Multiplication with different granularities

Not sure if this is what you wanted... but you can take it and shape it into something you want.

// Let's assume that
// 1. You've got an Orders table with
//    orders in there OrderID, ItemID, OrderStatus
//    where OrderStatus is the same for all lines
//    with the same OrderID.
// 2. You've got an OrderItems table with
//    items that belong to an order from the
//    Orders table (ItemID is unique across all Orders)
//    The columns in OrderItems are
//    ItemID, Area, Delivery, TimeValue
// An open order is one that has OrderStatus < 70 in
// Orders.
// Relationship: Orders[ItemID] * <-one-way- 1 OrderItems[ItemID]. 
// One order can have multiple items but each item in
// OrderItems can belong to only one order.
//
// The above setup is a bit strange. What it really should be
// is this.
// Orders - stores data on orders and each line is one order.
// Items  - stores all available items that an order can contain.
// Order2Item - stores the relationship between an order and an item.

[# Open Orders] =
CALCULATE(
    DISTINCTCOUNT( Order[OrderID] ),
    KEEPFILTERS( Order[Status] < 70 )
)

[Avg Delivery Time Per Order] =
IF( HASONEVALUE( Orders[OrderID] ),
    AVERAGE( OrderItems[Delivery Time] )
)

[Avg Delivery Time Per Open Order] =
IF( [# Open Orders] = 1,
    AVERAGE( OrderItems[Delivery Time] )
)

[Avg Delivery Time] =
    AVERAGEX(
        VALUES( Order[OrderID] ),
        [Avg Delivery Time Per Order]
    )
    
[Avg Delivery Time for Open Orders] =
    AVERAGEX(
        VALUES( Order[OrderID] ),
        [Avg Delivery Time Per Open Order]
    )

[Final Measure] =
    [Avg Delivery Time for Open Orders]
    * [# Open Orders]