Executives commonly say their decisions are based on data, but many don’t operate that way as often as they could, because they fear “paralysis by analysis” and end up going with their gut instincts. That’s the view of Jeanne Harris, who leads research in analytics at Accenture’s Institute for High Performance. In 2007, she and Thomas Davenport coauthored Competing on Analytics, which CIO Insight cited in its list of the “most provocative, engaging business books of all time.” Last year she was coauthor of Analytics at Work. Journalist William Bulkeley asked Harris about why businesses should lean more on data analysis.
TR: How far have businesses come in recognizing the value of data analytics since you wrote your 2007 book?
Harris: In 2007, when the book first came out, 9 to 10 percent of companies we surveyed said that analytics was a key element of their strategic capability. We looked at 35 countries and 19 industry sectors. In every one we found several enterprises that said they compete on analytics or aspire to do so in the future. Today, while we don’t have hard numbers, the percentage has really skyrocketed.
But still there is room for improvement, you argue.
A survey we conducted a few years ago revealed that nearly three-quarters of executives would like to make decisions based on facts. But only 40 percent said they had made their last major decision based on facts. There’s a big gap between aspiration and reality.
What’s the most effective way for companies use analytics: to improve efficiency and cut costs, or to improve customer relationships and boost revenue?
It depends on the industry. In general there are limits to the cost-cutting side. There’s lots of upside potential in growing your markets. A lot of the excitement is in the customer analytics space. Starting out, an organization might focus on improving customer segmentation and understanding buyer behavior. More advanced organizations rely on analytics to optimize the entire customer life cycle. In telecommunications, for example, churn management predicts which customers are most likely to leave and the best strategies for keeping them.
Are Internet-only companies way ahead of brick-and-mortar and hybrid companies?
Many successful Internet entrepreneurs tend to be analytical and comfortable with numbers. Netflix, for example, is a company that is essentially built around an algorithm. Cinematch [the Netflix algorithm] not only predicts which movies a customer will like, it also guides many business decisions. Internet companies like Netflix have other advantages. They can analyze every customer mouse click, not just sales data. They also have fewer barriers to integrating and analyzing customer data. And Internet businesses often take an experimental approach to fine-tuning their website and services, which enables them to collect even more data.
But it’s really about the culture. Many companies, like General Electric, Procter & Gamble, and Marriott, were founded by people who have been analytically managing their business from day one. And every organization has unique information which can potentially be game changing. Brick-and-mortar retailers have information about customer behavior that purely Web-based companies can’t get.
Brick-and-mortar stores have the ability to use sensors and video-mining capabilities to provide information about in-store behavior that can impact store design and merchandising. Salespeople can also gather more qualitative feedback from customers about merchandise and returns. For example, they can get details about defective products, above and beyond the information they would get on a return packing slip, so they can work with suppliers to fix issues.
Do companies actually know their customers better today than they did a decade ago?
A lot of them know their customers better. But they don’t know them nearly as well as they did 100 years ago. In some ways, analytics is a way to get back to the intimate knowledge that the typical retailer had before the invention of the automobile.
Is analytics making customers better off?
If a company uses analytics appropriately, the information will only be used to help customers in ways they want to be helped.
What’s an example of how analytics has led companies to understand customers better?
Best Buy is a company that’s good at timing cross-selling opportunities. When you buy a digital camera, they know you are unlikely to purchase a digital photo printer at the same time. But they also can predict that in five weeks you will have printed some pictures on your current printer. They know you probably weren’t happy with the result. That’s the time they e-mail a coupon for a new photo printer.
Does analytics take the human element out of marketing?
Most hypotheses are human generated. They don’t come from data mining. People see analytics as very quantitative and scientific. They fear it will drive out creativity. We find the opposite. The companies that are most analytical are most experimental. No one would say that Google isn’t innovative. Everything there comes down to some kind of quantitative analysis.
Where will analytics go over the next five years?
Analytics is rapidly moving beyond numeric data. There’s tremendous interest in tapping into data from social-media sites. People want to analyze the information on the Web locked in videos, images, and graphics. We can use facial recognition to ID people in photos. Location services let us know when and where the photo was taken. Organizations are experimenting with sentiment analysis applications to learn how people really feel about their company and products.
The inside story of how ChatGPT was built from the people who made it
Exclusive conversations that take us behind the scenes of a cultural phenomenon.
How Rust went from a side project to the world’s most-loved programming language
For decades, coders wrote critical systems in C and C++. Now they turn to Rust.
Design thinking was supposed to fix the world. Where did it go wrong?
An approach that promised to democratize design may have done the opposite.
Sam Altman invested $180 million into a company trying to delay death
Can anti-aging breakthroughs add 10 healthy years to the human life span? The CEO of OpenAI is paying to find out.
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.