Why You Can’t Forget About Small Data

Why You Can’t Forget About Small Data | The Sterling Woods Group

The phrase “big data” has been on the lips of every executive for several years now. Breathless presentations at conferences and glowing articles in business publications have extolled the virtues of big data. The promise of big data, the internet of things (IoT), machine learning, and artificial intelligence (AI) are all intertwined, and every leader wants to be at the forefront of this seismic shift in the way we do business.

The folks at the helm of the biggest brands out there, the Amazons and Walmarts of the world, are knee-deep in big data. But for executives leading smaller organizations, there might be a hesitation to get into the big data game.

Smaller companies naturally have fewer data reserves. Of course, a company with 10,000 customers is going to have less data than a company with 100 million customers.

However, that doesn’t mean that only huge organizations can reap the rewards of data. While big data has become a buzzword, small data has begun to establish itself as its equally valuable baby sibling. Let’s take a closer look at small data: why it matters and how an organization of any size can harness it to make smarter business decisions.

Let Your Analytics Be Driven by Strategy, Not Numbers

Let’s start by dispelling the myth that it’s the volume of your data that matters. As with most things in life, to use data to generate actionable insights, it’s about quality, not quantity.

So don’t feel discouraged or sheepish if you only have small data reserves. Each analytics move you make should be driven by your strategy first, rather than the sheer volume of data you have access to.

McKinsey hammers this point home in its article about the importance of purpose-driven data. Creating successful data projects starts with asking the right questions, not diving into the numbers.

What are you looking to change within your organization? Do you have a problem with churn? Is a new product or service underperforming? By identifying what it is you’re investigating, you can find the best data points to help you do it.

Let’s say you run a B2B publication. You notice a dropoff in your subscription rates, and you want to know why.

So you take a closer look at the relevant numbers. Are there fewer leads discovering you early on in the process? Has there been a dropoff in the number of registrations happening on your website?

By gathering all of the relevant numbers in a dashboard, you can quickly identify bottlenecks or changes in customer behavior. Maybe after examining the data, you discover the issue is that subscription registrations on your website have tapered.

From there, you can ask additional questions to learn why. Follow up with those hot leads who suddenly went cold.

Perhaps you discover that your site’s lack of security signifiers have made consumers wary of inputting their credit card information. And voilà! Your small data has led you to a simple solution to help get your subscription numbers back to where they should be.

Big Data Isn’t a Prerequisite

Did you know you can do amazing things with only a couple hundred data points? That’s really small data, but research published in the Harvard Business Review indicates that it’s more than possible to enact meaningful change with tiny bits of data.

Not only that, but these small data projects don’t require advanced degrees in data analytics. It’s possible to empower your existing team to make changes with the data you have on hand right now.

When it comes to finding the benefits of small data, one of the biggest changes you must make is to your mindset. Encourage your team to embrace an approach that’s grounded in testing and experimentation.

Get them involved with identifying areas ripe for fixing with small data projects! They’re in the trenches every day, so they see those points of inefficiency that could be improved by a small data project. Give them the green light to come to you with hypotheses about ways you can improve your existing systems and processes. Then, guide them through the process of applying the Scientific Method to looking for solutions in your data.

Small Data Plus Human Touch Can Unlock AI Possibilities

Some discussions about AI paint it as a magic bullet. It’s perceived as something that comes in and automatically replaces every last one of your human workers. Reality couldn’t be further from that.

Humans must train AI models in order for it to learn how to undertake processes within your organization. When AI is fed too much information or the data isn’t clean, it can get confused and become ineffective.

When it comes to AI, it’s actually small reserves of data plus a stellar human team that can wring the most out of the technology. In this article from the Harvard Business Review, leaders from Accenture explored how an expert human team armed with small data could train a medical AI system to get better at identifying links between medical conditions and treatments to find the appropriate insurance code for a given patient.

When the human experts got involved in reviewing the AI’s work in coding charts, they didn’t just influence changes on the individual chart in front of them. They also taught the AI how to behave with similar charts in the future.

This investment in a small data project, plus the trust in a human team, enabled the organization to code charts more efficiently. The AI was able to take over the simpler coding cases. That freed up the human team to focus in greater depth on complicated coding issues.

Small Data Puts You in Touch with the Real Customers Behind the Numbers

The danger presented by an obsession with big data is that you can lose sight of what that data represents. Yes, in aggregate, that data can tell you something (if you know how to put it to work for you effectively). But on the other side of each of those individual data points is a real, live customer or prospect.

That’s why business transformation expert Martin Lindstrom is so enamored by the power of small data. During his interview on the Knowledge@Warton podcast, he gives several examples of major brands, like Lego and Walmart, who have gotten so bogged down in their vast data reserves that they ignored what actual individual customers were telling them.

By way of contrast, he also shares a story about IKEA founder and owner Ingvar Kamprad. He’s famous for sitting at a cash register, personally checking customers out and inquiring about their purchase decisions. Lindstrom asked him why he did this, and Kamprad replied, “Because this is the cheapest and most efficient research ever.”

Businesses with fewer data reserves can find themselves at an advantage over those multinationals with millions of data points. By maintaining a closer connection with the people behind the data, it’s easier for small data-focused organizations to hone in on the right questions to ask of their data. From there, they can come up with answers that move the needle in the right direction for their business.

It’s undeniable that data can help businesses make smarter, more informed decisions. And that’s true of any organization, regardless of the size of their data reserves. Whether you’ve got millions of data points or only a few hundred, there’s always an opportunity for you to ask the right questions and find the best answers in the data.

About the Sterling Woods Group, LLC

The Sterling Woods Group’s mission is to help clients make sense of their data to predictably grow sales. We apply data science to help you optimize your sales funnel, improve your marketing ROI, launch new products successfully, and enter new markets profitably.

We use a hypothesis-driven, data-supported methodology to discover insights that no one else is paying attention to. Then, we help you assemble the right sales strategies, marketing plans, technologies, and resources to seize this opportunity.

About the Author

Rob Ristagno, founder and CEO of the Sterling Woods Group, previously served as a senior executive at several digital media and e-commerce businesses, including as COO of America’s Test Kitchen. Starting his career at McKinsey, his focus has always been on embracing digital technology and data science to spur strategic growth.

Rob is the author of A Member is Worth a Thousand Visitors and is a regular keynote speaker at conferences around the world. He has been featured on ABC, NBC, CBS, Fox, and Digiday.

He holds degrees from the Harvard Business School and Dartmouth College and has taught at both Harvard and Boston College.

Rob lives outside Boston, MA with his wife, Kate; daughter, Leni; and black lab, Royce.