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Big Data

Brands Must Beware Of Data Reliance

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Brands Must Beware Of Data Reliance

Data are important. And, data are increasingly used to help us in all areas of society. However, there is an underlying issue, the role of data and research is to inform, not to decide. Research provides direction and raises questions. Data do not take into consideration ambiguity, fear or our daily human experiences. Data do not recognize peer pressure, family conversations or neighborhood rallies. Data do not comfort or care. Data do not interpret how you feel when it is either paying the rent or putting food on the table. What data can do is inform decision-making, but it does not make decisions. Researchers interpret the data. They make the decisions.

Data do not decide; people do. Data do not think; people do. However, interpretation of data is a skill. Judgment about what data mean takes confidence and insight.

Business executives often expect data analytics to reveal answers. Data do not take into consideration mission, context, policies or priorities; people do.

Data Misses The Why

In his 2003 book, How Customers Think, Harvard Professor Gerald Zaltman wrote that marketers and C-suite executives must remember that data do not speak for themselves, people do. He said, “Managers’ interpretation of data is the meaning they extract from the data. Rarely does a number by itself have meaning. It is the manager’s prior experience or the consensus of the group of managers that makes a number meaningful.” Management by metrics has become the order of the day. We are mesmerized by metrics.

While there is much that we can measure, there is also much that is not measurable. Unfortunately, as business becomes more demanding, business becomes more defensive. In a world where budgets are squeezed by limited resources, managers and marketers lean towards an over-reliance on the mystical muscle of measurement to take over the role of marketing expertise and experience.

In 2017, Professor Jerry Z. Miller, at Catholic University of America, wrote a book titled The Tyranny of Metrics. Professor Miller focused on “metric fixation.” Metric fixation is our tendency to become mesmerized by metrics. As discussed in a Bloomberg Opinion piece Justin Fox wrote that Professor Miller was critical about our belief in the overarching power of data. Mr. Fox explained that Professor Miller sees one of the main characteristics of metric mania as the idea that “… it is possible and desirable to replace judgment… with numerical indicators of comparative performance based on standardized data.”

Mr. Fox pointed out that Professor Miller is not alone in his concerns about data reliance. Billionaire John Doerr wrote a book also dealing with the problems of over reliance on metrics and performance measurement. Mr. Doerr stated that data reliance without judgment and without knowing “why” people behave the way they do, is the wrong approach. Mr. Doerr is not against metrics. But, he told us that the best metrics are used to inform rather than form opinion.

The problem with using data to replace judgment is that we will only focus on the “what” and not the “why.” Data are a resource. Data can provide correlations. Data do not attest to causality, even though we may think so. Data do not say, “A caused B to happen.” But, data can suggest a relationship between A and B.

Insight Reveals A Hershey Strength

For example, as reported on CNN, Hershey, maker of the ubiquitous, iconic Hershey Bar, Reese’s Pieces and Reese’s Peanut Butter Cups, saw data showing that areas of the country with high numbers of Covid-19 cases also had high chocolate sales. The Hershey data revealed that those zip codes with numerous Covid-19 cases saw demand for milk chocolate soar by 40% to 50%. The data revealed a correlation but could not tell Hershey “why” this was the case. The data could only point out people’s behavior.

Hershey used the data to focus on understanding the “why.” Hershey used the data to figure out what was driving the relationship between coronavirus and chocolate. Hershey determined that due to the virus, people were spending more time outside. One great outdoor activity is making S’mores. The ingredients in S’mores are graham crackers, marshmallows and Hershey Bars. The marketers at Hershey used the data as a platform for creativity, not as the creativity itself.

This Hershey approach is cited as one of the reasons Hershey performed so well in the third quarter of last year. According to The Wall Street Journal, Hershey stated that its brands increased share due to its adapting to changing customer behavior, part of which was producing more Hershey bars for S’mores. Hershey’s North American comparable sales increased 5.5%. Hershey’s net income rose from $325.3 million to $447.3.

Lack Of Insight Reveals An Amazon Weakness

On the other hand, for all the wondrous personalization from Amazon, its data do not understand time. For Amazon data, last time is all the time. For example, if you buy baby gifts for your new grandchild in April, you will still receive suggestions for baby things a year later. If you buy your son-in-law tools for his outdoor grill as a holiday gift, you continue to receive grill tool sets suggestions for time immemorial. Amazon knows what you bought, but is less certain why you bought. Amazon data do not seem to care that time goes on, babies grow up and one gift set of grill tools is sufficient.

In the seminal work, Big Data by Schönberger and Cukier, in 2013, the authors pointed out that data can lead to both understanding and misunderstanding. Data can spur innovation. But, “the spark of invention comes from what the data do not say. In a world of big data, it is our most human traits that will need to be fostered… since our ingenuity is the source of our progress.”

For example, one appliance company saw data indicating that noise was a huge problem with vacuum cleaners. Taking the data as decisive, the engineers developed a near-silent vacuum cleaner. The silent vacuum cleaner did not sell. Why? Customers perceive certain sounds as conveying powerfulness: think Dyson. Without sound, customers thought the vacuum’s suction would be weak. The loud sound was not a problem: it was evidence of a powerful vacuum. Data did not provide this critical piece of information.

In this increasingly competitive, uncertain marketing world, there is a pervasive fear of taking a leap of faith based on judgment. Informed judgment is not guesswork. Marketers must use their expertise and their judgment and their creativity to make reasoned, informed and insightful decisions.

Data do not create ideas. Data show areas where ideas are possible. Creativity is a mindset, not a metric. Real, actionable insight will not come from superior data collection and analysis. Superior analysis provides understanding of where we are, and how we got to where we are. It does not provide insight into what kind of future we can create. It does not tell me “why”. Marketers must use their expertise, their judgment, and their creativity to make reasoned, informed, insightful, and bold decisions. Data can provide direction for decision-making. Data inform decisions. Data do not make decisions.

Data do not decide; people do. Data do not think. People do. Do not let data become the decision-maker.

Contributed to Branding Strategy Insider by: Larry Light, CEO of Arcature

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