As technology increasingly rules our lives, the gathering of information – especially at the enterprise level – has become all-pervasive. The governance and management of this information forms the core of Enterprise Information Management (EIM). Despite all the news EIM makes, many organizations have failed to adopt it in any meaningful way. Information continues to be mismanaged – it is not stored, governed, archived or disposed of properly, resulting in multiple overt and hidden costs.
This behaviour can be harmful to the organization’s growth at best, and catastrophic to the organization’s very existence, at worst. I believe there are some key the symptoms of information mismanagement in modern-day enterprises. The symptoms of mismanagement information can be found in many enterprises, if you dig just a little bit under the surface: from poor data quality to bad (or no) governance, from business failures due to bad information to litigations, the effects can be everywhere. Here are some of my top symptoms:
Poor data quality: According to a senior industry analyst, one quarter of the Fortune 1000 companies are working with poor quality data. Inconsistent data, redundant information, inaccuracy and irrelevance are some of the hallmarks of poor data quality. Data that is incomplete also falls under this category. When data is bad, the old idiom “Garbage In, Garbage Out” will really tell – in the poor outcomes of CRM and BI initiatives, for instance.
No ownership: Who owns data – IT or business? This is a huge grey area in many companies, as ownership carries the baggage of management, including data quality, access and security. When there is no real owner, valuable data can be orphaned in a vast organization, leading to dangerous consequences. Companies will report to auditors that all customer data is safe in a secure database, ignoring the fact that chunks of it reside on employees’ laptops – in the form of spreadsheets, on the email servers and in backup systems. True data “stewardship” will track data from “cradle to grave” and ensure it is secure at all points, and destroy irrelevant or redundant data.
Hoarding: The converse of no ownership also infects some organizations: “hoarding” of sales data and sensitive information in ring-fenced Excel spreadsheets and extraction of select extrapolations from such hoarded caches to a (generally) disbelieving audience are some of the symptoms of this.
Information should be centrally available and shared across the organization in a controlled manner. Isolated caches of information should not be relied upon for any decision making.
Non-compliance: Over the last several years, regulatory authorities have mandated governance of data, especially of sensitive information such as health- and finance-related ones. Companies that do not comply with such mandates suffer sooner or later in the form of litigations, fines or worse. Media reports cite the example of a Fortune 100 corporation that had 150 workers reviewing material including 1.5 million emails, as part of an acquisition, in order to meet antitrust disclosure mandates.
Bad data retention policies: Data that is of good quality must be analyzed, shared and stored in a timely fashion – and summarily deleted when it is no longer relevant or valuable. Companies with bad or no data retention policies fail to establish protocols on what to retain, and what to dump – leading to huge costs in securing and maintaining physical assets that store irrelevant data, or in deleting valuable data without proper evaluation of its value.
Misuse of information: Organizations drown in a sea of data, with no one having a clue as to how to extract meaningful information out of it that can benefit the stakeholders. Such organizations lack any policies or people to perform information analytics. The healthcare industry seems to particularly suffer from this malaise.
An analysis of industry literature and media reports points to bettering data quality and governance, standardizing infrastructure, improving access to data, and most importantly securing valuable data as some of the key trends of EIM in the coming years. Specific verticals will follow industry-specific trends: for example, healthcare will adopt “just-in-time” data use and speedier access to data to enable specialties such as clinical analytics and disease management.
So what you ask? Information Management at the enterprise level requires an overall understanding of industry practices and trends, as well as analyses of what ails the specific organization. EIM specialists can understand the symptoms of mis-governance and guide the organizations towards the path of optimal EIM to benefit the organization. The cost of not doing so can be catastrophic for the organization, its customers, vendors and even society at large.