Erickson Methodology for Enterprise Architecture Abstract

January 14, 2021 – By #Douglas T. Erickson, President, ENTARCO USA Inc.

Even though automation technology has significantly enhanced enterprise productivity and quality, costly and unnecessary enterprise infrastructure problems have persisted. Advances in technology have not solved the fundamental, persistent enterprise infrastructure problems.  Enterprise alignment, integration, flexibility, responsiveness, data quality and cost, business process fragmentation, gaps, redundancy, overlap, and inconsistency persist.  Significant technological advances have masked these problems, and in many cases, created layers of unnecessary activity and costs that can, and should be, eliminated. 

The Erickson Methodology for Enterprise Architecture (EMEA) is not a new automation/information technology.  The EMEA is a knowledge and skill-based methodology that produces an enterprise architecture designed to develop an enterprise infrastructure that:

1. solves existing infrastructure deficiencies,
2. dramatically reduces enterprise costs,
3. produces exceptional data and process quality, and
4. reduces cost and lead-time to deployment technology

The EMEA provides a better way to align and integrate the enterprise by using several architecture innovations in architecting and designing an enterprise infrastructure.  Some of the key EMEA methodological innovations include:

1. Basing the enterprise motivation or purpose on the product or service produced by the enterprise. The enterprise's primary resource, its products or services, dictates the supporting resources employed by an enterprise.
2. The Resources Life Cycle Management concept provides an objective method for identifying and defining enterprise business processes that must be performed to provide the enterprise products or services to the market.
3. Decision/Event Analysis further provides a method for objectively partitioning processes to identify and design a process infrastructure that is complete and modular, without redundancy, and allows for massive reuse of elementary processes throughout the enterprise.
4. Identifying and defining enterprise data based on the objects of interest (mostly the resources managed and their relationships), not on the use of the data.
   
   Example: A person or an enterprise has a name.  A customer, employee, a student, or a patient does not have a name; they inherit the person or enterprise name.  This concept contributes significantly to reducing the curse of redundant data.

5. Designing data to keep track of every fact over time. This approach significantly improves the data quality, and the data is available for simultaneous operational and analytical use.  It eliminates the need to design, implement, and maintain "history" data/tables because history is embedded in the stored data.  This approach also reduces the amount of stored data.  Since there are only ten (10) temporal entity types, we can standardize the logic for each of the entity types for handling the database interactions.  Combined with our ability to dramatically reuse data, this further reduces the time to code, and test data handling logic.
6. Designing for change. Designing for change improves enterprise flexibility and responsiveness.  Simultaneously, it dramatically reduces enhancement/maintenance cost, time, and effort to accommodate change.  Designing for change is amplified by using the twin concepts of independent variables that decouple objects that can change independently; and the concept that requires modeling object primitives from composites of primitives.
7. Aggregate resources. Every enterprise has three aggregate resources – establishments, organization, and projects.  It turns out that every enterprise has establishments (at least one), an organization structure, and uses projects for managing (planning and controlling) the allocation of revenue-producing resource (product or service) and cost-producing supporting resources (labor, equipment, materials, funds, etc.).

Reduction in IT costs and delivery lead time.  By eliminating redundant data, collecting and storing one fact in one place, and effectively and efficiently achieving enterprise-wide reuse of high quality data and application logic, IT costs and effort are significantly reduced and the lead times shortened substantially.

1. We routinely achieve an average of 14 reuses of each attribute. This reuse of the data eliminates the time and effort to code and test for 13 occurrences of over 2000 potentially redundant attributes.
2. By designing each attribute for reuse, each successive application implementation does not have to design, code, and test data conversions and data interfaces. The savings of cost and time continue to increase with each successive application implementation.  Over time, if you follow the EMEA, the need for project by project data conversions and data interfaces diminish and can eventually be eliminated, further reducing implementation lead times. 

The use of the EMEA to develop an enterprise architecture will provide the foundation for achieving:

1. Alignment - with the business requirements,
2. Integration - of data, process, and operations,
3. Flexibility - to adapt to change,
4. Responsiveness - in a timely manner,

AND also dramatically improve:

1. Data integrity, and
2. Process consistency,

WITH the benefits of dramatically:

1. Lower cost,
2. Shorter lead times, and
3. Lower maintenance cost.

The EMEA will enable acquiring very high quality business systems in up to one-third to one-half the time.

The EMEA will enable you to implement many business changes in hours, days, and weeks instead of months and years.

The EMEA will enable you to acquire very high quality business systems at:

1. One-fifth the cost of traditionally developed systems, and
2. One-third the cost of purchased packages!

Last Modified: 01/14/2021 12:00:00 am MST

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