Data literacy: Overcoming the “so what” objection
As we explored in our recent white paper, data literacy is key to building a culture of data, which in turn forms the bedrock of a truly data-driven organization. Yet data leaders in businesses across industries continue to encounter resistance to data literacy programs, much of which takes the form of the question “Why should I care about data literacy?”
Fortunately, leaders can address and overcome this objection by educating teams and individuals on three key reasons why data literacy benefits the individual, their team, and the organization as a whole.
1. Data is the new competitive advantage
Twenty years ago, Netflix approached Blockbuster about forming a partnership that would enable the latter to offer an online service. According to former Netflix CEO Barry McCarthy, Blockbuster “just about laughed us out of their office.” Netflix had been hit hard by the .com crash, and Blockbuster figured they could copy the online subscription business model and grab that share of the market. It didn’t work. Today, Netflix is a Fortune 500 powerhouse, and Blockbuster no longer exists.
Organizations like Netflix, Airbnb, Amazon, and Uber have adopted data-driven insights to disrupt their industries, while their competitors scramble to keep pace or face the consequences. Forrester estimates that “insights-driven businesses”—companies that “systematically harness insights across their organization and implement them to create competitive advantage”—grow at an average of more than 30 percent annually.
By gaining the basic skills and knowledge they need to understand, interpret, and take action on data, individual team members are positioning themselves to help grow the company’s competitive edge, which is a win-win for everyone.
2. Data provides a common language
Imagine two stakeholders discussing the state of their organization’s customer service offering. One person is concerned that callers are waiting too long on hold and wants to increase the number of agents. A second person may not think there’s a problem with hold times — after all, everyone expects to have to wait when they call customer service, and most of the company’s customers use the self-service app anyway … don’t they?
This is just one example of a situation where the missing link is a common language: one person sees a serious threat to their customer satisfaction while another sees a minor inconvenience that affects a few individuals. Data provides a common language that can help these two people get a clear picture of the situation, offering real-world answers to guide their decision.
| Question: Are call wait times a problem we need to address? | |
| Without data | With data |
|
“I just think/don’t think it’s a problem.”
“Leadership thinks/doesn’t think it’s a problem.”
“It’s [never] been a problem before.”
“We’re getting complaints.”
“The customers I’ve talked to don’t seem to mind.” |
“Let’s look at the data and find out …
• How many customers seek support and what percentage come through the phone
• Our customer satisfaction percentile for our industry
• How long it takes to manage 90% of all support calls
• Whether customers with longer wait times give lower Net Promoter Scores or have higher rates of attrition” |
If the organization ensures that stakeholders have the skills needed to interpret and draw insights from data (and, of course, provides access to well-curated information), it creates a common language that can facilitate discussion, collaboration, and consensus.
By establishing a common language, organizations can take the first step in creating a data culture—a shared set of behaviors and beliefs of people who value, practice, and encourage the use of data to drive decision making. This cultural shift paves the way for the adoption of data-driven insights and evolution to a data-driven organization, in which no one would think of making a major decision without first asking “What does the data tell us?”
3. Data professionals can’t do it all
Most larger organizations employ professionals who are tasked with managing data and delivering data-driven insights. However, the volume, velocity, variety of data flowing into and around organizations is escalating daily, and the job of translating data into business intelligence has become too enormous for a small group of specialists to handle alone.
Even when decision makers do rely on data professionals, the time gap between the request and delivery of the information could cause the organization to miss out on time-sensitive business opportunities. Also, when business users become self-sufficient data consumers, they review data through the lens of their own experience and knowledge, which enables them to adopt new data-driven insights that may not be apparent to the company’s data professionals.
Organizational change rarely follows a smooth path, and the changes required to build a data-literate workforce are no exception. Employees whose schedules are already full may balk at the idea of taking time to learn how data works and adding data reviews to their regular to-do lists. By helping them understand how growing in data literacy helps them do their jobs better while also benefiting the organization as a whole, data leaders can overcome the “so what” objection and prepare the way for a successful data literacy program.
This article is the first in a three-part series on data literacy. You can read Part 2, "Enterprise data literacy: your step-by-step guide," here.
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Nick Kelly is the Director of Visual Analytics at Logic20/20. He is a hands-on leader in analytics with over 16 years of international experience in analytics and software development, deployment, adoption, and user experience.
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