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Jennifer Reynolds is the chief executive officer of Women Corporate Directors (WCD). Her 25-year career in the financial services industry includes senior roles in investment banking, venture capital and global risk management and corporate director roles in the banking, insurance and asset management sectors.

As we begin to head back to the office, most women will be pulling warm sweaters and wraps out of the closet to shelter from the arctic office temperatures that prevail in our workplaces. The summer months are always the trickiest for women as our clothing for outdoors becomes even more dramatically different than what we need in our office. I have long wondered how this universal office temperature was chosen and recently found my answer. Data. The standard office temperature formula was developed in the 1960s based on the metabolic resting rate of the average 40-year-old, 70-kilogram man. A recent study looked at the corresponding data for women and found the standard office temperature is about 3 degrees too cold for women. My point is not to start a movement for raising office temperatures, but to highlight how a data gap can affect decisions and outcomes – often to the detriment of those not represented in the data.

The gender data gap is more pervasive than you may think. From business, to health care, to public policy, the data used to make decisions often lacks representation of women. How significantly different are some of those outcomes as a result? In the case of automobile safety, significant. Men dominate the number of people injured in car crashes, however, when a woman is involved she is 47 per cent more likely to be seriously injured than a man (71 per cent more likely to be moderately injured), and 17 per cent more likely to die. One would think that these divergent testing outcomes would have been identified in car-crash testing, yet while crash test dummies have been used since the 1950s, the use of female crash test dummies only began in the United States in 2011. In the EU, tests are only conducted with female dummies in the passenger seat. Pregnant female crash test dummies were only developed in 1996 (but are not widely government-mandated).

Workplace safety is another area where the gender data gap creates significantly different outcomes for men and women. A study by the Women’s Engineering Society found that the design of 74 per cent of personal protective equipment (PPE) is based on sizes and characteristics of men. Less than 10 per cent of women working in the energy sector, and 17 per cent in the construction industry, wear PPE designed for women. Likewise, protective armour in the police force is often unsafe and less effective for women because of its size. Further, workplace safety research is more focused on male-dominated industries such as construction or manufacturing, whereas women dominate in the less-researched service sector. Research and data related to workplace safety for occupations such as caregivers or house cleaners is limited, yet both are prone to injury from activities such as lifting heavy weight and exposure to chemicals.

One would think the technology industry, where data fuel so much of its innovation, would have identified the importance of data gaps, but there too we see the impact of the gender data gap. Take voice recognition, Google is 70 per cent more likely to comprehend a male versus a female speaker. Voice recognition software for doctors has been shown to produce higher transcription-error rates for women. Given that the most commonly used linguistic data are based on 69 per cent male-voice recordings, these are not surprising outcomes. Consider sports technology. The treadmill measures the calorie burn of males, who burn 8 per cent more calories than women of the same weight. Before anyone contemplates elevating their training regime, the good news is that a study of 12 of the most common fitness monitors underestimated steps during housework by up to 74 per cent, and underestimate calories burned by 34 per cent.

In a world where data have so much power to influence decisions and outcomes, it is time to challenge the concept that one size fits all. While it might seem like a lot of work to change long-lived assumptions and practices in an organization, the opportunities that can be created by that exercise are immense. Product design starts with deciding what problem needs solving. Those organizations that have data which represent the entire population, and diverse teams to assess that data, will be able to capitalize on opportunities that those with a data gap cannot see.

This column is part of Globe Careers’ Leadership Lab series, where executives and experts share their views and advice about the world of work. Find all Leadership Lab stories at and guidelines for how to contribute to the column here.

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