If you were unable to attend our recent webinar, Bringing Estimation and Business Intelligence to the Enterprise, a replay is now available.

Successful software development estimates depend upon more than just inputs, especially at the enterprise level. They require collaboration between stakeholders, consistency in estimation methods, and historical basis. It's also essential to account for uncertainty and risk. In this webinar, Keith Ciocco demonstrates how SLIM-Estimate and SLIM-WebServices work together to bring reliable business intelligence to the enterprise, while leveraging historical data to increase estimation accuracy and credibility.

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image via Techwell

A large part of software estimation is dealing with the unknown. At the earliest stages of a software project, the uncertainty surrounding schedule and budget is at its highest and diminishes as a project reaches completion. In the estimation community, we refer to this as the "cone of uncertainty." Of course, it is at the widest point of this cone where estimation is typically needed. So how can organizations keep their customers feeling secure and informed when requirements are still being flushed out and budgets aren't yet established? In his recent a blog post on Techwell, Noel Wurst identifies strategies for flattening the dreaded cone of uncertainty.

Read the full post here!

Watch the webinar replay for Bringing Estimation and Business Intelligence to the Enterprise, presented by Keith Ciocco.

Successful software development estimates depend upon more than just inputs, especially at the enterprise level. They require collaboration between stakeholders, consistency in estimation methods, and historical basis. It's also essential to account for uncertainty and risk. In this webinar, Keith Ciocco demonstrates how SLIM-Estimate and SLIM-WebServices work together to bring reliable business intelligence to the enterprise, while leveraging historical data to increase estimation accuracy and credibility.

As Vice President of QSM, Keith has more than 25 years of experience working in sales and customer service, with 17 of those years spent at QSM. Keith's primary responsibilities include managing business development, existing client relations, customer retention and response.

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Software projects often commit to unrealistic schedule and budget expectations due to little or no information about the size and scope or productivity. Yet the business reality is that projects must be estimated early in the life cycle to support business goals and strategic planning. These challenges can be overcome with a transparent and collaborative estimation process. It depends on metrics collection, analysis, risk comparison, and a structure for sharing the right information with the right people at the right time.

In an article recently published on Projects at Work, Laura Zuber explores the benefits of collaborative software project estimates and identifies best practices for implementing them.

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Function point analysis has played an important role in software measurement and analysis for 30 years, but what will be the role of function points in the future? Will they have staying power? Expanding off of a recent article for IFPUG's Metrics Views, Don Beckett looks at the QSM software project database and examines a set of validated projects counted in function points that have completed since the year 2000 to see what they tell about productivity, schedule, and staffing. We are fortunate to have several thousand projects in this sample to work with as this allows us to parse the data many different ways and still have enough projects to be statistically significant. For this study only unadjusted function points were used.

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It's no secret we're advocates of smaller teams, but it's always nice when others agree. Baseline's Tony Kontzer leveraged some of our most recent data for an informative slideshow about team size.

At one time or another, almost all information technology professionals have heard cries for more resources. They may even have been the one asking for help. "If only there were more people available for this project," they've said, "then maybe it would get done on time." Well, it turns out that more staffing is not the equivalent of optimal staffing. In fact, smaller project teams are more productive and can complete projects cheaper and faster than larger ones, according to a recent study from software life cycle consultancy Quantitative Software Management. That should be good news for IT departments that have seen their ranks depleted in recent years.

To see more results from QSM's recent study, read Don Beckett's post on the correlation between staffing and schedule.

It’s becoming clear to organizations adopting Agile methods that one still needs to estimate how long a project or a release of a product will take. It won’t suffice for businesses to simply take guesses or accept unreasonable constraints. We must be able to derive credible estimates, based on a history of similar projects. How can we estimate a project in advance while still maintaining the ability to manage the backlog in an agile manner?

In this article, recently published on Projectmanagement.com, QSM's Andy Berner answers that question, compares release-level estimation to the techniques used for iteration estimation, and gives some pointers on getting started with release estimation in an agile environment.

Andy Berner is a software engineer and methodologist. He came to QSM in 2012 after over 25 years in both large and small software organizations, including, among others, EDS (now HP), Rational Software and IBM. Based on his experience in almost every role in software development, Andy has consulted with numerous organizations on using software development methods and tools to improve productivity and quality.

Read the full article here!

Agile is all the rage these days, but what happens to Agile projects when they're forced to scale to the size of major government enterprise initiatives? In this article, originally published in the May-June 2013 issue of Modern Government, Larry Putnam, Jr. looks at 93 Agile projects completed between 2002-2012 to see how these projects fared as their sizes increased. The study examines Early Adopters (2002-2008) vs. Later Adopters (2009-2012), as well as analyzing Agile vs. Non-Agile projects. The results may surprise you!

Read the full article here.