(US and Canada) Wendy Batchelder, SVP of Global Data Governance & Chief Data Officer of Trust, Salesforce, speaks with Peggy Tsai, Chief Data Officer, BigID, about her role, ways to ensure data quality, and the challenges of proving the worth of data governance in an organization.
Batchelder says that in her role at Salesforce, priorities boil down to enablement, simplicity, and connectivity.
“I want to make sure that the company understands how data governance can enable speed and unlock the insights that we need to run our businesses,” she says. “I also have a bias towards simplicity and consistency. It's very easy to be complicated in the data space, but to be able to scale and unlock value, making sure that things are as simple as possible for all of our users, is key for me. And then, it’s bridging connectivity and understanding what all of our data assets are and how to access them.
Batchelder notes ways to ensure that all users contribute to improving data quality. She says that it has to be made practical for the individuals who touch data, whether they're data experts or not. “You have to learn to speak like the locals and ensure that you are not using a bunch of jargon or aren't making it too technical,” she adds. “Thoroughly explain it to them in terms that matter to them. Explain what they are, what they can do, and also explain why that makes a difference.”
In other words, start with the basics and stakeholders understanding data.
“In many organizations, they don't really know what to do with the chief data officer. They know they need one, but they don't know what they should do. And so it's our job to help explain that,” Batchelder points out. “What can we not do now, what kind of risks do we have, because we don't have strong data governance or data management? And what could we do in the future? It's important to make sure that teams understand that data is not a project. You don't just do it once.”
When it comes to metrics, she advises explaining things in terms of business outcomes — like improvement in transaction speed and opportunities to upsell to customers — instead of using technical language.
To understand how technology helps the data team solve the challenges of source, storage, and quality of data, Batchelder believes it’s necessary to first understand the requirements of the business.
“It's important to focus on business needs as being the driver for the technology of data. I do think that the right technology does help data teams solve those challenges, and I would definitely have a bias towards automation and simplicity, making sure that teams can do things without having to continue to add resources,” she says. And part of that's because we have such a shortage of talent in the data space across all disciplines.”