Over the past decade, Big Data has generated immense expectations for businesses, akin to discovering a promised land. The anticipation was that it would serve as a fantastic hotline, instantly revealing the habits, desires, and needs of target customers.
In May 2011, a Special Research Reportby management consulting firm McKinsey asserted that "Big Data would underpin a new wave of productivity growth, innovation, and consumer surplus, becoming a core foundation for future business competition." Around the same time, a report by IBM highlighted the rapid growth of data generation, stating that 90% of the world's data at that time had been created in the previous two years.
However, the results of the NewVantage Partners 2020 Big Data & Executive Surveyreleased in 2021 reveal a present that differs from initial expectations. This survey involved responses from 1,000 executives within Fortune-listed companies who were responsible for overseeing and managing data initiatives.
- Only 26.8% of companies have established a data-culture.
- Only 37.8% of companies responded that they are operating in a data-driven manner.
- Currently, only 45.1 companies are actively competing in the data and analytics field.
Of course, it's important to acknowledge that cases of Data mining for Customer Intelligence have undoubtedly brought joy to the shareholders of companies like Netflix and Amazon.
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However, despite the enormous increase in data volume and the success of a few companies, the reality is that most organizations struggle to derive the profound insights they initially hoped for. Ultimately, data analysis is merely a tool. When we employ such data analysis as a strategy, we inevitably make assumptions about people and their behaviors.
Specifically, incorrect assumptions that are not grounded in the real world of people.
In other words, Big Data itself can lead companies to misunderstand people.
Firstly, Big Data leads to Thin Data. In the field of social sciences, the data used to understand human behavior is broadly classified into two categories. Among these, Thin Data is primarily derived from people's digital footprints. For example, this includes superficial information such as, 'She wears size 44, has brown eyes, and drinks Pinot Noir wine.'
The other category, Thick Data, provides insight into how people actually experience the world. For instance, it encompasses rich information like, 'She could smell the grass after the rain, saw the person she was walking with as someone special, and her sneakers made her feel light on her feet'— meaningful information.
In essence, Big Data focuses on correlations linked to products but shows little interest in the causal relationships within people's lives. However, understanding human behavior as social beings is fundamentally rooted in causality. Without insights into the genuine thoughts and feelings of customers, Thin Data alone can have limited meaning and utility. According to Accenture's Analytics in Action report, only 20% of organizations that claim to possess superior performance management capabilities have 'discovered a proven causal link between what they measure and the outcomes they seek to drive.' This serves as evidence that algorithm-centric companies are losing their ability to grasp human behavior.
Above all, without critical thinking skills, Big Data can never reveal patterns that hold strategic value within its depths. Here, critical thinking involves comparing and examining situations in light of objective evidence, clarifying 'causality'and acting based on the judgments derived from this process. The need for companies to cultivate management's ability to interpret human behavior correctly can be explained through this lens.
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The most profound types of interpretive thinking in humanity come from the social sciences.
The humanities, including history, literature, philosophy, and anthropology, which have shaped the past 2,000 years, teach us the critical thinking skills necessary for correctly understanding human beings. Only by grasping human behavior at a deep level can we comprehend and explain the dramatic shifts in customer behavior. And from there, we can discover the potential for innovation.
Ultimately, if we can uncover the answers to 'Why,' businesses can forge their own valuable perspectives amidst the current commotion of the Big Data movement. And these companies will become the only entities capable of truly understanding people.
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