Stop Calling It “Real” Work - The Myth of Measurability

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Photo Credit Alexandra Sinn on Unsplash

**This article is part 3 of a 3 part series on “Real” Work - for a longer conversation on this topic, check out this episode of Uncover the Human - a Siamo Podcast

Myth #3 – Real Work is Measurable

This is a numeric spin on the other myths -if results are quantifiable, the work is real; if it isn’t easily quantified, it is a waste of time.

 

It’s easy to see the lure of relying on numbers, data, and measurements. Given the right data, we can make better strategic decisions more confidently with supporting evidence, and everyone benefits from good decision making. As the phrase “data-driven” buzzes throughout LinkedIn and Forbes articles, the pressure increases to find hard evidence to back our decisions, but this compounds the potential consequences of chasing data alone.


The most common pitfalls in putting data first fall into these main categories:

  1. We don’t have the right data (and don’t necessarily realize it) – let’s say we want to know what employees deserve maximum raises this year. Looking too narrowly, like only measuring someone’s in-office attendance, may not correlate to employee performance at all

  2. We are asking the wrong question in the first place – assume we are trying to enhance employee engagement, is it better to ask what would make people happy or investigate why people are leaving?

  3. We discount certain options because data is not readily available – take choosing between two potential CRM platforms, the newer one is not “road-tested” but advertises newer features, the older one has big name customers and many good reviews. Is this enough to write off the new platform?

  4. We wait too long to find data - searching for the right data, we experience analysis paralysis and miss out on major opportunities

Data can provide assistance (and comfort) when making difficult decisions, but if we want to gain maximum utility from it, we need to be ready to challenge our own assumptions about what the data means and what data we need.

 

Confronting this Myth

Separate assumptions from data

A particularly easy and consequential mental trap is the logical fallacy of “personal incredulity,” which is to say: I can’t see how that would be true, so it must not be. We may not immediately understand how a plane can stay in the air, but as we can see: it happens. Anytime we are making decisions because we can’t see how the opposite would be true and we assume it must not be, we could be shooting ourselves in the foot.

The trap of assumptions is easy to fall into, as we have to rely on our experiences and memories to guide us through any decision in life. Looking back, however, we have all felt the stomach lurch of those assumptions being harshly corrected. To avoid this fallacy, we need to look for more information and particularly search for contradictory information to long-held beliefs. When we challenge our own assumptions, we more easily determine what is “real” and what criteria can help us evaluate which of our efforts has the greatest true potential.  

 

Most of reality has not been measured…yet

For a long time, we had no data on whether people were engaged at work but with practice and diligence, we developed more sophisticated models to evaluate this previously “immeasurable” value. If we apply a more curious mindset to a decision facing us, we can find measurements and correlations for “softer” metrics we otherwise might have dismissed. This opens our perspectives about what creates value and thus what constitutes real, worthwhile work.

Similar to comparing a stalwart, existing CRM platform versus a brand-new player in the space based on reviews alone, the data we wish we had simply may not have been recorded yet. If we want to catch a trend early, we have to rely on criteria that does not have existing data.

 

Realize the value of subjective data, including gut feelings

When we look for hard and fast numbers, we often filter our data down to only tangible numbers like physical product dimensions, number of sales, company valuation, number of likes on a tweet, etc. While these metrics are useful, we often need to bring in subjective data points to complete the picture. Believing subjective data is too squishy to be informative is a denial of the reality that we rely on subjective data all the time.


Consider Amazon reviews - one person’s idea of “4 stars” may be entirely different from another’s, but with a large enough sampling size of reviews, we end up with a clear picture of how people feel about a product. In statistics, this the “Law of Large Numbers” - taking the average of a large enough sample of an experiment (in this case “what is the rating of this product”), you will close in on the “expected value” or the presumed “answer” to the experiment. Seeing thousands of reviews average to a 4.6 star rating, it’s easy to believe a product generally elicits a positive response.

 

Amazon compounds this subjective data with the addition of the question “was this review helpful?” Again, with enough positive responses we can feel more comfortable in the review, and vice versa if very few people found it helpful. Different people may find different information “helpful,” but seeing a picture of this subjective measure on-the-whole is a useful metric.

 

Author of Good to Great, Jim Collins, keeps data about every day of his life, divided into how many hours he spent working in different disciplines, plus a subjective number about how he feels about a day. This number is purposefully ambiguous. If he sees enough low numbers in a row in his subjective column, it’s time to change something. Not only can he see that trending over time, but he can find correlations with the other “hard” numbers he records on each day and gain ideas on how to adjust for a more positive result.

 

Keeping our primary focus on objectivity distracts us from the bigger picture. This is particularly when deciding how to spend the limited time we have on the planet.  Basing our decisions only on what is measurable and objective by the frameworks of others can lead us away from choices that align with our own values.

 

As a company, we may believe we care about our employees more than anything else, but when a recession hits, we lay off staff members first to reduce our cashflow. Taking cashflow as the most important priority is in conflict with our stated values (employees first), but it’s immediately measurable. Not only do studies contradict this choice, but we are choosing a path that moves us away from our stated values. This creates dissonance in those making the choice, and the inconsistency will be quickly recognized by all employees, reducing trust.

 

Values-based conflict arises in our personal lives as well when we chase only numbers, like deferring an opportunity to develop a career we love because we have an offer with a higher salary available now. The two potential salaries facing us may provide stark, contrasting numbers, but if we ignore our gut feeling on what we prefer, we end up suffering more in the long term. Trusting our gut to provide accurate subjective data takes practice and often feels scary as we are actively choosing to base a choice on ourselves alone. We have full responsibility at that point for the consequences, and we must work against voices in our head (and our close relationships) that will happily deliver an “I told you so” should we fail.

The perceived consequences will guide our decisions if we are not deliberate. We can quickly imagine the regrets we could have by not having a higher salary, but it is harder to feel the long-term regrets of living outside our values in the present (unless we have made that mistake before, of course). But even when we do see the potential regret, we need to access internal comfort in asserting that our values are important enough to guide our decisions. For this reason, it can be helpful to identify our personal values and goals so they can become more like “data” and less “squishy” or easy to ignore.

Summary

In changing how we evaluate what work is “real,” we have not changed wanting to see real results. Instead, we simply confront the limiting beliefs about what makes certain work “real,” and this allows us to change how we evaluate inherent worth. Connecting with deeper personal value provides us the space to pursue satisfying work and deliberately choose what we agree to do or not, without taking on unnecessary shame.

 

Practicing this deliberation creates a virtuous cycle in our lives, moving us closer to personal fulfillment and access to our full potential.

**For more of this type of content, or subscribe to the Uncover the Human newsletter or check out the rest of the Siamo blog

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Stop Calling It “Real” Work (Part 2)