Similar origin skillsets can be derived from strange sources. Take night auditors and web analysts, for instance.

Let’s start with definitions.

A night auditor is somebody who works in a hotel, on the night shift, usually from 11pm until 7am, balancing the days receipts.

Early in my working life, before university, I was a senior night auditor at a very large hotel. It had a night club, a gaming lounge, two restaurants, a pub, and two front desks. It also featured an overburdened accounting staff which was responsible for 4 other hotels, and as a result, much of the accounting functions were downsourced to the night audit team. Not complaining, just saying.

I wasn’t a statistician then, and it wasn’t as though any of the insights I could have provided would have been acted against.

I noticed quite a few relationships. For instance – how did the closing of the kitchen at 10pm on Sunday’s affect our relationships with our five largest corporate clients, most of whom arrived at the hotel after long flights, hungry? (I know qualitatively that it did, I don’t know quantitatively how it contributed to losing several major clients).

How did the closing of the kitchen at 11pm on Saturday’s affect the amount of liquor served after midnight at the night club?

How does hotel occupancy impact food sales?

How does the occupancy rate and price rate on jacuzzi suites impact food and liquor sales?

What’s the impact of weather on company-wide liquor sales?

I was very frustrated at the time because I knew I was sitting on a gold mine of information. I was too young and too uneducated to really know how to extract that value from the data.

Dennis, who was the senior night auditor, two senior auditors before I, had become the night club manager. Dennis was brilliant because he used to go back into my office and ask for sales figures of various items throughout the night. He’d use those figures to determine if and when a drink special would be announced, and the duration. He was a real time restaurant analytics user, that’s for sure. And he succeeded for a long time.

I’m not saying that night auditors ought to be statisticians or marketing scientists of any sort. In fact, most night auditors have enough trouble getting through the night and balancing debits with credits to zero. I learned a lot though, and they contributed to my course towards web analytics.

I learned spreadsheet reporting. I learned the dismal science of restaurant, club, hotel, pub, steakhouse and gambling economics – long before I took advanced courses in macro and micro economics. I learned how to run a team, and how to methodically track problems. I learned about reporting paralysis – the problems associated with reporting too much information, or the wrong information, too often, and incorrectly – long before I saw such issues in web analytics. I started to learn and appreciate business analytics. Understanding how a business is run is an important aspect in web analytics, in my opinion, at least.

Not every night auditor should morph into a web analyst. Night audit is the major jumping off point into management. (Several of the night auditors I trained have long since gone on to run their own hotels, and night audit is an important catechism in hotel economics.) But, there are root skills in night audit that are incredibly applicable to web analytics.

Something to think about when you’re reviewing resumes, is all. 🙂 You wouldn’t expect that sort of relationship, I suppose, but I think it’s neat.