Category Archives: Software Quality

Disorganization and Changing Your Mind are Both Expensive

NOISERon DuPlain forwarded me an interesting post from November 2008 (via @duanegran, I believe) called How much do websites cost? It’s a great comprehensive overview of the different kinds of web sites that can be built – the spectrum of customization, interactivity, and intent that dictate whether a web site will cost $200 or $2 million. But what really struck me about this article was one tiny little section that talks about value, emphasizing the relationship between quality, waste, and the changeability of human wants, needs, and desires:

2.) A small company site that has 5 to 10 pages describing the products/services offered by the company. $500 to $2,000 depending on how prepared you are, and also on how clear in your own head you are about what you want. Disorganization and changing your mind are both expensive.

Disorganization is expensive because it blocks action. When your house is disorganized, you waste time and energy trying to find stuff. When the processes you use in the workplace are disorganized, time and physical energy can be wasted engaging in non-value-adding activities, and mental and emotional time and energy wasted in unproductive communications. Wasting time and energy can generate short-term real costs (for example, moving parts or products around a factory or supply chain can delay time-to-market while costing more in fuel for transport), long-term real costs (e.g. reinforcing negative behaviors that lead to breakdowns in interpersonal relationships, teamwork, or morale) or opportunity costs.

Changing your mind is expensive for the same reason: it either blocks new action from taking place, or it eliminates the value that could have been added by prior work. A task is not actionable unless you have the 1) resources to do the job, 2) the information and interest to complete it, 3) the skills and capabilities to make it happen, as well as a clear idea of what needs to be done, and 4) an execution environment that supports getting things done. Changing your mind can erode #2 or #3.

To reduce the risk associated with development, and to control the costs of the project, find out:

  • How much do you really know about what you want?
  • What essential elements are you pretty sure you’ll still want or need in 3 months, 6 months, 1 year, 5 years?
  • What parts do you have the resources, information/interest, capabilities/skills/clarity, and execution environment to get done now? (I call this RICE to make it easier to remember)

The lesson: to get higher quality and lower costs (that is, greater value), focus on those parts of a project that are least likely to change and do those first. This is, of course, if you have the luxury to be agile (highly regulated environments may impose restrictions or limits). Then stop – figure out what your experience working on those parts tells you about how you can approach the problem more systematically and effectively– and repeat the cycle until you iterate to the desired solution. This is the essence of applying organizational learning to your day to day tasks.

Achieving Quality when Something is Always Broken

frac1In the quality profession, we are accustomed to thinking about product and component quality in terms of compliance (whether specifications are met), performance (e.g. whether requirements for reliability or availability are met), or other factors (like whether we are controlling for variation effectively, or “being lean” which is realized in the costs to users and consumers). So this morning I attended Ed Seidel’s keynote talk at TeraGrid 09, and was struck by one of his passing statements on the quality issues associated with a large supercomputer or grid of supercomputers.

He said (and I paraphrase, so this might be slightly off):

We are used to thinking about the reliability of one processor, or a small group of processors. But in some of these new facilities, there are hundreds of thousands of processors. Fault tolerance takes on a new meaning because there will be a failure somewhere in the system at all times.

This immediately made me think of society: no matter how much “fault tolerance” a nation or society builds into its social systems and institutions, at the level of the individual there will always be someone at any given time who is dealing with a problem (in technical terms, “in a failure state”). Our programs that aim for quality on the scale of society should take this into account, and learn some lessons from how today’s researchers will deal with fault tolerance in hugely complex technological systems.

It also makes me wonder whether there is any potential in exploring the idea of quality holography. In large-scale systems built of closely related components, is the quality of the whole system embodied in the quality of each individual part? And is there a way to measure or assess this or otherwise relate these two concepts operationally? Food for thought.

Quality of an Interactive System

n1041950747_53558_5249Today, I spent some time in a remote visualization tutorial presented by John Clyne of NCAR. He referenced a 2005 answer to the question “What is meant by interactive analysis?” by Mark Rast of the University of Colorado:

Definition: A system is interactive if the time between a user event and [the system’s] response to that event is short enough to maintain my full attention.

If the response time is…

1-5 seconds: I’m engaged
5-60 seconds: I’m tapping my foot
1-3 minutes: I’m reading email
>3 minutes: I’ve forgotten why I asked the question!

I liked this because it defines a quality attribute: a high-quality interactive system maintains the user’s attention.

Not Invented Here

peacockIf you are part of the software development world, no doubt you are familiar with “not invented here” (NIH) syndrome. It is the scourge of the software development culture, the unfortunate tendency within a group of software-minded people to attribute value to the code that members of the group or the group itself has written, while devaluing code, modules or COTS packages that have not been written by members of the group.

“Not invented here” is so prominent that it has a wikipedia entry, with text that assures us that this tendency is indeed a facet of many a social, corporate or institutional culture. Bloggers and even Harvard Business Review have touted its benefits, suggesting that this characteristic of a culture may catalyze innovation.

Today, I attended a meeting where I had an even bigger revelation about NIH. About 10 people attended, and we talked about how to search a large archive of metadata across multiple data sources. Attendees spoke of the problem as something that really needs to be done, as something that our organization really needs to spend time on – and we need resources to do it. There’s only one problem with this picture – a couple of people within the organization have been working on this problem for the past 18 months, have produced a prototype that’s consistently getting about 100 hits a day (which is substantial given the problem domain), and have received positive reviews and helpful suggestions for moving forward from the user community. The releases have been published in inter-organizational emails, the company newsletter, and other venues where it would be very easy for everyone in this meeting to have learned of the new functionality and used it. But apparently no one has bothered to pay attention!

The moral of the story: when a NIH culture is observed, perhaps the resources and opportunities that are available to a group or an organization that could use them are truly invisible to the people who need them. The people can not see the opportunities because they are not looking; they are not paying attention.

Is paying attention to opportunities a value within your software development organization? It requires conscious effort.

The ITEA Criteria for Software Process & Performance Improvement

(I originally wrote this article for the ASQ Software Division Newsletter compiled in the first quarter of 2009. I’m reproducing it here because I’ve found the ITEA criteria to be remarkably useful for all kinds of planning since I was introduced to it last year.)

frangipani-flowersFor software professionals, particularly those of us who manage product development or development teams, it is important to track progress towards our goals and to justify the results of our efforts. We have to write effective project charters for software development just to get things moving, evaluate improvement alternatives before making an investment of time and effort in a process change, and ultimately validate the effectiveness of what we have implemented.

This past fall, I had the opportunity to serve as a preliminary round judge for the ASQ International Team Excellence Award (ITEA). My subgroup of judges met at the Bank of America training facility in Charlotte, North Carolina, where we split up into teams to evaluate almost 20 project portfolios. A handful of other events just like ours were held at the same time across the country, giving many people the opportunity to train and serve as judges. Before we evaluated the portfolios, we were all trained on how to use and understand the ITEA criteria, a 37-point system for assessing how well a project had established and managed to its own internal quality system. The ITEA criteria can be applied to any development project or process improvement initiative in the same way that the Baldrige criteria might be applied to an organization‘s strategic efforts. For software, this might include improving the internal processes of a software development team, using software improvements and automation to streamline a production or service process, and improving the performance or quality of a software product. (For example, I can envision the ITEA criteria being used to evaluate the benefits of parallelizing all or part of a software system to achieve a tenfold or hundredfold performance improvement.)

You can review these criteria on the web at yourself. There are five main categories in the ITEA criteria: project selection and purpose, the current situation (prior to improvement), solution development (and evaluation of alternatives), project implementation and results, and team management and project presentation. An important distinction is in the use of the words Identify/Indicate, Describe and Explain within the criteria. To identify or indicate means that you have enumerated the results of brainstorming or analysis, which can often be achieved using a simple list of bullet points. To describe means that you have explained what you mean by each of these points. To explain means that you have fully discussed not only the subject addressed by one of the 37 points, but also your rationale for whatever decisions were made. Sustainability of the improvements that a project makes is also a major component of the ITEA criteria. Once your project is complete, how will you ensure that the benefits you provided are continued? How can you make sure that a new process you developed will actually be followed? Do you have the resources and capabilities to maintain the new state of the system and/or process?

The ITEA criteria can serve as a useful checklist to make sure you‘ve covered all of the bases for your software development or process improvement project. I encourage you to review the criteria and see how they can be useful to your work.

Quality is Better When You Feel Good

blue-brainHow you perceive quality is influenced by your expectations. And sometimes, your expectations are subconscious or emotionally driven.

For example, a product may have all the features you, as a consumer, could possibly want and need – and it might perform well too! But it still might not satisfy everyone, or generate the magnitude of sales that were originally projected. How could this be?

Understanding the psychology of quality and value, based on affect, provides insight into how this can happen. Merriam Webster’s Medical Dictionary defines affect as “the conscious subjective aspect of an emotion considered apart from bodily changes.” In short, affect describes how something makes you feel. For example, working on a task that you really enjoy promotes positive affect. Spending time with “de-energizers” who are negative, critical, and generally unhappy can create negative affect.

Research in psychology indicates that positive affect corresponds with the ability to solve problems more readily and effectively, while negative affect can impede problem solving, even for simple tasks. As a result, usability can be considered a function of the positive or negative affect that is generated when a user interacts with a product. This applies to all products, including software and web-based applications.

These studies also suggest that effective design translates to positive affect – meaning that before use, perceived quality and perceived value are more closely related to the perceived quality and value that will be experienced after use. Aesthetics thus play a role in promoting positive affect. As interpreted by Don Norman (2004) in Emotional Design, where many of the aforementioned studies are referenced,

the emotional system changes how the cognitive system operates… [it is] easier for people to find solutions to the problems they encounter… [there is a] tendency to repeat the same operation over again is especially likely for those who are anxious or tense.”

An entertaining example is the ATM case, which I’ll write about tomorrow.

Software Hell is a Crowded Place

fireI’ve been thinking a lot about management fads lately, and ran into this 2005 article by Nick Carr, titled “Does Not Compute”. Here’s the part that caught my eye:

“A look at the private sector reveals that software debacles are routine. And the more ambitious the project, the higher the odds of disappointment. It may not be much consolation to taxpayers, but the F.B.I. has a lot of company. Software hell is a very crowded place.”

Carr continues by describing two examples of failed projects: a massive systems integration effort at Ford Motor Company, and a overzealous business intelligence initiative embarked upon by McDonald’s. Both projects were cancelled when the price tags got too big: $200M for Ford, $170M for McDonald’s. The catch is that failure is good, because when we fail we at least know one solution path that’s not workable – we just need to 1) understand that it doesn’t have to be expensive, and 2) have more courage to allow ourselves and our colleagues to fail without getting depressed or thinking our coworkers are idiots. This is often expressed as “fail early, fail often“. (But note that the assumption is that you persist, and as a result of the learning experience, ultimately meet your goals.)

Without an effective team culture, rational managers, healthy relationships with stakeholders, and capable programmers dedicated to continually improving their skills, all roads can lead to software hell. The process of getting there – which is hellish in and of itself – is the famed death march. This is where a software-related project, doomed to fail, sucks up more time, people, resources, and emotional energy at an ever increasing rate until the eventual cataclysm.

Carr also cites The Standish Report, which in 1994, asserted that only 16% of projects were completed on time, and budget, and meeting specifications. By 2003 the percentage had grown to 34% in a new survey. Other projects that were still completed ran, on average, 50 percent over budget. (And this is for the survey respondents who were actually telling the truth. I know a few people who wouldn’t admit that their project was quite so grossly over budget.)

One way to solve this problem is by focusing on sufficiency and continuous learning, starting the blueprint for a system based on these questions:

  • What features represent the bare minimum we need to run this system?
  • What are the really critical success factors?
  • What do we know about our specifications now? What do we not know?
  • What do we know about ourselves now? What do we want to learn more about?

Software development is a learning process. It’s a process of learning about the problem we need to solve, the problem domain, and ourselves – our interests and capabilities. It’s a process of recognizing what parts of building the solution we’re really good at, and what parts we’re not so good at. Let’s start small, and grow bigger as we form stronger relationships with the systems that we are developing. Having a $170M appetite sure didn’t get McDonald’s anywhere, at least in this case.

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