Is Your ‘Wastebook’ Overflowing?

Posted By PPizzutillo on January 4, 2012 | Software Analysis

Every year, Senator Tom Coburn compiles the Wastebook – A Guide to Some of the Most Wasteful and Low Priority Government Spending of 2011.

According to Senator Coburn in the report:

“This report details 100 of the countless unnecessary, duplicative  or just plain stupid projects spread throughout the federal government  and paid for with your tax dollars this year that highlight the out-of-control and shortsighted spending excesses in Washington.”

The list of $7B in wasteful projects is as amusing as it is disturbing. As a taxpayer, reading a list of this ilk makes our leaders and decision-makers seem detached, self-serving and simply incompetent. Political motivations aside, Coburn’s act of holding a mirror to the process – not to mention to the decision-makers – is a relevant example for us all.

In this economy, none of us can continue to get away with spending money poorly. The rationale behind decisions and priorities isn’t always apparent to those outside the process. However, especially in the business world, we are counting on those people for support and to execute such decisions.

Fact-Based Insight

As reported in Government Computer News, this year’s report includes a number of high-tech projects “involving Twitter, Facebook, video games, podcasts, holographs and other new technologies.”

The ability to support decisions quickly and objectively has always been a portfolio management struggle. Many companies look to enterprise tools to bear this burden, when in reality most tools in the market are spreadsheets on steroids and hollow shells that simply automate poor practices. Instead, organizations should shift their focuses to systems and processes that provide objective rationalization of their portfolios. We usually know such practices by the monikers Application Performance Management (APM) or Performance Prediction Model (PPM).

One of the most obvious examples of when APM or PPM fails is found in the notion of “technical risk”. Many tools offer the ability to view a portfolio in two dimensions: business value and technical risk. The business value component typically applies some science to user-defined inputs concerning an organization’s mission-critical applications. In similar fashion, these tools take the same approach when deriving technical risk. Combining these two semi-subjective indicators provides “insight” for decision-makers.

Taking the Risk Out of Technical Risk

There are many definitions of technical risk including this one from BusinessDictionary.com: “Exposure to loss arising from activities such as design and engineering, manufacturing, technological processes and test procedures.”

Rather than utilizing subjective input on these parameters, wouldn’t employing a more rigorous process that provides objective assessment of technical risk provide far better information?  First, it would reduce the gaming of the portfolio rationalization process. Second, a repeatable and automated process would reduce risk and effort to generate better quality information.

If this capability existed today, I wonder how many projects would make it into the “Wastebook” portfolios of corporate IT departments. Well it does exist in the form of automated analysis and measurement platforms that provide companies with the comprehensive visibility and control needed to achieve significantly more business productivity from complex applications with an objective and repeatable way to measure and improve the application software quality. And not only can they improve application software quality, they can identify areas of technical risk, help monetize them, and provide a basis for comparison with business value to determine a course of action.

I wonder what Government Computer News would have said about the duplicative and shortsighted decisions made by IT departments in the private sector if it were to apply automated analysis and measurement. Would it find the private sector’s “Wastebook” as overflowing as the government’s?

Tags: Application Quality, automated analysis and measurement, Government, Project Management, quality, quality assurance, Software, Software Quality, structural quality