You may have heard the saying, “big data” is about machines, while “small data” is about people, and the saying still has merit. Yes, big data can be quite distracting: it’s diverse, it’s constantly flowing, and it contains incredibly helpful information to guide and support your business objectives. But don’t let it pull you entirely away from ultimately what’s important, the human element.

While advanced algorithms can lead to better machine learning or AI, better customer insights and better forecasting, they can also remove extensive human understanding into core data sets and create a divide between those who embrace big data and those who don’t. It’s important to bridge the gap between humans and machines in a world that is being driven by powerful data.

Building a Bridge Between Your Data and Your Company

The continued adoption of big data technologies, cloud services and machine learning or AI have provided an unprecedented opportunity for businesses to experiment at scale and cost effectively⁽¹⁾, but often at the cost of human judgment and thorough understanding. Often, businesses find themselves reliant on analytics software powered by learning algorithms they don’t understand. As a result, companies leave these algorithms to their own devices and often accept their insights and conclusions as gospel.⁽²⁾ It’s important to find and employ the talent, whether it be consultants or data scientists, to not only translate big data into value but also to apply ethics and morality to data-driven dilemmas, something algorithms cannot currently do. Ultimately, these teams should be able to build a bridge between data and human understanding.

Another bridge that employers must build within the company is the one between the data believers and the data sceptics. The most successful enterprises “foster a culture designed to promote collaboration and data analytical skills” by building teams that consist of both IT and business execs.⁽²⁾  Each employee brings different skill sets to the table whether it be data analytics or organic customer/employee experience, and collaboration between this diverse culture results in decisions that have a high percentage of buy-in.

Building a Bridge Between Your Company and Your Customer:

When we say small data is about “people,” we are generally referring to users, customers, and their behaviors. Small data highlights the reason why behind the trends of big data and therefore can be very insightful and actionable. But again, small data should not only be mined from big data, it should also be mined from genuine human interaction.

New York Times best-selling author and public speaker Martin Lindstrom explains small data in its most human form. Many years ago, to interview IKEA founder Ingvar Kamprad (now deceased), he went into one of his stores in Stockholm, Sweden to meet up with him. Kamprad was nowhere to be found in the main offices, so Martin asked the staff, ‘“Where is he?”

“Well, he’s probably at the usual spot,” they replied.

“Where is that?”

“…The checkout.”

Lindstrom went down to the checkout, and there stood Kamprad, sitting behind one of the cash registers and ringing up his customers’ purchases. Lindstrom said to him, “Why are you doing that?”

He replied, “Because this is the cheapest and the most efficient research ever. I can ask everyone why they choose it and why they didn’t choose it.” Kamprad’s response is the essence of how good business leaders can continue to embrace the human element of their businesses.⁽³⁾

There is only so much the data and an algorithm can determine for you. Speaking directly to the consumer or having more intimate knowledge will help one understand why someone purchased or chose one product over another. Was it based on size? Color? Or some other differentiating factor that AI or machine learning may not pick up. Yes, small data can be gathered by mining big data, but that doesn’t allow for true customer interaction. An algorithm cannot compute a satisfied smile, it cannot monitor a pivotal conversation between sales associate and customer, and it cannot “hang” around the water cooler” to gauge employee satisfaction. Let’s face it, there are still some sacred places where human interaction dominates.

Ultimately, building bridges between your data and the human element builds trust and understanding. And finding the right data scientists and consultants to interpret that data frees you up to leave the computer screen to visit the water cooler, the shop floor, even the checkout line for a more organic assessment of your company’s success…and the occasional chocolate-covered donut.

1.) Lane, A. (2020, August 9). Why analytics still needs the human element: Analytics can technically be used by itself, but needs the human element. Innovation Enterprise. 2.) Lindstrom, M. (2016, March 24). Why small data is the new big data. Knowledge@Wharten: Wharten@University of Pennsylvania. 3.) Mazzei, C. (n.d.). Addressing “the human element” in data analytics. CIOReview. 

.