Data Driven Diversity + ROI

A superb case-study I just discovered that was published earlier this summer, outlines many of the strategies EqualTogether is working on enabling employers to seize—and, huzzah, make measurable strides from! Private-facing functionality for employers to see how their employees performance reviews fare by age, race, and gender, are among the powerful Employer Dashboard tools slated for development in the year ahead. 

A great snippet from the article on how employers can act on diversity analytics to see a quick returns, is below:

One of our customers shared a story with me recently. Their VP of Culture and Diversity was puzzled that despite hiring  a more diverse workforce, their minority ratio hadn’t improved. By digging into their full range of data and quickly analysing results for different locations, teams, roles, tenures, pay grades and more, they were able to uncover and pinpoint the exact cause of their challenge. They found that  three groups of specific minority employees were walking away faster than they were hiring. Diverse employees in a certain department and role, with a certain age and tenure, were more likely to resign. They were then able to cost and implement programs to address these very specific groups, and get quick results. More importantly they were able to use evidence to explain this to their executive leadership team.

By having a clear picture of the overall health of your organization’s diversity levels, you can identify areas for improvement, then implement diversity programs with laser-guided precision. By tracking progress over time, you can demonstrate the ROI of your efforts.

My sole "nit" with the article, is that they reference gender equity as "the female ratio." This just feels abrasive. Why? Because first and foremost, it demonstrates a poor understanding and subsequently, a superficial plan-of-attack around rectifying gender imbalance across roles and throughout a workforce. 

Gender inequity isn't just about getting more women on staff, or more women in specific roles. It's about balance. It's about ensuring that fathers on staff receive the same opportunities in schedule flexibility to tend to parenting matters, as mothers. It's about ensuring that men who get promoted, aren't just coming from the office cliques that watch sports & chug beer together, or participate in other, innocently gendered, unofficial team gatherings. It's also about ensuring that the pool of admin assistants and other assistive roles, is well balanced between men and women—and that (as is often the case) it's not mostly a group of attractive young women.

Targeting superficial and poorly understood KPIs, rarely works. Hacking ecosystems is what gets results. Not simply establishing a problem, with a follow-up targeted metric identified as "problem solved!"

Yes, when the oil tank in a car runs dry, that's a problem—but it's a problem because the piston-rings need lubricant to carry up through the cylinders, lest the friction caused from a dry piston's travel cause the metal parts to overheat, bulge in the process, and eventually seize. Which is both dangerous at-speed, and really expensive to repair. As a mechanic though, I will admit—it is always fun to pull a piston with some gnarly seizure-skids on the side, and a toffee-twisted/shattered crank-arm to match. :) 

Groupon Is The Latest To Release Diversity Numbers

It's been a slow several weeks, but on Friday Groupon emerged as the latest in this Summer's flurry of Tech companies to release their diversity statistics. With ~10,000 employees nationwide, that's a healthy chunk of a workforce to receive numbers on.

12% of Groupon's leadership are women, and 18% of their Tech workforce is women. Those numbers I admittedly find to be shockingly bad. Even though the claimed percentages of women tech workers were also 17% for LinkedIn (~3,300 employees) and 10% for Twitter (~3,000 employees). Facebook, Salesforce and Yahoo! were all tied at 15%. Each has ~4,300, ~3,500, and ~6,200 employees, respectively. Groupon having ~10,000 employees though, I'd expect to have better numbers. Well, the only way to go from here is up!

Reporting Round-Up

Google was the first to lead this Summer's pack of diversity releases with their May 28th blog post. Google employs ~27,000 in the US, and their numbers are kind of all in the above described range, too. Salesforce was a quick second to follow, and their numbers were near identical.

Leadership is where statistics continue to remain the fuzziest to me, because almost none of these businesses have given concise (or any) parameters for the three classification buckets everyone seems to have universally adopted in reporting on job types & hierarchies—Tech, Non-Tech, and Leadership. Facebook claims 23% of their “Senior Level" folks are women, Twitter claims 21% of their leadership to be women—Pinterest reported 19% of their leadership to be women (in a ~500 employees company), LinkedIn reported 25% (~3,300 employees), and Yahoo! reported 23% (~6138 employees). 

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Phlebotomists, Umpires, and Web Developers: Oh My!

I have no idea what a "Phlebotomist" is. None. So I thought it'd be fun to start this article off with that, and of course look it up later. 

As medical diagnosis have their own mind-numbing classification system of numbers—ICD9—so do occupations. Meet the US Federal SOC system, where Pathologists, Proctologists, and Veterinarians have a neat and ordered presence within the greater-whole of American employment occupations. Umpires are mentioned, too. Social Media Marketing specialists or Data Scientists? Nope. 

Grinding, lapping, polishing, and buffing machine tool setters, operators, and tenders, metal and plastic have their own code, and are clearly distinguished from 7920 51-4021 Extruding and drawing machine setters, operators, and tenders, metal and plastic. 

Shown in the image above, are Detroit factory workers hard at work grinding, lapping, polishing, and buffing engine blocks, in Diego Rivera's epic Detroit Industry mural. Rivera painted the mural between 1932 and 1933, when dozens of classifications for machine operators of all varieties, mapped well to the occupational landscape in our country.

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Room To Improve... A LOT!

Shown above, is LinkedIn’s EEO-1 filing from 2013. It’s what the data from their recent diversity numbers release was pulled from.

The numbers are current, to probably sometime in December of last year. They’re 6mos off. The design of the form is typical for government compliance filings—how they taxonomize race, is especially puzzling to me. Moreso, the segmentation of job types is mostly irrelevant to most industry sectors—as with Muzak, it's a "jack of all, master of none". 

We can do better than this. We NEED to do better, than this. Real-time reporting and benchmarking ourselves by numbers, is how our own industry sector rolls—Tech. We’re not going to change without data to measure our methods, because otherwise we're just shooting solutions into the dark. Likewise, speaking specifically to the Tech sector: if we can't even go for a jog or get on a scale w/o an app to track that we did it and how we did... I think today's Diversity efforts can be best likened to that gym membership everyone buys January 2nd of each year. 

As HumanAxis' first project, EqualTogether is ready to be that tool. Being real, there will never be any "there's an app for that" solution to solve for social woes as complex as workplace inequality. EqualTogether is not seeking to in and of itself, fix the inequality woes. Instead, we're seeking to put a measurement-platform in place as a first-step, through which all subsequent solutions can be measured from.

The latter, being most critical. EqualTogether’s program is multi-faceted, but the public-facing real-time reporting of HR data is a sweet-spot we’re excited about. If you’d like to contribute as an investor or technology partner, please—contact us!