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Last month, the Wall Street Journal published a provocative article entitled, Data is the New Middle Manager. The major focus of the article is a recent phenomenon taking place in startups: Forgo hiring middle managers by granting employees total access to their relevant performance data.
Our first analysis of the article extrapolated its findings specifically within the inside sales sector. Today, we take a broader focus: Employee engagement.
How Data Science Can Save Employee Engagement
Let's look at an important excerpt from Christopher Mims's article:
Now that every employee can have the tools to monitor progress toward any goal, the old role of middle managers as people who gather information and make decisions doesn’t fit into many startups. Nor do the leaders who remain need to poll middle managers to find out how employees are doing, since transparency and accountability are the essence of the data-driven company.
Using this quote, I'd like to posit the following thesis: Big Data will save employee engagement by giving each employee a better sense of personal ownership over his or her performance.
I've worked at two startups: One silo'd my performance data, while the other gives me total access to it. Or, put another way: At my prior job, my manager told me how I was performing. At my current company, a poster child of the data-driven startup, I get my performance data straight from the source.
The two main ways Big Data can save employee engagement: 1) Mitigate biased performance appraisal. 2) Cut out the middle man.
How Data Science Mitigates Bias
A recent article from the Harvard Business Review gets down to the brass tax of this issue. Human beings are inherently flawed evaluators of other human beings. The biggest finding: How a manager evaluates an employee says more about that manager than the actual employee. And if you don't think employees at organizations all over the world leave performance reviews muttering that under your breath, spend 15 minutes at a local Happy Hour.
The detrimental effects on employee motivation here are unfortunate and a major lynchpin in the argument for switching to purely data-driven performance feedback.
How Data Science Removes the Middle Man
We'll cover this more in-depth later, so I'll reserve this section for some anecdotal evidence. In my current role as Ambition's Marketing Director, I have access to all the data on our Marketing efforts from Google Analytics and Pardot. And I experience data-driven impacts on engagement every day.
At the positive end of the spectrum, there's the jolt from seeing a major spike in daily site traffic or inbound leads. And at the negative end, well, a few sub-average days in a row on my numbers turns me into an ornery, feral, but very productive employee until things improve. It's not speculation. For me, personally, data is without question the most consistent driver of my engagement at work.
How Technology Drives Employee Engagement
In 2014, Gallup reported that only 30 percent of American employees were engaged at work. That's an astoundingly low number. The major objective of Ambition is to improve employee engagement in the sales, marketing and customer service professions. How so? By giving them a greater sense of ownership over their performance.
And it's working. Largely due to the same psychological factors that make social media such a powerful workplace distractor are what make data a more powerful engagement engine than a manager. #1. Social Interaction Theory. #2. Intermittent Positive Reinforcement.
Social Interaction Theory
Read about this theory, because it's the most powerful argument for big data saving employee engagement. The gist: Humans are drawn to online communication because it's less taxing on them cognitively and emotionally. Why? When you communicate in person, your correspondent can see your emotional reactions to the conversation.
In online communication, the computer is your neutral communication partner, ignorant to your visceral emotional response, buffering you from the communicator at the other end of the digital world.
Big Data compounds this effect. Not only is the communication about performance online, but the communicator is wholly indifferent to you, the employee. My boss can fire me. Google Analytics can't. As a result, checking my performance data on Google Analytics feels like a much safer exercise than, say, going to my boss's office and asking for a review of my numbers. And, therefore, I'm prone to do it much more often.
Blame human psychology. For most employees, we much prefer digital, real-time performance data to a monthly one-on-one sit down with the boss.
Intermittent Positive Reinforcement
Data-driven employee engagement starts with the feelings of safety in online social interaction. It snowballs with the emergence of our second psychological theory, intermittent positive reinforcement.
In the case of intermittent positive reinforcement, studies indicate that variance in reward frequency is behind the addictive qualities of both gambling and Facebook use. Experiencing a variance in outcomes from certain behaviors, sitting down at a Blackjack table, for examplem, is what stimulates repetition of that behavior. And I've experienced it firsthand with big data in my workplace.
As Marketing Director, I monitor site traffic on Google Analytics and lead generation on Pardot. Typically, I check Google Analytics 3 times a day, whereas I check Pardot at least 10 times a day. Why the discrepancy? With Google Analytics, there's an element of certainty in our daily site traffic. I can estimate within a reasonable interval how traffic is doing, depending on the day of the week. Checking Google Analytics creates much more consistent outcomes.
With Pardot, there's a much greater element of randomness. Our daily lead generation volume is prone to fluctuate, spiking on days when there's no discernable cause and falling below expectations on days we have high traffic. That's also the reason I refresh Pardot at least 10 times a day. Some days I feel like I just won at blackjack, while other days I feel like I've gone bust. My dealer: enterprise software.
Data's Role in Employee Engagement
A keypoint: Using data science to inspire anxiety-driven employee engagement will backfire. Why? The war for talent. Don't expect elite performers to react docilely to a work environment fraught with fear and anxiety.
Companies that try a fear-based approach to data-driven employee engagement can expect their top talent to disappear to a competitor at the first opportunity. In contrast, companies that focus on employee empowerment will have their doors beaten down by qualified candidates.
A Data-Driven Future for Employee Engagement
The prediction: Big data is the sleeping giant that can crush the ongoing epidemic of disengagement at the workplace. It's key to remember that, as employees, we are at the mercy of own own psychology. It's hard to ignore urges to check social media and even harder to ask managers to confront us with our performance data.
Data for the masses is the most promising way to improve employee engagement. In the very near future, I predict we'll see more organizations fighting technological distractions with equally compelling technological visualizations of performance data. Thanks for reading, and feel free to contribute your thoughts on this subject in the comments section below. Now if you'll excuse me, I have to go check Pardot.
Ambition: Sales Motivation & Performance Management
Ambition clarifies and publicizes real-time performance analytics for your entire sales organization. Using a drag-and-drop interface, non-technical sales leaders can build custom scorecards, contests, reports, and TVs.
Ambition is endorsed by Harvard Business Review, AA-ISP (the Global Inside Sales Organization), and USA Today as a proven solution for managing millennial sales teams. Hear from our customers below.
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