Two issues back, we reported on findings from a Temple, Barker & Sloane study of the use of scanner data by consumer products firms (QMRR, November, 1989, p. 8). One of the study's most important findings was that many of the companies felt they weren't getting as much out of the data as they could be, for two primary reasons.

First, the sheer volume of information made it difficult to perform lengthy analyses - just when one batch of data had been examined, another came along. Second, several survey respondents said that their companies hadn't committed enough personnel to data analysis, and that the employees who were involved lacked the training and experience necessary to squeeze the most from the numbers.

Bottom line: there just aren't enough qualified people available to analyze the data.

Linda Burtch would agree with that assessment. She is vice president of New York-based recruitment firm Smith Hanley Associates, Inc., and she says that marketing researchers with a strong knowledge of multivariate analysis and other statistical areas - which she calls "marketing scientists" - are much in demand with the major packaged goods and other large companies and organizations she recruits for.

"Many major marketing organizations today have an unprecedented amount of data available from both existing and new sources, but they're hard put to analyze it effectively - mostly because of the pressing lack of qualified marketing scientists," Burtch says.

"Technology gives us all sorts of fresh data, on who's watching what, ads seen, brand loyalties, buying patterns, you name it. The truth is, however, that most companies are still unable to make good use of it, to find out, for instance, how effective their advertising really is or how to improve the targeting of their direct mail. The recurring problem has not been inadequate technology, but the fact that there are still not enough experienced statisticians to clean up and analyze the vast amounts of data."

She says she began to see the potential for a shortage about five years ago, when technological advances began to make huge quantities of sophisticated data available to companies. More and more, statisticians began popping up in market research departments.

"In looking at the marketing research groups within companies I found that there were always one or two people in a group who knew a little bit more about the computer, and about the statistics and the database, beyond just cluster and factor analysis. As I saw these research groups growing, it was clear to me they really needed somebody trained to manipulate databases. It was fairly obvious that they were really not answering some of the questions with the data that had become available to them."

Estimating that there are fewer than 100 true "marketing scientists" in the field today, Burtch says that because of the shortage, qualified people entering the job market are able to command high starting salaries.

"Someone with a B.S. in statistics from a good college can start at $30,000 a year," she says. "All of our clients are willing to train these people in the marketing area, but anybody that goes on the market with a couple of years experience on the quantitative marketing research side is very valuable."

What's the solution to the "problem?" What can be done to increase the supply of qualified people? Burtch says the respected business schools must develop stronger quantitative programs and make more statistics-related classes mandatory ("The MBA's avoid those classes like the plague," she says). And the statistical schools should realize that entering business with a degree in statistics is a viable option.

"Most of the statistical schools don't realize the demand for their people to get into marketing applications. They're so busy churning them out for the more traditional statistical applications that they forget all about business applications."

They do so, she says, primarily because few of the professors possess a business-related background, which adds a bit of a Catch-22 to the situation, because how can they teach something they have no experience in?

With no easy answer available, Burtch says companies will have to rely on their ability to snare those who are qualified and train them accordingly, because the need for people to make sense of the numbers can only increase as the data gathering technology advances.

"As competition increases, people are going to have to use this data correctly, and unless they get people who understand the ins and outs of data analysis, they could be making some major mistakes. It's very costly to use this data and I'd be a little fearful of hiring people without the appropriate skills and having them make decisions they shouldn't be making.

"But on the other hand, you have to weigh that danger with the danger of letting your competition run over you because they have a better person in there analyzing the data. It's a double-edged sword, because while the data is complex and voluminous, it can't be ignored as too complex, because the competition may be using the information, and if you ignore it, you could be left behind."