If you’re a knowledge worker, i.e., a white collar worker, how do you measure your productivity?

Measuring productivity of manual labor is easy. How many X can Y do/produce in Z time? How many button holes can one worker punch in one hour? How many cars can this factory produce in a week? How many bricks can this bricklaying team lay on a curved surface in this particular pattern in one day? Calculations can get more complex, but it’s still generally easier to measure output when the output is a physical object or result.

Measuring the productivity of knowledge workers is often much harder. Not all knowledge workers produce measurable results, despite all the CFOs and management teams who would prefer it otherwise. How do you measure the contribution of one team member who over time helped convince another business to partner with yours?

Perceived Productivity

Whether knowledge workers are “productive” often comes down to how productive they feel. Researchers call this “perceived productivity.” It’s common in studies for researchers to ask knowledge workers to rate how productive they are, rather than try to measure it.

To be fair, it’s a little bit bullshit. I feel more productive when I work on an assignment that’s easy. I feel unproductive when I face a difficult project that requires a lot of effort to investigate. I feel less productive when I’m stressed about having to take my dog to the vet, but that doesn’t mean I procrastinate starting my tasks or that I work with less vigor. Rating perceived productivity isn’t precise or in many cases even helpful, but often it’s the only method we have.

Time on Task

Another way we can sometimes gauge the productivity of knowledge workers is by measuring time on task. It comes in handy for certain kinds of work, such as reading x-rays and CT scans or answering support tickets. How much time does a person spend reading a medical scan before deciding whether it contains an abnormality, and how often is the person correct? How many minutes, on average, does it take to respond to a support ticket, and how many follow-ups does it take to fully resolve the matter?

Measuring time on task can be useful, although it helps if the task being done is the same each time. There’s a huge difference between a support ticket that says, “I’d like a refund, please” and one reading, “All the data in my account disappeared and I desperately need to recover it. Help.”

Over time, maybe the results average out well enough, and you can get a sense of what a highly productive day look like, in terms of your response time. But you also need to how common it is for you to deviate from the average and by how much. And you should probably take into consideration the fact that your skills are improving with time, too. Is improving your skills the same as being more productive? Some would argue no. That’s up to you to decide.

Time in App

Another way to measure productivity is time on task or time in application. There are apps, such as RescueTime, that record time spent in different computer applications and websites automatically. There are also apps like Exist that let you pull together data from a number of different sources that you then classify, merge, and dissect in whatever way you want.

At the end of the day, you might see that you spent five and half hours in applications and on websites that are related to your work. That’s your productive time. You’ll also get a report of the number of minutes you spent in non-work apps and sites, which you might label unproductive time.

Unfortunately, the raw amount of time that your computer is open to a particular application isn’t a great indicator of your productivity. You can launch Powerpoint and spend three hours changing the typefaces and background colors of your slides. When taking a long-term look at productivity, however, time-in-application can be useful for spotting bad behaviors. Sometimes we genuinely don’t realize how much time we tent to waste when we read articles that are unrelated to our work or look at social media. Seeing a report of the actual time spent doing those activities can be a wakeup call.

Completed Intentions, Tasks Completed

How else might we measure knowledge workers’ productivity? We could look at the number of tasks that one intended to complete that day and did. We could call it “task completion” but I think “completed intentions” is better.

“Today I intend to send three emails with informational requests and finish a draft of a new article.” If I complete all my intentions, then I am productive. If I don’t complete them all, then I was less productive than I could have been.

If we want to look at completed intentions, we must first assume that we’re capable of coming up with intentions that are realistic for the given time period. You don’t want to oversell or undersell yourself. Also, while it might seem like you can easily rate each task at the end of the time period as either completed or not completed, there might be gray areas. Did you complete a task to email a contact if you wrote and sent the email but got a bounce back for a faulty email address at the end of the day? You technically completed the intention, but you didn’t further the task. So does it count?

Doing Unproductive Things Can Make You Productive

In knowledge work, measuring productivity isn’t always a useful exercise. Instead, it might be more informative to spend time figuring out how you contribute value to whatever it is you do. You might not be able to quantify it easily, especially if quality is a factor of your work and judging that quality is a subjective act.

Shifting focus from productivity to value contributions also shifts the focus from short-term to long. If your work is creative in nature, then you cannot be productive without also nurturing your creativity, and that can’t be measured and tracked in a day. If your work involves complex problem solving, then you probably want to keep your cognitive functions sharp through lifestyle choices that encourage it. You might also ask the deceptively simple question, “Will being more productive give me what I want?”

Pretending like the productivity of knowledge workers is something we can easily quantify and improve through work hacks is silly and can distract people from thinking about these weightier issues.

Image by tracy ducasse, CC.