Now we are moving into a new IT era that includes concepts never dreamed of years ago, such as social media. One of the most powerful trends is that computers are now being integrated more and more into things, such as cars, appliances and power grids. These computers have software intelligence that process operational data, such as monitoring the tire pressure on cars. That requires sensors and other infrastructure components, such as RFID tags. Although the resulting data is typically used locally for operational purposes, in many cases data is sent over a network to a central site for analysis, such as managing supply chain processes moving products to the right store at the right time.
All of these new sources of information, plus finding new, productive uses for existing streams of information lead to what is sometimes simply called "analytics." As these analytics move more into the core of the business, decision-making can be improved, leading to added value. Improvements may range from a supply chain process that cuts costs to a targeted marketing campaign that results not only in more revenue dollars, but also more overall average profit per customer, or improved quality of health care through pattern detection on real-time physiological data that can predict emerging infections up to 24 hours in advance. The first two examples are traditional examples that affect the bottom line of businesses. The third illustrates that "business" applications are moving into areas far out of the old spectrum. Even though cost savings may come into play (such as lower hospitalization costs), improving quality of service also improves customer satisfaction, which can result in more business for a particular health care organization.
Information Governance as a Way to Create Order Out of Information Chaos
Now using data for better decision-making is fine, but what has that to do with information governance? Well, the IT infrastructure in any enterprise is typically built piece-by-piece over time with each piece justifying itself. The end result--as might be expected--is likely to be unsightly. One would like to use data for decision-making, but not if the quality of data is poor or untrustworthy. Moreover, external factors, such as compliance and eDiscovery, are putting new demands on the IT infrastructure that were unanticipated, and therefore difficult or impossible to accommodate.
Information governance, a.k.a. data governance, is about creating order to the extent necessary and possible out of the existing information infrastructure chaos with the goal of aligning people, processes and information to achieve better use of information.
For example, the role of information governance in data protection is critical. Data protection is not only about the ability to restore data from a backup but also touches on compliance, eDiscovery and data privacy. That means an organization has to know "what" data is has and "where" that data is. An organization has to have a formal data retention policy in place not only to make sure that it does not run afoul of what is mandated, but also to avoid the risk and cost of storing and managing no longer useful data. All this is not going to happen on its own volition; a formal process, i.e. information governance, has to be put in place to do the job. (Please see my book, Data Protection: Governance, Risk Management, and Compliance, for a more detailed discussion of the need for data governance in conjunction with data protection.)
