How to Implement Information Governance Across the Enterprise
You may not think about information governance as a cost-saving measure, but it turns out, it can potentially save you millions.
That’s because most companies are so worried about regulatory compliance, they overshoot on data retention, according to a recent CIO.com column by Actiance Vice President Doug Kaminski.
More than 70 percent of data stored in discovery collections has no business, legal or regulatory value, Kaminski writes, citing findings by the Compliance, Governance and Oversight Council (CGOC).
Overall, about half of the data in your discovery collection will be duplicates, with another 20 percent mere office chit-chat or other news sources. That leaves only 30 percent of your data that is actually relevant or responsive, according to Allison Walton, CEO of Fortis Quay, an information governance consultancy.
Even if you can hunt down only half of the useless data, that would still generate a budget savings in the millions, Kaminski adds.
In his article, Kaminski details six ways to trim the data fat from compliance stores. It is actually good advice for any information governance project. Here’s the abridged version of his list:
- Involve all stakeholders.
- Start small by targeting one or two departments.
- Invest in the right tools. (The article didn’t provide any product promotion, but Actiance offers a tool specifically for managing discovery collections. Deduplication and data quality solutions would also be key to trimming data down, I suspect.)
- Grab the biggest, lowest-hanging fruit first.
- Set milestone goals.
- Change behaviors upstream to keep data lean.
Kaminski doesn’t specify how you can achieve number six, but you already know: If you want to cut the bloat throughout your data systems, you’ll need an enterprise-wide approach to data governance.
“Data governance is a powerful pill as it not only knocks out the causes of the common data headaches, it helps prevent them,” writes Anee Buff, SAS Best Practices thought leader, in a recent Information Management column. “A finely tuned data governance program can reduce duplicate data throughout the organization, reduce errors in reporting and coding and reduce costs associated with poor data quality.”
It can save money during data migrations, too, she writes, by improving accuracy and efficiency while reducing the time it takes to complete the migration.
