I decided to make an important point using a story that’s been all over the news this week.

In the world track and field championships in Berlin, the women’s 800 meter dash was won by Caster Semenya of South Africa.  There’s no question about that, just as in most sporting competitions, especially with advanced technology, there’s almost never any question about who wins and loses, there is a “right” answer, and sometimes it’s a tie, not often, but sometimes.

The reason this story made news, initially, was because some have asked whether Caster Semenya is a woman.  But that’s not why it’s staying in the news.  As this article explains, the real reason this story persists, is that it turns out that in about 1% of the population, it can be very difficult to reach a conclusion, despite hormonal, chromosonal, and even physical appearance tests.  It makes me very sad that this athlete is making world news because their gender is so hard to determine, and I sincerely hope that she proves to be a woman (and that people feel comfortable with whatever standard is used) and that she can keep the gold medal she was awarded on Thursday.

There are other cases in sports where there isn’t a clear and obvious answer, even with technology.  Did the tennis ball going 110 miles per hour graze the in/out line when it bounced?  Did the football player have possession of the ball before it was knocked out of his hands (making the difference between an incomplete pass and a fumble).

Math problems have right and wrong answers, and when I was in school you could look in the back of the book to immediately learn whether you got the right answer to the math problem.  English essays, by contrast required some waiting, and even when the teacher assigned a grade, you couldn’t really go back to them and say “you’re wrong, this is an A paper, not an A minus paper.”

The same is true in business, but that can be both good news and bad news.  Something like sales is in the category of right and wrong answers for most businesses – how much revenue did we bring in this month?  We wanted to sell 15 more units this month than we sold last month, yes, or no, did that happen?  But how do you know if marketing is really helping sales, for example?  In some cases that’s really hard to measure.  Even when people try to quantify something such as customer satisfaction with a survey, how do you know you are asking the right questions, or if there are right and wrong questions?

I often see people write down goals along the lines of “Better revenue” (I have not seen that exact one, but it works for the example) and I will ask what “better” means, and the person will often say something like “more”, and then I will follow with an array of questions, how much more? is all revenue the same?  are there categories of revenue that are easier for us to get (lower cost of sales)? and so on to help them get more specific so they can have clear answers that can make it easier to make decisions about when things are going well, or not so well.

My point is to be as quantitative as you can in setting your goals, such as 24% increase in revenue, and be as specific about it as you can (so it might be a 35% increase in North America, 15% increase in Asia, and 12% increase in Europe that makes up that overall 24%).  More importantly, attach metrics for what causes an increase in revenue.  a 24% increase in revenue coming from an 11% increase in marketing spending is very different from coming off a 35% increase in marketing spend. Of course this applies to lots of areas of work, not just sales and marketing.

Be specific where you can, attach related metrics to one another to track the causes of changes in performance, and finally, keep asking if you have the right metrics (do you have confidence in your customer satisfaction survey questions, and why?).

-Ric