We often talk about data’s critical role in becoming a digital business—because data is the only way to continually grease the wheels of agility. But having data is just the start. Knowing how to organize it, govern it, and leverage it is truly what determines an organization’s success with it.
That, in a nutshell, is the chief data officer’s job. Yet each CDO’s priorities are different based on their organization’s data maturity.
The fact is digitally native companies excel at data. Unlike traditional players, they’re not encumbered by legacy systems and cultures. And those traditional players are the ones that need to improve their data game—fast—to compete in the digital economy.
After spending a week with chief data officers and data experts at the MIT Chief Data Officer Symposium in Cambridge, we heard the following five important insights that business and data leaders should be following:
The buzz-phrase of the week was “democratizing data.” While widely used in data circles, the phrase essentially means that data is available, trusted, and useable for business decision-making, no matter where it originates or is governed. It’s getting data out of people’s spreadsheets on their computers and into the public sphere where others can see it and leverage it. This sounds easy (see #2) but is incredibly challenging as people and departments hold onto their data for one reason or another.
While every organization’s journey is different, there is a common understanding that data too highly centralized becomes unusable and not agile. On the flip side, data that is entirely distributed runs into quality and compliance issues. The best data organizations have foundations that everyone ascribes to, but enough freedom within a framework to keep data democratized—and keep people innovating with it.
The biggest barriers to useable, democratized data are the people and organizational structures that can hold it back. The two primary barriers in this area include 1) governance that lacks a multidisciplinary approach and 2) the “not-my-job” mindset that can come with owning, sharing, and governing data.
One speaker, a vice president at Pepsi, shared that their two-year vision for data maturity started with transforming the culture—not buying new technology or building up a massive team of data scientists, but getting everyone across the organization aligned on a common vision. And the most effective part? Telling everyone they are a data owner. Much like a digital mindset, data isn’t someone else’s job—it’s everyone’s job.
When planning the conference, there were zero presentations dedicated to ESG. By the time the conference started, at least five had popped up—demonstrating the fast and furious nature of ESG’s entrance onto the business priority list. While the presentations covered the different areas of ESG—from data’s role in ESG investing to using AI—one thing was crystal clear: The only way to “do” ESG is by having auditable, real-time data. This was eye-opening for many of the attendees.
The bad news? The pressure is mounting to have all the data related to ESG goals from new and many hard-to-reach sources—and fast. The good news? The pressure is so great that executives aren’t willing to take on the risk of not being able to report on it properly. That means they’re more willing to invest in foundational data infrastructure—from technology to talent to governance—to get there quickly. This represents a huge opportunity for data teams to increase their maturity sooner than expected and apply it across other business priorities, not just ESG.
While most companies are focused on corralling their internal data, some companies are starting to use more external data to fill gaps or get to value faster. External data can come from a host of sources, including social media, partners (vendors, clients), and syndication companies that aggregate and sell data, among others.
Organizations can make better use of external data once they have a dedicated data curation function. We heard a couple times of instances where organizations are paying for the same third-party data more than once because the buying centers are spread across the organization. These instances show how valuable external data can be, but venturing into third-party data sources comes with a need for centralized curation.
Data and digital maturity are intrinsically connected—the more mature your data infrastructure and governance are, the more trusted and democratized your data is across the organization—and the more it can be used to grease the wheels of organizational agility, from making upgrades to your digital products to understanding customers.
Apart from measuring certain characteristics that define data maturity, there are two things to keep in mind as your organization works toward it: First, digital transformation is different for every company—there is no one-size-fits-all blueprint. This means your purpose and mission matter that much more because it leads and determines the playbook for your organization. Data must follow this north star, too. Second, a common guiding principle should be how you can take your data from back-office functionality (i.e., compliance, cost center) to front-office value creator (i.e., monetization).
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