How to identify a data pattern?

Hi all,

I have 7 quarters of sales data per sales rep. On average, a sales rep books 3-4 sales transaction/quarter. Typically, a transaction is around $25,000.

How do I identify a typical sales pattern for a sales rep who will have a quota of $250,000/quarter? In other word, a sales rep who books $25,000, $12,000, $100,000 and $123,000 a quarter to meet his $250,000 quota is a typical sales rep? Is the $250,000 quota is too high or too low for a sales rep?

I don't know where to start. Please help!

Thank you so much.

This is super open-ended.

But let's consider something:
$25,000 / transaction
3.5 transactions (average) / quarter
=> $25k * 3.5 = $82,500 / quarter

so compare the kilobucks: 250 / 82.5 => your quota is three times typical number of transations times the typical transaction value.

Well, basically, you should figure out:
1) The average number of transactions
2) The deviation in those transactions
3) The average value of a transaction
4) The average deviation of a transaction

Well, that's where I would start. Once you've got all those averages, you can get what a numerically average quarter looks like; you can also get an idea of what kind of variance you're running. Like, if the deviations are really high, then a sales rep could be way under, or way over, an average without it being remarkable.

I'd also check what kind of performace you have per quarter; you might have busy seasons (near the end of a fiscal year when clients are looking to clear out their CAPEX budget for example) and slow seasons (during the clients' busy production times when they're not interested in changing anything).

But... this is like, really vague.

You might be best-served putting this in a pivot table + chart so you can throw variables around and see what kind of patterns you find.

Thank you, ben_hensel, for the suggestion. I'll do more number crunching then.

Try this..