Form Follows Function on SPaMCast 442

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A new month brings a new appearance on Tom Cagley’s Software Process and Measurement (SPaMCast) podcast.

This week’s episode, number 442, features Tom’s excellent essay on capability teams (highly recommended!), followed by a Form Follows Function installment based on my post “Systems of Social Systems and the Software Systems They Create”. Kim Pries bats cleanup with a Software Sensei column, “Software Quality and the Art of Skateboard Maintenance”.

In this episode, Tom and I continue our discussion on the organizations as system concept and how systems must fit into their context and ecosystem. In my previous posts on the subject, I took more of a top down approach. With this post, I flipped things around to a bottom up view. Understanding how the social and software systems interact (including the social system involved in creating/maintaining the software system) is critical to avoid throwing sand in the gears.

You can find all my SPaMCast episodes using under the SPaMCast Appearances category on this blog. Enjoy!

This is not a project

Gantt Chart

My apologies to René Magritte, as I appropriate his point, if not his iconic painting.

After I posted “Storming on Design”, it sparked a discussion with theslowdiyer around context and change. In that discussion, theslowdiyer commented:

‘you don’t adhere to a plan for any longer than it makes sense to.’
Heh, agree. I wonder if the “plan as a tool” vs. “plan as a goal in itself” discussion isn’t deserving of a post of its own 🙂

Indeed it is, even if it did take me nearly four months to get to it.

The key concept to understand, is that the plan is not the goal, merely a stated intention of how to achieve the goal (if this causes you to suspect that the words “plan” and “design” could be substituted for each other without changing the point, move to the head of the class). Magritte’s painting stated that the picture is not the thing. The map is not the territory (and if that concept seems a bit self-evident, consider the fact that Wikipedia considers it significant enough to devote over 1700 words, not counting footnotes and links, to the topic).

Conflating plan and goal is a common problem. To illustrate the difference, consider undergoing an operation. Is it your desire that the surgeon perform the procedure as planned or that your problem gets fixed? In the former scenario, your survival is optional.

This is not, however, to say that planning (or design) is useless. The output of an effective planning/design process is critical. As Joanna Young noted in her “Four Signs of Readiness – Or Not”:

I’m all for consigning the traditional 50+ pages of adminis-trivia on scope, schedule, budget, risks that requires signing in blood to the dustbin. However no organization should forego the thoughtful and hard work on determining what needs to be done, why, how, by whom, for how much – and how this will all be governed and measured as it is proceeds through sprints and/or waterfalls to delivery.

The information derived from the process (not the form, not the presentation, but the information) is critical tool for moving forward intelligently. If you have no idea of what to do, how to do it, who can do it when and for how much, you are adrift. You’re starting a trip with no idea of whether the gas tank has anything in it. Conversely, attempting to achieve 100% certainty from the outset is a fool’s errand. For any endeavor, more will be known nearer the destination. Plans without “wiggle room” are of limited usefulness as you will drift outside the cone of uncertainty from the start and never get back inside.

Having a reasonable idea of what’s acceptable variance helps determine when it’s time to abandon the current plan and go with a revised one. Planning and design are processes, not events or even phases. It’s a matter of continually monitoring context and whether our intentions are still in accordance with reality. Where the differ, reality wins. Always.

Execution isn’t blindly marching forward according to plan. It’s surfing the wave of context.

Stopping Accidental Technical Debt

Buster Keaton looking at a poorly constructed house

In one of my earlier posts about technical debt, I differentiated between intentional debt (that taken on deliberately and purposefully) and accidental debt (that which just accrues over time without rhyme or reason or record). Dealing with (in the sense of evaluating, tracking, and resolving it) technical debt is obviously a consideration for someone in an application architect role. While someone in that role absolutely should be aware of the intentional debt, is there a way to be more attuned to the accidental debt as well?

Last summer, I published a post titled “Distance…is the one true enemy…”. The post started with a group of tweets from Gregory Brown talking about the corrosive effects of distance on software development (distance between compile and run, between failure and correction, between development and feedback, etc.). I then extended the concept to management, talking about how distance between sense-maker and decision-maker could negatively affect the quality of the decisions being made.

There’s also a distance that neither Greg nor I covered at the time, design distance. Design distance is the distance between the design and the outcome. Reducing design distance makes it easier to keep a handle on the accidental debt as well as the intentional.

Distance between the architectural decisions and the implementation can introduce technical debt. This distance can come from remote decision-makers, architecture pigeons who swoop in, deposit their “wisdom”, and then fly away home. It can come from failing to communicate the design considerations effectively across the entire team. It can also come from failing to monitor the system as it evolves. The design and the implementation need to be in alignment. Even more so, the design and the implementation need to align with particular problems to be solved/jobs to be done. Otherwise, the result may look like this:

Distance between development of the system and keeping the system running can introduce technical debt as well. The platform a system runs on is a vital part of the system, as critical as the code it supports. As with the code, the design, implementation, and context all need to be kept in alignment.

Alignment of design, implementation, and context can only be maintained by on-going architectural assessment. Stefan Dreverman’s “Using Philosophy in IT architecture” identified four questions to be asked as part of an assessment:

  1. “What is my purpose?”
  2. “What am I composed of?”
  3. “What’s in my environment?”
  4. “What do I communicate?”

These questions are applicable not only to the beginning of a system, but throughout its life-cycle. Failing to re-evaluate the architecture as a whole as the system evolves can lead to inconsistencies as design distance grows. We can get so busy dealing with the present that we create a future of pain:

At first glance, this approach might seem to be expensive, but rewriting legacy systems is expensive as well (assuming the rewrite would be successful, which is a tenuous assumption). Building applications with a one-and-done mindset is effectively building a legacy system.

Form Follows Function on SPaMCast 438

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Once again, I’m making an appearance on Tom Cagley’s Software Process and Measurement (SPaMCast) podcast.

This week’s episode, number 438, features Tom’s essay on using sizing for software testing, Kim Pries with a Software Sensei column (canned solutions), and a Form Follows Function installment based on my post “Organizations as Systems and Innovation”.

In this episode, Tom and I discuss how systems must fit into their context and ecosystem, otherwise it can be like dropping a high-performance sports car engine into a VW Beetle. Disney-physics may work in the movies, but it’s unlikely to be successful in the real world. If all the parts don’t fit together, friction ensues.

You can find all my SPaMCast episodes using under the SPaMCast Appearances category on this blog. Enjoy!

Square Pegs, Round Holes, and Silver Bullets

Werewolf

People like easy answers.

Why spend time analyzing and evaluating when you can just take some thing or some technique that someone else has already put to use and be done with it?

Why indeed?

I mean, “me too” is a valid strategy, right?

And we don’t want people to get off message, right?

And we can always find a low cost, minimal disruption way of dealing with issues, right?

I mean, after all, we’ve got data and algorithms, and stuff:

The thing is, actions need to make sense in context. Striking a match is probably a good idea in the dark, but it’s probably less so in daylight. In the presence of gasoline fumes, it’s a bad idea regardless of ambient light.

A recent post on Medium, “Design Sprints Are Snake Oil” is a good example. Erika Hall’s title was a bit click-baitish, but as she responded to one commenter:

The point is that the original snake oil was legitimate and effective. It ended up with a bad reputation from copycats who over-promised results under the same name while missing the essential ingredients.

Sprints are legitimate and effective. And now there is a lot of follow-up hype treating them as a panacea and a replacement for other types of work.

Good things (techniques, technologies, strategies, etc.) are “good”, not because they are innately right, but because they fit the context of the situation at hand. Those that don’t fit, cease being “good” for that very reason. Form absent function is just a facade. Whether it’s business strategy, management technique, innovation efforts, or process, there is no recipe. The hard work to match the action with the context has to be done.

Imitation might be the sincerest form of flattery, but it’s a really poor substitute for strategy.

Systems of Social Systems and the Software Systems They Create

I’ve mentioned before that the idea of looking at organizations as systems is one that I’ve been focusing on for quite a while now. From a top-down perspective, this makes sense – an organization is a system that works better when it’s component parts (both machine and human) intentionally work together.

It also works from the bottom up. For example, from a purely technical perspective, we have a system:

Generic System

However, without considering those who use the system, we have limited picture of the context the system operates within. The better we understand that context, the better we can shape the system to fit the context, otherwise we risk the square peg in a round hole situation:

Generic System with Users

Of course, the users who own the system are also only a part of the context. We have to consider the customers as well:

Generic System with Users and customers

Likewise, we need to consider that the customers of some systems can be internal to the organization while others are external. Some of the “customers” may not even be human. For that matter, sometimes the customer’s interface might be a human (user) rather than software. Things get complicated when we begin adding in the social systems:

Generic EITA with Users and customers

The situation is even more complicated than what’s seen above. We need to account for the team developing and operating the automated system:

Generic System with Users, customers, and IT team

And if that team is not a unified whole, then the picture gets a whole lot more interesting:

Generic System with Users, customers, and IT teams

Zoomed out to the enterprise level, that’s a lot of social systems. When multiplied by the number of automated systems involved, the number easily becomes staggering. What’s even more sobering is reflecting on whether those interactions have been intentionally structured or have grown organically over time. The interrelationship of social and software systems is under-appreciated. A series of tweets from Gregory Brown last week makes the same case:

A number of questions come to mind:

  • Is anyone aware of all the systems (social and software) in play?
  • Is anyone aware of all the interactions between these systems?
  • Are the relationships and interactions a result of intentional design or have they “just happened”?
  • Are you comfortable with the answers to the first three questions above?

Organizations as Systems and Innovation

Portrait of Gustavus Adolphus of Sweden

Over the last year or so, the concept of looking at organizations as systems has been a major theme for me. Enterprises, organizations and their ecosystems (context) are social systems composed of a fractal set of social and software systems. As such, enterprises have an architecture.

Another long-term theme for this site has been my conversation with Greger Wikstrand regarding innovation. This post is the thirty-fifth entry in that series.

So where do these two intersect? And why is there a picture of a Swedish king from four-hundred years ago up there?

Innovation, by its very nature (“…significant positive change”), does not happen in a vacuum. Greger’s last post, “Innovation arenas and outsourcing”, illustrates one aspect of this. Shepherding ideas into innovations is a deliberate activity requiring structural support. Being intentional doesn’t turn bad ideas into innovations, but lack of a system can cause an otherwise good idea to wither on the vine.

Another intersection, the one I’m focusing on here, can be found in the nature of innovation itself. It’s common to think of technological innovation, but innovation can also be found in changes to organizational structure and processes (e.g. Henry Ford and the assembly line). Organization, process, and technology are not only areas for innovation, but when coupled with people, form the primary elements of an enterprise architecture. It should be clear that the more these elements are intentionally coordinated towards a specific goal, the more cohesive the effort should be.

This brings us to Gustavus Adolphus of Sweden. In his twenty years on the throne, he converted Sweden into a major power in Europe. Militarily, he upended the European status quo in a very short time (after intervening in the Thirty Years’ War in 1630, he was killed in battle in 1632) by marshaling organizational, procedural, technological innovations:

The Swedish army stood apart from its’ contemporaries through five characteristics. Its’ soldiers wore uniform and had a nucleus of native Swedes, raised from a surprisingly diplomatic system of conscription, at its’ core. The Swedish regiments were small in comparison to their opponents and were lightly equipped for speed. Each regiment had its’ own light and mobile field artillery guns called ‘leathern guns’ that were easy to handle and could be easily manoeuvred to meet sudden changes on the battlefield. The muskets carried by these soldiers were of a type superior to that in general use and allowed for much faster rates of fire. Swedish cavalry, instead of galloping up to the enemy, discharging their pistols and then turning around and galloping back to reload, ruthlessly charged with close quarter weapons once their initial shot had been expended. By analysing this paradigm it becomes apparent that the army under Gustavus emphasized speed and manoeuvrability above all – this greatly set him apart from his opponents.

By themselves, none of the innovations were original to Gustavus. Combining them together, however, was and European military practice was irrevocably changed. Inflection points can be dependent on multiple technologies catching up with one another (since the future is “…not very evenly distributed”), but in this case the pieces were all in place. The catalyst was someone with the vision to combine them, not random chance.

Emergence will be a factor in any complex system. That being said, the inevitability of those emergent events does not invalidate intentional design and planning. If anything, design and planning is more necessary to deal with the mundane, foreseeable things in order to leave more cognitive capacity to deal with that which can’t be foreseen.