Video produced by Steve Nathans-Kelly
At Data Summit Connect 2020, The AI-Powered Enterprise author and CEO of Earley Information Science, Seth Earley discussed how to build data architectures with customer experience in mind.
Full videos of Data Summit Connect 2020 presentations are available at www.dbta.com/DBTA-Downloads/WhitePapers.
When enterprises start building out this architecture, combining this experience of improved efficiencies and contextualized experience, companies have this "North Star" as a blueprint, Earley said.
"This vision of an enterprise architecture that will leverage these terms and concepts consistently across the organization. This is aspirational. This is a North Star," he said.
At the end of the day, it's about building that seamless customer experience, understanding that customer, getting them the right data and content in the right time, in the right format, Earley explained.
Establishing those baselines by understanding those problems and data sources means understanding the impact to stakeholders. There's a lot of different prioritization approaches.
"You can get those conversations started when you start putting these into a framework to say, what's the business value and what do we need to do and how complex does it need to be? And we want to take those big-picture-vision objectives and translate them into very tangible goals that can be part of the business imperative and the departmental and process metrics," Earley said.
The vision of being a data-driven organization or an AI-powered organization is great and must translate to things organizations can do today, he observed. And then enterprises have to translate that message according to the different stakeholders and what they need and how they will use the data and the outcomes and how they will benefit.
"And at the end of the day, it really has to be developing these multiple levels of scorecards and dashboards because it'll help you course-correct. It'll show the value, you'll measure the ROI," Earley said. "You'll be able to fine-tune and continually adjust these decisions that are made. And this goes into a metrics-driven governance playbook, which really helps you allocate resources for data initiatives. It helps you allocate resources for infrastructure for technology, and it helps you understand that you are in fact getting the return on investment and that the organization is on track while you're doing these projects, because it's going to take time to see some of the results."