A recent survey by analytics consultancy New Vantage Partners found that only 24.4% of executives claimed their firm possesses a data culture. What can organizations do to encourage more widespread data literacy?
An analytics community of practice can serve as a peer-to-peer way to share knowledge and best practices about working with data in an organization. But without a solid design and buy-in, it is likely to be met with confusion or even resistance by managers and staff.
To learn more about establishing analytics communities of practice from those who have successfully done it, I spoke with the following (pictured left to right):
- Kathleen Maley, Chief Analytics Officer at datazuum. Kathleen has worked with hundreds of data analysts to, in her words, “elevate their role from reactive data provider to proactive strategic partner.”
- Sarah Eisele-Dryli, Assistant Director of the Connecticut Data Collaborative. Sarah manages a community of practice for individuals of all roles and skill types in nonprofits and community groups across Connecticut to build their data literacy.
- Chris Goodman, Senior Manager at PwC. Chris is an Alteryx ACE and leads PwC’s Alteryx Community of Practice. He also is the co-author of the popular Alteryx blog, Alter Tricks.
- Lisa Schultz, Assistant Director of Data Science and Analytics at Northwestern Mutual. Lisa is responsible for coordinating an analytics community of practice at the Fortune 100 company.
Why a community?
As you’ll come to see from this article, building an analytics community of practice is a lot of work. If your goal is to build your organization’s data competencies, how is a community going to help over relatively more straightforward formal training programs?
The answer lies somewhere in Aristotle’s famous dictum: “We are what we repeatedly do. Excellence then, is not an act, but a habit.” While attendees may pick up a tip or trick, one-off training sessions are unlikely to influence longer-lasting behavior and culture changes.
By contrast, the long-run nature of a community provides a forum for individuals to collaborate and learn from each other on a frequent basis. This repetition serves as a sort of muscle memory leaving a permanent mark on an organization’s culture. You will see in the next sections from the experts themselves that a successful community of practice grows cross-functional bonds and shifts how people think about the value of data in their organization… tall if not impossible orders for a basic training session.
… a set of skills and the ability to answer questions with data.
Designing the community
An analytics community of practice can find its legs in different ways. For example, Sarah reflects that it just started by professionals sharing articles with each other. “Over time, they were really engaged,” she said, “so we asked to plan the group.” On the flip side, the community can get started with large net. As Lisa put it “We didn’t start small – we went wide! We invited all analysts from across the organization to participate.”
The community’s goals should be considered in these planning stages; in many cases, it’s best to start with principles of data literacy. “In the early days, improving data literacy is important,” Chris mentioned. Sarah agrees: “We really focus on the idea of data literacy as a set of skills and the ability to answer questions with data.” Over time, the community of practice can account for increasingly sophisticated topics as its members gain confidence.
But ultimately, a community of practice should help its participants drive more business value with data. As the community finds its purpose among data users, it’s also important to consider its impact on the outside business.
For Kathleen, this means setting expectations among analytics and business users: “I will have a conversation with my analysts and tell them, ‘Your job is different than it was yesterday. Your job is no longer to produce data. Your job is to answer questions and provide solutions.’ I will also tell the partner that what you’re going to hear from the analysts will look and feel different… work with them, because if we’re going to provide value, we can only do that if we know the problem to be solved.”
Keeping the community engaged
It’s also important to hold members’ interest as the community develops over time. A great way to do this is keeping an ear to the ground of what analysts are up to day-to-day and responding to those efforts. “It’s important to have people who know the tooling get involved,” Chris said; “people who know the art of the possible.” This effort is to meet people where they are now, with the interests and challenges that they have currently.
At the same time, it’s worth keeping the goal of working more smoothly with the business in mind. “Analytics is not the data in itself, but the act of studying that data,” Kathleen explains. “It should work with strategy, and not upend it.” In this regard, the community of practice may resemble on-the-job training or an apprenticeship, as analysts learn together how to work well with the business. In this way, non-members and business leaders can see for themselves the community in action.
Mixing the variety of formats can also help: “We try a variety of methods to break down barriers. We try different topics, like use case share-outs, and when we have a topic with more technical depth we try to explain the overall gist of what the topic is prior to diving right in,” Lisa explains.
Engaging all skill levels
One significant logistical challenge of a community of practice: how do you keep everyone engaged when they may be coming from various skill levels? In a technical area like data analytics, which can entail so many activities, this can feel tricky to navigate.
Providing supplemental channels and learning opportunities is one way: “We leverage deeper technical knowledge sharing via other channels and can refer people to these,” Lisa explains. “We are also providing opportunities to advance the data literacy of all community of practice members through programs, experiences, and learning opportunities.”
Special interest groups on topics of varying technical levels can also help. As Sarah put it: “we know not every event will be relevant for everyone.”
All that said, there can still be ways to engage data professionals of varying technical abilities all at once. Chris gives a great use case: “A community of practice can act as a medium for data scientists to share what they’re building with citizen data users, and those analysts will often have a use case for it.” At that point, “you have beginners asking expert level questions.”
This ability for data professionals of varying technical levels to work and learn from each other reminds me of a lesson from Empowered by Data (see Resources) that while a formal data academy can be a great resource, so can an informal data schoolhouse of data users coming together to learn from each other, like in a community of practice.
You know it’s been successful when business leaders want analysts in the meetings with them.
Getting to steady state
As the community of practice catches on, participants become more confident in their abilities to grow. “They get into a continuous learning mindset where they know they don’t need another course, but know they don’t know everything,” Chris says. At that point, a community of practice can be a place for people to work through those challenges collaboratively.
On the other hand, it may be that the community fulfills its purpose and doesn’t hit a steady state. “You may just need to close it and be OK with it,” Sarah says. After all, the community is for the benefit of its participants. If they don’t need it, don’t force it.
Evaluating the impact
I had to ask as a data analyst myself: How do you evaluate the impact of an analytics community of practice?
It’s complicated.
While there are ways to measure the impact such as the number of certifications achieved and the improving of team skills over time, likely the benefits are going to be more in the culture itself. Chris puts it like this: “It’s important to have KPIs, but don’t beat yourself up about them. You likely won in other areas.” These wins could be more staff with a growth mindset and better collaboration among analysts and other teams.
Kathleen’s example? “You know it’s been successful when business leaders want analysts in the meetings with them.”
Conclusion
Interest is growing in data literacy and other data-related workforce development programs. An analytics community of practice should go hand-in-hand with these efforts, allowing a place for members to freely learn and exchange knowledge.
I want to thank Kathleen, Sarah, Chris and Lisa for sharing their wisdom on this topic with me and my readers. Perhaps their experiences can inspire and inform your own journey with building an analytics community of practice.
Resources
Some additional resources for you to continue learning about this topic:
- Follow Kathleen on LinkedIn
- Follow Sarah on LinkedIn
- Folow Chris on LinkedIn
- Follow Lisa on LinkedIn
- Read Empowered by Data: How to Build Inspired Analytics Communities by Eva Murray. Check out my review of the book.
- Read Cultivating Communities of Practice: A Guide to Managing Knowledge by Etienne Wenger, Richard McDermott and William Snyder
- Read People Powered: How Communities Can Supercharge Your Business, Brand, and Teams by Jono Bacon
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