The stats are in

Like major league baseball managers, sales managers need access to a wide range of metrics to manage more effectively.

by Todd Youngblood

Most sales managers measure the performance of their reps based on a single number, revenue production. Some use three or four metrics including things like calls made, proposals submitted, profitability and growth rate. A very few use as many as a dozen.

By contrast, any 9-year-old with Internet access can instantly get 109 up-to-the-minute indicators of how well each member of a major league baseball team is performing. Can you imagine a professional baseball manager who uses only one metric — like number of wins — to manage the team?

So, how many metrics of sales performance does a bona fide sales manager really need?  Fundamentally, the answer is, more than you’re using today. Consider the following scenario.

You just volunteered to manage a little league baseball team. Maybe you played the game yourself at age 10 or so, but assume that for the most part you have no idea what to do. (By the way, even if you know little or nothing about the game, the analogy will still be quite clear.)

One of your first tasks is to decide on the batting order, the sequence in which the kids step up to the plate and attempt to hit the ball. Having no metrics at all, a random decision is the only choice. That is, the success of your first management decision will be based purely on luck.

Change the scenario. Add a metric. Assume that you find a listing of last year’s batting average for each kid on the team. Now you know the percentage of time each batter will likely get a hit. You can now make a better batting order decision. One sensible approach would be to put the kid with the highest average first, the second highest, second, etc. That way, the best hitters have a greater chance at getting more turns at bat. Other approaches — based on your data — could also make sense. The point is, your decision is no longer random. Success is no longer based purely on luck.

Change the scenario again. Add a second metric. Assume you also find the percentage of time each kid actually got on base last year. This is different from batting average. In addition to actually getting a hit, a batter can get on base by drawing a walk, getting hit by a pitch, or on an error made by a fielder on the other team. You can now make an even better batting order decision.

For example, put the kids with the three highest on-base percentages up to the plate first, second and third. Put the kid with the highest batting average up fourth. Doing so increases the odds that your best hitter will go to bat with three runners on base, thus increasing your odds of scoring more runs. One metric yields a better decision than no metrics. Two metrics yield a better decision than one.

The scenario can continue to change. What if you also knew each player’s stolen base percentage, runs batted in and extra-base hit percentage. Each additional metric enhances the manager’s ability to make a better decision.

Now, shift gears from the local little league. How many metrics does a real baseball manager use?  Major League Baseball’s Web site (www.mlb.com) lists 109 distinct measurements of individual performance. Since both individual and team metrics are important, it’s really twice that, or 218. Also, in the real world, they consider right-handed and left-handed pitching, so it’s 436. Then you have day games and night games (872). Then there are those other measures that aren’t published on the Web site. You get the picture.

Big league baseball managers use literally thousands of metrics, along with the possible combinations and permutations. They do so because they are committed to excellence. They do so because their competition is tough. They do so because each additional metric enhances their ability to make good management decisions. Metrics help them predict what is most likely to happen on the next pitch, which in turn enables them to maximize the odds of having the right player in the right place at the right time, anticipating the right thing.

To further reinforce the point, consider Major League Baseball’s Oakland Athletics. Since 1998, they have been extremely aggressive in applying process engineering and statistical analysis to winning baseball games on a tight budget. Their total budget for player salaries is less than one-third of the New York Yankees ($57 million vs. $180 million). In 1999, Oakland ranked 11th of 14 in the American League in terms of total salaries paid to players and fifth in the number of games won. In 2000 they were 12th in salary paid and second in wins. In 2001, 12th and second again. In 2002,  they were 12th in salary, but first in wins. The Yankees spent roughly $1.8 million for each of their wins. Oakland spent only a bit more than $600,000.

Not only does extensive, aggressive use of metrics produce excellent results, it also dramatically decreases the investment required to do so.   

Now, back to the original question. How many metrics of sales performance really are optimal?  It’s the same as before, more than you’re using today. Every additional metric of sales performance enhances the sales manager’s ability to make better decisions.

Here’s an action plan. First, clearly and explicitly define your sales process. Write down all of the steps. Flow chart it. Make it as clear as the rules of baseball. Next, figure out how to measure each step, begin collecting data and analyze, analyze, analyze.

Look especially close at the numbers for reps who deliver the most revenue. What are they doing more of, more often than the rest?  Show those numbers — the documented, quantitative proof of what really works — to the rest of the sales team. Make sure they understand that executing certain activities at a certain frequency increases the odds of making a sale. Repeat this “Sales Process Engineering” for as long as growth in sales is important to you and your company. Keep adding metrics. Keep improving the process.

Don’t have time for that much effort?  Maybe your competitors will continue to manage like little leaguers.

Todd Youngblood is managing partner and CEO of The YPS Group Inc., a sales process engineering and sales training firm. The YPS partners are all obsessed with the sales productivity of their clients. He can be reached at , or at www.ypsgroup.com. To find out how your sales team compares to other distributors, click here.

This article originally appeared in the November/December 2003 issue of Progressive Distributor. Copyright 2003.

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