Sales Success Can Now Be Predicted

Three years ago a Fortune 100 pharmaceutical firm approached us to see if they could better predict sales success. They employed 278 sales representatives in the USA and this division had reached annual billings of $1.1 billion. The first thing we suggested doing was to conduct a Top/Bottom study of their sales force. This is the age-old method for determining what, if any, skills differentiated top sales people from those performing at the bottom of the sales staff. We psychologically profiled the entire sales force and correlated this psychological information against the individual's actual sales performance. As predicted, we were able to identify five key areas of personality, which were held by the top performers and were absent from those performing at the bottom.

In fact, two psychometric profiles emerged as top sales profiles. One we called the Entrepreneurial profile, because this personality was high energy, lacked sensitivity to rules and guidelines and was highly driven to persuade others. The second profile, and by the way, the more successful profile, we called the Systematic profile. These people were very tenacious in following through, were rules driven, service minded and received their gratification from educating and helping people rather than through direct persuasion.

For many years now the psychological community believed it knew exactly what personality skills were required to sell, regardless of the industry or product/service. However, several years back, in sifting through the myriad of data available on this subject, including that held in our archives, a trend was emerging. The trend seemed to suggest that rather than identifying the skills required for achieving success, it was simply uncovering those who would fail to succeed in sales. The more we probed into the data, by collecting customer feedback on the performance of those hired for sales, the more evidence surfaced supporting the trend.

The question we then had to ask was why this reversal in data interpretation? We studied and studied the data and the way the information was collected and analyzed. In our infinite wisdom, we could not understand why the data did not hold up - meaning, why was the data inconclusive in predicting the sales success and only valid in understanding "who wouldn't be successful?" That is until one day our client educated us.

We thought we had the answer to the golden question posed by our client, "what skills differentiate top from bottom performers?" Little did we know, we did not have the answer. After a year of helping this firm screen sales representatives who matched one of these model profiles, the feedback was disappointing, to say the least. Just like the years of data we sifted through earlier in the company's life, we were very helpful in recognizing who would not perform well in sales, but there was very little insight into who would perform well. If we did not recommend the person for hire, 9 out of 10 times the person performed poorly in sales. However, if we did recommend for hire, the best that occurred was 60% of this population performed at a top level. Statistically, we should have been very happy with these numbers. Professionally, we were quite disappointed. Back to the drawing table.

A second analysis took us in a new direction. This time we invited the customer to research with us. After days of sorting through study material after study material, we uncovered the answer. In fact, we uncovered the answer to the question, which puzzled us for years - "why couldn't sales success be predicted with real certainty?" The answer is the study methodology employed. For years, the Top/Bottom study approach was effective. But why for years and not today?

Simply, the Top/Bottom approach does a wonderful job at understanding what worked yesterday, but was miserable at predicting what would work in a changing marketplace. Think about it. Was the sales market much different 20 years ago versus 15 years ago? For those of use who remember that far back, there was no difference. Ask that question today; "has sales changed from 5 years ago to today?" Unless you've been under a rock, your answer would be a resounding - definitely. Looking at what was effective yesterday does very little to determine what will work today and tomorrow.

Now with this new understanding, we embarked on developing a profile that would predict success in today's turbulent marketplace, one full of change. This time, instead of taking a traditional approach, we forged a new horizon - we went to our customer's customers and asked them what they would like in a sales person who would be calling on their account? We visited 100 international, national and regional firms that were either customers of our customer or were firms with whom our customer would like to do business, but to date has been unsuccessful. We asked customers about the personality they would prefer to work with, what levels of decision making authority they would need, what industry knowledge was necessary, both the client's industry and pharmaceutical industry, and more.

Armed with this information, we constructed a personality model, which we call "the customer created model". We designed personality testing to assess against the profile and put a working model in place two and one half years ago. The results have just been completed and they are amazing.

If the sales applicant matched the "customer created profile" within a 3% deviation, they inevitably rose to the top of the sales force, with sales equaling 375% more than the average. And as the applicant's profile deviated to a greater extent, there was a corresponding drop in sales performance. In fact, if the applicant's profile deviated from the model more than 15% +/-, their sales performance fell to the bottom of the sales force, selling at less than half the average sales production.

Surprised? Yes, we were. However when you think about it, we really should have known the outcome because all we did was ask the customer what they wanted and then gave it to them. It doesn't take genius to understand that! Sometimes the simplest ideas make the most sense.

We then took this "customer created profile" and tested it in other industries, staffing services being one of them. We had to fine-tune the model a bit because customer requirements were slightly different, but the power of understanding the customer and their requirements works just as well for staffing firms as it does for Fortune 100 firms.

Wouldn't you like to have the sales staff that could perform like these did?

If the sales applicant matched within 3% deviation, average sales were $1,050,000. When deviation varied at 6%, sales average fell to $778,000. At 10% deviation, sales average was a respectable $565,000. At 15%, $290,000. The company-wide average for all sales staff was $296,000.