Best of Blogs

My most recent blog series is about The Snowman Architecture.

• Part 1: The Snowman Architecture; Overview.
• Part 2: The Snowman Architecture; The Economic Benefits
• Part 3: The Snowman Architecture: The Technical Benefits.

These are some of my favorite of my previous blogs.

• Wake-up Call for the Banking Industry. Why the Banking Industry is starting to pay attention to complexity and enterprise architecture.
• The Mathematics of Agile Development and Snowmen. Why Agile needs Snowmen.
• The Fundamental Flaw of Complexity Management. Why most current approaches to Complexity Management are flawed.
• The Mathematics of IT Simplification. Introducing the paper that laid the groundwork for a theoretical understanding of IT complexity.
• SIP and TOGAF: A Natural Partnership.
• The 3000 Year Old IT Problem. IT just doesn't get it. Blame Julius Caesar.
• Radical IT Transformation. IT is not delivering enough value for its cost. It is time for a Radical IT Transformation. This blog sets the stage.
• Gartner: Complexity Reduction One of Top Ten Technical Trends
• The Misuse of Reuse. In IT, is reuse as important a goal as we seem to think?
• The Equation Every Enterprise Architect Should Memorize. We can quantify the complexity of an enterprise architecture. Here is the formula.
• The SIP Complexity Model. In the SIP methodology, potential solutions are categorized based on two values: complexity and business value.
• The Relationship Between IT Project Size and Failure Rates. Are you getting ready to start a large IT project? You may be doomed before you start. This blog contains an embedded web short.
• The Mathematics of Cloud Optimization. Are there formal rules we can apply to creating a "good" cloud architecture? His blog contains an embedded web short on this topic.
• The SIP Methodology for Project Optimization. We know we need better approaches to optimizing large IT projects. SIP is the first methodology to tackle this problem. This blog contains an embedded web short.
• The Problem with Standish. Over and over again, we hear the Standish numbers of IT failure. But there are some fundamental flaws with how this research is being done.