Summary: We’re often asked why our data is so valuable, in an era when “big data” is on everyone’s mind. My response: “Smart data beats big data any time.” Here’s another way of saying it, from Tricia Wang over at Medium. “When I was researching at Nokia in 2009, which at the time was the world’s largest cellphone company in emerging, I discovered something that I believed challenged their entire business model,” Wang writes. “After years of conducting ethnographic work in China from living with migrants to working as a street vendor and living in internet cafés, I saw lots of indicators that led me to conclude that low-income consumers were ready to pay for more expensive smartphones. I concluded that Nokia needed to replace their current product development strategy from making expensive smartphones for elite users to affordable smartphones for low-income users. I reported my findings and recommendations to headquarters. But Nokia … said my sample size of 100 was weak and small compared to their sample size of several million data points. In addition, they said that there weren’t any signs of my insights in their existing datasets.
“By now, we all know what happened to Nokia. Microsoft bought them in 2013 and it only has three percent of the global smartphone market. There are many reasons for Nokia’s downfall, but one of the biggest reasons that I witnessed in person was that the company … put a higher value on quantitative data, they didn’t know how to handle data that wasn’t easily measurable, and that didn’t show up in existing reports. What could’ve been their competitive intelligence ended up being their eventual downfall.
“Since my time at Nokia, I’ve been very perplexed by why organizations value quantitative more than qualitative data. With the rise of Big Data, I’ve seen this process intensify with organizations investing in more big data technology while decreasing budgets for human-centered research. …According to a Gartner study of companies who had invested in Big Data capabilities, only 8% of were doing anything significant with their Big Data. The rest were only using Big Data for incremental advances. This means that a lot of companies are talking and investing in Big Data, but they aren’t doing anything transformational with it.” Tricia Wang, “Why Big Data Needs Thick Data,” Medium.