The data in the US, “land of shopping and malls”, is staggering. In 2017, year to date, there have already been more bankruptcies in this sector compared to the data from all of 2016. Employment data in steadily declining, department stores alone reduced more than 100,000 jobs in six months (!) and they now employ one-third the number of employees they had in 2001. For a comparison, that is 18 times the loss of jobs in the coal mining industry over the same period.
I’m a LinkedIn power user. At Yale SOM I lived on LinkedIn: reaching out to global employers, training global executives how to be thought leaders, and teaching students how to search alumni and track opportunities. These days I use it only slightly less with more focus on building partnerships and teaching students in my online courses how to use it.
So I say this with much love and experience: LinkedIn is so ridiculously mediocre.
I can’t for the life of me understand how a company with so many users and Microsoft-backing still spends so much time trying to get me to spam my inbox.
Yet when I get those connections, LinkedIn makes it ridiculously hard to organize and keep up with those connections.
My connections are all parked in a feature-poor list. If I’m looking to connect with someone working in fintech in Seattle, the sort feature offers little to help me find them (when’s the last time you remembered a conference contact by their first name?) Even the search feature doesn’t work properly:
Yet when I want to search alumni from my school, I get this incredible, visual, search feature.
Why isn’t this feature replicated for contacts? If the point of LinkedIn is to stay connected to your contacts, why don’t they make it as easy as possible to find and visualize your contacts? (side note: What is the point of LinkedIn?)
Also, it’s worth noting that this is the result after they redesigned it to be more user-friendly.
Then there are all the attempts to get you to upgrade.
Not sure that’s the best way to motivate me to use premium.
LinkedIn is also pushing the online learning opportunities. There too I find their suggestions and course-dump lacking.
I have zero connection to digital arts or animation.
LinkedIn has all the resources, deep data, and millions of users. Yet these are the results.
LinkedIn, hopelessly mediocre.
Before you continue reading, reflect on the last bad manager you had. Remember how they made you feel. Remember the things they did that made your life miserable. Remember the incompetence. Remember that managers don’t get promoted to management because they’re good managers.
I know, it’s not pleasant. I’ve have some pretty awful managers too (but I’ve also had a billion jobs so it’s inevitable).
Ok. Now read on.
Enter all the startups ready to make managers lives easier/employees lives more miserable with algorithms to solve all the HR problems. The Wall Street Journal takes a peak into the future of management in How AI is Transforming the Workplace:
“Veriato makes software that logs virtually everything done on a computer—web browsing, email, chat, keystrokes, document and app use—and takes periodic screenshots, storing it all for 30 days on a customer’s server to ensure privacy. The system also sends so-called metadata, such as dates and times when messages were sent, to Veriato’s own server for analysis. There, an artificial-intelligence system determines a baseline for the company’s activities and searches for anomalies that may indicate poor productivity (such as hours spent on Amazon), malicious activity (repeated failed password entries) or an intention to leave the company (copying a database of contacts).Customers can set activities and thresholds that will trigger an alert. If the software sees anything fishy, it notifies management.”
Now remember your asshole manager. Imagine if they had access to this tool. Imagine the micromanagement.
(Side note: I wonder if employees get access to their bosses computer logs. Imagine that!)
Let’s keep going.
Another AI service lets companies analyze workers’ email to tell if they’re feeling unhappy about their job, so bosses can give them more attention before their performance takes a nose dive or they start doing things that harm the company.
It’s hard not to read that as an unhappy worker is somehow a threat to the company. Work isn’t all rainbows and unicorns. We can’t be happy 40 hours a week even in the best of jobs. Throughout our work lives we deal with grief, divorce, strained friendships, children, boredom, indecision, bad coworkers, bad bosses, bad news, financial stress, taking care of parents, etc etc etc. And sometimes that comes out in the course of our days spent buried in emails. The idea of management analyzing your emails on the watch for anything that isn’t rainbows ignores the reality of our work lives.
What data is the algorithm built on? What are the signs of unhappiness? Bitching about a coworker? Complaining about an unreasonable deadline? Micromanaging managers? What’s the time frame? One day of complaints or three weeks? Since algorithms take time to tweak and learn, what happens to employees (and their relationships with management) who are incorrectly flagged as unhappy while the algorithm learns?
Moreover, what do those conversations look like when “unhappy” employees are being called into management’s office?
Manager: Well we’ve called you in because our Algorithm notified me that you’re unhappy in your role.
Manager: Right… so … can you tell me what’s making you so unhappy?
Employee: I’m fine.
Not according to The Algorithm. It’s been analyzing all your emails. I noticed you used the word “asshat” twice in one week to describe your cubicle mate. Your use of the f word is off the charts compared to your peers on the team. You haven’t used an exclamation point to indicate anything positive in at least three weeks. The sentiment analysis shows you’re an 8 out of 10 on the unhappy chart. Look, here’s the emoji the algorithm assigned to help you understand your unhappiness level.
Employee: It’s creepy you’re reading my emails.
Now remember, you signed that privacy agreement at the beginning of your employment and consented to this. You should never write anything in a company email that you don’t want read.
And do companies who purchase this technology even ask the hard questions?
The issue I have with this tech, apart from it being ridiculously creepy, is that it makes some seriously bad assumptions. They assume:
- All managers have inherently good intentions
- All managers are competent
- All organizations train their managers on how to be effective managers
- All organizations train their managers on appropriate use of technology
- Managers embrace new technology
Those are terrible assumptions. Here’s a brief, non-exhaustive list of issues I’ve had with managers over the past ten years:
- Managers who can’t define what productivity looks like (beyond DO ALL THE THINGS)
- Managers who can’t set and communicate goals
- Managers who can’t listen to concerns voiced by the team (big egos)
- Managers who can’t understand lead scoring and Google analytics (from the CEO and VP of sales and marketing no doubt)
- Managers who can’t use a conference call system (technology-am-I-right?!)
- Managers with no interpersonal communication skills and lack of self-awareness
Maybe we can all save ourselves by adding a new question when it’s our turn to ask questions in the interview:
“Tell me about your approach to management. What data do you use to ensure your AI technology accurately assesses employee happiness?”
Maybe I’m just cynical. Maybe it’s because I’ve had a few too many bad managers (as have my peers.). Maybe I just feel sorry for good employees struggling under bad management. And maybe organizations should get better about promoting people who can manage (i.e. people with soft skills) instead of those who can’t before this technology is adapted.
Anyhow, to wrap up, this whole post has my feeling so grateful for the good managers I’ve had. The ones who got it right. Who listened, encouraged, and provided constructive feedback on all my work. And though I’m sure they’re not reading this post, a shout out to my favorite, amazing managers from two very different jobs: Kirsten and Cathy. They didn’t need an algorithm to understand their team performance and employee happiness. They had communication skills, empathy, and damn good skills that made working for them a delight.