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The Data Literacy Imperative - Part I: Building a Data Literacy Program

Participants raising hands in a data literacy workshop

It seems that everyone is talking about data literacy today. CDOs position literacy among their top priorities and many organizations count it among their pressing needs. A Qlik survey finds that only 24% of business decision makers are confident in their abilities to work with data and that less than one-third of C-Suite leaders are viewed as data literate. A recent report by Wayne Eckerson finds that only 20% of organizations have a data literacy program, yet 68% believe that data literacy has significant impact on financial performance. The need for greater literacy clearly exists, and the level of awareness is high. The puzzle is in what comes after awareness. How do you create data literacy? Where to start and how to grow data literacy? 

This is the first in a series of articles where I’ll address those questions: Where to start and how to grow data literacy? Let’s begin by acknowledging that it is a big undertaking. Data literacy is fundamental to success as a data-driven organization, and literacy at the level needed is not something that will happen casually. You’ll need a data literacy program—formalized, funded, sponsored, planned, executed, and measured. Further, you’ll need a program that addresses all three dimensions of data literacy—people, knowledge, and culture. And to get started, you’ll need to agree on a definition of data literacy. Definition is prerequisite to goal-setting, planning, execution, and measurement. 

What is Data Literacy?

Data literacy is the ability to understand, find meaning, interpret, and communicate using data. Just as language literacy is the set of knowledge and skills to communicate and inform with words, data literacy encompasses a similar set of knowledge and skills to communicate and inform with data. 

Data literacy is both an individual and an organizational skill set. A data literate individual has the ability to understand, interpret, and apply data to fulfill communication responsibilities of their specific job role. A data literate organization has the ability to communicate, collaborate, and innovate using data. 

People and Data Literacy

With the variety and diversity of data-related job roles, data literacy is clearly not a one-size-fits-all set of knowledge and skills. Yet it is impractical to define, develop, and measure literacy uniquely for each job role. 

For purposes of data literacy program planning and management, it works to address data literacy for two distinct groups. I’ll refer to the groups as data analysts and data strategists. But let these labels apply somewhat liberally; they are roles, not job titles. In the data analyst group, include anyone whose role includes responsibilities to analyze data. That might be a full-time data scientist, a marketing manager who analyzes campaign responses, or virtually anyone who participates in self-service analytics. In the data strategist group, include executive and leadership roles with responsibility to set direction, secure funding, establish policies, and drive initiatives to create value with data. 

Data Analysts. Nearly everyone in business today works in the roles of business analyst and data analyst as part of their day-to-day activities. Data literacy is an essential set of skills to be successful with data and business analysis. Data literacy often makes the difference between understanding and misunderstanding, and between communication and miscommunication. Developing data literacy through trial and error is a high-risk approach, and the cost of errors can be exceptionally high. A literate data analyst has knowledge and skills related to:

  • Data and database fundamentals

  • Data governance and metadata responsibilities

  • Data integration, data warehousing, and data lake concepts

  • Basics of BI and analytics

  • Data searching and data evaluation

  • Data preparation processes and techniques

  • Data analysis and data visualization

Data Strategists. Business executives and leaders fill critical roles in the quest to be data driven. Becoming a data-driven organization depends less on technology than on people, processes, and culture. They create the data vision, define and communicate data strategy, and shape data culture. In these roles data literacy is important not only to communicate with data, but also to communicate about data. A literate data strategist has data knowledge and skills related to:

  • Value creation

  • Risk management

  • Governance practices and processes

  • Culture and data sharing

  • Roles and responsibilities

  • Processes and technologies

  • Use cases ranging from reporting to data science

  • Data analysis and data visualization

The goals of a data literacy program are to ensure that every individual in each of these groups has the knowledge and skills needed to fulfill their responsibilities, and that the organization collectively has all of the skills needed to communicate, collaborate, and innovate using data. 

Building a Data Literacy Program

Building a data literacy program is a complex endeavor involving many activities to develop people and build knowledge, and several more activities to create a culture of data literacy. Figure 1 illustrates the activities and their relationships. 

Figure 1. Data Literacy Program Activities

The data literacy program is a cross-functional effort that minimally involves data analysts, data strategists, data governors, data coaches, and HR management. People and knowledge activities focus on literacy assessment and filling knowledge gaps. Culture activities are directed at weaving data literacy into everyday work activities – data literacy as part of job descriptions, data literacy in governance practices, etc. Individual literacy assessments are aggregated to derive organizational metrics, which in turn inform culture-oriented activities. 

This is but an initial introduction to the scope and activities of a data literacy program. At first glance, it may seem overwhelming or intimidating, but don’t shy away. It is a pragmatic way to address the pressing need for data literacy, and it should be done incrementally to grow and evolve data literacy over time. There is much in the diagram that needs deeper explanation. That explanation becomes subjects of future articles to discuss:

  • The data literacy body of knowledge (DLBOK)

  • Data literacy assessment and learning resources

  • Measuring, monitoring, and managing data literacy

Read - The Data Literacy Imperative - Part II: The Data Literacy Body of Knowledge

Dave Wells

Dave Wells is an advisory consultant, educator, and industry analyst dedicated to building meaningful connections throughout the path from data to business value. He works at the intersection of information...

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