Strategic advice to leverage new technologies

This is the second in a series of Executive Updates that examines enterprise architecture (EA). Part I addressed questions about the practices of EA organizations.1 This Update focuses on the perceived effectiveness of EA.

Event analysis is a counterintuitive but "easy to understand and use" approach for designing or redesigning processes and systems. If used consistently and extensively, it simplifies architectures, increases structural parallelism, identifies needed controls, and expedites the eventual enhancements of applications, middleware, and operating systems.

Two important benefits afforded by data warehousing and BI are that they enable the distribution of standardized business information and standardized measures across the various parts of the organization.

Data integration solutions that perform well, especially on "big data," evolve from good design. These solutions exhibit one or more of the following characteristics: high level of parallelism, maximized bulk operations, reduced network data overhead, and an optimized/ nonduplicated transformation layer. While these considerations look straightforward, unfortunately, there is no silver bullet. A design solution is context-specific and is often a combination of the above characteristics.

In 2002, Harvard Business Review republished what it described as one of its best articles. Originally published in 1988, the piece outlined how to "get innovative," and in it Harvard Business School Professor Andrall E. Pearson proposed what he called "tough-minded ways" for companies to build an innovative organization.1

I recently worked on Kanban adoption with a new customer, who informed me that Kanban was already underway and wanted me to help finish the adoption.

Recently, I was working with some clients to create conceptual architectural models, and the discussion turned to the common levels of abstraction that we reference in architecture; namely, conceptual, logical, and physical.