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CEO / CIO Best Practices
CIO Enterprise Risk Management
Enterprise Amnesia
Organizations
Have Lost Their Minds
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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