Hi

This blog came into being as I found myself making more and more observations on the role managerial statistics could play in our work. And as I have lately been getting deeper into quantitative analysis at work, there have been quite a few very interesting things I noticed. I will try to share them with you, mainly so that I can get critical feedback on my methods and observations. Of course, for NDA reasons I will not be taking names of my company or its clients here. Neither shall any "data" be extracted or derived from my work.

Okay, now that we are done with the disclaiming bit, here are a few things to watch out for.

1. Take the context and source of data into careful consideration. I cannot over-emphasize this. It has been stated over and over in all the literature I have read that data taken out of context is just numbers, and drawing conclusions as such is suicide.

2. Do not assume applications of a given technique. In all probability it was designed for a specific set of conditions and you should factor in all the differences between the case you are reading and your own situation. A very common mistake of this sort: assuming that correlation determines causality.

3. Mathematical techniques must be followed to the T. It is common to see enthusiasts consider only the stated output of the calculation and plug in whatever comes in handy. Common mistakes of this sort are using non-normalized data and using unadjusted data (where normalization or adjustment are clearly called for). How does one know? Read, read, read. Find a crisp article that clearly states the usage of the particular calulation.

All said and done, I hope you find this blog easy to read and helpful, and that you will comment freely. The effort here is to make and realize mistakes in theory, so that the practice is perfect.

Proof of the pudding is in the eating.

A $24,924 million revenue company, ConAgra was taken for a spin by a civil engineering professor. It was 1999; ConAgra's brand Healthy Choice was promoting its products through a mail-in offer. The deal was that for every barcode from 25 cent pudding package, the buyer could redeem 500 frequent flyer miles from Healthy Choice (ConAgra). David Phillips, a professor at University of California, calculated that the miles far outweighed the 25 cents and set about collecting all the pudding he could find in the town of Sacramento, and even had more ordered through a store clerk. To avoid suspicion, he told people he was stocking up for Y2K.

Phillips ended up with 1,253,000 frequent flyer miles for $3,140. Enough for 31 round trips from California to Europe.

Brings the phrase "breaking the bank" to mind.

The importance of playing the numbers right cannot be emphasized enough in management. While much of business can seem like a gamble, and many times you have to simply play against odds in order to win, wisdom lies in knowing when to wing it and when to calculate. The best, of course, take as much guesswork out of the guesswork as possible. It can be called modeling, risk management or forecasting. Promotions, cross-selling, revenue and sales forecasting, evaluation of marketing metrics, web metrics, logistics and business planning in general are all realms that have a lot to gain from simple Excel sheets. It just boils down to using the right numbers correctly.

Our Pudding Man is currently using the frequent flyer miles, but earning them back 5 times faster than he spends. He donated all the pudding to charity, earning a $815 tax write-off.

And ConAgra? In 2001 they were hauled up for mis-reporting income from 1998 to 2001, to the tunes of thousands of millions of dollars. They have been also been indicted for employment bias against hispanic females, high salmonella count, spraying water on stored grain to show increased weight, besides having been to the brink of bankruptcy.