Lies, Damned Lies and Statistics: Equality and Diversity

Posted by: Nigel Girling Post Date: 6th October 2016

Discrimination on the grounds of gender, ethnicity, religion, disability, or any other irrelevant factor is at best short-sighted and talent-wasteful, and at worst bigoted. It has no place in the 21st century, and as leaders, we are obliged to eradicate it.

However, these issues have been victim to our management obsession with data, and our ability to misinterpret it in increasingly ludicrous ways. Here, I want to illustrate the need for leaders to exercise critical thinking, and to be mindful of distortion and bias.

The gender pay gap

Lies-and-statistics-equality-and-diversity

During 2015 and 2016, a series of reports and articles on the ‘gender pay gap’ gained significant traction. Esteemed bodies and magazines such as Forbes, the Financial Times, the BBC, and the Chartered Management Institute picked up on this, often in increasingly florid and inflammatory language.

The conclusions drawn have been accepted as factual, and are referenced in articles and conversations daily. More rigorous analysis, though, indicates that they are far from accurate. Actually, they are often misleading, biased, and might have a negative impact on the validity of any related strategic leadership decisions. They could also be damaging to professional women, concealing the real challenges that exist behind the hype.

Recent reports on the gender pay gap tend to focus on the ‘conclusions’ below, predominantly based on figures published by the UK Office for National Statistics (ONS):

  • Women earn 22% less than men
  • Women work for free for 1 hour and 40 minutes every day
  • Women work for free for 57 days per year
  • The gender pay gap is £8,524, rising to £14,943
  • The average bonus is £2,531 for women and £4,898 for men

As a leader, there is a general rule that needs to be kept in mind: that attempting to derive qualitative conclusions from quantitative data is dangerous, and liable to misinterpretation. In this case, a difference in levels of pay does not, as the headlines have suggested, necessarily suggest discrimination, or that women are paid less fairly than men.

The trouble with these headlines is that they are a gross over-simplification of a complex issue, and don’t stand up to scrutiny. The data being used does not compare like-for-like work, and therefore does not of itself indicate a difference in the pay of men and women for work of equal value, as the rules of equality require.

Indeed, the ONS makes this point itself, a fact largely ignored by those writing about the apparent pay gap. The report also indicates that, between the ages of 20 and 39 (a substantial proportion of the workforce), women actually earn slightly more than men.

The initial data begins to make more sense when viewed within the context that nearly 41% of women have part-time jobs, whereas 88% of men are in full-time jobs, as the report goes on the show. The nature of part-time work compared to full-time obviously has a significant impact on overall levels of pay, and goes a long way in explaining average differences. Aside from this, assumptions about the gender pay gap do not take into account the different choices women and men make about the kinds of work they do, influenced by a huge variety of factors from personal interests to raising children. The statistics cited certainly do not refer to differences between the pay men and women receive for doing exactly the same jobs with the same working patterns.

The gender pay gap is a classic example of making the facts fit a desired conclusion, something leaders are often guilty of when seeking to gain support. As a friend of mine used to say: ‘Hell hath no fury like a vested interest masquerading as a moral principle’.

The reality of gender inequality

One of the influencing factors is that the media (and leaders who have become so mindful of poor PR), are afraid to challenge the assumptions made in the reports for fear of prompting a backlash from women’s groups, and of appearing chauvinist and anti-feminist.

I assure you that I am neither (though I suppose I would say that, wouldn’t I), and that in my own organisations over many years I have championed the cause of female leaders. Today, my own CEO is female, as is the director of the division in which I operate. In my last role as a CEO, my board consisted of two men (including me) and four women, and I appointed them all. I say this simply to put my comments in context.

I don’t deny the inequality that still exists in many organisations. Instead, I want to encourage anti-stupidity, anti-bias and anti-lazy thinking, and to indicate the dangers of creating a culture of ‘arithmocracy’, the situation in so many organisations where often-unchallenged data is king. I aim to reinforce the absolute need for leaders to think critically and challenge assumptions.

There is much that needs to be done to improve equality and diversity in our workplaces, particularly at senior management levels. The glass ceiling is a reality for many, and our senior teams do not yet reflect the composition of the communities they should represent. The relatively low proportion of women in senior leadership has not served us well, and sustains an overly ‘macho’ culture in many organisations.

While not solely an issue for women at work, support for childcare remains poorly addressed in many sectors, leaving women faced with the same old choice between career and children. There are almost 2 million lone parents in the UK, and 90% of them are women. How well is all that talent being deployed in our workplaces?

The continued insistence on ‘9 to 5’ start times in so many workplaces remains unhelpful and inefficient. This is exacerbated by the habit of dragging people into a central workplace when so much of their work could have been handled remotely. This is maintained by too many autocratic managers and organisations who still don’t trust employees to work unsupervised, and results in a situation that perhaps disadvantages women more than men.

Avoiding data-based assumptions in leadership

As a leadership-related example, if you want to reach a conclusion that is based on comparative data concerning business performance from one year to another, you can’t afford to do so without a great deal of analysis and consideration of influencing factors.

Let’s say that a business has increased turnover by 12% compared to the previous year; does that mean it is doing well? Does that mean it has been well managed? Does that indicate that the trend will continue? Many more questions will need to be asked and accurately answered before a leader can reach a robust conclusion. For instance:

Has profitability been consistent or improved?

It’s relatively easy to ‘buy’ an increase in turnover with significant price cuts or expensive promotional and sales campaigns – but is that a good thing?

Was the previous year typical?

If the previous year was significantly worse than other years because of extremely difficult trading conditions, then a 12% increase this year might be the least you would expect, and may even be indicative of poor performance.

Are trends suggesting that this is sustainable?

It is possible that a 12% increase in turnover might relate entirely to one factor, such as the launch of a new product, acquisition of another firm, or penetration into a new market or geographical area. This may not be sustained year on year and is not, of itself, an indicator of good performance.

This is the bare minimum of challenge that should be applied to any unsupported assertion that purports to be substantiated by data.

The leadership lesson is this: as a leader, it is essential to be wary of data that is unrepresentative, information that has been poorly analysed, conclusions that are unvalidated and may mislead, bias and distortion designed to support a case that is actually unproven, or indeed any other way in which quantitative information is used to produce qualitative conclusions.

In other words, leaders need to think. Deeply, often and with care. Reacting to unchallenged and unvalidated information is not leadership.

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