Project managers and estimators have long struggled with the issue of how to measure software size. Really, before you can calculate cost and schedule, you will need some notion of how big the project will be. There are myriad of ways to size a project depending on the methodology you use and where you are in the planning process. Here at QSM, it's one of the common questions we receive, so we've devoted many years of research to the topic. Our website features a wealth of resources on sizing and in this post, we will highlight a few of the most valuable for anyone grappling with this issue or looking for a place to start.

General Sizing

• QSM's Software Sizing infographic is a great place to start. This easy to understand visual resource helps explain the most popular sizing methods and when to use them, the difference between functional and technical size, sizing challenges and more!
• Measuring Software Size - Insights from the Past to Guide the Future is another helpful guide if you're struggling with which sizing units to use. This PDU-approved webinar will help you determine what sizing measure will work for you based on your own historical data. This presentation is worth a watch no matter what development methodology you use and can help improve future estimates and in-flight project forecasts.

Function Points

QSM is a leading demand and vendor management company. We have many years of experience working with outsource management professionals, evaluating software project vendor bids and monitoring the development progress of those bids for our clients. We are often hired to help them with their vendor management process because their past projects have failed to meet cost, effort, reliability, and duration expectations. 

It starts with the independent estimate and bid evaluation process. Our main clients are CIOs, PMO managers, purchasing managers, software project managers, and business stakeholders. Our clients will usually have a large software development or package configuration project pending. They are initially trying to figure out which vendor to hire. Vendor A will offer them a bid of 20 million dollars with a specified duration commitment and Vendor B will offer them a bid of 30 million dollars with a different duration commitment. How do we know which vendor to choose? Can Vendor A really finish with a lower cost and shorter schedule? Is the system going to work when it’s done?

The way it usually works is the client will make a decision based on their experience or gut feel. Or if they have already worked with a specific vendor in the past they will go with that vendor again based on some personal relationships that have evolved. Then the problems start. The work that was promised doesn’t get done within the promised time or the promised budget. The vendor then comes back and says they will add people to the project and everything will be ok. The client approves the revised project plan since they don’t have a way to confirm the accuracy of the revised proposal. Then even bigger problems start. More money is wasted, the schedule slips even more, and relationships sour.

Arithmetic mean (aka average) is often a misleading number. One reason for this is that mean is sensitive to outliers. A very large or a very small value can greatly influence the average. In those situations a better measure of center is the median (the 50th percentile). But there is a second huge pitfall awaiting anyone using average for estimating or benchmarking: software size.

Even though we know that software size has a major influence on the key metrics (e.g., effort, duration, productivity, defects) many people insist on reporting and comparing and using the average value. Let’s look at an example. Consider a sample of 45 completed telecommunications application type projects. Picking one of the key metrics already mentioned, duration of phase 3, we can generate a histogram and calculate the mean. The average duration is 27.5 months. Does this tell us anything useful?

The histogram of durations shows a skewed distribution (many projects have a shorter duration, few have a long duration), so we will need to do some sort of normalization before the average is a measure of center.  And even then, what about size?  In a typical SLIM scatterplot of duration versus size for these projects, we can see that in general larger projects take longer than smaller ones.  

I have been a software project estimator for 20 years.  Like many people who have worked a long time in their profession, I find myself applying my work experience to other events in my life.  So, when a family member tells me that he or she will be back from a trip into town at 3:30, I look at their past performance (project history) and what they propose to do (project plan) and add an hour.  Usually, I am closer to the mark than they are.