Let's face it, despite the inclusive sentiments, workplace diversity coverage isn't easy. How do you extract themes you can apply to your own projects?
Diversity is highly personal and tied to work cultures. Yes, the tech industry has a diversity problem. But when you take workplace culture into account, what works in one situation might not fly in another.
This is one topic where we can all stand to learn and improve. Here's my review of diginomica's recent workplace diversity pieces - with lessons for enterprises to consider.
1. Designing-for-all leads to better products and services
Derek du Preez just got back from RedMonk's MonkiGras event, where accessibility and diversity issues were front and center (Lessons learned on accessibility, inclusion and diversity at RedMonk’s Monki Gras - listen up and take action).
Derek points out that with events, if you're able-bodied, you tend to think everything is well-designed, but that's not often the case. After noting that six out of ten U.S. citizens deal with some sort of chronic condition, and one in five of us are likely to have a disability at some point in our lives, du Preez writes:
The key thing to take away from all of this is that designing services for EVERYONE does not make a service ‘lesser’. In fact, it makes a service better. And designing for one group of people that need additional support, usually has positive benefits for all other users.
Examples? Derek cites "curb cuts," initially introduced in the US in one town because they were championed by a veteran wheelchair user. But as it turns out, many other use cases benefit from curb cuts, from people pushing prams to elderly people with reduced mobility: "A number of unintended benefits for other users occurred."
As I read through Derek's lessons from Monki Gras, I find myself wondering how many enterprise teams have accessibility experts? How many have that know-how on hand when they are designing new events or services? I think that's what Derek's getting at when he writes:
In other words we need to really start to focus on user need and do proper user research across a broad range of people, not just for the ‘stereotype’ of what we think people need.
2. Culture matters - but we need metrics too
Culture eats everything - strategy, technology. It probably even eats blockchain. As Cath Everett notes in Culture challenges on the digital agenda for 2019, culture is at risk of becoming a very fluffy topic indeed. Get ready: the culture consultants are waiting in the wings:
Company ‘culture’ is having a moment. Not only is it now being talked about at boardroom level as a tangible issue, but more and more consultancies are also springing up to advise leaders on how to get it right.
Despite all the hype, it's clear that something is missing from digital transformation. Everett: "A key problem though, according to McKinsey, is that as many as 70% of digital transformation initiatives fail to meet expectations." Which brings us back to culture. Bennett quotes Thomas Davis of Temporall:
One of the biggest barriers to digital transformation is culture, so there’s something about culture and people that organisations have simply not been getting.
When you toss waterfall aside for continual improvements, culture comes to the fore. Davis again:
It's not about a single digital transformation project with an end-date any more – it’s about being in a state of continual transformation and to do that, it has to be driven by culture.
But culture - and culture change - is notoriously difficult to measure. In the second half of the piece, Bennett gets into the progress being made on that front. It's early days, but it has do to with asking the right questions, gathering data with the help of AI/ML, and, perhaps, displaying "culturally-embedded KPI scorecards."
So how does measuring culture tie back to diversity? That's a longer discussion, but in this piece on the diversity and the accounting field, I cited this stat:
- A 2015 McKinsey report found that companies in the top quartile of racial and ethnic diversity were 35% more likely to have financial returns above the median for their industries; gender diversity delivered a 15% boost.
Then there's this:
- There is a clearer understanding of how living an “open” (as opposed to closeted) identity at work can improve productivity.
Madeline Bennett takes up the issue of ethnic diversity in Silicon Valley, pursuing answers from Facebook while framing the big picture. Mark S Luckie, former Facebook partnership manager, called attention to these persistent issues with “Facebook is failing its black employees and its black users”. Bennett:
There is general consensus that the points raised are indeed an accurate reflection of life at Facebook, and this no doubt is the case among many other organisations and not just in Silicon Valley.
And it doesn't stop at U.S. borders:
Racial diversity in the boardrooms of the UK’s top tech companies is lagging seriously behind the US. In the States, 17 percent of hi-tech leadership positions are held by ethnic minorities, compared to just three percent on UK tech boards.
Bennett writes that the lack of ethnic diversity in tech companies, from the boardroom on down, is not a talent pipeline problem. In the U.K, more ethnic minority students are taking science, engineering and computing degrees than white students.
The problem kicks in after graduation, where ethnic minority graduates in the UK are three times less likely to be in full-time work six to 12 months after leaving higher education compared to other students:
And if they’re not working in the technology sector, they can’t work their way up to take leadership roles at tech companies.
Bennett quotes Ashleigh Ainsley, who co-founded colorintech:
All available data suggests this is an issue, so armed with the stark reality of [ethnicity pay gap] data, firms might actually do something about it.
More diversity coverage highlights
- AI, meet accessibility - new potential for upping skilled employment - Martin has a fresh angle on applying AI to accessibility. "Technologies such as machine learning and AI are moving the goalposts in a way that can really play to the strengths of the disabled, taking away at least some of the need for skills in areas such as manual dexterity and opening up the number of ways their brains and intellects can be exploited."
- Is AI an asset to hiring, or will it bring us down a sinkhole of algorithmic bias? - I bring out a debate on whether AI will improve or add to hiring bias. "We’re not going to slow this train down. If companies can legally employ facial recognition in HR and beyond, they probably will. I believe that ethical companies have a good chance of using AI ethically if they apply rigor."
- Hire for skills, not degrees - a new paradigm to tackle disenfranchisement in the digital economy - Stuart on Davos 2019 and the digital have and have-nots. "For her part, IBM's Rometty opened up her wider agenda, citing her ‘New Collar’ worker ideas. These argue that alongside traditional white and blue collar workers, businesses now need to look to develop a generation of New Collar workers, digitally-skilled and sourced in a new way."
My take - algorithms and ethics are inseparable
We know that a narrow focus on gender diversity is not going to cut it. This collection of pieces grapples with a broader scope, from accessibility to ethnic diversity to the digitally excluded. Diversity is no longer the terrain of the "do the right thing" crowd; the business case supporting workplace diversity has been fleshed out considerably.
For companies looking to grow, extending the reach of talent and recruiting matters. We also know that ethnic strife, anti-immigrant sentiment and revolts of excluded populations are not just "externalities" but topics of deep concern for enterprises. Growth won't be sustainable if the macro-economy falters.
To me, what's different in this collection is a clearer emphasis on culture change - what it takes, what the obstacles are. Add in: a more nuanced view of how today's technology can support those efforts, processing and measuring an extended range of data, guiding hiring managers to broader applicant pools - or not. Algorithms and ethics are inseparable. We are accountable for whether machines help us close these persistent gaps, or make them worse.