Zero One: Why Companies Fail with Data
Imagine being adrift in the open ocean, surrounded by water, and dying of thirst. Customer data is much like this, we’re drowning in the stuff. While most companies amass information about their customers, only three out of 10 marketers say they’re good at turning data into measurable business outcomes, according to Forrester.
“Most firms are swimming in data, but they’re only using a third of it,” says Forrester analyst Sharyn Leaver, in her report, “Top Five Imperatives to Win in the Age of the Customer.”
Forrester isn’t alone in shedding light on corporate America’s missed data opportunity. In a recent McKinsey Consulting survey of more than 500 executives across regions, industries and sizes, a whopping 85 percent said they were only somewhat effective at meeting goals they set for their data and analytics initiatives.
To better understand what’s at stake, one only needs to look at the few companies doing it right. The biggest winners, of course, are famed digital disrupters that took advantage of customer data insights to improve the customer experience and upend entire industries.
Generally speaking, customer-obsessed companies using data to fuel insights, create differentiation, and drive revenue with the customer experience have the highest median three-year growth in sales, Forrester says. They also boast the highest levels of both customer and employee satisfaction.
There’s no question customer data leads to valuable insights, differentiated products, a better customer experience, and more sales. In fact, companies leading in customer experience have five times the revenue growth of customer experience laggards, Forrester says. In some industries, the gap is even wider.
So what’s stopping companies from unearthing and executing on customer data insights? It’s a complex problem often requiring a massive overhaul in company culture, technology, and processes – a daunting digital transformation.
For example, most companies have separate functional groups working independently under a command-and-control style. Data doesn’t flow freely, insights aren’t shared. While this model drives clear accountability and predictability, Forrester says, it creates long decision cycles and conflicting customer experiences.
Instead, companies might want to consider deploying small teams made up of members from different disciplines. These agile teams, informed by customer data insights, might be focused on improving a particular customer journey.
Bedrock technology, too, might need to be broken down and rebuilt. In a report this spring, “What’s Now and Next in Analytics, AI, and Automation,” McKinsey Consulting says companies have to re-think how data is generated, collected and organized.
“Many incumbents struggle to switch from legacy data systems to a more nimble and flexible architecture that can get the most out of big data and analytics,” McKinsey Consulting says. “They may need to digitize their operations more fully in order to capture more data from their customer interactions, supply chains, equipment and internal processes.”
Based in Silicon Valley, Tom Kaneshige writes the Zero One blog covering digital transformation, AI, marketing tech and the Internet of Things for line-of-business executives. He is eager to hear how digital transformation is impacting your business. You can reach him at email@example.com.