While manufacturers are not there yet, the shift to global enterprise resource planning (ERP) systems is happening. More than one-third of respondents to a recent Cutter Benchmark Review survey have a global ERP system in place. According to AMR Research, this number was much closer to 20% just a few years ago [1].

Service-oriented architecture (SOA) is often approached as very much a technology-centric initiative. However, while SOA infrastructure and technical design both have vital parts to play, they must be judged at the end of the day as enablers of business improvement. A good SOA is only as good as the business knowledge that goes into its construction.

In Part I of this two-part Executive Update series, I presented a variety of issues that arise in large organizations that attempt to deploy agile software development methods across a broad range of such projects.1 I categorized these issues as emphasizing people, culture/politics, or process. Here in Part II, I outline seven guiding principles for successful efforts to adopt agile methodology.

Once a decision has been made to outsource one or more IT services -- to reduce costs, improve service quality, provide adequate technical support, or for other prev

Once a decision has been made to outsource one or more IT services -- to reduce costs, improve service quality, provide adequate technical support, or for other prev

Organizations committed to the development of a measurement program to track and improve innovation efforts have at their disposal several off-the-shelf metrics commonly adopted by companies whose measurement programs are more mature. Where do managers turn, however, when they need to complete an innovation management program with internally developed measures unavailable on a store shelf?

Organizations committed to the development of a measurement program to track and improve innovation efforts have at their disposal several off-the-shelf metrics commonly adopted by companies whose measurement programs are more mature. Where do managers turn, however, when they need to complete an innovation management program with internally developed measures unavailable on a store shelf?

How do agile organizations plan in today's world in which the future looks murky? I would recommend a two-pronged approach: set a strategic direction and be prepared to adapt. In thinking about strategy, I'm drawn to Virginia Postrel's words:

In the last Trends Advisor, I wrote about the increasing interest in "semantics" among the leading-edge software folks (see "Semantics Is Hot; Data and Objects Are Not, Part I: The Emergence of the Semantic Web," 19 March 2009).

In the last Trends Advisor, I wrote about the increasing interest in "semantics" among the leading-edge software folks (see "Semantics Is Hot; Data and Objects Are Not, Part I: The Emergence of the Semantic Web," 19 March 2009).

In the last Trends Advisor, I wrote about the increasing interest in "semantics" among the leading-edge software folks (see "Semantics Is Hot; Data and Objects Are Not, Part I: The Emergence of the Semantic Web," 19 March 2009).

Many client organizations nearing the end of an outsourcing contract start to consider whether they should retender the deal.

Many client organizations nearing the end of an outsourcing contract start to consider whether they should retender the deal.

Many client organizations nearing the end of an outsourcing contract start to consider whether they should retender the deal.

Now that I am in Lexington, Kentucky, USA, the horse capital of the world, my thoughts have predictably wandered over to horses. I thought I might want to own a horse. So I called the family horse expert, my sister. She rode competitively in college and has owned and trained many horses. Currently, her daughters are riding competitively, and she is helping to teach them all about horses.

Operational technology will persist with hierarchical management structures, centralization, and standardization -- though the sourcing of infrastructure will change dramatically through "X as a service" delivery models, open source software, and thin-client architectures, among other infrastructure opportuniti

Operational technology will persist with hierarchical management structures, centralization, and standardization -- though the sourcing of infrastructure will change dramatically through "X as a service" delivery models, open source software (OSS), and thin-client architectures, among other infrastructure opportunities.

It's been five years in the making, and perhaps a few years later than promised, but TOGAF 9 was finally released to the public in mid-February 2009.

This Executive Report by Douglas K. Barry describes an incremental service-oriented architecture (SOA) technique that improves project selection in such a way that the chances of success for that project are also improved.

Recently, problems with service-oriented architecture (SOA) projects have been the focus of some public statements, ranging from one saying that 50% of SOA projects are a complete failure to reporting rage over the changes instituted as part of SOA projects. These seem to report a pretty dismal scenario. But is it reality?

Despite the generally positive and upbeat outlook for SaaS and cloud computing, there are a number of risks and pitfalls that must be carefully managed in order to exploit the potential offered by the emerging paradigm. Our contributors offer important insight that will help you assess the risks as they manifest themselves in your specific context.

Computer science is still a relatively young body of knowledge, strongly linked to technology and therefore to the market. This explains why its historical development has followed complex and hardly predictable paths, including strongly emphasized topics soon forgotten (the network computer, just to mention one); promises never realized (fully automatic generation of software); and brilliant concepts that remained almost unknown for many years (object orientation). As it is commonly said, in computer science it is not easy to distinguish the hyper from the hype.

Cloud computing and software as a service (SaaS) have captured plenty of industry and press attention, but they have also created an equal share of confusion and even controversy. While there are solid reasons to be cautious about how to approach these rapidly evolving Web-based alternatives, there is also growing evidence that they are no passing fad. Instead, cloud computing and SaaS represent a fundamental shift in the way technology and business applications will be packaged, priced, delivered, and utilized going forward.

In this issue of CBR, we bring our mixed academic/practitioner approach to benchmarking to the domain of software as a service (SaaS) and cloud computing. These are just two instantiations of a long-time move toward making the ability for a firm to acquire computing resources as a service, as needed, a reality.

This survey investigated software as a service (SaaS) and cloud computing. Sixty-five percent of the 68 respondents who completed both parts of the survey are with organizations headquartered or based in North America; 21% are headquartered or based in Asia/Australia/Pacific; 12% in Europe; and the remainder in the Middle East and Africa.