In my role as Information Governance Architect, I often have recurring meetings with many of my clients. I have one such meeting today with a new client who has already informed me that they are having massive data growth issues and are at risk of data loss. I think back to a similar client a few years ago who was facing the same struggle.
I walked into that monthly meeting and met with Rebecca. She was the CDO for an entertainment company that was in the process of moving through a lot of mergers and acquisitions. She relayed an issue to me telling me due to a miscalculation by someone on her staff, they were quickly running out of storage and there was a real risk that they would completely consume their available storage within a month. The worst part is that they did not have any money in the budget for more storage and she was taxed with simply deleting massive amounts of data to make room. The only problem was knowing what to delete and what to keep. She was sure her job would be on the line for accidentally deleting something that shouldn’t have been deleted.
When I meet with customers to talk about Data Management and the overall Information Governance landscape, I always think back to my childhood and my father’s auto restoration business. My dad was a master craftsman who could make any car look like it just rolled off the showroom floor, even if the car was 50 years old and had been overtaken by rust.
When I was 13 we quickly ran out of space in our small cinder block garage and I soon I was helping build an addition to the garage. Many more years passed and we had to expand again, moving some items to a storage facility at the edge of town.
Data Management is a lot like this isn’t it? Every day I hear arguments for simply adding storage or using block-level deduplication systems to reduce the storage footprint. After all, storage is cheap, right?
- “I’m running out of space so I’ll just add more storage.”
- “I’m not using this anymore but I probably should keep it just in case so I’ll move it a cheaper storage area or “archive” it.”
All of this data hoarding causes downward drags on the business based on three factors:
- Time – Time consumed to manage, find, and backup data.
- Money – Many industry reports show that nearly 2/3rds of IT budgets are spent on infrastructure costs.
- Risk – Keeping data beyond its usefulness to the business opens up litigation issues. Any data that you store is accessible to court cases and could cause you to lose your case.
So how do we correct these downward drags on the business?
When my father outgrew his garage, what if he would have gone through the items that he stored and made decisions on what to keep based on how often he used those items. Could we have stayed in the same garage and saved money by simply applying an intelligent management solution to our method of cleanup?
What I’m talking about, and the key to an effective data management solution is INSIGHT.
Insight empowers you to make informed decisions on your data by:
- Gaining visibility into governance problems and devising a strategy to fix them.
- Taking action by implementing a policy that aligns people’s behaviors with goals.
- Assuming control by implementing data management practices to reduce risk and avoid liabilities and costs.
So how does this address those three factors (money, time, and risk) that cause downward drags on your business we talked about earlier?
- Save money – by spending less on storage, backup and eDiscovery.
- Save time – because there is less to manage and you get the benefit of automation.
- Reduce risk – by retaining only what is necessary to the business and controlling access to it, while defensively deleting data that does not hold business value.
My client did not run out of space. The CDO did not lose her job. She also did not delete any information that held business value. By providing insight into the data in her environment she was able to quickly determine what information was valuable to the company and what was “stale” and could be removed from the environment. She was then able to form policies on managing the data going forward.
Not only did my client free up nearly 70% of her first-tier storage, she was able to extend her next storage purchase and use that money for other strategic initiatives saving her nearly $1M when she planned her next budget.
A good Information Governance vision and strategy centers around the idea that not all data is created equal so business value should be placed on data to determine what should (or should not) be retained by the business. It is also important to provide a way to guarantee retention to match corporate policy, while promising defensible deletion when the data is no longer required by the business. All of this should be in the form of policies so you can take advantage of automation, removing human error from the equation.