Information lifecycle management manages the interrelationship of data, storage assets and IT processes. One of the most important justifications for ILM is that data is associated with storage devices and IT processes in accordance with its value to the enterprise. In other words: less important data is assigned to less valuable storage and less intensive processes, while data that is more valuable gets better treatment. A linkage is made between business process and the value of data at each stage within the data's life.
IT managers considering ILM as a means of driving more efficiency into their shops should ask themselves two questions. The first is "How often do we actually move data?" The answer, in most cases, is "not a lot."
Typically, old data eventually gets archived and moved off-site, but other than that it is a rare IT operation that moves data from one array to another (or from one level of RAID to another) unless a piece of equipment is being retired. Once data is assigned to a storage device it tends to stay there until it is archived to tape or just overwritten.
"How often do we actually move data?" has both quantitative and qualitative answers however, and if the quantitative answer is "not a lot," perhaps the qualitative answer is "not enough."
Data that stays in one place throughout its life, no matter how the value of the data may change, probably does so because the historical corporate IT policy - one that perhaps dates back to the era of mainframe DASD-only storage - has never provided managers with a cost-efficient alternative. While this certainly works, it does so with decreasing efficiency when compared to competitive IT operations that take advantage of the newer technologies.
Such remnants of the "if it ain't broke, don't fix it" school of management perpetuate IT environments that are identifiably sub-optimized when they are compared to other companies' IT processes. The result is that the businesses they support are increasingly at a competitive disadvantage.
If "not enough" is an accurate reflection of your IT policies when it comes to transferring data to more cost-efficient assets, then the second question becomes clear: "How efficiently will a proposed data migration solution actually move data for me?"
Automation lies at the heart of efficient data migration. Why? Moving data is a labor-intensive task, and is thus rife with operational expenditures. These are repetitive and often dwarf the capital expenses involved.
When it comes to migrating data, remember that you are doing it to improve IT efficiency. Drill down a bit. It makes good sense not only to understand what is being done, but how.