This is Part 4 in a series about Collective Data Empowerment. If you want to get the whole series and accompanying tools in an ebook, go here.
You are in a dark forest. Above, the dense canopy of branches and leaves hides the sun’s position. Your phone died miles ago. You hear animals cry in the distance as you strain to listen for highway sounds that will lead you back to safety.
Before your mind thinks it, your gut feels it: you’re lost.
All you have is intuition, so you start walking in the way that feels right. You wish you had a compass. You wish you remembered that thing about moss growing on trees. Most of all, you wish you weren’t alone.
Working with data in an enterprise can feel like a less-terrifying version of this. Your hidden data workforce is lost in the wilderness. The tools they need are missing (like the compass) or unusable (like the cell phone). The knowledge and practices they need are hidden (like the sun’s position) or forgotten (like the moss trick). And the people who can help just aren’t there.
But, what if…
A short time later, a park ranger finds you wandering. She doesn’t just point you to the highway, she gives you a compass and a map. And she walks with you, teaching you navigation techniques along the way.
With your new tools and knowledge, you’ll be prepared for the next hike. In fact, you’re excited for it! You share what you learned with your friends and start hiking with them every weekend. The group grows and attracts people of all skill levels and backgrounds. Each new member contributes something different to the collective. You all become better hikers, equipped, prepared, and confident. Each excursion is slightly more challenging than the last. Before you know it, you’re an experienced and skilled hiker surrounded by thoroughly capable peers.
If you’re an expert data practitioner, how can you lead your hidden data workforce through the wilderness? If you’re a subject matter expert with less data literacy, what will it take to use data more frequently, more confidently? And if you’re a data executive with a mandate to create a data-driven culture, what’s the quickest path out of the dark forest?
The answer is Collective Data Empowerment: the thoughtful combination of tools, practices, and strategies that makes everyone more productive with data. Here are some of our favorite examples of Collective Data Empowerment in enterprise.
Tools & education: Airbnb’s data portal
Airbnb is building a truly data-driven culture across the entire company. The vision of Data University is one of Collective Data Empowerment.
Data University is data education for anyone at Airbnb that scales by role and team. Our vision is to empower every employee to make data informed decisions.
–Jeff Feng, Product Lead, Data at Airbnb
Central to the program is Airbnb’s homegrown data portal. It’s purpose-built to foster collaboration between employees of all data literacy levels and to empower them with data.
Practices: Salesforce’s socratic diagnostic process
In Part 2 of this series, we wrote, “When companies win, when companies fail, people feel it.” So, what does a company with a $108B market cap do when it misses a sales target? It digs into the data and the culture. We can learn a lot from how Salesforce took a rigorous and inclusive approach to understanding the context, asked laser-targeted questions about the problem, and designed a process and solution around the people with the most knowledge and the most skin in the game.
When we decided to build our own forecasting technology, it started with domain understanding. By that, I mean understanding the sales realm, sales pipeline, teams, structures, and processes. We sat down with sales leaders, reps, and all of the constituents to dig into the sales pipeline as a framework.
–Robin Glinton, VP Data Science Applications at Salesforce
The hidden data workforce — in this case, the sales team — was involved at every step, from finding the heart of the problem to creating and improving the solution. The resulting tool worked so well that it’s now a product they sell. You might not need an AI-powered sales forecasting tool, but if you want to create a data-driven culture fast, you do need the Collective Data Empowerment thinking that helped this Salesforce initiative succeed.
Strategies: AP’s data journalism program
Effective data sharing goes beyond just sharing spreadsheets. The Collective Data Empowerment approach to data sharing means people across the data literacy spectrum understand where the data comes from, what it means, what they can do with it, and other context to improve understanding and usability.
Knowing this, The Associated Press collects, prepares, and packages the data in their data catalog so its members can easily discover and report local stories. Every dataset ships with ready-to-fire SQL queries and simple instructions, so members can easily segment the data for their local news markets.
Hey @AP Data Distro members: just shared a pretty nifty dataset and analysis from @larry_fenn to help you gauge the impact of Trump tariffs on your area; webinar tomorrow at 2 p.m., don't miss this one— Meghan Hoyer (@MeghanHoyer) August 21, 2018
Through AP’s data journalism program, journalists from 300+ organizations have gained access to a user-friendly source of vetted and story-rich data to power local news.
We thought if we could put this data into the hands of our members and customers, they could find stories in the data we’d never see.
–Troy Thibodeaux, Editor, Interactive Newsroom Technology at AP
Now you know what you can do with Collective Data Empowerment, are you ready to get started?
Get right to it and download the complete guide to building a data-driven culture through Collective Data Empowerment.
Check out the rest of the Collective Data Empowerment series!
- NEXT: 3 ways to find out what your data people aren’t telling you
- The high stakes and staggering opportunity of data-driven culture
- 16 patterns you see in pre-data-driven companies
- You can’t build a data-driven culture without your hidden data workforce
(Editor’s note: This post was updated on 9/19/2018 to add new resources and reflect the completion of the initial series of posts.)