Sunday, April 27, 2014

How to Define the Target for Enterprise Information Management

In my recent post "The Organizational Challenge of Enterprise Information Management", I recommended to create a high-level conceptual data model as a target map for Enterprise Information Management (EIM), with Master Data Management (MDM) and Data Governance being core strategies to transform the organization from legacy structure to a data-driven business.

Below I have included a (not necessarily exhaustive) example of a high-level EIM map for an insurance company. 

Created with SILVERRUN RDM Relational Data Modeler - Tool for Conceptual, Logical and Physical Data Modeling
Click to enlarge

(The blue rectangles are Master Entities while the grey rectangles represent the major transactional entities.)

The decisive advantage of such an EIM map as a strategic orientation is: This target is not moving! As long as the business subject does not change (in this example: as long as the business does not add or drop any insured risk), this model does not need to be altered. It represents a sound structure that was valid 20 years ago (even if the term Master Data Management was not coined at that time), it is applicable today, and I dare to predict that it will still be in 20 years from now.

If applications are aligned to this model, they can answer business questions that a disparate system cannot (or cannot sufficiently), e.g. such as:
  • Which policies are owned by a certain party? (Single view of the customer)
  • Who are the most profitable / most risky customers? (Risk management)
  • Are there same groups of people that are - with changing roles - repeatedly involved in car accidents? (Fraud detection)
Being implementation-independent, a high-level EIM map will help any business in any industry to develop a long-term strategy to move from a siloed data / application architecture to integrated Enterprise Information Management and to provide answers to any organization's respective business questions.


Sunday, April 13, 2014

The Organizational Challenge of Enterprise Information Management

Medium and large enterprises as well as public administrations are constructed hierarchically, and that is for obvious reasons the best, if not the only principle to successfully conduct any endeavor that involves a certain number of people.

At some point in history, when the benefits of information technology were discovered, enterprises innocently imposed the same paradigm on their applications and also organized them by department. As a consequence, multiple information objects have been reinvented in several departments, and isolated data silos have been created, causing the known problems of conflicting definitions, redundancy and inconsistency that hinder to obtain complete customer views, to create real-time analytics as well as to swiftly respond to external legal and/or regulatory requirements. 

However, business information does not live in hierarchies but is represented by a network structure: the (conceptual) data model with master entities as their central objects.

Click to enlarge
Such a conceptual model on its highest levels serves as a target map for Enterprise Information Management (EIM) with Master Data Management (MDM) and Data Governance being core strategies to transform the organization from legacy structure to a data-driven business.

Since MDM and Data Governance demand harmonization throughout multiple departments, many organizations have set up committees to solve the related issues.

However, work for and participation in committees will always have to compete with departmental day-to-day tasks and therefore are in permanent risk of being treated as second priority. Also, EIM requires "central" tasks which do not have any "natural" representation in existing business units and therefore tend to end up in "IT" where they do not belong.

As a viable alternative, I suggest to replace the committee(s) by an additional permanent business unit that acts as the CEO's "right arm" to execute all central as well as coordinative tasks of EIM. For illustration purpose, I will here just name a few:
  • Develop and maintain the conceptual model that serves as the target for EIM
  • Define shared business entities e.g. Party (which then assumes its different roles such as Customer, Supplier, Employee in the operational business departments)
  • Develop strategies to accomplish legal and/or regulatory compliance 

In a future post, I will elaborate further on the role of the EIM unit, on necessary peer roles in the operational business departments and comment on frequently suggested responsibilities such as Chief Data Officer (CDO) and Data Stewards.