The CDO Midwest Summit 2022, hosted by CDO Magazine and ComSpark, delivered some of the industry’s most relevant, data-related discussions. In the “If You Build It, Will They Come?”session,the following expert panelists discuss data end-user needs and share strategies to build data for organizational development.

• Reginald Mathews, Co-Founder & CTO of Data Economy

• Jonathan Paul, VP, Director of IT Data Governance Fifth Third Bank

• Rich Robinson, Chief Strategist, Open Data and Standards, Bloomberg LP

• Tracy Ruberg, President/Executive Director, T6 Group/The Circuit

Siva Kondamadugula, Co-Founder and COO of Data Economy, moderates the session.

Initiating the conversation, Paul says it is fundamental to get the customer’s viewpoint to understand what they need from data. He speaks about categorizing automated tools and assisting people in learning how to create and configure them.

Ruberg refers to the “five why” rule,  noting, "We have to start to flip our thoughts and say ‘What are we trying to do?’ before thinking about a tool in math.” He emphasizes organizations must understand the problems before offering solutions.

According to Mathews, customers are mostly unable to specify what they want. He developed Data Element 360, a guide to data characteristics everyone should be aware of, which includes information about data characteristics everyone can benefit from.

Mathews then discusses managed versus unmanaged data for large enterprises. He explains that managed data contains curated and governed data; unmanaged data is left up to the audience to decide whether it requires management moving forward.

According to Robinson, career pathing is crucial for promoting data literacy and data culture within organizations. He discusses how the availability of global data enhances several business areas, such as sales and customer goods and services.

Robinson elaborates on the training courses that teach individuals how to use data to solve problems and promote organizational mobility. To spread the data-first culture, he established a data lab where others could develop ideas for new data sources.

Subsequently, Mathews suggests that firms should concentrate on making data-driven decisions to understand data literacy better. He maintains that when innovation grows, it is essential to develop contextual knowledge as part of the search, which increases literacy. Mathews also discusses knowledge graphs as a tool for fostering literacy because they assist in building relevant contexts and guide people in making data-driven decisions.

In addition, Robinson claims that silos exist because "they share culture and processes for a specific purpose," such as community practice. He suggests that organizations attempt to understand the various siloed languages and focus on translation rather than breaking silos.

“You get more data-literate within your organization by not forcing everybody to speak the same, but understand why they speak differently,” Robinson notes.

Tracy says it is crucial to collaborate with end users and go to the locations where data is produced and consumed to reach critical mass.

Robinson recommends organizations have a basic sociolinguistic and change-management awareness of the communities they work with. In addition, Mathews underlines that companies should ensure two things: participation and automation. 

He states that to reach that critical mass, the data stewards must participate in crowdsourcing and metadata curation to improve the organizational data landscape.

Mathews highlights four critical metrics for measuring an organization’s data impact:

1. Ensuring successful implementation of data governance

2. Data evaluation

3. Productivity improvement

4. Ability to create data products

On the other hand, Paul describes data storytelling as the unsung hero. He defines it as “the ability to pull together your data and have it tell a story through visualizations and narrative. Then, you use that as a benchmark of how well you are able to do this as an organization.”

In conclusion, Robinson states that quantitative and qualitative measures are essential to assess the significance of data within an organization. Ruberg acknowledges, however, that only some problems have a technical solution.

Watch other CDO Midwest Summit 2022 sessions HERE