Information Management

Area Description

Information is nothing new to the scaling digital organization. Like other topics in this document in the enterprise context, the digital organization has been managing information in some way since the earliest days of your organization.

Perhaps the company started by offering a social media-oriented service. It needed to track users and their activity. Or perhaps it started off with a focus on data science and analytics; the first product was based on harvesting insights from large data sets. Just as this document does go into detail on the specifics of programming languages or infrastructure technologies, it also leaves the more technical aspects of data science and analytics to other guidance.

However, it is at the largest scale that organizations require the establishment of formal governance, control, and management techniques for information as a distinct and coherent problem domain. Before, the practitioner might have been interested in “customer data” or “sales data” or “supply chain data”. Now, they are concerned with data in general, and how to manage it, wherever and whatever it is.

They are also concerned with information, knowledge, records, reports, and a wide variety of other overlapping, and often difficult to define, concepts.

Information is the lifeblood of business. Simple records are the foundation of survival: lose the customer’s order, and the business will not be in business long. Beyond such basics, the insights that can be gained from your data are increasingly critical competitive advantage. Whether or not the company started with a focus on data science, it probably has data scientists at this level of scale.

The sheer scale of the data is starting to become unmanageable. It costs money to store, and how much is needed? Lawyers start questioning whether it is truly necessary to keep certain data indefinitely; they seem to think there is risk there.

We are also periodically confronted with seemingly wasteful duplication of data – is it not possible to be a bit more efficient? Quality and security concerns are also increasing. We see competitors go out of business due to cyberattacks, and pervasive data quality issues also can be a serious threat to your operations and customer relationships.

Yet, when attempts are made to manage for more efficient or better-governed uses of data, the resulting cost and bureaucracy cause concern (not to mention receiving complaints about development delays and loss of business agility). It is an ongoing challenge, and it does not seem anyone anywhere has it entirely figured out.