April 2016

April 2016

How Can We Make Annual IT Budgeting Easier?

One of the things I hear from many c-level managers is how difficult it is and how long it takes to generate reliable resource plans at the enterprise level. Many organizations take months to generate their annual budgets and often times the negotiated budgets end up being unrealistic. To fix this problem we need to combine good capacity planning with good demand management. There are a number of project portfolio management tools to help with the capacity planning. The problem is the numbers will be off if we don’t get the demand management part right.

There are world class demand management tools available that can be used by business decision makers. These tools allow us to come up with empirically based, reliable project and enterprise level resource plans. In the SLIM-Estimate view below you can see the forecasted effort by role by month.

IT Budget Planning

The view below shows the plan being sanity checked with industry data so we can better negotiate our budgets with confidence.

IT Budget Planning

The even bigger news is that we can automatically feed our empirically based demand numbers into our PPM tools, making the job of capacity planning much easier and more reliable. In the view below you can see two separate plans, represented in side by side columns. The original PPM plan was updated automatically from an empirically based and sanity checked plan from SLIM-Estimate.

New Article - 5 Core Metrics to Reduce Outsourced Software Project Failure

Software Estimation Best Practices

Outsourcing was supposed to make government IT executives’ lives easier. Yet in too many cases, it’s had the opposite effect, leading to cost overruns, inefficiencies, and solutions that do not work. Remember the initial rollout of Healthcare.gov? Exactly.

It doesn’t have to be this way.  Believe it or not, there’s a proven solution that has stood the test of time.  In 1977, Lawrence Putnam Sr. discovered the “physics” of how engineers build software by successfully modeling the nonlinear relationship between the five core metrics of software: product size, process productivity, schedule duration, effort and reliability. 

In this article for GCN, QSM's Joe Madden explains how the five core metrics of software estimation make a powerful tool that can be used at each phase of the software acquisition life cycle to help government IT program managers make more objective, quantitative decisions.

Read the full article!

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Articles Metrics Project Management

Roots Run Deep: The Journey to Software Application Estimation and Risk Management

The story of QSM and software application estimation begins during my time in the Army. I was assigned to Sandia Base, NM to research methods for protecting soldiers from the effects of nuclear explosions.  I had to do several calculations to determine the impact of an explosion (blast calculations) on soldiers using a slide rule, which was very tedious.  Sandia National Laboratory was next door to my office, and they had just gotten the biggest and best engineering computer available at the time.  They offered computer time for anyone needing it and even offered to teach me programming, so I decided to take a course in FORTRAN programming over my lunch hour so I could do my blast calculations quicker. These lessons aided me in completing my work at Sandia and followed me to my future assignment at the Pentagon. 

For my tour at the Pentagon in the 1970s, there was not a lot of need for my nuclear experience so I was assigned to the Army’s computer program. We had to defend our program budget to the Department of Defense (DoD) budget review authority (OSD). One system, SIDPERS, the Army enterprise personnel system, had been in development for five years and after having a peak staff of 110, we were projecting 93 people for the next five years. The analyst looking at the budget asked what should have been a simple question, “What are these people going to do?” I did not have a good answer, and later, going back to the project team, neither did they. Because of this we lost $10M in our budget.

Blog Post Categories 
Estimation Risk Management