Last January, I discussed important new developments in IBM's Watson natural language-based analytics question-and-answering system (see "IBM Bets the Future on Watson").

We are on an annual mission to salvage our lawn. For years we have watched the slow descent into mud and murk, and this year, we decided to hire the big guns. In interviewing lawn services, I was frequently reminded of the sales pitches I had heard as an executive.

Adequately managing software development and delivery is a serious business and of critical importance to the enterprise. The importance of software development continues to grow, and the velocity of business presses for constant change.

The online world has moved to a more open and social model in which popular applications (Facebook, YouTube, Pinterest, etc.) function by engaging consumers through sustained interactions consisting of conversations, collaboration, and sharing.

It is not too strong an assertion to say that these last few years have been transformative in the potential role and structure of IT in most businesses.

Depending on how you count, Agile development is nearing either its 13th or 20th birthday. If you start counting from the publication of the Agile Manifesto, then "Agile" is just entering its teen years, a tough time for individuals and approaches.

We hear of few organizations that debate whether the enterprise needs a marketing function. However, there is interminable wrangling about the value proposition for EA, and considerable effort devoted to crafting and articulating persuasive arguments for EA's existence. It is obvious that value propositions are necessary only because EA's value is not readily apparent.

Business architecture is gaining recognition as a game-changing discipline that enables businesses to address major challenges in new and unique ways.

The ongoing IRS scandal, in which various groups were targeted according to keywords such as "tea party" in the search for infractions, has important lessons for emerging big data techniques.

There are times when major trends intersect. Sometimes they reinforce each other; other times they cancel each other out.

There has been a growing interest in scaling frameworks for Scrum in the past year.

Data and analysis are the mainstays of deterministic decision making. In conversational language, deterministic decision making relies on five elements: data, analysis, logic, reasoning, and judgment. What could be bad about that? It turns out, plenty.

Just a couple of years ago, we were witnessing -- and some of us were deploring -- the "irrational exuberance" as well as the uncontrolled fears of many customers and decision makers about cloud computing.

You have no doubt heard by now about Flash Boys, the new book by Michael Lewis.

I have recently seen the SAFe framework criticized by the Scrum founder as well as the Kanban founder (see "unSAFEe at Any Speed" and "Kanban -- The Anti-SAFe for Almost a Decade Already"). Method wars are not new, however, and could go on forever. In the face of these discussions, it is important to remember the real intent behind Agile methods.

Information technology and systems underpin the operations and existence of all organizations today, with very few exceptions.

Risk management is central to the concept of resilience, and the ability to manage risk has grown significantly through the increasing sophistication of governance, risk, and compliance (GRC) systems.

A couple of years back, I was in a very large requirements meeting for a big project. The subject was the design of something relatively technical, and the young outside consultant running the meeting was trying to get a consensus from the group so she asked for a vote.

The latest industry development concerning the advancement of the IOT is the recent formation of the Industrial Internet Consortium (IIC) by AT&T, Cisco, GE, IBM, and Intel. This not-for-profit group (with an open membership) is important for several reasons.

"I cannot tell you why it took years for a safety defect to be announced." So admitted new GM CEO Mary Barra this week in her testimony to the US House of Representatives Energy and Commerce Committee, which is looking into why it has taken over a decade to recall GM automobiles that were sold with a now-acknowle

People seem to equate programming with coding, and that's a problem. Before you code, you should understand what you're doing. If you don't write down what you're doing, you don't know whether you understand it, and you probably don't if the first thing you write down is code.

[From the Editor: This week's Cutter IT Advisor is from Cutter Fellow Robert N. Charette's introduction to the March 2014 issue of Cutter IT Journal, " Workforce 2020–2025: What Skills Are Needed to Survive and Thrive?" (Vol.

Artificial intelligence (AI) has developed in fits and starts since the 1970s, resulting in numerous advances, but often failing to achieve the levels of capability that had been imagined.