Category: Sales Management

“The next four weeks will feel like taking a sip from a fire hose!” I remember the trainer telling us on the first day of sales training. It was 21 years ago. I had just landed my first real job, in sales for a large software company. He was warning us about the onslaught of information he was about to deliver. All I remember is wondering how I would take it all in and make sense of it.

Today, we have more data at our disposal than ever and less time to interpret it. Reason being, we have more tools than ever to observe, measure, and record information. Facebook was started as a quest for one crucial piece of data: which young women on the Harvard campus were single.

Using the same tool, we as users, measure the popularity of every picture and hilarious or profound message we post. Companies also analyze and record what we post, like, and view. Again, the net result is that they have more data on us as ever. And, need we speculate on how much of our personal information the government has?

At work and at home, we tell ourselves that more information gives us more insight. We make better decisions, and have better connections with others because of it. We reason that simply having more data on the actions of employees and consumers must , in itself, prove it’s value.
It’s this need to make sense of all the data that can cause us to betray ourselves and others.

Measurement to Metrics – from the essential to the absurd

Measuring as a way of collecting data has been the key to humanity’s survival. How else would early man know how many buffalo to bring back for the tribe?

Today, you car’s speedometer keeps you from sailing over a cliff. Your alarm clock lowers your likelihood of needing unemployment benefits. We put our lives in the hands of measurements every time we step on plane. I rest assured knowing somebody knows what all those gauges mean!

Sports, it can argued, are essentially a form of measurement. Which team is better than which? Take a peak at a replay of an old football or baseball game and what will be missing from the screen? Many of the stats we see today (eg Yards per catch, on base percentage, etc). Heck, you may even be hard-pressed to find the score! Given our propensity to bet on sports, a whole industry providing “valuable stats” is sprung into being. You now can know how your favorite football team is likely to perform coming off Thursday night loss, on the road, in the snow.

Measurement and the collection of data has even seeped into our art. We no longer have talent shows. We have talent competitions in which the TV viewers rate performances. Why? Because we can! When watching a TV performance, I’ve never wondered what the rest of America is thinking. Call me a Luddite! Perhaps the fact that we have access to new information implies it must be important?

Thanks to technology, we have the ability to measure more than ever at work as well. Some of us may not be aware that spreadsheets were actually created on paper at one time. Today, there’s no edge of the page to prevent us from creating more columns for more things. And, since we have computers to do all the calculating, we can make new measurements combining two or more current ones. This beckons us to increase the complexity of our measurements.

Over time, we’ve replaced “measurements” with the more sophisticated sounding “metrics”. In the course of performing our jobs, we’ve begun to measure many more things. Salespeople arent’t just measured by their sales. They’re measured with things like sales call to close ratios and calls per day. Physicians aren’t measured by how many patients they cure or see. Their performance is measured in RVU’s or relative value units (a way of determining how valuable the work they do is to the hospital).

So, we live in a cycle of ever-increasing metrics, which create more data, which in-turn creates the opportunity for more metrics. Clearly, we’re beyond the point of measuring for survival, but who cares? More data legitimates the need for more managers to analyze it. It gives viewers a reason to tune in. It tells how much we are “liked”.

Monet-tizing Data

American businesses have learned how to take the data gleaned from metrics and turn it into revenue, an act referred to as “monetizing”. YouTube is no longer just a sharing service for videos of amateur stunts or people’s cats. It’s a sophisticated tool for advertising to select groups of people. Your video watching habits tell advertisers exactly what ads to send you. Sometimes this works and you see a video for something you’d actually consider buying. Many times it doesn’t.

Statistical science gives us ways to compare information and make legitimate sense of it. The problem is that most of us are not scientists. In the absence of verifiable statistical methods, we still try to make sense of all the data we have. Smiling at our own genius, we often draw conclusions from information like someone who is walking backward in order to take in an Impressionist painting. I call this act “Monet-tizing”.

The nice thing about metrics and the knowledge they provide that they make you feel smarter. You now see correlations between things you never noticed before. Things make more sense, or so we tell ourselves. Stories abound about companies finding one crucial metric that helped them create a turn-around. They found the Monet painting in the data, aka. the meaning of it all.

Paradoxically, the more we want our data to tell us, the less it actually delivers. Daniel Kahneman’s Thinking Fast and Slow, is so insightful, that I don’t mind being the hundredth or so writer to reference it. In the book, Dr. Kahneman cites several ways that we commonly misinterpret data. He refers to them as cognitive biases. They illuminate why, after we collect our data, we often draw faulty conclusions. We may see patterns in the data that paint, for us, the picture we’re looking for.

In reality, our brains have evolved to find what we we’re looking for and disregard the rest, giving us a skewed view of reality. Sometimes, we draw conclusions when we don’t have enough data. In short, there are many ways we can misunderstand the information we have and it’s implication to our work.

Why We Need to Find Pretty Pictures

Despite technology, our basic needs of food, shelter and companionship haven’t changed. These needs aren’t the result of rational choices. They’re our needs as human animals, not human beings.

How well am I doing at my job? How much money will I make this year? How much closer am I to winning that promotion? These are the typical metrics we put above all else at work. I call these our core metrics. They feed our basic needs.

To achieve some desired level in our core metrics, we happily place more metrics on the outside world than on ourselves. This includes managers critiquing a growing list of metrics on their employees. The popular business mantra ,“I can’t control what I can’t measure” gets inverted to mean that everything measurable is controllable.

We rely on a multitude of external metrics to insure we deliver on our core metrics. Beneath all the data, however, we’re all still anxious sports fans, holding our hands in prayer, hoping we win the metrics game. We’re hoping that the next article we write explodes in popularity or our next business venture is an overnight success.

Measurement Madness

On a personal and deeper level. We often fail to realize that we look for, in measurements, self-validation. We want our efforts in our work to tell us that we have value. We want our work to prove we are worthy of praise, respect, love, etc. We crave what Cognitive Psychology expert Albert Ellis called, Conditional Self-Acceptance or CSA.

If CSA, were a mental illness, most of the World’s population would need to check into a health facility. We all have it, to some degree. Just as measurement can keep our lives on track, their overuse can derail us. Nicholas Nassim Taleb, author of Fooled By Randomness, believes that we always have only one true reason for doing everything we do. Everything else is fluff, or useless information we use to justify our decisions.

Simply saying to yourself, “I am a good at my job” without any supporting reasons probably seems irrational. Shouldn’t you have proof of your skill? Some backing evidence, perhaps?

Ironically, it’s the meaning that we assign to the “proof” we seek that is irrational. Saying to myself something like, “I must be popular to truly be a good writer!”, would actually be irrational. There are plenty of popular authors that I don’t care for. Instead, I can decide that I accept my writing as “good” without needing the approval of others. Even better, I could chose not to make my proficiency as a writer as a condition for liking myself.

Defining Your Own Metrics

Dr. Ellis called the willingness to accept oneself regardless of any faults or misgivings USA, or unconditional self-acceptance. It involves much more than being one’s own personal cheerleader. Instead, one discovers the beliefs that cause irational thoughts and disputes them. Perhaps the Monet you’ve created of yourself is based on erroneous or irrelevant information. USA allows you to throw it in the trash like a garage sale replica.

I’m not sure where the rush of data is taking corporations or consumers. We may be continue to be measured in ever-increasing ways at work. Our future social lives may be evaluated in more ways, not less, and there may be databases we simply can never remove ourselves from. What I do know is that we as individuals don’t have to let it define us. We can chose not to measure ourselves.

Sincerely,

Meaning2work

Ps. I’d also like to credit Srinivas Rao and his book: An Audience of One: Reclaiming Cretivity for Its Own Sake for providing the inspiration for this writing.