Metrics for the Chief Information Officer (CIO) – It’s All Semantics
I will be the first to admit that I can be kind of picky about certain things. Hey, everyone has his quirks! Although I try not to take political correctness to an extreme – a fact that those who know me will attest to – I do cringe when I hear certain words used in a certain context or see grammar issues clouding up the intended meaning of a message. That said, I do have actually reasons behind my thinking; I’m not just some word-hating sociopath that wants to see Webster’s knocked down a peg or two. Here are a few examples of words and phrases that I believe have the potential to create the wrong kind of environment and the word or phrase that I would use in its place and why.
Maximize vs. Optimize
Back when I was a college CIO full-time, we would have revenue discussions around the need to maximize revenue. At first blush, that sounds like a perfectly reasonable goal until you start to think about what the word “maximize” really means. To many, the word means to get as much of something as possible and at any cost. Let’s take college tuition increases, for example. When I worked full-time in higher ed, we spent significant time attempting to determine what the right tuition amount would be for the coming year. When you look at how colleges are funded, annual revenue is made up of the number of students that want to come to your school times the amount of tuition that they pay.
If one wanted to “maximize” tuition increases, that would be easy! Just add a couple of zeros to the end of the existing tuition price and call it a day. Unfortunately, that would have the affect of decimating the college’s bottom line because no students would be able to afford to attend.
It’s just like sales. People selling goods want to find the optimal price point at which they can get maximize their bottom line. But, they key word here is “optimal.” The price may not be the maximum price, but we’re looking for the optimal price that will allow the company to achieve its goal of boosting the bottom line.
Efficiency vs. effectiveness
Suppose you’ve been charged with analyzing the current technical support structure in your company and have been told to maximize its efficiency with regard to resolution time. Now, let’s suppose you work for Dell and you’re on the support line that helps home PC users fix system problems.
To meet the goal that has been laid out for you, you have a really easy job in front of you! It’s simple: For every call, simply ship the customer a brand new PC that you know works. Let’s say it takes 5 minutes to collect the information from the customer. Once the replacement order is placed, it becomes a different department’s problem, therefore your first call resolution rate has now jumped to 100% and the time to resolution is now just 5 minutes.
Congratulations!
Wait, what’s that you say? The customers are still not happy and management is demanding to know why costs for support have gone through the roof?
Well, you see, that’s because, in the process of creating the most efficient process, you didn’t create the most effective one. Fixing a broken mouse by shipping a customer an entire new PC isn’t an effective fix.
I use an exaggerated example here on purpose to demonstrate what I mean. The goal here is that we want to make sure that effective processes rule the day. If they’re also efficient, great.
It’s really all about metrics
Although wording matters, in these examples, it all really boils down to metrics. If you’re measuring things the way things are supposed to look on an outcomes basis, you need to measure them the right way. Analytics like this define the how and the what and the words can help provide context.
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