In my last blog, I looked at some of the data management costs businesses face. Here are a few more hidden costs that go beyond primary storage expenses.
Seeing Double: The Soft Costs of Dirty Data
Hard dollar costs are one thing, but the soft costs of managing data are quite another. These costs are hard to quantify, yet no less important. TalentIQ estimates that up to 20% of corporate data is dirty, meaning “it is either duplicate, incorrect altogether or a combination of the two.” The source gives an example of an applicant tracking or customer relationship management system with 10 million profiles, and estimates the cleanup cost of 2 million questionable profiles to be between $40 million and $100 million.
TalentIQ notes that there can be other significant impacts of duplicate data, as well, such as damaging a company’s reputation or its relationships with customers. If used for marketing, for instance, duplicate profiles could lead to inaccurate market segmentation. In sales departments, it might lead salespeople to inadvertently call the same customer multiple times. Whether organizstions incur soft or hard costs of data management, neither scenario is particularly efficient or cost-effective.
Costs in the Data Life Cycle and Its Surrounding Ecosystem
Another TechTarget article describes the process of calculating the real cost of data storage. In short, it is about calculating what it takes “to store a single piece of data over its entire lifetime.” Included in this analysis is not just the underlying storage but the “ecosystem of information services” involved in the “life cycle cost of data storage.” Cost areas include data migration, data protection, archiving and long-term retention and disaster recovery.
Another way organisations might look at how much it costs to manage the data life cycle is to break data into its various costs: The cost to store it, the cost to access it, the cost to secure it, the cost to protect it, the cost to archive it, the cost to migrate it, as well as the cost to extract competitive differentiation and meaning from it. These costs can be tough to calculate, so to make this exercise more digestible and uncover new ways to reduce costs, look for experts versed in best practices and methodologies who can help the organisation effectively reduce its own data management burdens.