The argument was getting heated. At one end of the table stood the Linux bigots, banded together and angry. At the other end were the Microsoft bigots, standing stalwart and snooty. At stake was the future of operating systems for a new business intelligence platform. Neither side would retreat from its position that its product was superior.

As discussed in the first Advisor in this series (see "A Capability Trilogy, Part I: The Politics of Capability," 25 March 2009), capability-oriented thinking is becoming increasingly influential in methodologies, enterprise architecture frameworks, and business strategy.

Make no small plans for they have no power to stir the soul.

-- Niccolo Machiavelli

Recent developments have brought together parallel processing and cloud computing technologies in such a way that they are set to change the way organizations look at analyzing massive amounts of data. In fact, I believe that these developments hold the promise of ushering in a new era in high-end, affordable data analysis.

The world of business technology is dramatically changing. Everything about it is changing, including what we acquire, deploy, support, the way we support it, and -- perhaps most important -- the way we manage it all.

Preparing for a couple of conference presentations recently, I started thinking about a graphic to illustrate the key components of scaling agile projects, many of which have been discussed in prior Advisors. Visualize a house structure with a roof, a foundation, and three pillars (see Figure 1).

Recently, I had a conversation with Julie Zawisza, director of communications for the Center for Drug Evaluation and Research at the US Food and Drug Administration (FDA).

It's déjà vu all over again. The cycle has repeated. The economy is and will continue to shed jobs. Businesses are trying to get leaner. Again, IT is expected to not only shrink itself, but help other units in the firm shrink themselves. A key approach for doing so involves reengineering the business process (BPR).

Companies today are trying to lower costs and increase staffing flexibility by taking some, or even all, of their development activities overseas. Many of these same organizations have teams that are using agile development practices to increase quality and improve project performance. What happens when these two trends in our industry intersect?

One of the most difficult parts of project portfolio management is deciding how to rank the projects -- that is, determining which should be done now, later, and, most important, never. There are several ways to rank a project portfolio. Each is useful in specific situations and not so useful in others.

They say "What doesn't kill you makes you stronger," and perhaps this is true for architects as well. I recently went through an experience that all architects and IT professionals should go through occasionally, but not too often. An insipid virus infected my computer, having evaded the defenses of my firewall/security product and, slowly but surely, rendered my laptop useless.

The March 2009 edition of Harvard Business Review has an excellent article titled "When Should a Process be Art, Not Science?" by Joseph M. Hall and M. Eric Johnson. The article contains many great insights, but there is a sense in the article that we need to choose; that the answer be one or the other: art or science. This appears to be true with most things that we try to categorize.

At the beginning of the year, I said that the most important BI-related initiative for organizations in 2009 would remain business performance management (see "Business Performance Management Tops '09 Strategy List," 6 January 2009).

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].

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).

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.

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.

COTS (commercial off-the-shelf) products are great. Someone else does all the research, development, design, and manufacturing; we just read the spec sheet and buy the products. What could be better? Beware, however, the curse of COTS.

Several years ago I was working on a project to build a small device that used several COTS components. The device was a basic audio recorder. Some of the COTS in use included AAA batteries and SD memory cards. Both of these parts are available at any big-box retailer and both are inexpensive.

In a recent BI Executive Update (see "Open Source BI and Data Warehousing: New Directions," Vol. 9, No. 2), I discussed the possible impact on the BI market caused by end-user organizations adopting open source BI tools.

Like the stock market, IT projects can be volatile: requirements can change, scope can creep, unknown dependencies can appear, teams can get mired down in myriad ways, technology can fail, executive sponsorship can evaporate, schedules can jitter, and dates can slip.

It is sad but true that the economic crisis has now also appeared in Poland. Somehow, many of us here in Poland have been under the mistaken assumption that we would be undisturbed by the current economic crisis; that this was only an American and Western European problem. Of course, it couldn't remain that way.

What do you do when a team member is actually creating higher risk for the team, and yet you need that person and/or the organization insists you keep him or her? This is actually a far more common quandary than we care to believe.

The biggest trend to hit business intelligence (BI) since the days of executive information systems may not be an innovation in the technology itself but in the kinds of data the technology analyzes. The new BI foreshadows a time when, for example, a disease epidemic will be stopped because data can reveal to health officials the movements of infected people. Welcome to the world of "reality mining."