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Manufacturers Should Beware Of Information Reliance

Brands need to be wary of data dependency

Data is important. And data is increasingly being used to help us in all areas of society. But there is an underlying problem: the role of data and research is to inform, not to decide. Research leads the way and raises questions. Data doesn’t take into account ambiguity, fears, or our daily human experiences. Data does not recognize peer pressure, family conversations, or rallies in the neighborhood. Dates comfort or don’t care. Data doesn’t interpret how you feel when you either pay the rent or put food on the table. Data can influence decision making, but it doesn’t make decisions. Researchers interpret the data. You make the decisions.

Data doesn’t make the difference; People do. Data don’t think; People do. However, interpreting data is a skill. Assessing what data means requires trust and insight.

Corporate executives often expect data analytics to provide answers. The data does not take into account mission, context, guidelines, or priorities. People do.

Data lacks the why

In his 2003 book How Customers Think, Harvard Professor Gerald Zaltman wrote that C-suite marketers and executives need to remember that data doesn’t speak for itself, it speaks for people. He said, “Managers’ interpretation of data is the meaning they extract from the data. A number seldom has a meaning in itself. It is the manager’s prior experience or the consensus of the managerial group that makes a number meaningful. “Management by metrics is the order of the day. We are fascinated by metrics.

While we can measure a lot, there is also a lot that cannot be measured. Unfortunately, as demand increases, business becomes more defensive. In a world where budgets are tight with limited resources, managers and marketers tend to rely too much on the mystical muscle of measurement to take on the role of marketing literacy and experience.

In 2017, Professor Jerry Z. Miller of the Catholic University of America wrote a book called The Tyranny of Metrics. Professor Miller focused on the “metric fixation”. The fixation of metrics is our tendency to become intrigued by metrics. As discussed in a Bloomberg Opinion article, Justin Fox wrote that Professor Miller was critical of our belief in the overarching power of data. Mr. Fox stated 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 with his data dependency concerns. Billionaire John Doerr has written a book that also addresses the problems of being over-reliant on metrics and performance measurements. Mr. Doerr explained that relying on data without judgment and without knowing why people behave the way they do is the wrong approach. Mr. Doerr is not against metrics. However, he told us that the best metrics are used for information rather than opinion.

The problem with using data as a substitute for judgment is that we only focus on the “what” and not the “why”. Data is a resource. Data can provide correlations. Data does not confirm causality, even if we believe so. Data doesn’t say, “A caused B.” However, 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 showed that in those zip codes with numerous Covid-19 cases, the demand for milk chocolate increased by 40% to 50%. The data showed a correlation but couldn’t tell Hershey why it was. The data could only point to people’s behavior.

Hershey used the data to focus on understanding the “why”. Hershey used the data to find out what drives the coronavirus-chocolate relationship. Hershey noted that because of the virus, people were spending more time outside. A great outdoor activity is s’mores. The ingredients in S’mores are graham crackers, marshmallows, and Hershey bars. Hershey’s marketers used the data as a platform for creativity, not creativity itself.

This Hershey approach is cited as one of the reasons why Hershey did so well in the third quarter of last year. According to the Wall Street Journal, Hershey said its brands increased their stake as they adapted to changing consumer behavior. Some of it produced more Hershey bars for S’mores. Hershey’s like-for-like sales in North America increased 5.5%. Hershey’s net income increased from $ 325.3 million to $ 447.3 million.

A lack of insight shows a weakness in the Amazon

On the other hand, for all of Amazon’s miraculous personalization, data doesn’t understand time. On 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 items a year later. When you buy your son-in-law’s outdoor barbecue tools as a Christmas present, you will continue to receive barbecue tool kit suggestions for the ages. Amazon knows what you bought, but is less sure why you bought it. Amazon data doesn’t seem to care that time goes by, babies grow up, and a gift set of BBQ tools is enough.

In the pioneering work Big Data by Schönberger and Cukier in 2013, the authors pointed out that data can lead to both understanding and misunderstanding. Data can drive innovation. But “the spark of the invention comes from what the data doesn’t say. In a world of big data, our most human qualities must be nurtured … as our ingenuity is the source of our progress. “

For example, an appliance manufacturer saw data that indicated that noise was a major problem with vacuum cleaners. Based on the data, the engineers developed an almost noiseless vacuum cleaner. The quiet vacuum cleaner didn’t sell. Why? Customers perceive certain sounds as powerful: think of Dyson. With no sound, customers thought that the suction force of the vacuum would be weak. The loud noise wasn’t a problem: it was evidence of a strong vacuum. The data did not provide this important information.

In this increasingly competitive, insecure marketing world, there is a pervasive fear of leaping belief based on judgment. Informed judgment is no guesswork. Marketers need to use their expertise, judgment, and creativity to make informed, informed, and insightful decisions.

Data doesn’t create ideas. Data shows areas where ideas are possible. Creativity is a mindset, not a metric. Real, actionable insights are not obtained through superior data collection and analysis. Superior analysis provides an understanding of where we are and how we got to where we are. There is no insight into the kind of future we can create. It doesn’t tell me “why”. Marketers need to use their expertise, judgment, and creativity to make informed, informed, insightful, and bold decisions. Data can provide a direction for decision making. Data informs decisions. Data doesn’t make decisions.

Data doesn’t make the difference; People do. Data don’t think. People do. Don’t let data become the decision maker.

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

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