Free Clip from Managing IT: Metrics and Measurements - Measurement Effort vs. Importance

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This course was published via Pluralsight.

The level of effort you put into obtaining a measurement should be proportional to the importance of a measurement. For example, rating something between 1 to 5 requires a simple observation without expensive tools or a lot of effort. Rating something between 1 to 10 requires a little more sophistication since the scale is more granular and it becomes a little harder to get an accurate measurement rating. Something between 1 to 100 requires a complex method and/or tool. This level of accuracy is clearly more important, and the measurement just became more expensive to obtain.

Let's use running as an example. A casual runner may just take a quick glance at a clock before he starts and after he finishes. His accuracy is within a minute, which is all he needs. And his level of effort to obtain his rough estimate time is low and costs nothing. Someone who is thinking about racing competitively needs more accuracy, perhaps within a second. Purchasing and remembering to wear and use a watch affords her the ability to obtain the accuracy she needs. Some more effort is required, and it certainly has a small cost. An Olympic sprinter needs even more accuracy, down to the 10th or 100th of a second. For this, he needs to purchase an expensive stopwatch. He will also need to find someone else to time his runs. This level of accuracy requires a special single‑use tool and a whole lot of effort. Our casual runner could use a stopwatch to time his runs, but why? There's an expense to that and a lot of hassle for no real benefit. Our Olympic sprinter cannot take a quick glance at a clock or use a simple watch with a second hand to time his runs. Those times would be inaccurate and worthless. You need to apply the proper level of effort to each measurement based on how important the measurement is.

This course was published via Pluralsight.