Goals

What kind of questions and expectations will you find in the Data Fluency Survey and its components?
Component 1: Data Fluency Literacy
The survey assumes that “some level of basic data literacy skills are needed by nearly all employees”. Data literacy skills are the skills needed to “thoughtfully consume data”. It also looks for the employee’s individual attitudes towards data.

The survey does not assume that all of your employees will have the same level of skills. It does suggest that you might want to try to measure the skills of people before your hire them and that you can use the survey itself to identify existing employees that might benefit from more training.

These are the kinds of skills the survey is interested in:

  • Summarize, average and total data.
  • Understand distributions of values and find outliers.
  • Recognize trends.
  • Understand charts and graphics.
  • Recognize “actionable” insights in data.
  • See inconsistencies and weaknesses in data.

These are the kinds of attitudes towards data it asks about:

  • Does the organization use data to guide decisions.
  • Do presentations have clear messages.
  • Is the organization’s strategy linked to performance metrics.
  • Are insights and conclusions drawn from data valued.
  • Is the reliability and validity of data sources considered.

Take the Data Consumer Literacy component

Component 2:Data Product Author Skills

These are the kinds of skills with tools it is looking for:

  • Presentation tools
  • Spreadsheet tools
  • Statistical analysis packages
  • Visual analytics tools
  • Software for taking organizational activities
  • Tools for creating dashboards and visualizations

These are the kinds of questions it has for data authors:

  • Do you have the access to the data you need
  • Do you have the tools you need
  • Do you consider your audience when you build presentations
  • Do you consider your audience’s audience
  • Do you put non-essential or extraneaous information in an appendix
  • Do your presentations help the audience decide what is important
  • Do your presentations encourage specific actions
  • Do your presentations highlight exceptions and provide alerts for problems.
  • Do your data products communicate progress and success
  • Do you reduce distracting elements in your presentations.

These are the attitudes it asks about:

  • Are data products expected to guide decision making
  • Can data products be filtered to match the needs of their audience
  • Are data products linked to the organization’s mission and vision.
  • Do data products have a reference guide or help for new users.

Take the Data Product Author Skills component

Component 3:Data Fluent Culture

This component values “leaders identifying and communicating a set of key metrics” and “developing a shared understandings for data usage”. It thinks “performance metrics should be directly aligned with strategy and mission” at all levels of the organization. It also looks for policies that “help create a shared understanding of the data being analyzed.”

Questions about Leadership:

  • Do leader’s presentations us data to support the organization’s mission and vision
  • Is each element of the organization’s vision tied to specific data elements
  • Does the organization test of for data fluency when hiring
  • Is the data fluency of employees considered when placing them in teams or giving them positions.
  • Does the organization provide ongoing support and development for its employees data fluency

Questions about key metrics:

  • Do all employees understand key metrics
  • Do the organization’s key metrics align with its mission and vision
  • Do team leaders/managers align their metrics to those of the organization
  • Do employees understand how their work aligns with the organizations key metrics
  • Do organization leaders reference key metrics when they communicate

Questions about shared understanding and everyday data use:

  • Do people who use data understand how it is collected
  • Does the organization collect information about its data sources
  • Do users of data share a common vocabulary
  • Do people in the organization have easy access to raw data
  • Can the organization evaluate and use data without being sidetracked by natural variations.
  • Are data reports timely enough to be used in decision making
  • Are decisions based on data analysis

Take the Data Fluent Culture component

Component 4: Data Product Ecosystem

Looks for “data products that are of consistent quality, respond to end-user needs, are easy to find and evaluate, and evolve based on feedback.”

Questions about demand and design:

  • Does the organization identify areas where better data is needed.
  • Do employees have influence over what data products are created and shared
  • Are reports designed with ease of use in mind
  • Do reports come with information to explain their context
  • Are there guidelines for creating consistent data products

Questions about Development:

  • Does the organization have the tools and processes to create data products efficiently
  • Do users receive data products in a timely manner
  • Do data products allow easy customization
  • Are end user needs considered throughout the process of data product development.

Question about Discovery:

  • Are data products easily shared
  • Is it easy for users to find the data products they need
  • Can users browse data products by title, author, description or category
  • Is there a centralized online environment where users can search for data products

Questions about discussion:

  • Do colleagues discuss insights from data
  • Are data analysts encouraged to share their insights
  • Are data insights valued and recognized
  • Do data products filter out irrelevant content
  • Are data products continually improved based on user feedback
  • Are data products that are not used retired or archived

Take the Data Product Ecosystem component

Take the Full Survey