Monday morning I received an email that read:

Hi All,
You can set your clocks to it: the birds flying north for spring, daylight savings time, and this email being sent on the Sunday before the tournament begins.  That's right, March Madness is upon us my friends, and we’ve officially made it through winter. 

The message continued with details about how to participate, but as you can see, it’s time for QSM’s annual March Madness tournament.  So how do I justify spending company time filling out brackets?  By blogging about how this is actually related to project management.  As I went through the exercise of predicting the course of this tournament, I realized that many of the thoughts I had also go through the minds of project managers.

Before I reveal my picks I want to give some background information.  I’m new to this whole March Madness tournament thing.  I’m not familiar with the teams.  I don’t know the players’ strengths and weaknesses.  I didn’t watch their games earlier in the season, so I don’t know their stats.  All I know is that my significant other went to Ohio State so I want them to win.

It’s easy to get confused or overly concerned about measuring velocity. Actually, the concept is almost embarrassingly simple. Velocity in Agile is simply the number of units of work completed in a certain interval. Like in many fields, Agile proponents appropriated existing terminology.

Here is one typical definition, from agilesoftwaredevelopment.com:

In Scrum, Velocity is how much product backlog effort a team can handle in one Sprint. Velocity is usually measured in story points or ideal days per Sprint… This way, if the team delivered software for 30 story points in the last Sprint their Velocity is 30.

Velocity as a capacity planning tool used in Agile software development is calculated from the results of several completed sprints. This velocity is then used in planning future sprints.

The concept of velocity comes from physics. In physics, velocity is speed and direction, in other words, the rate of change of position of an object. Speed can be measured in many different ways.

In software, speed is frequently measured as size per unit of time (sometimes this has been called delivery rate). The measure of size could be any of the common size measures: lines of code, function points, requirements, changes, use cases, story points. The measure of time could be calendar time (month, week, day) or it could be specific to a project (sprint, release). As to direction, in software hopefully the direction is positive, but sometimes projects go backwards (for example, backing functionality out of a system).

In his book, The Functional Art, Alberto Cairo sets out to explain what data visualizations are, why it is significant to pair data and design, and how to assess whether a data visualization is "good" or not.  In the first chapter, Cairo presents an example from Matt Ridley's book, The Rational Optimist: How Prosperity Evolves.  Ridley asserted that the global population was decreasing over time, using only one line chart.

Cairo  was uncomfortable with that assertion, so he used the UN and World Bank data for fertility rates (the average number of children born to a women in each country) to create a graph that used individual country population data instead of using aggregate data.  The chart below shows all the fertility rates for every country over time.

There are so many stories in the data that it's overwhelming, so Cairo created the following graphic which highlights just a few countries in order to pull out the story within the data:

Scope creep is a frequent topic of discussion among project management professionals.  A recent Project Management Institute (PMI)^® i Community Post, Fighting the Dreaded Scope Creep, reported some responses PMI members offered as their weapon of choice.  The various suggestions can be summarized by two general practices:

• Avoid making on-the-spot decisions (uninformed or politically motivated)
• Communicate the impact of the change to stakeholders and let them decide (analyze the cost, schedule, and risk impact)

Regardless of the specific practice, all of the recommended defenses included some process for change control.

I like words.  When I need to understand a topic, I pull the dictionary off the shelf (or access the online version), and look at the basic definition.  To determine why scope creep is such a formidable enemy, I looked up the word “creep”:  2. to approach slowly, imperceptibly, or stealthily; 4. to sneak up behind someone or without someone's knowledge.  A vast majority of results from a general internet search defined scope creep as “uncontrolled change.” 

If you were unable to attend our recent webinar, Using Benchmarking to Quantify the Benefits of Process Improvement, a replay is now available.

With increasing pressure to improve quality while cutting costs, process improvement is a top priority for many organizations right now; but once we've implemented a process improvement initiative, how do we accurately measure the benefits? Benchmarking is critical to determining the success of any serious process improvement program. As with any type of measurement program, it requires an initial reference point to measure progress. To set our point of comparison, we first need to perform a benchmark on a contemporary sample of projects that are representative of the typical work that we do. In this webinar, industry expert Larry Putnam, Jr. will take you through the necessary steps to perform a successful benchmark - from collecting quantitative and qualitative data to establish the initial baseline benchmark all the way through to performing follow up benchmarks on new projects and process improvement analysis.

Larry Putnam, Jr. has 25 years of experience using the Putnam-SLIM Methodology. He has participated in hundreds of estimation and oversight service engagements, and is responsible for product management of the SLIM Suite of software measurement tools and customer care programs.

Watch the webinar replay!

“You can’t know where you’re going until you know where you’ve been.”

At this point, we’re about one month into 2013 and many of us have abandoned our New Year’s resolutions.  Personally, I prefer to set my yearly goals about a month in because it gives me some time to reflect on what I really want to improve without being distracted by everyone’s bandwagon resolutions like getting in shape or eating less junk food.

The other reason I prefer to wait a month before resolving to do anything is because it gives me time to collect some baseline data.  In his Wall Street Journal article, Bill Gates writes, that “you can achieve incredible progress if you set a clear goal and find a measure that will drive progress toward that goal.”

To use the common example of getting in shape, I’m going to explain:

1. How to set a goal, and
2. How to measure it so that you can effectively achieve your goal.

First you need to set a baseline measure of what your abilities are.  How fast and far can you run?  How much weight can you lift?  How much do you weigh?  Knowing the answers to these questions can help you determine what needs improvement.  

Next you need to identify your end goal and find a way to quantify progress towards that goal.  What does “get in shape” actually mean?  Do I want to be able to run faster?  Farther?  Do I want to be able to lift more weight?  Do I want to weigh less?  All of these goals can be quantified (e.g. I want to be able to run a mile 30 seconds faster than I currently do, I want to run a 10 miler, I want to be able to bench press 100 pounds, I want to lose 20 pounds).

As more of our clients adopt Agile methods, they often wonder how SLIM-Estimate fits into the Agile planning process? It’s not uncommon for teams to claim that Agile makes estimation obsolete. But regardless of which features end up in a particular release, businesses still need to know how much functionality can be delivered within a given schedule and budget. Because I have been working with more customers to estimate Agile projects, the first Agile planning and analysis practice suggested by Ellen Gottesdiener & Mary Gorman got my attention ‒ Use Three Planning Horizons: Now-View, Pre-View, and Big-View. Simply stated, each level of the view hierarchy represents more fine-grained planning and analysis:

• Big-View – general idea; how the product will fit in with other products
• Pre-View – enough detail to start planning the next release
• Now-View – delivery team analyzes and estimate activities needed

Their statement, "we don’t think of agile as a methodology per se. Rather, it’s a disciplined discovery and delivery framework (emphasis added)" is consistent with QSM's approach to estimating Agile projects. Macro estimation techniques allow the business to allocate resources to product development efforts by identifying the number of releases to be built during the next budget cycle, which corresponds to the Big-View horizon. More detailed release planning is performed later in the process, using the prioritized product backlog to determine delivery goals for each iteration.

On Thursday, Feb. 7, at 1:00 PM EST, Larry Putnam, Jr. will present Using Benchmarking to Quantify the Benefits of Process Improvement.

With increasing pressure to improve quality while cutting costs, process improvement is a top priority for many organizations right now; but once we've implemented a process improvement initiative, how do we accurately measure the benefits? Benchmarking is critical to determining the success of any serious process improvement program. As with any type of measurement program, it requires an initial reference point to measure progress. To set our point of comparison, we first need to perform a benchmark on a contemporary sample of projects that are representative of the typical work that we do. In this webinar, industry expert Larry Putnam, Jr. will take you through the necessary steps to perform a successful benchmark - from collecting quantitative and qualitative data to establish the initial baseline benchmark all the way through to performing follow up benchmarks on new projects and process improvement analysis.

Larry Putnam, Jr. has 25 years of experience using the Putnam-SLIM Methodology. He has participated in hundreds of estimation and oversight service engagements, and is responsible for product management of the SLIM Suite of software measurement tools and customer care programs. Since becoming Co-CEO, Larry has built QSM's capabilities in sales, customer support, product requirements and most recently in creating a world class consulting organization. Larry has delivered numerous speeches at conferences on software estimation and measurement, and has trained - over a five-year period - more than 1,000 software professionals on industry best practice measurement, estimation and control techniques and in the use of the SLIM Suite.

Having data is great, but if you don't understand how to display it, you can't get your point across.  The focus of this blog series is to explain the various chart types available to you in SLIM-Metrics so that you can efficiently analyze your data, as well as to provide helpful tips and tricks. 

Bar charts break a data set into bins or categories and provide the number/percent of projects or the average metric value for each category.

Unlike scatter plot charts, bar charts can display both numeric and text metrics. There are two metrics tabs on a bar chart property sheet — one for the independent and one for the dependent metric. To create a bar chart, highlight the independent and dependent metric you want to display and select Choose, or simply double-click the desired metric. Once chosen, the selected metric name appears in the field to the right of the Choose button. 

Histograms

Histograms display continuous numeric data (each bar spans the interval between dependent axis ticks) grouped into evenly spaced bins on the independent axis, for the first data set. Additional data sets are overlaid over the bars in a line style with symbols. The Bin Size or Number of Bins can be customized, or you can select Auto to accept the default bin settings.

Histograms show both values and distributions, which is an important way of evaluating single summary statistics, such as averages.  For example, if a PI histogram follows a normal distribution, then you can probably use the average PI for estimation.  If a PI histogram does not follow a normal distribution, then it is a good idea to choose a different method to pick PI.

It’s tempting to do things that you shouldn’t.  In software development, unrealistic deadlines and changing requirements often lead teams to make counterproductive decisions, such as adding additional staff in order to achieve a deadline.  This not only creates more defects on the current project but also takes resources away from other projects.  

I recently faced a similar dilemma when deciding whether or not to indulge in the holiday treats in the office breakroom.  Should I consume the sugary snacks that taste delicious but have the potential to cause obesity (among other health consequences) or should I eat the banana I brought with me?  Perhaps to me, this internal debate became exaggerated after reading Kidd et al.’s (2013) study and watching the accompanying video on environmental stability and satisfaction.  However, after some thinking, and more indecision on my snack choice, I came to the conclusion that software is like a marshmallow.