Building a Data Fluent Organization
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This document discusses building a data fluent organization. It defines data fluency as the ability to use data to fluidly exchange and explore ideas within an organization. It presents a data fluency framework with four quadrants: data literate consumers, data producers, data fluent culture, and a supportive data ecosystem. The framework provides examples and recommendations for developing skills and processes to improve an organization's data fluency.
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Building a Data Fluent Organization
- 1. copyright Juice, Inc. 2016 Building a DATA FLUENT ORGANIZATION Zach Gemignani, Founder & CEO, Juice Analytics
- 2. copyright Juice, Inc. 2016 Improvements More about what data fluency means. Flows of information From data to action Data is expensive. Information is valuable. Culture slide is boring. Data producers —> authors http://www.presentationzen.com/presentationzen/2009/05/making-presentations-in-the-ted-style
- 3. copyright Juice, Inc. 2016 1. Three short stories… What do they have in common? Show that data is the new language. And people 2. At Juice, we are known for our ability to visually communicate with data. At the same time, we’ve worke But when Nathan Yau and Wiley asked us to write a book — after 10 years of blogging, white paper (cred 3. What is data fluency? What is at stake? Why does it matter? Informed decisions; organizational alignment; digital divide; 4. How do you do it: Explain/build framework. Four quadrants — What it is + example + our recommendat 5. What does that mean for me? What can I do? — personally, professionally Outline
- 4. copyright Juice, Inc. 2016 Day after day, day after day, We stuck, nor breath nor motion; As idle as a painted ship Upon a painted ocean. Water, water, every where, And all the boards did shrink; Water, water, every where, Nor any drop to drink. — The Rime of the Ancient Mariner, Samuel Coleridge
- 5. copyright Juice, Inc. 2016
- 6. copyright Juice, Inc. 2016
- 7. copyright Juice, Inc. 2016 Big Data Has big data failed to meet expectations? Gartner Hype Cycle Forbes, 2/14/14
- 8. copyright Juice, Inc. 2016 http://www.flickr.com/photos/rocor/6398436515 We need to refine data into products and decisions that drive your organization forward copyright Juice, Inc. 2016
- 9. copyright Juice, Inc. 2016 Spreadsheet proliferation Lack of BI adoption Ivory-tower analytics Stuck data warehouse projects Many, disparate data sources Inaccessible reporting Lack of management support for data projects Data scientists Dashboards Data visualization and storytelling Big Data Technologies ROI-justification of data projects Self-service BI Master Data Management Cross-trained analysts Lots of problems, lots of solutions
- 10. copyright Juice, Inc. 2016 https://www.flickr.com/photos/kebabette/229919555/ What does it take for an organization to be able to unlock the value in their data? What skills, culture, processes and technologies are required? copyright Juice, Inc. 2016
- 11. copyright Juice, Inc. 2016 Data fluency: the ability to use the language of data to fluidly exchange and explore ideas within your organization.
- 12. copyright Juice, Inc. 2016 People & skills Communication Leadership Technology More data Tools The focus of data fluency
- 13. copyright Juice, Inc. 2016 Data product authoring Data fluent culture Data ecosystem Data literate consumers Data Fluency Framework Data Consumers Data Producers Individual Organization
- 14. copyright Juice, Inc. 2016 Language of data Critical consumer How to find insights Data sources Data Literate Consumers
- 15. copyright Juice, Inc. 2016 Fantasy Football 25 million football fans transformed into sophisticated data consumers
- 16. copyright Juice, Inc. 2016 Message & audience Data visualization Data storytelling Form, aesthetics User actions Data Producers
- 17. copyright Juice, Inc. 2016 Rising standards for data viz
- 18. copyright Juice, Inc. 2016 Data Fluent Culture Leaders set expectations Shared language Well-understood key metrics
- 19. copyright Juice, Inc. 2016 Apple App Ecosystem iOS SDK Developer rules & tools App Store sales and reviews iOS device users App Store
- 20. copyright Juice, Inc. 2016 Development tools Standards and training Feedback and improvement Discoverability and sharing Data users Data Ecosystem An environment that supports fluid movement and sharing of ideas through data
- 21. copyright Juice, Inc. 2016 Ability to understand and draw meaning from data products Skills to create effective data products Ecosystem for building and sharing data products Foundation for common interpretation of data products Data Fluency Framework Data Consumers Data Producers Individual Organization
- 22. copyright Juice, Inc. 2016 So you’ve got Big Data… You have all the data and technology you need Data is only as good as the people using it Shared understanding and communication is the missing link
- 23. copyright Juice, Inc. 2016 Our perspective A decade of working with businesses who wonder: “How can I get more value from my data?” • Web dashboards • Visualizations • Analytical tools We work with great companies! copyright Juice, Inc. 2016
- 24. copyright Juice, Inc. 2016 info@juiceanalytics.com Twitter: juiceanalytics Linkedin: linkedin.com/company/juiceanalytics
Editor's Notes
- However, our experience in many organizations feel more reminiscent of the famous poem “Rime of the Ancient Mariner”. Particularly this line: “Water, water, every where, Nor any drop to drink”. Data is everywhere, but it seldom seems to quench the thirst for smarter decision. As a side-note, this poem originated the phrase “albatross around your neck.” — which is how a lot of CIOs feel with both the data and expectations getting bigger.
- Big data is hot. And the stories about what can be done with big data are tantalizing. IBM has done a particularly good job of stoking interest — data can make doctors smarter, deliver exactly the right product to the right customer. Expectations are high because it feels like there are near-endless possibilities given all the data available.
- Let me share a couple examples: We’ve been working with a large healthcare informatics company — a company that literally specializes in analyzing and reporting on data. But like a lot of companies, complexity rules. They need to report to their hundreds of customers. But to do so… And they have made multiple efforts to clarify and simplify this process, always derailed by a culture that prizes complexity
- If data is like oil, we need the ability to transform oil in to entry In many ways, data is like oil - and it is certainly so in the economic engine of your organization. Just like you can't pull crude oil from the ground and pump it directly into your gas tank, or mold it into a plastic Lego, you can’t dump data into an organization and expect it to grow. Creating value from data is a complex puzzle, one that few organizations have solved. While there isn't a simple answer (and thus why so many organizations struggle), the good news is that understanding the nature of the problem offers a starting point for our path forward
- The problem with data is that everyone is touching a different part of the elephant.
- Specifically, the problem might be lack of management support, lack of end-user adoption, poorly defined requirements. And for each of these issues, there has emerged a solution that can help solve for that pieces of the puzzle. Data visualization….Hadoop…more data scientists…self-service BI.
- This is the puzzle we want to piece together…specifically… This is the subject of a book I’m writing with a few colleagues which will be published in the fall.
- The answer we have come to revolves around this phrase: DATA FLUENCY. We define it as the shared ability to: speak the language of data, exchange and understand data, create tools to facilitate this exchange of data.
- Sure, data fluency requires analytical tools, the ability to handle and manipulate big data. But that isn’t what it is about. On balance, it is more about communication, people with data skills, and…perhaps most importantly…leadership and expectations to build data fluency in an organization.
- This is how we think about it. To us, Data Fluency requires capabilities both at an individual level and an organization level. In addition, it exists for both consumers of information and for those people who create the reports, dashboards, and analyses…data product authors. Introduce you to the four players…
- How do you create people who can understand data in the same way as they read an e-mail? What does it take for someone to be data literate? They need to understand where data comes from; how to find insights in that data; be an educated and critical consumer of “data products”; and speak the language of data
- When I talk about data consumer — I’m talking about people who have become comfortable with working with data. Fantasy football offers an awesome example. Who here plays a fantasy football? Don’t look now, but we’ve been taught how to think about data, how to read charts, consider probabilities, combine data with context (injuries)
- What makes a great data producer? Those are the consumers of data. How about the people who author the data products? A data fluent organization needs a healthy group of these people with the skills to design reports, dashboards, analyze data and create the presentation that explains the analysis.
- Leadership: Setting expectations; Actions to demonstrate commitment Shared understanding: Key metric: what is important?; Data sources: what can be trusted?; Terminology: what does it mean? Everyday commitment: Training data consumers; Quality data products; Data in discussions
- People — those who can communicate it and those who understand it
- Let me start by giving you a sense of where we come from on questions of data. Since the founding of Juice, we’ve generally worked on the business-side, consulting with executives who feel they have access to valuable data but wonder how to unleash this value. Our focus has always been on how this data can be better communicated and presented to get the right data into decision-makers hands…in a form they can understand. We’ve worked across many industries, but have a particularly deep experience in healthcare, and advertising and media.