But before data is inventoried for its own sake, organizations should think first about what they’re trying to accomplish, and what data, reports and analytics they’ll need to accomplish those goals.
“Before you start thinking about inventorying your data, you need to inventory all the key decisions to need to make and prioritize those to determine what data may be relevant to those decisions and whether you can get access to the data,” said Ernst & Young’s Johnson. “Time and time again, clients have taken a data-first approach to itemize the data they have. They’ve wasted time and energy because they haven’t been able to drive any new, informed decision at that point.”
Consider a center of excellence
Not every company has the resources to establish a formal center of excellence (COE), but those that have one are in a better position to help individual operating units and the enterprise as a whole because they have an enterprise-wide view of what’s used, who’s using it, and for what purposes. A COE can help eliminate redundant efforts and can help fuel the adoption of best practices throughout the organization.
“People with sophisticated analytics are moving toward a COE,” said Shawn Rogers, chief research officer at predictive analytics software provider Dell Statistica. “I believe for larger companies with diverse reporting and analytics landscapes, the only way to do it is to establish a COE and assign personnel to become the enabler of insights for the entire company.”
COEs can help identify the data-related investments that have been made and the gaps that exist, as well as democratize relevant capabilities that may be popular in one department but completely foreign to another.
“IT has produced a lot of this stuff, but once it’s produced, they don’t have the manpower to go back and examine whether or not it’s being used,” said Rogers. “COEs help ensure that you’re not building stuff that’s not consumed, and they can help you maintain focus on the smartest and most impactful things you need to do for the business. I’ve been in too many meetings where one person says it would be great to have a certain capability and another says his department has been doing that for the last three years.”
Some companies, particularly large companies, have also appointed a Chief Analytics Officer (CAO) and/or a Chief Data Officer (CDO), whose reporting structures and responsibilities tend to differ across industries and organizations. The CAO tends to focus on driving business insights through analytics, whereas the CDO typically focuses on governance—although the responsibilities can vary from company to company. In some organizations, a CDO’s role may evolve to include CAO responsibilities after an appropriate foundation has been established. Alternatively, one person with a CDO, CAO or other title may be responsible for both areas.
“The organizations I’ve seen do this best have a strong CDO and a strong CAO who work very well together,” said Ernst & Young’s Johnson.
The chicken and egg dilemma
Effective decision-making needs to be based on reliable data, but the desire for timely insights and the time it takes to ensure data quality can often work against each other. In the past, organizations built data warehouses and data marts to store their enterprise data, but to lower storage costs and to take advantage of massive volumes of unstructured data, they’ve been adopting newer technologies—including Hadoop and Spark.