Current month vs avg of previous 6 months - sql-server

Question

Anyone know an efficient way to write a query to compare a current month's revenue to the average monthly revenue for the past 6 months?
Here's an example with just 2 columns, the actual month and the month's revenue
Columns:
MonthYear RevenueAmt
Jan2017 120
Dec2016 75
Nov2016 50
Oct2016 100
Sep2016 75
Aug2016 100
Jul2016 100
so....the average of the previous 6 months (Jul to Dec) is
(75 + 50 + 100 + 75 + 100 + 100) = 500
500 / 6 = 83.33
The current month (Jan2017) is 120,
so the difference becomes-
120 - 83.33 = 36.67
So, Jan2017 is 36.67 higher than the average of its past 6 months.

Answer 1

You can use the window functions and set the frame via ROWS BETWEEN 6 PRECEDING AND 1 PRECEDING
This is a rolling variance, and I did make one modification... I used an actual date so we can set the proper Order By in the Over clause
Edit: I added the Prior6MthAvg column to illustrate the math
Declare #YourTable table (MonthYear Date,RevenueAmt int)
Insert Into #YourTable values
('2017-01-01',120),
('2016-12-01',75),
('2016-11-01',50),
('2016-10-01',100),
('2016-09-01',75),
('2016-08-01',100),
('2016-07-01',100)
Select A.*
,Prior6MthAvg = avg(RevenueAmt+0.0) over (Order By MonthYear ROWS BETWEEN 6 PRECEDING AND 1 PRECEDING)
,Variance = RevenueAmt-avg(RevenueAmt+0.0) over (Order By MonthYear ROWS BETWEEN 6 PRECEDING AND 1 PRECEDING)
From #YourTable A
Order by MonthYear Desc
Returns
MonthYear RevenueAmt Prior6MthAvg Variance
2017-01-01 120 83.333333 36.666667
2016-12-01 75 85.000000 -10.000000
2016-11-01 50 93.750000 -43.750000
2016-10-01 100 91.666666 8.333334
2016-09-01 75 100.000000 -25.000000
2016-08-01 100 100.000000 0.000000
2016-07-01 100 NULL NULL

Answer 2

I was going to comment, but it is more of an answer....
Please note: efficiency, and planning thereof, requires a broader scope of design. That said, in general - assuming a larger amount of data - the most optimal way (in my experience) is to keep a separate table for the "running averages."
To explain, I would keep a separate table (single record, if only 1 set of data - i.e. not company based), keyed by current month, with the given average AND the 6th month total.
Once done - insert a trigger for adding a new month (again, in general, or by company, if divided) that will subtract the 6th month, and add the current.
Then, either the total, average or both are stored separately, and quickly accessed.
Once done - a simple join will bring the total/average into any given query.
Edited to add: (NOTE: my T-SQL may be rusty, but this should give you the idea)
NOTE: it assumes the base table of ClientData, with a Secondary Table SalesAvg, linked by id (of the rep) and the date (the month marker, if the date can vary, you would need to split out month/year for the key and link). Pulling it from the same table as given will basically task the server at the point of query. This method distributes the work to the point of insertion (normally more spread out) and as the average is keyed, allows for quickest retrieval using an inner join.
CREATE TRIGGER UpdateSalesAvg
ON schema.ClientData
AFTER INSERT
AS
DECLARE #ID as INT;
DECLARE #Date as DATE;
DECLARE #Count as INT;
SET #ID=new.id;
SET #Date=new.date;
SELECT #Count = ISNULL(RunCount, 0) FROM schema.SalesAvg
WHERE id = #ID AND monthdate = #Date;
IF (#Count = 0)
BEGIN
INSERT INTO schema.SalesAvg (id, monthdate, RunAvg, RunCount, LastPost)
VALUES (new.id, new.monthdate, new.value, 1, new.value);
END
ELSE IF (#Count = 6)
BEGIN
UPDATE schema.SalesAvg
SET RunAvg = ROUND((RunAvg * 6) - LastPost + new.value) / 6, 2),
LastPost = new.value
WHERE id = #ID
AND monthdate = #Date;
END
ELSE
BEGIN
UPDATE schema.SalesAvg
SET RunAvg = ROUND( (RunAvg * RunCount + new.value) / (RunCount + 1), 2 ),
RunCount = RunCount + 1,
LastPost = new.value
WHERE id = #ID
AND monthdate= #Date;
END
GO