Data catalogs function as a central library of information about content and data across an enterprise, making them a useful metadata management tool. They can aid  organizations that struggle with poorly documented metadata, duplicated data work, and wasted time due to the inability to find proper resources. As my colleague Joe Hilger further elaborates in his post on The Top 5 KM Technologies, data catalogs can benefit companies seeking to manage siloed content and improve resource findability. The key to unlocking the knowledge management and data insight advertised by catalog providers requires a careful catalog implementation strategy.

I have led the training and adoption process for data catalog implementations for my full tenure at Enterprise Knowledge (EK). During this time, I have consulted with both our client catalog program managers and catalog provider implementation teams to determine what did or didn’t work to drive catalog adoption at their companies. I have reviewed catalog user research studies across widely differing organizations to learn how various implementation approaches affect the data teams they intend to support. 

My key finding is that successful adoption of a data catalog requires both a user-driven program design and integrating the tool into your team’s day-to-day tasks. In this white paper, I consolidate my experience and findings into three strategic pillars essential to create the necessary catalog environment:

1. Cater to your company’s culture.

2. Make it easy (and enticing) to use.

3. Measure how it’s going.

As each company is unique in both its data ecosystem and goals, there is not a singular approach or definition of “success” for this framework. Each use case requires context-based solutions. I present these pillars as a guide to help you brainstorm an implementation strategy specific to your organization. If you would prefer expert assistance, EK’s team of data specialists is available to help you design an enterprise catalog program tailored to your unique team and data strategy. 

1. Cater to your company’s personas

A culture-driven design means defining an initial use case that satisfies the requirements of the organization as a whole, including both your executive stakeholders and your data users.

Top-down approach 

Obtain support from stakeholders by aligning catalog program goals with the broader data strategy at your company.

As a first step, clarify why your organization is moving to implement a catalog. What are you trying to accomplish by adding this tool to the data ecosystem? Once you’ve ascertained your organization’s why, then move on to the how. What level of investment are you able to put in? Which catalog providers fit in that scope? Secure executive and stakeholder sponsorship by demonstrating how the addition of a data catalog will fit with the broader data vision. Working to align these two strategies will help you to develop your catalog program high-level goals.

What does success mean for your program overall? With your high-level goals in mind, what specific use cases should you focus on first to step forward towards those goals? Is your priority increased efficiency or increased findability? You understand that by talking to the teams who will use the data catalog for their regular operations. What do your users need to be successful?

Bottom-up approach

Consult with your data team and prospective catalog users to determine what solutions they need to reach the company’s broader goals.

Collaborate with your users to define a range of catalog use cases. To do this, you must clearly define who your company’s catalog users will be. What are their needs, current workflows, and vital tools? Do not assume; ask them. 

Different data personas will have different needs. For example, catering only to data consumers and neglecting the data producers will not build a lasting catalog. Conversely, a catalog with only detailed technical metadata will exclude business decision makers and less technical users. Strive to create a data ecosystem that supports all of your personas. When everyone on the team feels heard, teams trust each other and work together. Therefore, it is vital to explore and clearly define the catalog personas specific to your company and data strategy before you design the catalog. Model the catalog metadata fields around the personas you develop – What problems are your users trying to solve? What information do they need to be able to solve them? 

The goal of combining top-down and bottom-up approaches is to build a culture of community and shared purpose around the catalog. Empathy between user groups leads to workflows that unite, rather than clash, in support of the group effort. To achieve this, the catalog must be approachable, accurate, and integrate into the team’s established workflows. 

2. Make it easy (and enticing) to use

Data catalogs become more valuable as more people use them. How can you recruit more users?

Meet your team where they are

Don’t let catalog adoption be an added stress to your users. Design a program and select a tool that fits their current workflow. Simplify the onboarding process with customized training offerings. 

Technology ecosystem – Integrate with current workflows, embedding commonly used tooling where possible. Actively engaged users make it easier to keep the catalog updated. A catalog that is too burdensome or convoluted to use will collect dust and depreciate. Then, when users log in and find inaccurate data due to neglect, they will lose their trust  in the entire catalog and adoption will fail. Avoiding this requires smart tool selection. Determine and understand the tooling that is vital to your users and confirm it is able to integrate with the catalog provider you select. The goal of this segment is to configure a catalog that will become part of the team’s daily operations for data work. Having constant access and collaboration from your teams helps to ensure accuracy and completeness of metadata by surfacing issues sooner.

Education – Aim to provide self-serve documentation so users can learn at their own pace as their unique needs arise. EK suggests creating customized training materials for the tool using company specific resources, use cases, and your catalog instance UI. This helps your users envision how the catalog fits with their workflow and how they can use it to successfully complete their unique tasks. It can be helpful to designate a few catalog SMEs within your data teams, train them to be power users, and then set them up to help onboard additional users.

What’s in it for me? 

Develop a marketing strategy to broadcast catalog capabilities and internal successes.  

At first, the catalog may seem like added work for your users. Some might think, “Oh great, management is adding another ‘solution’ to our already busy process.” Why should your team make the time to interact with it? What is the reward? The technical benefits of a properly implemented catalog should speak for themselves, so broadcast these! 

EK’s experience has found that you don’t need to recruit everyone all at once. Aim to first establish something beneficial for an initial core group of users and develop some success stories to share. Then, market to the broader audience. Let the benefits speak for themselves and entice people to seek out the catalog rather than trying to force it.

For example, did a data manager curate metadata for x amount of resources, supporting the y team to save z units of time using the catalog? Create a case study to share this success with your organization. A well-crafted case study serves two purposes – first, it recognizes the team members who have added the catalog to their workflow. Second, it increases awareness about the success your data team can unlock using the catalog. Ideally, you want to create an atmosphere where new users are drawn to the catalog by witnessing the success of their peers.

The best way to entice your data team is through testimonials from users similar to them supported by actual performance data. Strategize your internal marketing plan before implementation begins. Plan to do an initial marketing push at regular intervals to recap the growing success of the catalog and showcase the increasing number of teams and users engaged with it. After the catalog has been established, consider sending updates whenever there have been substantial wins or when teams develop new use cases. 

Some data catalog products facilitate sharing catalog usage and successes directly in the user-interface. When choosing a catalog, look for tools that include the ability for users to collaborate within the app and view the activity of other users. Being able to login and see what other team members are working on not only invites discussion but also encourages new users to contribute. 

3. Measure how it’s going

What is working as expected and what is not? Do you need to change course? How can you demonstrate value and progress to stakeholders?

Key Performance Indicators (KPIs)

Use quantifiable results to demonstrate ROI and to monitor catalog usage. 

Have a KPI monitoring plan in place before tool selection. Will your catalog of choice enable you to measure what matters to you? To determine what metrics to measure, reflect on your use case. What is your desired outcome? What are the success criteria to support it? 

It is important to know not only what to measure, but when to measure it. For example, we have  found that effective catalog use doesn’t necessarily mean users will go to the catalog every day. Catalog use may peak during the discovery phase of a project and then steadily decline. When reviewing a decline in user stats, is this decline because your users could not find the resources they needed and abandoned the catalog? Or did they find valuable resources and now are deep in analysis, which won’t require daily catalog use. How can you determine the reason? Survey your users!

User feedback

Successful catalog adoption hinges entirely on your users. Seek out feedback to understand how the catalog is (or isn’t) working for them.

In the case of a data catalog, better content quality enables greater product functionality. While usage monitoring and KPIs will help inform you how users interact with the catalog, it is also essential to frequently engage with your users. Direct user feedback can help you improve the platform’s usability and highlight value to stakeholders. Methods for gathering feedback include focus groups, surveys, and direct interviews. Demonstrating that you value and act on gathered feedback will build their trust in the catalog program. When your users trust the catalog, they will rely on it as part of their default workflow

As you progress from implementation to the next phase, use feedback to learn from your users whether the next iteration should focus on refactoring what currently exists, deepening the current use case, or exploring new territory. 

Conclusion

A user-driven catalog approach is adaptive to changes in data needs and flexible when scaling for both more users and use cases. Centering your users when designing your catalog program provides the most value to your team members who rely on it. When your teams are successful, they will push the broader data strategy forward for the entire organization.

EK’s team of metadata management and data modeling specialists have the experience needed to help you explore and adapt these pillars to your unique organization. Contact us to learn more about how Enterprise Knowledge can help drive your data catalog adoption to success.