• Leila Ainge

The Debrief - March

It used to be really difficult to get good data from systems, you'd be forgiven for thinking that more data would be better, but we often graze on it without questioning what it means, or understanding what the gaps and assumptions are. Like many women, I've been inspired by Caroline Criado Perez's book Invisible Women, the overwhelming evidence she has gathered about the data we fail to collect on women is deeply troubling. There's so much more we can do to challenge our assumptions, and be mindful of bias when asking questions and collecting data. In this month's debrief:

Why we make shortcuts when we collect data, and how to measure what is important in your business Enjoy! Leila x

p.s get the debrief, business & psychology insights direct to your inbox every month click here

Grazing is a shortcut Measuring stuff helps our decision-making processes, what we measure and how we measure is intrinsically linked to the things we value, and the things we know. When I work with business owners, I‘m interested in the data they collect, but I’m also trying to understand what is not measured, and what this tells me about the decisions that business is making, and what they value most. Diving into data might not sound like the most exciting activity but being curious about what you do and do not measure is a competitive advantage. In psychological terms we know that we have evolved to process complex information by developing shortcuts, and in psychology we call these heuristics, the idea that we think about what we can bring to mind, categorise, and what we can estimate based on existing information. Heuristics are simple strategies to help us make decisions. Essentially, it’s educated guessing, when we link performance or success to a single event without having specific data or feedback to tell us, we are drawing an assumption without fact to back it up. We use past experiences and understanding to help us make decisions about future activity, and heuristics also gives us an explanation as to why stand-out stories stick, whether the data backs it up or not. Take the economic indicator the ‘Lipstick Index’ – coined by the beauty billionaire Leonard Lauder to describe the phenomenon of women’s spending habits. When unemployment is low, women buy more lipstick, except in a pandemic when women are wearing facemasks. A better indicator of consumer spending during the current pandemic seems to be skincare products but it hasn't stopped a multitude of newspaper articles using the phrase as a way to frame other habits. This index has generally been a good indicator for beauty retail during economic downturns because it is a stand-out story, the specific data that led to the phrase is not required to grasp the idea, it’s also representative of a situation and it can be adjusted or reframed- by applying the same principles to other products. Women’s retail spending is clearly interesting, it's useful if you work in retail or want to understand how retail spending contributes to our view of the overall economy. Stand-out stories become less helpful though when we graze on the information. What about the psychology behind the spending, women buy more lipstick to become more desirable and increase chances of finding a partner, this is the conclusion of a study that explored the 'lipstick effect'. The data collected shows the average female participant was 19

and attending an American university, the priming of male and female students about economic conditions showed a clear positive effect on lipstick spending for females compared to an equivalent product for males (face cream). You can draw your own conclusions on the limitations of this study, but my point is this, we don't always see diversity when we look at differences, if you ask predominantly white, heterosexual 19 year old women and men what they would buy, they are going to answer for that demographic, it is one spending habit amongst many. It doesn't tell us about the wider actions or habits of women or men during a pandemic, and as long as we graze on information we accept this data as the habits that count. Despite the orginal phenomenon appearing twenty years ago, this is a stand-out story that is easily accessible, believable, and quoted. We might ask where is the data discussing risk taking, entrepenuership and side hustles? is that more or less of an economic indictor than what women & men spend on skincare? how do we know unless we value and measure it? How does this relate to business? We make better decisions if our starting point involves curiousity and finding different ways of understanding the data around us. Here are some practical ways you can approach data in your business

  1. Does your data measure the things that you and your customers or clients value and how are you asking what your customers value?

  2. What does your data collection exclude? an easy example, digital first data often ignores the human to human interactions, how are you measuring this?

  3. What does your data represent? It might tell you what the majority of your customer segment is, and you might focus activities on that area. It is worth considering who or what is not represented. Why is that?

  4. Look at rich data, not just statistics. Volume data is great for understanding trends, it focuses on what we know. Rich or qualitative data provides a different insight, it often shines a light on the stuff you don't know.

What I'm listening to right now I had a sneak preview of the REALWORK podcast last week, Fleur interviews incredible women who are working on their own terms. It is joyful, clever and will make you laugh. The first two episodes land on Tuesday 16th March - subscribe so you don't miss it. Head to the podcast

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