<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Simulation on A Field CTO Perspective</title><link>https://gaberger.github.io/tags/simulation/</link><description>Recent content in Simulation on A Field CTO Perspective</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Fri, 26 Jun 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://gaberger.github.io/tags/simulation/index.xml" rel="self" type="application/rss+xml"/><item><title>Breaking the Capability Trap</title><link>https://gaberger.github.io/2026/06/breaking-the-capability-trap/</link><pubDate>Fri, 26 Jun 2026 00:00:00 +0000</pubDate><guid>https://gaberger.github.io/2026/06/breaking-the-capability-trap/</guid><description>&lt;h2 id="a-systems-approach-to-safe-fast-network-change">A Systems Approach to Safe, Fast Network Change&lt;/h2>
&lt;p>A whitepaper on applying System Dynamics to network change management, and the business case for pre-change simulation&lt;/p>
&lt;h2 id="executive-summary">Executive Summary&lt;/h2>
&lt;p>Network change is one of the riskiest things an enterprise does to itself. A single routing or firewall edit can quietly break an application dependency, pull reachability from a whole region, or take the business offline for hours.&lt;/p>
&lt;p>The usual response (freezes, heavier approval boards, rarer maintenance windows) feels like risk reduction but isn&amp;rsquo;t. Research from MIT Sloan&amp;rsquo;s System Dynamics group shows it does the opposite. Each control added after a failure quietly raises the odds of the next one, and the organization spends years tightening the loop on itself.&lt;/p></description></item></channel></rss>