I have been enjoying Alan Cohen's A Deep Breath of Life. I read it every morning with pen in hand, never failing to find at least one or two profound sentences to be my watch-words for the day. One of the July writings contains this quote: "Only infinite patience begets immediate results."  David writes about the perils of rushing through life, and how a lack of patience can causes us to create unnecessary chaos in our daily rounds. He writes, "Rushing never improves the quality of our life or the results we seek; to the contrary, it muddles our vision and causes us to make errors that cost us twice as much time and energy to repair."

One of my first thoughts was about my work at QSM, and how SLIM-Estimate demonstrates the power of patience in software development. Is it possible to exercise patience when there are important business objectives and profit margins to achieve? The Putnam software production equation, backed by 30 years of industry data, shows that relaxing the project schedule gives the best “bang for your buck” to produce value for your customers.

In spite of 30 years of structured programming, CASE tools, OO development, 4th GL languages, CMMI, and PMI, the failure rate for larger projects has failed to respond to all of this love and attention. We normally think of failure as a negative thing; but it can have its upside. Saddling a competitor or enemy with a doomed project could stain their career or at the very least inflict a high level of pain on them. A CEO about to retire, or whose focus is on near term stock options, may be able to boost quarterly profits by continuing to add staff to a doomed effort:  one for which the customer pays for the added staff, of course.

Since failure is a constant, here is a management guide on how to assure failure. While any one step in the process can be overcome, taken together they create the perfect software project storm.

Step 1: Start work as soon as you can

Come on. You don’t really need to spend all that time in requirements meetings and documenting assumptions. Real projects take the ball and run.  Be sure to begin coding as quickly as possible. Call it prototyping if you will; but do get started. You can always circle back to tweak things if needed.

Step 2: Estimation is overhead

Nothing is more frustrating and time wasting as having to go to some external group who know nothing about your project and have them tell you how long your project should take, how many people should be on it, and what the trade-offs are. What can their mathematical models possibly know about your project? A good end run around this situation is to create a project plan and call it your estimate. Make sure that it is very detailed and contains decimal points, since these will make it more difficult to challenge.

The thirty years I have spent in software have bridged a period of remarkable and ever accelerating change. Mercifully, coding an online system on a black and white CRT that accesses an IMS database is mostly a quaint memory. Technology, tools, and processes have all evolved. Why is it, then, that we continue to have the same problems we experienced in the Information Technology Dark Ages? Here are the symptoms:

• Software projects that continue to overshoot their schedules
• Quality problems have neither disappeared nor lessened to an acceptable level
• Budgets are regularly exceeded: sometimes wildly
• Project estimates are inaccurate

I see two principal reasons. I’m certain there are others.

Our Focus on Technology

We are not Luddites resisting change; we love technology and embrace it whole heartedly. We have a rich array of programming and testing tools at our disposal. Why, then, have problems with cost, schedule, and quality persisted?  

One reason is that we focus on technical solutions to problems with many non-technical components. Suppose you have the choice of coding a project in COBOL or Visual Basic. (Suspend your disbelief for a moment and accept that both languages are suitable for the task at hand.) You will produce far less code in VB than in COBOL. You may see some slight reduction in cost and schedule; but it will not approach the 40 – 50% reduction in code that will be seen if you choose VB over COBOL.  

The reason is fairly simple. On a project of any size, coding and unit testing is not where most effort is expended. One number that is touted puts coding/unit testing at 30% of total project effort. This means that a 50% reduction in coding effort yields only a 15% reduction in project effort. While we want and need more effective tools for coding and testing, they have little impact on the remaining 70% of project effort.  

Here's a risk question for you:

If today’s weather forecast predicts a 40% chance of rain and it actually rains, was that forecast “inaccurate”?  If the weather channel predicts a 40% chance of rain, but the sun shines all day, was the forecast “accurate”?

Software project estimates, like weather forecasts, should always be accompanied by some explicit attempt to quantify the risk that the actual outcome will differ significantly from the estimated outcome.  Estimates delivered without explicit risk assessment are more like targets: goals someone wants to achieve.

It turns out that whether it rains or not is actually a poor measure of forecasting accuracy.  A 40% chance of rain forecast is accurate if, on 100 days where the forecast said 40%, it rained on 40 days and didn’t rain on 60. Likewise, the accuracy of an individual software project estimate is not determined by whether the project actually achieves its committed estimate.  We can see this with a simple example: if SLIM-Estimate predicts only a 10% probability of achieving a schedule but the organization decides to commit to a plan with a 90% chance of failing, we could actually consider the estimate to be “more accurate” if the software project fails than if it is successful.

What most organizations are really looking for is not so much accurate estimates as accurate commitments, where the commitment is based on the estimate plus an appropriate level of risk resourcing.  But even with best contingency planning, there is always a finite chance of “failure”—it’s just a lot less than if we don’t resource risk. 

After being away from QSM and the software world for three years, I was blown away by SLIM v8.0's dynamic product integration. I knew it was coming, yet I was still impressed by the simplicity and power of analysis promoted by real-time data and tool links across the SLIM Suite that frees managers to focus on the important program issues.

SLIM-MasterPlan is the center of the SLIM Suite product integration.  It improves upon previously existing program management features of aggregating multiple SLIM-Estimate projects and ancillary tasks with two new capabilities: 

• Linking SLIM-Control workbooks to provide real-time project tracking and control at the program level 
• Performing What If analysis at this higher management view to consider a wider range of potential outcomes.

The What If analysis feature is what I want to highlight.

A good personal development coach knows the "power of the question."  Questions lead to discovery, innovation, and action that brings about positive change.  Better questions lead to better answers.  SLIM's power and distinction has always been fast and easy evaluation of the impact of change, and exploring the realm of possible outcomes.  That's what we are doing when we ask ourselves "What If…?" (or our boss asks us - and we better know the answer!).  SLIM's solution logs make it easy to compare estimates, plans, and forecasts to alternative solutions, QSM trends, and your historical project database.