Have you got Dark Data in your Procurement Files?
As data becomes the starting point of information and decision-making, it becomes useful to get into some of the meta-data concepts for a better understanding of the dynamics that data operates in. Dark data is one such interesting concept! It is the counter part of dark matter in business scenario. In Physics, dark matter is said to be something that cannot be seen directly with telescopes, and neither emits nor absorbs light or any other electromagnetic radiation at any significant level. Coming to the corporate world, a similar concept – dark matter – relates to the data that is not easily found, used or measured.
“Gartner defines dark data as the information assets organizations collect, process and store during regular business activities, but generally fail to use for other purposes (for example, analytics, business relationships and direct monetizing)”, as picked from the official website.
It is said that dark matter comprises of 26% of the total mass–energy of the known Universe based on the standard model of cosmology. That’s a big portion! However in the universe of company operations this break up wouldn’t be so readily available to each of us.
While dark data may not pose any threat, it can be a vacuum of sorts for some information gaps that will go unnoticed by the tracking processes one puts in place. It really takes someone who is too finicky about tracking and visibility to ensure that nothing gets missed. Usually this may happen if some data was stored on devices that have now turned obsolete. Certain other essentials are also required for data to be analyzed by applications. For example, they have to be tagged with a category for the application to pick it up.
Let’s think of this as contents of the drawers in your cupboard at home that you almost never open, out of habit or out of fear of some tedious tasks that await you inside. If similar drawers exist in your procurement cupboards, there might be lying some economic opportunities for further cost reduction. As we move toward big data analysis, it will be useful for us to make sure that the whole universe of the business data is input to the systems we trust so much for big decisions every day.