Is Small Data > Big Data?

Is Small Data > Big Data?

Martin Lindstrom just published a new book, Small Data: The Tiny Clues that Uncover Huge Trends. It’s a passionate description and defense of anthropological research by one of its most gifted practitioners. It’s also a not-so-subtle dig at the tendency to overpromise the power and underestimate the limitations of big data.

Martin has an amazing lifestyle. He’s spent much of the past fifteen years traveling to 77 countries, where he has interviewed thousands of people in their homes (I get tired just talking to him). His book talks about his commercial successes and also about his observations about the cultures he has experienced.

A favorite of his stories is about Lego, which in the early 2000s were down and almost out due to an inability to counter the digital game phenomena. Then they developed a new strategy - make Lego building more challenging because kids felt pride in completing the difficult and doing so better than others. This insight came from an interview Lindstrom had with an 11 year boy in Germany who had told him how proud he was of his skateboarding which was represented by some worn shoes. Not obvious for sure.

Then there was the e-commerce site in Russia which provided Russian mothers a chance to be heard, interact with others, and buy toys for their kids and grandkids. The inspiration came from talking to these moms about their inhibitions and limitations, but also observing their refrigerator magnets and how the location on the fridge and content said something about their lives. Martin has the advantage of looking at such clues across cultures. In this case, he compared Russian and Saudi Arabia moms with similar problems but different coping mechanisms.

Martin tells the ‘secret’ to his methodology – the 7C process. In general, the process involves the gathering of observations, the curiosity to explore them and their relationships in detail, and the ability to come up with insights and narratives that translate into an actionable idea. It is taking on the role of a detective to solve a puzzle with persistence and patience. Not for everyone. The 7Cs are:

  • Collecting - Observe everything by removing the cultural filter that keeps you from seeing what is really going on.
  • Clues - Ask questions like--What is most important in your life? What worries you the most? Try to create a narrative about what is going on. Observe emotional reactions.
  • Connecting - What are the consequences of the emotional reactions? At one retailer it was the striking absence of community and belonging.
  • Correlation - When did the behavior or emotion first appear? Was there a shift or change in a consumer’s behavior at some point? When did that take place?
  • Causation - Mount a timeline of photos and observations on a large board? Look for cause-effect relationships.
  • Compensation - What is the unmet or unfulfilled desire? What is the best way to fill it? For the retailer it was creating a sense of community.
  • Concept - What is the big idea related to the consumer desire you have identified?

Anthropological research has become widely used in the past two decades. A leader has been P&G where executives believe it is the key to innovation. They call it immersion in a consumer’s lives—living it (living with consumers), working it (acting as a service person serving consumers), and shopping it (going along with consumers on shopping trips).

It has its marketing roots in the motivation research era of the 50s and a bit beyond. Motivation research was discredited in the 60s in part because of its link to Freudian psychology which led to some flaky recommendations (don’t put ice cubes in a Pepsi drink because they mean death). There no such problem today as the emphasis is on methodology and customer relevant insights and not Freudian psychology.

Nikolai Kopelev, Ph.D., MSIS

Leader. Motivator. Relationship Builder. Procurement Expert. Information Professional.

8 年

Very true! In order to be impactful, data does not have to be big, but relevant, well-organized, high quality, etc. In some situations, big data could be even damaging because of resources needed to manage it, high level of noise it could generate, etc. Fully agreed with Mick!

Tam Cao

Consumer Services Professional

8 年

Big data equivalent to large sample... It just depends on how one collects them to turn the data into meaningful info. Up until now, there is no reverse way.

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Kunal Basak

Senior Developer at SAP

8 年

Big data help us pick up small data.. That's the significance of big data technology.

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Snehal Datta

Sr Data Engineer at Amazon Music

8 年

Sometimes with big data, we have to clean and then use only a part of it. In some cases, working with 'small' data provides the best solution

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