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CEO Best Practices

CIO Enterprise Risk Management

Enterprise Amnesia
Organizations Have Lost Their Minds

Jeff Jonas - Chief Scientist, IBM Entity Analytics

Jeff Jonas
Chief Scientist, IBM Entity Analytics

Well actually, organizations have never had a mind. When an organization misses the obvious (e.g., when other relevant information is trapped elsewhere in their organization) and then takes incorrect action – one might call this "Enterprise Amnesia" – or simply forgetting what was known or should have been known.

Enterprise amnesia poses a key challenge for CEOs and CIOs. As data volumes increase and as information systems become more distributed and complex, the frequency at which an organization overlooks opportunity or fails to assess risk is increasing. Enterprise amnesia is increasingly inexcusable, embarrassing, and costly. Two out of every thousand employees, hired by one large US retailer, were individuals who had previously been arrested for stealing from the same store that hired them.

Enterprise amnesia occurs when organizations don’t properly manage their enterprise information assets. A lender called me every week for five weeks in hopes of interesting me in refinancing my home – notably I had already refinanced my home with them. It is inefficient, expensive, and at times carries even bigger consequences. In recent years a Vancouver, B.C., government agency gave an infant girl named Sherry Charlie over to a foster parent. Within a month Sherry was killed. During after-the-fact forensic scrutiny government workers discovered the foster parent applicant had been a known violent criminal.

Some forms of enterprise amnesia simply make executives appear negligent. At other times this can lead to regulatory compliance issues, and in some cases suggest criminal negligence. The adverse consequences of inadequate information assets management are especially relevant in these turbulent economic times. Not only are organizations in desperate need to improve efficiency, it is also essential because amnesia-based blunders erode consumer confidence.

The leading cause of enterprise amnesia is perception isolation. The dispersed enterprise data, held in transaction silos, represent the net sum of what the enterprise knows – its perceptions. And when this data is scattered across the enterprise, key data becomes undiscoverable.

Today, organizations have numerous operational systems, each managing a specialized aspect of the business - each with its own information collection, behavior, rules, interfaces and data retention practices. Notably, the decisions these systems make are made, for the most part, without any awareness of enterprise context. A marketing system may for example include a name on a direct mailing list of an individual that the business would have no interest in attracting (e.g., someone already terminated as a customer for criminal behavior).
The transition from enterprise amnesia to enterprise intelligence has everything to do with better harnessing of an organization’s information assets.

There are four essential ingredients required to transform an organization. Information must be discoverable, like things must be counted correctly, related things must be noted, and enterprise transactions need to be treated as much like questions as data.
Information must be discoverable. Ask someone in the organization to locate every record related to a specific address or phone number. Or more pointedly, ask if the emergency contact phone number in the human resources system can be searched. It may be shocking to discover the degree to which enterprise information is inaccessible.

Therefore, it’s no surprise that internal investigations hunting for a suspected insider threat will never find out the phone number in the investigation if tied to the emergency contact of an employee. This is fixed with an enterprise-wide index – much like the index used by the library. Search for subject, title, or author and quickly find a pointer to related documents. Organizations will have indices on names, addresses, phone numbers, etc. Existing systems do not need to be re-engineered, rather a new policy must be established: as new information arrives in operational systems, a library card (of meta-data) must be created and submitted to the central index. Note this index is not for one class of data like customers - rather it would also include job applicants, employees, vendors, arrests, investigations, and future prospects too.

The advantage is that it is now possible to look in one place and find everything instantly, current to the sub-second (not periodically updated every few minutes or days). [Do not confuse this with federated search where there is no index - rather each system is called upon as needed.]

Like things must be counted as such. Does the bank think five distinct individuals each have one bank account or does it know it is one individual with five accounts? If an organization cannot accurately count, the rest of the processes are going to be deeply flawed. Think of this as “single view of the citizen.” Locating the entity with any attribute locates all the enterprise content. This means when presented with only an email address, it is possible to locate customer records that never had this mail address in the first place. Technologies that detect and bind like entities together are sometimes called “entity resolution” or “identity resolution.” This will need to be done in real-time, not in batches, or the organization will be at risk of missing the obvious all month and only discover what was missed at month end.

Related things must be noted. If an organization is going to clip some underperforming customers from the customer rolls, it would be important to know when the customer is also closely related to one of its top five customers. This is relationship awareness. This type of intelligence is best managed in the index and discovered and remembered as the data from the enterprise arrives. Knowing who relates to who significantly increases an organization’s ability to triage risk and increase opportunity (e.g., improve retention).

Enterprise transactions need to be treated as much like questions as data. With every new piece of data arriving in the enterprise the organization has learned something. Doesn’t it make sense that with each new data point it would make sense to think “If the organization knows this, has the organization learned something that matters?” Example: the organization qualifies a loan as low risk. Three weeks later a reorder for checks includes a new phone number – a data point that provides the necessary evidence to associate this new customer with other known fraudulent actors. When such data points fall into an organization’s lap today they risk going undiscovered, indefinitely.

Whether an organization is intent on better managing risk or improving its ability to recognize opportunity – system infrastructure that permits enterprise information to be placed into context and enables the discovery of relevance at the point of the transaction, is going to be what differentiates one organization from another. And ultimately may differentiate the survivors from the non-survivors.

About the Author
Jeff Jonas, Chief Scientist, IBM Entity Analytics
Jeff is one of the world's leading authorities on next generation identity analytics. He is responsible for the use of this new capability in the overall IBM technology strategy. Entity analytics contribute to critical societal interests such as clinical health care research, aviation safety, homeland security, fraud detection and identity theft. Jeff is a member of the Markle Foundation Task Force on National Security in the Information Age and actively contribute on privacy, technology and homeland security to leading national think tanks, privacy advocacy groups, and policy research organizations, including the Center for Democracy and Technology, Heritage Foundation, Center for Strategic and International Studies and the Office of the Secretary of Defense Highlands Forum. To learn more visit www.jeffjonas.typepad.com

 

 

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