There seems to be a great deal of interest in improving diversity in the tech industry—especially gender diversity. When I talk to executives in tech companies they acknowledge the issue and we spend a good deal of time on the “externalities” that are hampering their effort. Mainly things like the lack of women developers (a rapidly changing but still pervasive problem) and the fact that many of the talented women and people of color they want to hire are less interested in the job after the interview.

WTIA has made a significant commitment to help build technology talent in the region, but the responsibility to aggressively seek this talent AND create a culture – beginning with the interview – that works for women (and minorities) is in the hands of each company’s leadership. At New Legends we believe the first step is to acknowledge that the bias concerning women in tech exists. If you don’t think you have a bias, it might be time to understand more about the pervasiveness of unconscious bias.

Why should you care?

My experience with the very smart, energetic and committed leaders in the tech industry is that “where there is a desire, there is a way.” Any issue that they truly believe will hurt their chances for business success gets solved. The issue with diversity therefore may be that the tie between gender balance and business success just isn’t that clear.

I get that. If you are humming along, building great products, iterating on your technology and having success, it’s hard to see how having women on the tech team will make a difference.

But from a cultural perspective, and especially from an innovation culture perspective, the motivation should be substantial.  

What actually maximizes innovation?

History (and validated research) shows us that in spite of the cult of heroic individualism and the lone-ranger innovator, all great innovations happened within groups. When it comes to the problems and complexity of innovation, you must bring collective intelligence to bear.

IBM has been studying innovation for some time and seeking to better understand the circumstances that will allow group intelligence to flourish. They invited MIT professors Thomas Malone and Patrick J. McGovern (the founding director of the MIT Center for Collective Intelligence) to present their findings on collective intelligence at an IBM Think Forum on Leadership. You can see the video here. Professor Malone’s piece is at 12:26 minutes.

Perhaps the most interesting point in the MIT study is that group intelligence is not equal to the combined intelligence of the individuals in the group.  

So if it’s not smart people, what makes groups better at innovation?

Three consistent factors:

•         The average social perceptiveness of the group members
•         The evenness of conversational participation
•         The proportion of women in the group

It turns out that the same set of skills that lead many to believe that women belong at the margins of an organization, where the not-so-critical “soft skills” are needed, are the very skills necessary to foment and ensure innovation. The ability to connect to individuals and read social cues; a desire to see genuine (not pseudo) community; a commitment to fairness and balance; and a pre-disposition to collaboration. Admittedly, these are skills that men can also have. But whether by nature or nurture, we know that women excel in these skills.

In other words, there is a strong business case for gender parity in innovation.  It is more than just the “right thing to do.”  If you want smart groups and outputs, including innovation, you need women in meaningful numbers in every part of your organization—especially on the technology team.

But then there’s unconscious bias…

Turns out that the human mind is built to be biased. From infancy onward, we learn to sort and categorize inputs. We learn from our parents and other people what is “good and true,” and over time we take short cuts to the “truth” through assumptions that are driven by the beliefs, or mindset, we have developed. Our mindsets actually limit our capacity to see possibilities and  to recognize new data.

We are not even aware of our biases and assume that the way we are thinking must be true simply because it is the way we are thinking. Turns out this can cause big problems for business (and all other types of) relationships. We use a ladder of inference, a term coined by business theorist Chris Argyris. Essentially, we infer the truth from our existing mindset and knowledge without seeing how what we believe lines up with the actual data that is available to us. This is the behavior that causes men to ask questions in interviews and create work environments where women developers might not thrive.

For instance, many male developers enjoy gaming and are very competitive.  Young women developers have traditionally not been as likely to be gamers (although some are) and are less likely to be extremely competitive. If your interview questions are designed to be interesting to someone who exhibits those behaviors, or if in the interview you show these behaviors and the candidate has a less than enthusiastic response, the ladder of inference would lead you to conclude that the person is not a “good” developer or culture fit, simply because they don’t see the world as you do. You have limited the data you are drawing on based on your belief system. More often, these behaviors will cause the candidate to question whether they would be listened to or respected if their style is different than the norm.

So, what is there to do?

The first step is to give some thought to the evidence above about why you should care. What is your response? Do you want to embrace or reject the notion that how a team collaborates and demonstrates empathy and balance can have a strong impact on innovation?

If you decide you do believe it and want to do more, learn more about how to engage with and use the ladder of inference. Check your own process by walking up the ladder. Use it to unpack and address the unconscious bias within your organization. Seek to understand how unconscious bias is affecting the people in your company. Whose insights are being ignored? Whose voice has gone quiet because they weren’t being heard? Who have you completely missed hiring because they weren’t a “good fit?”

Finally, try to open yourself up to more of the data that is available when exploring diversity and tactics to engage with women and people of color on your technology team. Spark a conversation about bias on the tech team and see where it takes you. You might be surprised by how ready your organization is to open up to diversity, develop more inclusive practices, and gain the innovation edge.

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