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Data center consolidation, server virtualization and other IT projects can help you to better manage big data and optimize hardware and software resources, but they do not help you to reduce the amount of data. Data compression and de-duplication efforts may reduce data volumes, but they still do not address the fact that most organizations keep much more data than they actually need for regulatory, commercial, intellectual-property or knowledge management reasons.

Every year, the costs and risks of the dark side of your Big Data grows just as exponentially as all your other data: requirements for eDiscovery, governance, compliance, privacy and storage can lead to enormous costs and new risks. In today’s legal climate companies are increasingly facing court sanctions for the inability to find and produce electronic information with breaches of privacy and security being highly penalized. In fact, more and more organizations are confronted with the realization that their legal bills are also subject to Moore’s law: they are doubling every 18 months!

The path to neutralizing eDiscovery cost and risk issues begins with a proper and defensible legacy data cleanup project. The road continues with classifying documents with a proper filing plan and implementing data retention and destruction policies.

Now, most organizations do not have such filing plans, filing plans may no longer be up to date or they do not address the various types and locations of today’s electronic information.  Records management has become everyone’s individual responsibility and as a result, no one is doing it!

Now that the New Year is coming, there is a great opportunity to clean up our electronic data. A typical legacy data clean-up project consists of the following steps:

1. Create a project plan and align business processes and stakeholders
2. Create a basic filing plan
3. Identify relevant electronic data sources containing legacy data
4. Connect, collect, process and classify all documents
5. Review classification quality with statistical sampling
6. Generate reports on the contents of your legacy data
7. Implement retention, review and transfer actions based on the legacy data reports against your  filing plan
8. Store relevant document with the right security levels and retention periods in your long-term sustainable archive.
9. Document and archive audit trails from your legacy information clean-up process
10. Switch off your legacy servers and data locations!

All of these steps can be implemented very efficiently by using state-of-the-art technology. Together with a solid methodology, reports and form templates, one can defensibly dispose legacy information, identify valuable information, and at the same time analyze data for fraud, privacy, bribery and other risks.

In many cases, you will see that a large part of these efforts can be funded through savings made on the maintenance and support contracts of the legacy systems. In addition, data volume reductions of 90% or more are commonly achieved.

Further potential savings can be realized on legal costs and risks, should your legacy data become part of active litigation, eDiscovery or regulatory investigations!

So, if you were still looking for a new year’s resolution, here is one: start cleaning up your legacy data!