Baseballs and Hockey Pucks

“Keep your eye on the ball!” I was always coached when learning how to play baseball. Seemed like reasonable advice while standing at the plate, facing down the pitcher for the opposing team. Certainly wouldn’t want to be daydreaming or casting my gaze to the horizon. It didn’t seem to help, though. I excelled at striking out.

Later…much later…I came across Wayne Gretzky’s quote: “Skate to where the puck is going, not where it has been.” I wonder if I had learned to figure out where the baseball was going to be and made sure my bat was there to meet it if I might have spent more time on bases. Keeping my eye on the ball didn’t tell me much about when to start my swing.

No regrets. I still love the game (as it was, not as it currently is.)

I think of this Gretzky quote when I watch product owners struggle with organizing their backlog. (I also think how tragic it is that the business world has beat this quote into an intolerable pulpy platitude.)

Ask a product owner what their team is working on today, they should be able to give a succinct answer. Ask them what their team is going to be working on in three months and watch the clock. The longer they can go on about what their team is going to be working on, the healthier their backlog is likely to be. Struggling product owners scramble to keep their teams busy sprint-to-sprint. Good product owners can see where their teams are going to be in several months. Great product owners see to the end of the game.


Photo by Chris Chow on Unsplash

Innovation and Limits to Growth

In a basic growth model, some finite resource is consumed at a rate such that the resource is eventually depleted. When that happens the growth that was dependent on that resource stops and the system begins to collapse. If it happens that the resource is renewable eventually the rate of consumption matches the rate of renewal and the system enters into a state of equilibrium (no growth). This is illustrated by the black line in Figure 1. In this second scenario if the rate of consumption exceeds the rate of renewal the system will again collapse.

In the Solow model of growth (neoclassical growth model) a new element is introduced: the effect of technology or innovation on the growth curve. Without innovation, in systems where technology stays fixed, growth will eventually stop. The introduction of innovative solutions to resource problems, however, has the effect of raising the upper bound to growth limits. This is illustrated by the red line in Figure 1.

Figure 1 - Innovation Boost
Figure 1 – Innovation Boost

A prevailing assumption with innovation is that it is necessarily synonymous with invention. To be innovative is to create something that has not previously existed. This is an erroneous assumption. History is filled with accounts of dominant societies furthering their success by adopting innovative discoveries made by smaller societies. The adoption of Arabic numerals by countries that had previously used Roman numerals is a striking example of a dominant society integrating an innovation from a smaller society.

The challenge for an organization, then, isn’t so much how to be innovative, rather, how to better recognize and adopt innovations discovered elsewhere. More succinctly, how to better seek out and distinguish innovative solutions aligned with the organization’s strategy from those that simply rate high on the coolness scale.

False Barriers to Implementing Scrum – II

In a previous post, I described several barriers to implementing scrum. Recently, an additional example came to light similar to the mistake of elevating scrum or Agile to a philosophy.

In a conversation with a colleague, we were exploring ways on how we might drive interest for browsing the growing wealth of Agile related information being added to the company wiki.  It’s an impressive collection of experiences of how other teams have solved a wide array of interesting problems using Agile principles and practices. Knowing that we cannot personally attend to every need on every project team, we were talking through various ways to develop the capacity for exploration and self-education. I think I must have used the phrase “the information is out there and readily available” a couple of times to many because my colleague reacted to where I put the bar by comparing learning Agile to surgery.

Using the surgery metaphor, she pressed the comparison that all the information she needs about surgery is “out there and readily available” but even if she knew all that information she likely wouldn’t be a good surgeon. Fair point that experience and practice are important. And if that is the case, then everyone should be taking every opportunity they can to practice good agile rather than regressing to old habits.

More importantly, perhaps, is the misapplied metaphor. Practicing agile isn’t as complicated as surgery or rocket science or any other such endeavor that requires years of deep study and practice. Comparing it to something like that places the prospects of doing well in a short amount of time mentally beyond the reach of any potential practitioners.

Perhaps a better metaphor is the opening of a new rail line in the city. A good measure of effort needs to be expended to educate the public on the line’s availability, the schedules, how to purchase fares, where the connections are, what are the safety features, etc. Having done that, having “put the information out there where it is generally available,” it is a reasonable expectation that the public will make the effort to find it when they need it. It is unreasonable, and unscaleable, to build such a system and then expect that every passenger will be personally escorted from their front door to their seat on the train.

It is also interesting to consider what this does to the “empathy scale” when such an overextended metaphor is applied to efforts such as learning to practice Agile. If we frame learning Agile as similar to surgery then as people work to implement Agile are we more inclined to have an excessive amount of empathy for their struggles and be more accepting or accommodating of their short comings?

“Not to worry that you still don’t have a well formed product backlog. This is like surgery, after all.”

Are we as an organization and each of our employees better served by the application of a more appropriate metaphor, one that matches the skill and expectations of the task?

“We’ve provided instruction as to what a product backlog is and how to create one. We’ve guided you as you’ve practiced refining a product backlog. You know where to find suggestions for improving your skills for product backlog stewardship (wiki, books, colleagues, etc). Now role up your sleeves and do the work.”

Successful coaching for developing the ability in team members for actively seeking answers requires skillfully letting them struggle and fail in recoverable ways. It is possible to hold their hand too long. To use another metaphor, provide whatever guidance and instruction you need to so they know how to fish, then let them alone to practice casting their own line.


Photo credit: langll

Good Intentions, Bad Results

In The Logic of Failure, Dietrich Dörner makes the following observation:

In our political environment, it would seem, we are surrounded on all sides with good intentions. But the nurturing of good intentions is an utterly undemanding mental exercise, while drafting plans to realize those worthy goals is another matter. Moreover, it is far from clear whether “good intentions plus stupidity” or “evil intentions plus intelligence” have wrought more harm in the world. People with good intentions usually have few qualms about pursuing their goals. As a result, incompetence that would otherwise have remained harmless often becomes dangerous, especially as incompetent people with good intentions rarely suffer the qualms of conscience that sometimes inhibit the doings of competent people with bad intentions. The conviction that our intentions are unquestionably good may sanctify the most questionable means. (emphasis added, Kindle location 133)

That sounds about right. To this I would add that incompetent people with good intentions rarely suffer the consequences of imposing their good intentions on others.

The distinguishing feature of a competent individual with good intentions and an incompetent individual with good intentions is the ability to predict and understand the consequences of their actions. Not just the immediate consequences, but the long term consequences as well. The really competent individuals with good intentions will also have a grasp of the systemic effects of acting on their intentions. People with a systemic view of the situation are deliberate in their actions and less likely to act or react emotionally to circumstances. Doesn’t mean they will always get it right, but when they fall short they are also more likely to learn from the experience in useful ways.


Photo by Michael Dziedzic on Unsplash

Moving Past “I Don’t Know”

In 2015 I attended the Mile High Agile conference in Denver where Mike Cohn delivered the morning keynote address: “Let Go of Knowing: How Holding onto Views May Be Holding You Back.” As you might expect from a seasoned professional, it was an excellent presentation and very well received. A collection of 250+ scrum masters, product owners, and agile coaches is no stranger to mistakes, failures, and terrifying moments of doubt.

As valuable as the ideas in Cohn’s presentation are, I want to take them further. Not further into the value of keeping our sense of sureness somewhat relaxed, rather onto some thoughts about what’s next. After we’ve reached a place of acknowledging we don’t know something and are less sure then we were just a moment before, where do we go from there? It’s an important question, because if you don’t have an answer, you’re open to trouble.

The “I Don’t Know” Vacuum

Humans are wired to find meaning in almost every pattern they experience. The cognitive vacuum created by doubt and uncertainty is so strong it will cause seemingly rational people to grasp at the most untenable of straws. It’s a difficult path, but developing the skill for being comfortable with moments of doubt and uncertainty can lead to new insights and deeper understanding if we give our brains a little time to search and explore. Hanging out in a space of doubt and uncertainty may be fine for a little while, but it isn’t a wise place to build a home.

After acknowledging we don’t know something or that we’ve  been wrong in our thinking, it’s important to make sure the question “What’s next?” doesn’t go begging. I’d wager we’ve all had the dubious pleasure of discovering what we don’t know in full view of others and in those situations the answer to this question becomes critical. It may not need an immediate answer, but it does need an answer. If you don’t work to fill the vacuum left by “I don’t know” or “I was wrong,” someone else surely will and it may not move the conversation in the direction you intended.

The phenomenon works like this. Bob, a capable scrum master, ends up in a situation that reveals a lack of experience or understanding with the scrum framework and doesn’t know what to do. Alice, maybe immediately or maybe later, moves into the ambiguity, assumes control, and tells the team what should be done. If Alice is wise in the ways of agile, this could end well. If command-and-control is her modus operandi in the defence of silos and waterfall, it probably won’t.

So how can an agile practitioner prepare themselves to respond effectively in situations of doubt and uncertainty? Here are a few things that have worked for me.

Feynman-ize the Conversation

In his book “Surely You’re Joking , Mr. Feynman!,” Nobel physicist Richard Feynman tells a story from his early career where several building engineers started reviewing blueprints with him, thinking he knew how to read them. He didn’t. Having been surprised by being placed in a position of assumed expertise, Feynman improvised by pointing at a mysterious but ubiquitous symbol on the blueprint and asking, “What if that sticks?” The engineers studied the blueprint in light of Feynman’s question and realized the plans had a critical flaw in a system of safety valves.

That’s how to Feynman-ize a conversation. Start asking questions about things you don’t understand in a manner that challenges those around you to seek the answer you need. In essence, it expands the sphere of doubt and uncertainty to include others in the situation. This tactic is particularly effective in situations where corporate politics are strong. Bringing the whole team into the uncertainty space helps neutralize unhelpful behaviors and increase the probability the best answer for the moment will be found. It is no longer just you who doesn’t know. It’s us that that don’t know. That’s a bigger vacuum in search of an answer. In short order, it’s likely one will be pulled in.

The Solution Menu

Thinking of the agile practitioners in my professional circle, they are all adept at generating possibilities and searching their experience reservoir for answers based on similar circumstances. When the creative juices or flow of answers from the past are somewhat parched by the current challenge, it is natural to project the appearance of not knowing. Unless you’ve drawn a complete blank, you can still use the less-than-ideal options that came to mind.

“I can think of several possible solutions,” you might say. “But I’m not yet sure how they can be adapted to this challenge.” Then offer your short list of items for consideration. One of those menu choices might be the spark that inspires a team members to think of a better idea. Someone else may find an innovative combination of menu choices that gets to the heart of the issue. I’ve even had someone mishear one of my menu choices such that what they thought they heard turned out to be the more viable solution. This is just another way to leverage the power of everyone’s innate drive for finding meaning.

Design an Experiment

If there is a glove that fits the “I don’t know” hand, it’s experimentation. I suppose you could work to stretch the guessing glove over “I don’t know.” But if your team is aware that you don’t know something, it’s worse if they know you’re pretending that you do. Challenges and problems are the situation’s way of asking you questions. If the answers aren’t apparent, form a solution hypothesis, set up a simple test, and evaluate the results. And as the shampoo bottle says: lather, rinse, repeat until the problem is washed away. It’s another way to expand the sphere of uncertainty to include the whole team and increase the creative power brought to bear on the problem. If your shampoo bottle is this agile, I’ve every confidence you can be, too.

Now I’m curious. What has helped you move past “I don’t know?”

 

Image by Gerd Altmann from Pixabay

Cargo Cults in Management

 

I first read about cargo cults in Richard Feynman’s book, “Surely You’re Joking, Mr. Feynman.”

I think the educational and psychological studies I mentioned are examples of what I would like to call cargo cult science. In the South Seas there is a cargo cult of people. During the war they saw airplanes land with lots of good materials, and they want the same thing to happen now. So they’ve arranged to imitate things like runways, to put fires along the sides of the runways, to make a wooden hut for a man to sit in, with two wooden pieces on his head like headphones and bars of bamboo sticking out like antennas–he’s the controller–and they wait for the airplanes to land. They’re doing everything right. The form is perfect. It looks exactly the way it looked before. But it doesn’t work. No airplanes land. So I call these things cargo cult science, because they follow all the apparent precepts and forms of scientific investigation, but they’re missing something essential, because the planes don’t land. (p. 310-311)

I was a newly minted biochemist and Feynman’s unique perspective had a significant impact on my critical thinking skills. It established a “cargo cult” sensor in my brain. As my career developed and branched out into other areas of interest, the ubiquity of cargo cult thinking became apparent.

In the work place, “cargo cult” thinking may not necessarily be a bad thing. As a tool, it can be used as an “as if” frame for working out the solution to complex problems or gaining insight into black boxes. By assembling all the known and visible elements and arranging them to match the form as best as possible its easier to see what’s missing.

If an executive’s minions are behaving in a way that reflects his or her approach to management, is that a good thing? Here is where business leaders get into trouble. Are the executive’s minions imitating or implementing?

Less common, executives attempt to adopt practices that are successful at the knowledge worker level. About a decade ago I had worked to implement an Agile software development process with a small and highly capable development team. It was a daunting task: completely re-architect and develop a poorly coded application while supporting the old application. (In 30 years, this was the first and only time I recommended a complete redesign and rewrite of a major application.) Of course, we started each morning with a “daily scrum” meeting – sometimes called a “daily stand-up” – before the team set off to immerse themselves in code. These are very quick (15 minutes or less) meetings where everyone literally stands up for the duration of the meeting. The idea is that by standing, attendees are less likely to drone on about trivial matters or issues that do not require the entire team’s input. Complicated issues are quickly identified and scheduled for more detailed meetings, if necessary.

Six months into the project it was very clear our approach was working and insofar as the coding effort was concerned, we would be successful. The senior executive to this effort seemed impressed and decided to switch to a “stand-up” meeting format for the executive team meetings. They were “stand-up” meetings in name only. Rather than a once a week meeting that virtually always extended way beyond the originally scheduled 60 minutes, I now had to attend daily meetings that went on for 45-60 minutes during which nobody stood.

There were other issues with implementing the executive team scrum meetings. The senior executive did a poor job of modeling the behavior he sought and there was very little control over the clock. Developers are smart people and they notice things like this even though they are not directly participating. Among those being managed, it does little to inspire confidence in the management staff.

Nonetheless, I like the idea of applying Agile methodologies to management meetings. After action reports, as used by the military, would also help. There is also a place for storyboards and retrospectives. But implementing these and other elements would require a significant learning effort on the part of the management team. Not because the methods are difficult to understand, but because the MBA mindset of many management teams would have to loosen up a bit for the requisite unlearning to become possible.

Rethinking the idea of “management” in the context of Agile principles and practices blends quite nicely with many of the things I’ve learned around the idea of “Management as a Service.”

References

Feynman, R. P. (1985). “Surely you’re joking, Mr. Feynman!”: Adventures of a curious character. New York, NY: Bantam Books.


Image by Free-Photos from Pixabay

Expert 2.0

A common characteristic among exceptionally creative and innovative people is that they read outside their central field of expertise. Many of the solutions they find have their origins in the answers other people have found to problems in unrelated fields. Breakthrough ideas can happen when you adopt practices that are common in other fields. This is a foundational heuristic to open software development. Raymond (1999) observes:

Given a large enough beta-tester and co-developer base, almost every problem will be characterized quickly and the fix obvious to someone. Or, less formally, “Given enough eyeballs, all bugs are shallow.” I dub this “Linus’s Law.” (P. 41)

So named for Linus Torvalds, best known as the founder of the Linux operating system. In the case of the Linux operating system, no one developer can can have absolute expert knowledge of every line of code and how it interacts (or not) with every other line of code. But collectively a large pool of contributing developers can have absolute expert knowledge of the system. The odds are good that one of these contributors has the expertise to identify an issue in cases where all the other contributors may not understand that particular part of the system well enough to recognize it as the source of the agony.

This idea easily scales to include knowledge domains beyond software development. That is, solutions being found by people working outside the problem space or by people working within the problem space in possession of expertise and interests outside the problem space.

Imagine, around 1440, a gentleman from Verona named Luigi D’vino who makes fine wines for a living. And imagine a gentleman from Munich named Hans Münze who punches out coins for a living. Then imagine a guy who is familiar with the agricultural screw presses used by winemakers, has experience with blacksmithing, and knowledge of coin related metallurgy. Imagine this third gentleman figures out a way to combine these elements to invent “movable type.” This last guy actually existed in the form of Johannes Gutenberg.

 

Assuming D’vino and Münze were each experts in their problem space, they very likely found incremental innovations to their respective crafts. But Guttenberg’s interests ranged farther and as a consequence was able to envision an innovation that was truly revolutionary.

But if you, specifically, wish to make these types of connections and innovations, there has to be a there there for the “magic” to happen. Quality “thinking outside the box” doesn’t happen without a lot of prior preparation. You will need to know something about what’s outside the box. And note, there aren’t any limitations on what this “what” may be. The only requirement is that it has to be outside the current problem space. Even so, any such knowledge doesn’t guarantee that it will be useful. It only enhances the possibility for innovative thinking.

There is more that can be done to tune and develop innovative thinking skills. What Bock suggests touches on several fundamental principles to transfer of learning, the “magic” of innovative thinking, as defined by Haskell (2001, pp. 45-46).

  • Learners need to acquire a large primary knowledge base or high level of expertise in the area that transfer is required.
  • Some level of knowledge base in subjects outside the primary area is necessary for significant transfer.
  • An understanding of the history of the transfer area(s) is vital.

To summarize, in your field of interest you must be an expert of both technique and history (lest your “innovation” turn out to be just another re-invented wheel), and you must have a sufficiently deep knowledge base in the associated area of interested from which elements will be derived that contribute to the innovation.

References

Haskell, R. E. (2001). Transfer of learning: Cognition, instruction, and reasoning. San Diego, CA: Academic Press.

Raymond, E. S. (1999) The cathedral and the bazaar: Musings on Linux and open source by an accidental revolutionary. Sebastopol, CA: O’Reilly & Associates, Inc.

 

Image by István Kis from Pixabay

Drive for Teams

I recently re-read Daniel Pink’s book, “Drive: The Surprising Truth About What Motivates Us.” I read it when it was first published and I was still managing technical teams. Super brief summary: The central idea of the book is that people are mostly driven by intrinsic motivation based on three aspects:

  • Autonomy — The desire to be self directed.
  • Mastery — The urge to improve skills.
  • Purpose — The desire to engage with work that has meaning and purpose.

I find this holds true for individuals. However, when applied to teams optimizing for these three aspects can be problematic. If an individual on a team seeks to maximize autonomy, they are likely to come into conflict with the objectives of the team. For example, a software team that is tasked with developing a component that is expected to interact with several other components developed by other teams. If a single developer, in the interests of maximizing their individual autonomy, has decided to develop the component according to standards, design principles, and tools that are different from those of teammates and other teams (essentially, a local optimization,) then the result is likely to be sub-optimal overall.

Some individual autonomy must necessarily be sacrificed in the interests of effective collaboration. It’s possible, even desirable, that individual pursuits of mastery and purpose can be maintained. However, it may be necessary for an individual to focus on mundane tasks and the objectives of the team for periods of time. Finding ways to maintain a healthy balance between the intrinsic motivators and the purpose of the team is no small task and, when found, requires constant attention to maintain.

Perhaps it is possible to attach the team’s or organization’s purpose to the interests of the individual. Or sort for hiring people who have a personal purpose that is in-line with the organization’s purpose.

Image by M. Maggs from Pixabay