (
                        -2,
                        0,
                        ORDERBY ( ProcessData[Index] )
                    ),
                    [SumValue] >= MeanValue + 2 * Sigma
                )
            )
        VAR ZoneARowsNegative =
            CALCULATE (
                COUNTROWS ( ProcessData ),
                FILTER (
                    WINDOW (
                        -2,
                        0,
                        ORDERBY ( ProcessData[Index] )
                    ),
                    [SumValue] <= MeanValue - 2 * Sigma
                )
            )
        RETURN
            -- Flag the rows where the rule is violated
            IF (
                ZoneARowsPositive >= 2 || ZoneARowsNegative >= 2,
                1
            )

EVALUATE
SUMMARIZECOLUMNS (
    ProcessData[Index],
    "SumValue", [SumValue],
    "Process Mean", MeanValue,
    "-2 σ", MeanValue - 2 * Sigma,
    "+2 σ", MeanValue + 2 * Sigma,
    "Rule 2 Indicator", [Rule2Test]
)