Let me tell you a secret. Most organizations, from the mom & pop store next door to the Fortune 100 company, do not have access to information about their business – a critical ingredient for success in today’s fast-paced and dynamic business environment. What they have is DATA. Is there a difference? Yes, and it is huge. While data refers to numbers, characters, symbols, or images, information is INTERPRETED data. What this means is that most organizations have not successfully transformed their meaningless combination of numbers, characters and symbols, images and so on into knowledge that can be acted upon to improve their business operations!
If knowledge is so important to an organization’s success, why isn’t data being converted into information then? I can think of two major reasons:
1. Exponential Data Growth: Storage costs have become lower and lower over the years. In some IT organizations, the default solution for any data related problem has become “buy more storage”. This has led to unprecedented levels of growth in the amount of data being collected by organizations. These huge data sets require significant resources, especially in terms of processing power, before they can be adequately analyzed and converted into meaningful information that can support the business.
2. Disparate Systems: The IT applications and infrastructure of most organizations have grown organically, with a typical organization having a vast array of database systems, and data formats which are completely unable to ‘talk to each other’, or be interoperable.
With this heterogenous state of huge data sets, it is virtually impossible to extract the knowledge that is needed by the business. The solution? A data management strategy!
A data management strategy is essentially a plan for acquiring, storing, organizing and retrieving data. Organizations with a well-defined data management strategy are able to effectively capture and organize data in a manner that enables them to easily identify patterns, and trends that provide the information needed to drive the growth of their business.
So why do you need a data management strategy? I can think of three reasons.
1. Improved Data Access: a well-defined data management strategy enables organizations to have quick and easy access to their data. For industries like energy trading, where just one second could be the difference between a million dollar gain or loss, this could be a big deal.
2. Data Visibility: When the information gained from your organizational data says that summer is the best time to sell coffee in Texas, most people will probably ask: “how so?” A data management strategy will enable the creation of ‘data’ about data, also referred to as metadata. The metadata will provide users with insights into data sources, transformations, and other manipulation methods which have led to the current results.
3. Data Reliability: Information about your business is only as good as the trust your executives have for it. With low trust, no significant decisions will be made based on the information, and a lot of strategic opportunities will most likely be missed. The transparency of properly managed information will command high trust, and increase adoption by users within your organization.
I will be talking about the components of an effective data management strategy very soon. Stay tuned. 🙂