(1-2) Hello,

My premise is the lack of women developers in the US is an impediment to value delivery and product innovation in the software industry.

In light of this, Agile principles call on practitioners to confront hostile workplace conditions and enterprises to address the material impediments of pay and advancement.

This beneficial change in teams and companies can incrementally change perceptions in the larger society.

(3) To introduce myself

I’m a software practitioner not a consultant or educator. I’ve studied and applied Agile methods for nine years.

I’ve spent most of my career in woman run organizations.

(4) I have a daughter

…who loves technology and sought out a culturally diverse, math and science school in Brooklyn. So, this topic is personal to me.

C. Hayes. “The Incredible Shrinking Woman” in Gender Codes : Why Women Are Leaving Computing. T. Misa, Ed. Hoboken, N.J. IEEE Computer Society, 2010, pg. 33

(5) Women are underrepresented in Computer Science

According to the US Bureau of Labor Statistics, women represent 46% of the workforce but only 25% of software developers. Over two decades the percentage of women developers has steadily declined.

S. Hewlett and C. Luce,. “The Athena Factor.” Harvard Business Review, pp. 51, Jun. 2008.

(6) Women are leaving mid-career

Women are leaving IT in larger numbers than men. 56% of women leave mid-career across all technology occupations. 41% leave their careers in “high technology” compared to only 17% of men. Half of women leaving STEM careers leave the STEM sector completely.

Four Decades of STEM Degrees, 1966-2004: ‘The Devil is in the Details.’” CPST, Sep. 2006, pg. 3.

(7) Women are not studying Computer Science

According to the Commission on Professionals in Science and Technology, in the decade between 1986 and 1995 the number of women earning Computer Science bachelor’s degrees dropped 55%. As of 2010, the percentage was still falling despite growing percentages of women graduating from four year colleges. This is not typical of STEM where 49% of bachelor degrees go to women.

N. Zarrett and O. Malanchuk. “Examining the Gender Gap in IT by Race” in Women and IT. J. Chohoon and W. Aspray Ed. Cambridge, MA. The MIT Press, 2006, pp.55-88.

(8) Young Women are disinterested in pursuing high tech education or careers

The Maryland Adolescent Development in Context Study, a longitudinal study of 1,400 white and african american students found that women were much more likely to have no interested in IT related careers and degrees than men.

(9) At what cost to the software industry?

In the last decade, the U.S. software industry represented $200B in annual sales and employed 2.2M software professionals. McKinsey & Co estimates in this decade, demand for mid-career IT professionals will increase by 25% while the available pool will decrease by 15%. This in a country where 71% of workers are in jobs with low demand or an oversupply of eligible candidates.

(10) The cost of attrition

And let’s also get at the cost of attrition. According to HR magazine, it costs approximately 100-125% of an employee’s annual salary to replace them. Retaining one-quarter of the women who leave computer engineering mid-career could represent a ten year savings of $8B to the industry.

(11) Lost opportunity in the software industry (Product)

The lack of women on software teams is also a potential loss to product innovation…

(12) Women are our customer

Women directly or indirectly influence 61% of U.S. consumer electronics purchases[18].

(13) Women in gaming

Women are 42% of active game players and 48% of frequent game purchasers. And if you think they’re just buying them for their kids, industry research shows women 18 and over are 37% of game players whereas boys 17 and under are only 13%[19].

(14) Women on the internet

Half (50.4%) of the internet population is women 18 and over. They spend an average of 38 hours per month online. They spend 5% more time than men in online social networking and 20% more time on online shopping. Women account for 58% of internet buyers, 61% of internet transactions and 58% of internet dollars.

(15) Women are underserved

Software products are generally designed with no consideration for women as distinct user groups. In “Gender differences in Web Usability”, Frank Spillars states, “Gender differentiation is barely present in North American technology product design… let alone Web experiences[22].”

(16) how women perceive and use software

In “Towards Female Preferences in Design.” the authors found differences in the ways men and women perceive and describe software products. “The results of this research have revealed female-oriented themes that should… enlarge views of pleasurable product design attributes and language for the genders[23].”

(17) three ways companies fail.

Boston Consulting Group (BCG) highlights three ways companies fail to address women consumers: Poor product design: failing to tailor products to women’s unique needs and challenges.

(18) three ways companies fail.

Clumsy sales and marketing: based on outdated images and stereotypes.

(19) three ways companies fail.

Inability to provide meaningful hooks or differentiation: considering women indistinguishable from the general customer population or thinking of them as one monolithic segment[24].

I. Nonaka and H Takeuchi. The Knowledge Creating Company. New York, NY. Oxford University, 1995

(20) How would having women on dev teams help software better address the needs of women

For this, I’ll lean on the research of Nonaka Ikujiro and Takeuchi Hirotaka . This slide is an illustration of their concept of the product development cycle in serially innovative companies. It requires the creation and sharing of two kinds of knowledge within the organization. Explicit knowledge – that which we can explain in words – and tacit knowledge – that which can best be expressed by doing. This concept of knowledge creation and techniques for forming teams that support it are the roots of the most widely adopted Agile process framework, Scrum[39]. Nonaka and Takeuchi emphasize that an enabling condition for sustained innovation is, requisite variety, having a product team made of members with different backgrounds, perspectives and motivations. Requisite variety applies to cross-functional teams but also to team members with diverse life experience. Because it is through life experience that we acquire tacit knowledge.

T. Oshita, et. al. Bread Baking Machine. US Patent Office, 2004

(21) Matsushita Example of Tacit Knowledge

The classic example of the incorporation of tacit knowledge into a disruptive product design is the first Matsushita bread machine. It took a hands on experience of baking bread by one of the product engineers (a woman) to crack how to implement the mechanics of kneading dough in a bread maker.

(22) Team diversity and delivering value

Women are significant customers and influencers in the buying decision for software and software dependent technology. Statistically, women have different perceptions and preferences for software. Therefore, according to knowledge creation theory, it is a competitive advantage to have women individual contributors bring their tacit knowledge to software product development.