Scaling Like Organic Systems

A System

A system – as we will define it – consumes resources and energy to produce something that is more than the sum of its parts. Not only does is produce value it does so in a way that sustains its own existence. If we consider Henry Ford’s early Model-T production system that assembled automobiles, the raw materials – rubber, coal, plastic, steel – were meaningless as an unformed heap. Along the way, the “intrinsic” economic value of the raw materials were destroyed and could no longer be sold for their original price as raw materials. At the time, there would have been no resale value for many of the assembly pieces, because Ford created an entirely new value network and disruptive business model to create a market that could properly assess the value of the non-luxury automobile. Yet, once assembled, the assembly line put these pieces together to create value greater than the sum of its parts.

An example of a relatively simple organic system is a single-celled organism like some species of Plankton our oceans. A plankton lacks sophisticated embryogenesis, there is no differentiation of multiple tissue types, no embedded systems, and no coordination mechanism across cells. Nevertheless, the simple biochemical processes and the internal workings that complete these processes have continued for billions of years by not only producing its own self-maintenance, but also by managing to reproduce. There is a surprising large amount of DNA for such a simple, small, organism – but why did this legacy of code begin amassing in the first place? Whether we venture to call it “divine” or not, there was certainly a spark of some kind that began an explosion that has yet to collapse back into chaos and the dark.

Even with these simple systems, where we can trace each exchange in the value-transformation process, including materials, structures, energy, and ecological context, the sum total of the Model T and the factory that produced it is more than its parts heaped separately in a pile. Our difficulty in understanding such systems is a problem of multi-fractal scaling. For now, let it suffice to say that making a variable in a system better may not result in a linear change in outcome.

 

A Complex System

We have major issues understanding how (or worse yet, why) a system consumes resources and energy to produce value in excess to the sum total of the elements and energy amassed in the absence of the system that produced it. This problem is only compounded when we begin embedding specialized sub-systems within an organism. In the example of an automobile factory, we could say that every cell of every person is a system, that each person is a system, and that each distinct functional area, separated by distance, is a system. The accounting and finance “system” and the inventory and assembly “system” must interplay as part of Ford Motors, a system in its own right.

So we can define a complex system as having embedded sub-systems, causing the observer to not only see that the whole is greater than the sum of its parts, but the observer may also slip into a “confusion of levels” if they attempt to manipulate a part of a system to shift the outcome of the whole. Worse yet, confusion of levels can have disastrous, non-linear results that are the opposite of the intended change due to confusion of cause and effect. When sub-systems are embedded within each other, their interrelationships may act on differing scales, either in time or place. So we must careful when attempting to improve a complex system. We must use empirical process control to chart the change in systems outcomes rather than simply optimizing subsystems in isolation.

 

Multi-Fractal Scaling

A fractal is a pattern that repeats self-similarly as it scales. One of the most common fractal scaling patterns in nature is branching. From the trunk of a tree, to major its major limbs, to twigs, and finally leaf structures, this fractal scaling pattern enables a lifetime of growth cycles. Leaves can bud purely based on opportunism, in a relatively disposable manner. This is because the tree, as a seed, has all the legacy of generations of trees locked inside it. The tree does not aspire to be “the perfect tree” or assume that it will grow in perfect sunlight, humidity, soil pH, and water availability. The tree does not get angry when a major branch is broken off in a storm or struck by lightning. Instead, its fractal scaling pattern is prepared for intense competition for sunlight in the sky and resources from the ground. The tree’s scaling pattern has risk mitigation “built in” because it grows the same in the middle of a field with frequent rain as it does in a dense forest.

We see this branching strategy throughout nature, from ferns to human blood vessels. However, an even more effective approach to self-similarity comes from multi-fractal scaling. The ability to adaptively select between more than one repeating pattern or differentiated patterns based on scale requires a different kind of fractal: time-cycle. It is not just the branches of a tree that result in an environment-agnostic strategy for growth, it is the adaptation to cyclical daily growth, scaled to cyclical annual growth, than scaled to multiple generations of trees that grow. This final step is an important one. Multi-fractal scaling is not only the source of novelty and adaptiveness “built in” for a single tree, it repeats at an even larger scale as a species competes for dominance of a forest. Multi-fractal scaling encourages “just enough” opportunism to enable small-scale experiments that can be forgotten without loss at a greater scale, or thrive when conditions change.

 

Adaptive Multi-Fractal Scaling

The strength of multi-fractal scaling, from branch to tree to forest, is its total reliance on empirical process control.  The legacy code is a confusing jumble of competing messages that a human mind, attempt to “engineer a perfect tree” would attempt to simplify and beautify. That legacy code, however, wasn’t written with any intention of crafting a perfect tree. That code was written to create a minimally viable reproductive system. It is built for one thing: continuous experimentation.

Continuous experimentation happens at each level of multi-fractal scaling, risking economics appropriate to its scale to find asymmetric payoffs. An Oak tree risks very little per leaf that grows over the entire course of its life. In a dense forest, however, that continuous experimentation of growing leaves higher and more broadly opportunistically based on local returns on investment can suddenly break through the forest canopy or unexpected fill the hole left by another tree’s broken limb. An Oak tree does not require centralized control of where leaves will grow or which limbs to invest in. Instead, the legacy of continuous experimentation enables multi-fractal scaling that competes locally and opportunistically.

Again, we do not need to understand what spark set this fire ablaze, we only need to see that it is still spreading and we are a part of it. Over-simplification of superficial outcomes will lead to poor decisions about inputs. Organic leadership relies on context, structure, and enablement of continuous experimentation. Organic leadership is a “pull” system that relies on scaling patterns for decentralized empirical process control. Artificial “push” systems force requirements and attempt to bandage the inevitable inefficiencies of a non-adaptive system.

 

A Complex Adaptive System

A complex adaptive system does not merely take in resources and energy to produce itself and reproduce itself as a unified “whole” that is greater than the sum of its parts. It does not merely embed subsystems with multi-fractal scaling and decentralized control. A complex adaptive system also operates with a continuous experimentation system built in to its normal framework of activities. When we make the leap from an Oak tree to the human body (or any other mammal on Earth), we can truly appreciate just how complicated it is to improve the health of an individual, or an entire population, when we observe the interrelationships of various physiological and socioeconomic systems and sub-systems. Creating lasting change is not only complicated in terms of finding the correct level and understanding the full ramifications across the entire system, each complex adaptive system is also continuously experimenting and will adjust against such changes based on short-run, local, decentralized opportunism.

To care for a complex adaptive system requires not only an understanding of inputs, processes, and outputs, but also the multi-fractal scaling of continuous experimentation that maintains long-run viability. When short-run economics are working against long-run viability, it is not sufficient to reward “correct” behavior to counteract short-run opportunism.  Instead, we must shift the context of local decisions so that short-run opportunism serves long-run viability.

Accidents Will Happen

Accidents may seem to the observer to be unintentional, but continuous experimentation is built to test the boundaries of success, to ensure that precise empirical process data is also accurate for the needs of viability. In other words, if you’ve ever accidentally tripped and fallen, or accidentally loosened your grip on an egg and dropped it on the kitchen floor, this was a natural element of complex adaptive systems quietly running experiments.

Embedded in our own human code, our sub-systems are all built for continuous experimentation as a method of calibrating precision to accuracy, using multi-fractal scaling on short, long-short, long, and distributed cycles. A short cycle is an immediate reference point for an event, using data held in working memory, and is reactive to immediate changes. A long-short cycle compares current data to immediately recognizable patterns of events, more embedded memory or conditioned responses that have proven useful over time even if we assume the event is an occasional outlier. More significant, painful events can skew our “normal” for decades and even become passed to the next generation as part of our genetic code. A long cycle has been stored to our genetic hard drive for future generations. A distributed cycle is a socioeconomic artifact that requires a medium of exchange and may last for centuries.

As humans, our multi-fractal scaling of continuous experimentation results in the creation of complex adaptive socioeconomic systems. Our legacy code drives us toward exchange, tooling, building, and reproduction because the experiments that are in motion are far from complete.

Like our occasional fumbles and falls, our social systems produce results that appear to be accidents with no guilty party, pure coincidences of circumstance, which occur due to failed experiments. Organic leadership harnesses this natural propensity for decentralized opportunistic experimentation by encouraging it but setting boundaries for it, feeding it but ensuring checks-and-balances from opposing interpretations, and guiding it by changing context and opportunity rather than directly managing outcomes.

Have you failed at dual-track Scrum?

Dual-track Scrum is a red flag that no part of your organization is practicing lean agility in any way shape or form. It preserves the transactional, finite, short-sighted project mindset.

Cadence improves internal signalling, but layering staggered cadences means you missed the underlying economic factors that make Scrum so effective. 

To be transformational – to dramatically shift your business model, disrupt your industry, or move to long-run economic optimization – requires an understanding of multi-fractal scaling and how time, distances, investment, and exchange differs based on their scale. 

For an in-depth look at time-cycle scaling in a typical digital value stream, check out my playlist on YouTube:

Time Cycle Scaling Economics

7 Simple Steps to Agile Transformation

I am never sure how to answer someone who says “What is agile?” After all, my mind is racing so fast that my ultimate, simple explanation – “A way to innovate and deliver products more effectively” leaves me wishing I could kidnap people for a 3-day course on lean-agile and continuous delivery.

What I can simplify (for someone who has a basic understanding of agile) are the steps in a true transformation, so that they can let me know where they are in the process.  Note that I have ordered these quite logically, while the real world is full of resistance, grey area, and co-evolution.

  1. Establish a cadence of synchronization (typically, this is scrum). Hypothesize the results of every change ahead of making it, test it, and validate or invalidate the hypothesis.  Inspect and adapt.
  2. Change from a human resource allocation mindset to a well-formed team mindset.
  3. Change from a finite project mindset to a living product mindset.
  4. Sell who you are, not what you plan to have on a shelf in X months.
  5. Change from a P&L and ROI mindset to an Economic Value Flow across the organization mindset (including upgrades in equipment, training for knowledge workers, benefits that raise barriers to exit).
  6. Change from centralized (top-down) market research, innovation planning, and risk assessment to distributed control over prudent risks.  This requires a framework for self-validation of discoveries, exploitation of opportunities, and communication of results.
  7. Change from performance tracking and formal leadership to systems optimization and organic leadership.

Hit Contact if you’d like to discuss your scenario or any of these points – I’m always available.

Two Weeks’ Notice Manifesto

This is My Manifesto

I have had a now-familiar conversation hundreds of times in my career in the software industry. A sharp, hard-working millennial – a developer, designer, consultant, or support engineer – is completely burned out. She sees no way to change her situation without starting over somewhere else and wants to personally let me know that she’s given her two weeks’ notice. The reasons are the similar to my own when I leave a job (or begin actively interviewing).

There is an over-arching struggle to find meaningful work, the ability to take pride in it, to feel that there is a purpose to what I do, and feel that there is a path toward mastery at something I can say “This is my art”.

“I’ll stand for nothing less, or never stand again.” – Chevelle

I have quit many jobs, with or without two full weeks of notice, been laid off twice, fired once (in college), and was kicked out of the Army – and I’m still early and what is a pretty successful career in technology. Since I’ve never even once written a letter of notice or resignation, I think it is about time I draft one.

More importantly, on behalf of talented Millennials everywhere, I’d like you to know – truly understand – that the two weeks’ notice we give you as a manager typically comes weeks or even months after we crafted our mental first draft, started accepting the relentless prospecting of talent scouts, and gave up on your ability to get out of way in our search for meaningful work, a purpose, and mastery of our craft.

So this is my universal – and truly honest – Two Weeks’ Notice, for every time I didn’t write one, and for the many times in my future I most likely also won’t write one. This is my Two Weeks’ Notice Manifesto, a public statement of what it takes to make me disengage despite my natural brilliance and indefatigable enthusiasm.

Money

You played hardball with my salary when I joined and have given me no path to increase it.

You are painfully arrogant – and ignorant – regarding my value in the open market.  It currently increases by 20% per year yet you think I will settle for a 5% raise (or no raise at all).

“Started from the bottom now we here.”

Proactive efforts on my part to establish clear expectations, a career path, and an informal timeline for promotion or salary increases are answered with vague notions of trust, respect, and reputation that have nothing to do with performance or the impact I have.

Most importantly, if I am giving you this notice, I have taken every opportunity available to add more economic value than you expected of me.  I have deliberately worked to increase the impact I have on value-add processes, organization-wide efficiency and effectiveness, revenue growth, and actionable metrics.  I can now see that I have exhausted my opportunities and my tangible impact on revenue and margin is now waning – removing all leverage and motivation on my part – and it is due to poor strategic decisions outside my control or that of peers.

I’m just tryna stay alive and take care of my people
And they don’t have no award for that […]
Shit don’t come with trophies, ain’t no envelopes to open
I just do it ’cause I’m ‘sposed to – Young Money, Drake

 

Growth

You treat my initial lack of understanding of the “nuance” of your backward, inefficient “processes” as some kind of failure or lack of intelligence on my part.

“A hater’s gonna hate, hate, hate, hate […] I’m just gonna shake it off.” – Taylor Swift

You provided no actual on-boarding, leaving me to my own volition to review artifacts, like some anthropologist, in an effort to mimic current practices.

You have truly valuable constructive criticism you could provide based on the decades of experience you have over me – but you prefer sarcasm, derisive rhetorical questions, and generally insult my intelligence.

You know that you – and the company – are terrible at on-boarding and that I am intelligent enough, educated enough, and experienced enough not to put up with it; so you give me preferential treatment to shut me up rather than investing in everyone.  And no, I do not take this as a sign I should stay, it is an indication that you have no plan for the future.

You have a general disbelief regarding the breadth and depth of my knowledge, skills, and experience – attempting to restrict me to the smallest possible scope of responsibilities.

Culture

You stomp out creativity and enthusiasm organization-wide but tell me not to “lose that energy”.

You are condescending and use sarcasm and deconstructionism when you do not understand my nomenclature or the vocabulary of my academic and career specialization.

 

You focus on short-term gains and their related vanity metrics (e.g. Project ROI) rather than the flow of long-term economic value

You have created a psychologically unsafe environment for the information worker, where most employees – the only employees who last – display symptoms of learned helplessness and defeat.

So I’m tearing this and everything else,
between me and what I want to do to pieces.
I’m tearing you and everything else,
between me and you to memory. – Nonpoint

Your “leadership” strips away all possible reward for prudent risk. Any feeling of accomplishment when someone takes real initiative to accomplish something meaningful in a novel way is more than negated by the likelihood of retroactive empowerment, personal insults, or deconstruction-based criticism.

Progress

You talk about “baby steps” in internal changes or excuse your inaction due to “lack of executive buy-in” to justify to yourself why you lack the discipline and initiative to change, innovate, or evolve.

“It could have been so much worse, but it should have been better”

– Five Finger Death Punch

You are stuck in old models of business and outdated practices despite the fact you would be a very late adopter of thoroughly proven best practices, no matter how many employees have attempted to convince you.

You fail to challenge me, heaping busy work on me instead.

You see my attempts to improve myself and my peers – in my pursuit of mastery in my craft and love of investment in my tribe – as a distraction that needs to be controlled rather than an opportunity to harness.

You assume my youth (and open-minded millennialism) generally decreases the value of my knowledge – despite the fact that the tech industry and its ever-evolving best demonstrated practices make my youth in advantage when

It’s not you, it’s me.

In light of these problems and a clear and consistent history of leadership anti-patterns, I can see that you will absolutely not change and will definitely make no effort to meaningfully address my concerns in any way. Unfortunately I have outgrown you. I am different and better than I was – smarter, stronger, more passionate and more creative than the day we met. I really do appreciate the rare moments of effort to invest in me as two humans at work, building something together. I have interesting stories tell. Some of my worst days and your worst behavior rank among the most beneficial insights I have gained – of who I will not be, of who I am, of what I will fight for.

It is time for me to move on.

This is ten percent luck, twenty percent skill
Fifteen percent concentrated power of will
Five percent pleasure, fifty percent pain
And a hundred percent reason to remember the name!  – Fort Minor

 

Do Project Tasks go in a Scrum Product Backlog?

I get this question frequently when training agile and scrum teams:

Do Project Tasks Belong in a Scrum Product Backlog?

YES.

Since answers to this question I have seen in chatrooms are typically insufficiently argued as part of a crazed political debate full of comments taken out of context, this very pragmatic question deserves a bigger picture answer – because the need to ask the question is a symptom of a stagnating transformation.

A successful shift from stage-gate or waterfall development processes to agile, Scrum, or Kanban requires a fundamental change organization-wide: from maximizing ROI and shareholder value to maximizing Economic Value Creation and sustainable competitive advantage. If this shift does not occur, the improvements gained from agile practices will inevitably stagnate.

Jez Humble refers to this state as Water-Scrum-Fall, that unfortunate state where most agile and DevOps initiatives plateau.

Most often when I talk to development teams, Product Owners, and ScrumMasters, this is often blamed on a lack of executive buy-in.

I completely disagree.  

I have also blamed a manager or two for the imperfections in the agility of a company, so I can relate to this view. To show you why you might not even want executive sponsorship, let’s revisit the view of a corporation as a minimum viable superorganism.

Complex Adaptive Systems Leadership

A corporation is not a machine with various parts to replace or maintain in isolation, it is a superorganism. It is a biological phenomenon that is not sufficiently explained by social contract theory or through monetary theories of motivation. Judgments about this reality are very easily clouded. Unfortunately, once measurement and monetary incentives change the natural behavior of the superorganism, it is difficult to change back – making it easy to fallaciously claim this as proof of their effectiveness.

Quantum physicists have suggested that undisturbed systems in the universe naturally stay in multiple states simultaneously, unless someone intervenes with a measurement device. Then all states collapse, except the one being measured. Perhaps what you measure is what you get. More likely, what you measure is all you get. What you don’t (or can’t) measure is lost.  – H. T. Johnson, “Lean Dilemma”

So when you hear “We need more buy-in from management” this is absolutely incorrect.  It is even counter-productive!  Adaptations by a complex system, that disruptive creativity and innovation agile champions desire, can only occur through organic, emergent leadership – a tribal, heretical rebellion. Adaption to a new stimulus may have a focal point, a “leader” who organically builds up energy in a new direction – but this leadership is an emergent property the complex system. In contrast, formal leadership (“management”) is a crystallization of a complex system, an attempt to reinforce a desired “normal state” – a force that exists counter to emergent leadership and adaptation. By default, formal leaders at all levels of an organism are incented (through power, money, and Agency Dilemma) to maintain homeostasis – i.e. the status quo. Even if a formal leader becomes the emergent leader of adaptation, this will be odds with her formal leadership. Unless she is willing to risk the loss of formal leadership, she will dissolve her capacity for emergent leadership and resume promotion of homeostasis – no matter how much it dampens creativity, innovation, and sustainable competitive advantage.

Evolution of a superorganism through disruption – whether a lean or digital or agile “transformation” – cannot occur if any one piece of the system is optimized in isolation from the whole because any superorganism, as a complex adaptive system, will exert tremendous energy to maintain homeostasis. The larger the superorganism, the more likely that optimization of one function or team will result in a net loss of desired adaptation (whether the desirable “adaptation” is called innovation, process improvement, or “growth”).

So, when a formal leader blesses a piloting of lean and agile practices by a completely isolated team, this is the superorganism equivalent of a mother’s amniotic sac – the team can establish itself as a unique complex adaptive system while in isolation, fed by the resources of the maternal superorganism but shielded from the homeostatic processes of the parent system. The moment this new team is re-integrated into the larger system, continued adaptation is unlikely. The company attempts to spread the innovation and creativity culture they achieved but instead can only formalize a shift in a subset of practices.  These practice, outside the context of psychological safety, a well-formed collaborative team, flop. No single activity of the pilot team will have the same value implemented outside the context of the pilot team’s “bubble” that safeguarded it against the homeostatic forces of the superorganism!

But wait – what about that “net loss” in innovation, creativity, and efficiency I claimed?

In practice, a company that adopts an agile process (let’s say Scrum) as a change in behaviors isolated to the teams developing software causes the rest of the system to expend energy maintaining homeostasis, and even more energy wasted by agents accommodating these homeostatic forces so that the development teams can preserve their no-longer organic place in the system.

I think you know exactly what that looks like:

  1. Updating documentation processes without seeing them as “artifacts” that emerge from an adaptive process rather than social contracts that require formal sign-off.
  2. Replacing one tool with another, causing a new set of employee workarounds to occur.
  3. Increasing frequency of software releases without changing the size of organization commitments.
  4. New meeting names that don’t change communication patterns or the homeostatic, status quo, “normal” flow of information.
  5. Continuous backlog decomposition as a manual transfer of a large-batch investment into small-batch development items.
  6. Oops! Another manual transfer at the end –  of small batch engineering back into large-batch approval processes.
  7. Changing job titles without addressing diffusion of responsibility and the lack of psychological safety inherent in the culture of the system.
  8. More overhead and forced “transparency” than if nothing had changed, through extra meetings, reports, metrics, and analysis, due to the natural distrust between formal leadership and emergent leadership, and the lack of trust in information flow between the homeostatic processes and the aberrant nomenclature of the development teams.

In the middle of all this, a large organization grabs their Project Managers and their Business Analysts, or anyone cheap who is around and doesn’t have the “status” a Product Manager, Director, or VP, and switches around their responsibilities to call them “Product Owners” and “Scrum Masters”.

What a debacle.

The newly-minted Product Owner receives Project Plans full of important tasks and milestones and big nasty Use Case document and an even bigger, unapproachable set of Technical Specifications – and is told to manage what the team delivers with User Stories.

Now in the midst of all this, should the Product Owner include Project Tasks in the Product Backlog?  Or to get down to brass tacks, could a task ever be a Product Backlog Items?

Absolutely!

But not all of them.

Some “Technical” Tasks (specifically not User Stories) are still Product Backlog Items

Technical tasks that create demonstrable economic value that the organization can capture, a known cost of delay, but are completely invisible to the user STILL NEED TO BE PRIORITIZED relative to other potential Product Backlog Items.

This, of course, is why the question of if these belong in the backlog is sign that a systemic shift in thinking has not occurred. If you are optimizing for project ROI, then these tasks just don’t have the marketable, monetizable potential of each Use Case. If you have a systems view of optimizing the flow of economic value creation, these tasks are judged relative to any other potential investment. Economic investment is continuous, the economic value created can be judged continuously, delivery and value capture is continuous, and you can prioritize based Weighted Shortest Job First or another collaborative decision making process about the of Cost of Delay.

“Artifact” Tasks are an Agile Anti-Pattern

There is, however, another kind of project task in Water-Scrum-Fall that SHOULD NOT be in any development team’s backlog: artifact tasks. These are things like “Complete wireframe for new home page” and “Document Social Integration for PokemonGo”. No matter how you small-batch these tasks, these are not Product Backlog Items. These are not even artifacts. Artifacts are the tangible leftovers of the creativity and innovation of a strong agile software team. A documentation, design, or planning task is antithetical to economic value flow. It is a trap. A box you put your money in and bury. It takes all the value-add, throws it in a pile, and lets it sit there, unused, as it become gradually less valuable.

This mini-waterfall process – this outrageous, lean-agile anti-pattern – surfaces in three ways, all of which I whole-heartedly reject and will actively undermine the capacity of others to pursue it in hopes that my heretical tribal rebelliousness will gain emergent leadership support:

  1. Business Kanban and Program Increment Planning tasks that lock up all creativity and innovation prior to the development team passively receiving instructions (as you see in shoddy implementations of the Scaled Agile Framework)? FAIL! TRY AGAIN!
  2. Tasks for non-developer “members” of the development teams completed as Sprint Backlog Items separate from the User Stories, thereby formally dividing cross-functional collaboration and preserving us-them Guilds (whether in dual-track Scrum or within even the shortest sprint)? FAIL! TRY AGAIN!
  3. Sub-tasks that formally divide up User Stories into function-specific tasks to complete? FAIL! TRY AGAIN!

These are all agile anti-patterns that prioritize tools, social contracts, and “process” over collaboration, communication, relationships, and creativity. You will never disrupt your organization, and your organization will never disrupt your industry, sorry.

“Milestone” Tasks are a Continuous Delivery Anti-Pattern

Since we started this asking if the BA / PM as PO ought to put Project Plan tasks into the Scrum Product Backlog, I’d hate to leave out “milestones”. Now you may say, “Andrew, that’s ridiculous, no one would treat a dependency as Product Backlog Item!” Indeed, ridiculous. But that’s the ultimate sign of your Continuous Delivery anti-pattern. Truly optimizing the flow of economic value creation across the entire complex adaptive system would completely remove “milestones” and “dependencies”. If you can’t get rid of Project Plans completely, and continuously deliver and validate Finished Story Benefits for ALL work that the organization takes from identified pain to economic value capture, whatever you started pursuing in your agile, or digital, or lean, or devops transformation, you’ve plateaued as a company.

And this is the really the paradox that made the lengthy description of complex adaptive systems leadership necessary. This hurdle is NOT something that “Needs executive buy-in.” This is something that is accomplished through outright insurgency, tribal heresy, and fait accompli rebellion.

That’s because Continuous Delivery takes more than agile ceremonies and user stories. It takes developers who are proud of knowing business context. It takes refactoring that no one approved. It takes a team move to Git from Subversion without telling anyone. It takes a handful of people setting up a Continuous Integration server no matter how often the nay-sayers tell them it’s useless. Continuous Delivery is a change in engineering practices and development culture that tend to happen without formal leaders needing to approve anything.

It just takes the right people having enough pride in being BETTER that they draw a line in the sand and defiantly announce “THIS IS OUR CRAFT!”

A Heartfelt Epilogue: Real Creativity, Innovation, and Disruption is MESSY

Now listen, human-to-human, if all you know about “agile” comes from that one book you read, YouTube, or a two-day certification, I won’t be surprised you’re thinking, “Wait, Andrew, that’s nothing like agile! How do I report you! How do I get you stripped of all your certifications?” That’s great. That reaction means I hit a nerve. Fantastic! Contact me and let’s talk about taking agility to the next level.

Truth is, I don’t look to my four certifications, five training course, three conference, my blog, OR EVEN my five years of attending, speaking at, and hosting MeetUp’s on agile as the proof of my legitimacy on these topics. I measure my expertise in the number of experiments, including the major failures I have been through with my development teams. The reason is simple: complex adaptive system leadership is an emergent property that require deep entanglement and shared experiences in the trenches. And, as it turns out, I’ve been in the thick of every kind of good or bad lean or agile possibility, trained people in that context, debated ferociously about it in multiple companies, and I have compromised my values or experimented with teams to directly challenge every single principle your little YouTube summary glossed over.

If at this point you think some teacher let me down and it’s a real shame, I’ll be happy to give you a recommended reading list and YouTube list and introduce you personally to other thought leaders that dive, like I just did, into the MUD of how you actually achieve: creative innovation, strategic and operational agility, and lean, continuous delivery of disruptive economic value.

Either way, reach out so real dialogue can get started.

Are Robots Stealing Our Jobs???

I interview people at all levels of an organization during a Digital Transformation. Since the business case for transformation assumes lean process improvements, I have two goals:
– Make the information that runs the business into data a computer can “understand”
– Replace the non-human, monotonous tasks related to information with computers

To give away the ending here – the robots aren’t taking over. When I am done, all the social context, human relationships, and important judgement calls are still human-made. What we change is how quickly the mundane data-massaging, tiring research, and waiting between email chains that delay all of those human decisions. So I have a goal when I start interviewing: remove inefficiencies and make existing workflows more scalable. This implies automation.

One key thing here: nothing your business does is just chaos. I absolutely spend more time convincing people that an algorithm can capture the complexity of what drives decisions than I do formulating the algorithm. No matter how loosely controlled or gut-feel driven the decisions are, once a business grows into the 100s of employees, I can represent most of your processes with an algorithm. I could even replace the important human decisions with another algorithm that would succeed within a reasonable margin of the average employee, but that’s too risky. Instead, we make notifications and intuitive user interfaces to let one person make the same important decisions 10x or 100x as efficiently, making everyone more scalable. Don’t lay people off. Make it easy for them to increase their value-add.

Interestingly, there is a powerful cultural influence in these conversations due to the mistaken belief that “automation” somehow equals “artificial intelligence” – when what it really means is “fairly basic math equations tied together into one big powerful formula”. The intelligence is completely human-created, human-programmed, and human-managed. So I inevitably but happily show it works prior to convincing someone it works, because depending on their place in the company, the idea of automation replacing humans can be an ideal direction loaded with false optimism or a terrifying slippery slope where unrealistic pessimism prevails.

Both cultural perspectives ultimately distort the conversation.

In its really old roots in the Toyota Production System, the introduction of an “ejector” was a huge benefit to the safety, well-being, and efficiency of a machine worker. Before the ejector, a worker would carry a part to a machine that had just finished its task on a previous part. The employee would put down the part they were carrying, take out the previous part, pick up the next part to put it in the machine, then pick up the previous part. With an ejector system, the machine gets the previous part out of the way so that the worker just walks up and loads the next part, then takes the previous one, checks it for quality, moves it along the line.

Think of all your manual spreadsheet updates, paperwork, phone calls, and email chains just like that. You’ll still check the output for quality before passing along information or making a decision, but automation, notifications, workflow rules, and algorithms can save you a fair amount of your pain by pushing or ejecting what you need when you need it (keeping it out of your way the rest of the time).

This makes the value-add or revenue potential of every existing Customer Service or Sales or Marketing employee scalable beyond what additional hiring can accomplish. Lean Process automation doesn’t mean replacing all operations with an AI. This is the foundation of “Autonomation” – where a worker no longer manually labors at one machine, but becomes a manager of multiple “machines” – multiplying the value-add per employee. Replace the painful, slow, or unnecessary steps with a computer, while keeping the human element – the important decisions, the social context, the gut feel, human.

“Digital Transformation” Beyond the Hype

Living in the tech implementation space, the most exciting moment in a “Digital Transformation” for me is near the beginning of any project or initiative.  It’s the moment someone who is integral to operations finally opens the 5″ binder that has been sitting on their desk untouched; and finding the information contained in the binder is fundamental to all company revenue.  Or it’s the moment the battle book comes out from the sales VP and the ensuing conversation shows – to the collective surprise of the rest of the participants – there is no standardized pricing, and no tracking of how prices get negotiated.  Or it’s that moment I find a clipboard and start asking about the origin, purpose, and destination of each form.

That’s the juicy part.

On factory tours, in “working sessions” and project kickoffs, or detailing the business logic for an implementation, this is the moment my work is no longer just “make it prettier and online” and the conversation starts driving an actual transformation – of the workplace experience and overarching business model – using “digital” technology.

The reason this moment is so exciting for me happens to also the answer to the question I’ve heard at more than one barbecue from an older neighbor – “And what exactly are you transforming?”

I think that’s a great question in retrospect.

What we are actually transforming is information.

  • We take the information created purely for human consumption;
  • We make it easy for “computers” to read it efficiently instead of humans;
  • We use “computers” to present the information more quickly to more people.

It’s that simple. 

Pragmatically, that’s the process that takes the hard-to-maintain spreadsheets that become binders or clipboard papers and transforms them into intuitive digital interfaces (they are also “online and pretty”). By simplifying all of that socially complex and context-dependent information into a flat table a computer can understand, you become free to add all of the social and contextual perspective in multiple ways later (channel and audience specific) instead of just one way forever (in that binder).

Your ROI is Total BS

ROI is meaningless.  GP% is meaningless.  Signups.  Clicks.  Views.  None of these tell you anything meaningful or actionable.  None of this ensures survival.  In fact, it is through sheer mass that some enterprises survive.  It is the churn of hype cycles and perceived value that keep new customers fooled.  But it is definitely not sustainable.  Big investments end with big blunders that result in mass layoffs and enormous bankruptcies.  The name is the only thing that survives. Is that the company you set out to build?  No.

Let’s assume you are a software company selling enterprise SAAS.  Your entire company is the value stream.  The ongoing operating costs are less than ongoing revenue.  Investing in the sustainability of your model of economic value creation and capture is every dollar you spend.  Those dollars, little by little, react with the market either creating or negating value creation.

The problem is that most enterprises work from the assumption that large investments equate with economies of scale.  While this may be true of investment in automated manufacturing there are no economies of scale in software development.  It is the individual knowledge workers that create innovative software.  The velocity with which you can adapt as a system combined with superior understanding of problem-solution fit in the market is the key to competitive advantage.

The question of how to invest should be quite simple when you are a large company that has revenue growing at the same rate as costs – small investments per opportunity with maximum ability to correct an incorrect investment.

That is enterprise agility.

Enterprise Agility is the speed at which an incorrect decision is recognized corrected.  The smaller the investment decision, the faster the return is known. Lean trims the excess weight, off-balance feedback, and poor technique that undermine agility.  The effective flow of information across the creative process of knowledge workers is essential.

This is where you must realize that unless you layoff staff, you’re investing the same amount continuously.  The ROI of a project is as meaningless as the ROI of a developer day.  The input of resources is relatively static, maximizing the value stream as a system is essential.

This is why the a right-place/right-time, brilliant, socially-savvy entrepreneur-engineer is the most agile and lean possibility: perfect and instantaneous knowledge-sharing internally (in the brain), distinct competitive advantage through the extremely unique skill set (s)he has grown to master.  That is the sprinter that you want your Superorganism to become.  In the right place, at the right time, with the correct knowledge and materials, with instantaneous information flow across the value stream.

So if ROI is meaningless to decisions (because we are paying for individual pursuit of knowledge-worker-creativity regardless of rate of return), how do we possibly make rational financial decisions about innovation, discovery and exploitation of economics rents?  In fact, lean manufacturing has studied this for decades.  When the rate of investment (the cost of production) is held constant, prioritization of economic value added rather than expected rate of return should be our focus.  In a zero-sum competitive game with uncertain returns and asymmetrical information, the time between investment and value capture is the only meaningful variable we can impact.  While cost of delay versus product lifetime return on investment may be more difficult to understand when looking at Toyota and the Prius, this is easy to see with Software as a Service, because the continuous addition of value in exchange for subscription-based fees creates two roughly stable lines. The only meaningful way to improve investment is to exploit information asymmetry more effectively than your competition.  Since you are investing the same amount continuously, you must minimize the cost of delay of value capture.

To put it another way: In a system with continuous investment, only the opportunity cost incurred due to delaying an investment matters. This is not first-mover advantage at the new product-market level, this most-effective exploiter of innovation as an a competitive advantage.  This requires a shift to systems thinking and investment in strength of culture. Money is not your scarcest resource. Brilliance-time (that you’re paying rent for daily) is your scarcest resource.  To maximize value capture, you must maximize the time spent in a state of market information asymmetry.  At the current pace of innovation and obsolescence, the only way to maximize value capture is to minimize cost of delay due to incorrect prioritization.

This implies three goals:

1 – Minimize the impact of an incorrect investment of system-brilliance-time by reducing size of each commitment

2 – Increase the adaptiveness of the system to maximize throughout and future adaptiveness

3 – Minimize the time it takes to receive feedback (primarily through analytics) from the market

4 – Make appropriate risk-taking and experimentation a normal part of every creative process

Enterprise Toxic Waste

In a complex adaptive system of knowledge workers, the ability of a group to creatively adapt to an external stimulus becomes impossible once all of the organization’s energy is expended on maintenance of internal homeostasis. To the extent that leadership is an emergent property of the system – in which an individual organically focuses collective energy into new adaptation in response to an external stimulus – it can distribute the pressure to innovate across the entire organization.  When all potential energy is focused on individual self-protection, emergent leadership is stifled. The superorganism “behaves” exactly as any evolving species “behaves” – when conditions are favorable, individuals focus resources into reproduction, increasing the likelihood of variation and aggregate potential for adaptation as a species.  When conditions are unfavorable, resources are dedicated to individual self-preservation, reproduction is reduced, and the species is “culled” leaving only the adaptations that best fit the pressures of the current unfavorable context.  This ebb and flow of creativity and narrowing is seen within the organism as well: in favorable conditions, the cells work toward reproduction, maintaining the health of the system (the body) while in unfavorable conditions the individual cell maximizes its own self-preservation to the detriment of the body (cancer).

“Tech” – currently represented by software, apps, and the web, thrive on innovation and disruption.  The industry as well as organizations attempting to compete through innovation is driven by the desire to maintain a continuous state of innovation at the superorganism  level; instead, most superorganisms (companies, the enterprise) even in the software industry remain cancerous, slowed to a near-death state, presenting painful symptoms far removed from the root cause of dysfunction.

This wasted potential for innovation, sustainable competitive advantage, minimum viability, and adaptive survival is not the fault of any individual and is not strictly caused by the official mission or formal structure of the organization.  This is a cultural issue, not a policy issue.

The formal leaders of a complex system, the managers and executives who are synthetically, socio-contractually positioned to act as the official drivers of innovation (or “vision” or “strategy”) for the organization cannot bureaucratically force creativity and adaptation, as these must emerge organically from favorable conditions across the whole.  Often the formal leaders are charged with being the exclusive source of adaptive creativity despite the fact they are typically in the worst position possible far removed from the external stimulus – to be relied upon for the emergent leadership that drives innovative adaptation.  The inherent waste then is two-fold: the official manager is unlikely to consistently display emergent leadership while the presence of a formalized leader prevents others from organically emerging.  Whether the creative adaptation desired by a manager is valuable and likely to succeed or not, the manager must  force action against the system, as a toxin, a betrayal of the natural state of the system.  In response, the complex adaptive system protects itself against the likelihood of a failed adaptation through cancerous self-preservation of maladaptive patterns.

Unfortunately, if this continues in the context of increasing demand, the growth to supply it exacerbates the likelihood of failed formal leadership and the need for individual or self-preservation.  The waste only grows.  To counter the failure of fewer, more detached formal leaders, the existing formal leaders of many organizations continue to add formal layers in hopes that elevating “high-performers” to official power can mitigate the systemic failure to adapt properly.  This is problematic because the optimization of formal management further decreases the likelihood that any enmeshed individual could organically emerge to lead systems adaption – every individual is progressively more disconnected from the system as a whole.  Silos arise, stage-gate processes are crystallized, and creativity – without needing to be actively stifled – is now unlikely to impact the system as a whole.

Before we move on, promise me you understand:  lean does not mean layoffs.  Toyota’s dedication to the individual on the factory floor is central to its success.  If you try to mimic their process improvement, focus exclusively on eliminating waste, and then cut staff to save money, you’re doing it wrong.  That’s a huge leadership failure. Hacking off a portion of a complex adaptive system will direct any energy gained from increased efficiency toward self-protection.  It is never worth it.

Game Theory shows us that the best way to build sustainable competitive advantage is to invest in resources that create and maximize information asymmetry against our competitors.  On the other hand, we must also raise barriers to exit and increase switching costs for our scarcest resources, people. The more scarce, unique, and hard-to-steal your people are, the more defensible your unique value proposition and the higher your economic rents.  This requires a culture in which the individual has psychological safety in which to take prudent risks.  Trust – the kind that is earned through time in battle together – really trusting in peers, superiors, and subordinates is essential. The individual must be invested in and given the resources necessary for their pursuit of mastery, autonomy, and purpose.  Only then can teams organically self-organize around new forms of adaptation.

Inside that organization, you need the opposite conditions compared to the outward-facing competitive landscape in order to maintain margins and economic value captured.  Maximizing market information asymmetry requires close to perfect internal symmetry of knowledge – in other words, alignment.  Real alignment of understanding of the problem, the objective, and the acceptable risks in pursuit of a solution.  You need continuous throughput that maximizes value add and minimizes waste.  You need low barriers to meaning and purpose and high barriers to exit.  You need slack and creativity.  You need to encourage the tension and paradox and dissent that creates new ideas, while ensuring the organization as a whole is respect-based and disciplined about change.

In Lean we call this Minimum Viable Product. The “product” that must be minimally viable is not a product on the shelf that a consumer buys. The “product” is the sustainable business model that creates economic value that can be captured.   Whether there is one product for sale or hundreds, built by 15 people or 5,000, the minimum viable product is minimal if all consumers receive more economic value than their transaction cost at a price that is great than the cost of production; it is viable if there are enough consumers and enough demand to make the business model of production sustainable.

Seen in this way, the upgrading of any resource across the value stream to maximize minimum viable production should be considered as part of a single improvement roadmap, regardless of its handling by accounting “on the books” – whether it is an enhancement to a software product, brand recognition, acquisition of a competitor to gain market share, or training developers on a new programming language or delivery methodology.  In the end, all of these initiatives are the investment of capital for the purpose of economic value creation protected from competitive influences through creation and protection of unfair advantage.

This is critical – and why vanity metrics are so dangerous.  Even a very unhealthy, unsustainable company can create conditions of information asymmetry that protect its existence in the near-term, but touting a graph that shows increasing revenue, increasing company size, and increasing market share / number of customers does not paint a sufficient picture of the sustainability of the business model.  These numbers are a given. When they aren’t, companies love to find some other numbers that comfort them instead.

What a toxic, carcinogenic waste.

DevOps Athleticism

Let’s face it – being small makes it look easy to be nimble.  Look at your average kindergartener: they may not always be graceful, but their capacity for unexpected action or a rapid spontaneous change in direction at full speed is frequently mind-blowing (for each of mine, it was usually a sudden jump into the risk of oncoming traffic).

So it’s understandable for the established enterprise to look at the youth (and occasional hyperactivity) of startups – and small companies who never grew up – and feel a little fat, a little old, a little bit brittle.

That metaphor doesn’t need to end there, though, because there are also large companies maintaining a portfolio that balances finding new opportunities on the one hand and exploiting new opportunities on the other.  These are two very different operations, though, and companies find balance difficult.  Just like hyperactivity is internalized in the executive function of adults who had physically hyperactive childhoods, that rebellious startup creativity can survive unscathed within the mature organization. By doing so, you can simultaneously continue category-killing through innovation despite staying the course and reaping decades of fruits on already-mature markets and products.

Likewise, to extend the agility metaphor, life is full of athletes in the top quartile of height and body mass index. They top the BMI charts compared to average scrawny-but-chubby adults despite doing it with rather lean body composition.  They are practically outliers, and definitely don’t fit the “standards” set by statistical BMI.  More importantly these individuals put “nimbleness” to shame; and just look at those kindergarteners revere them. Look at the heroes of the NFL: agility doesn’t begin to describe their mastery of movement.  Look at star hockey players in the NHL: they move with the power of an elephant, the stamina of a gazelle, and the grace of a ballerina.  The stereotypical Hollywood karate master black belt may have a very thick, potbelly body-type, but the master needs very little movement, in just the right places at just the right time, to send an opponent flying.

So it’s simplistic at best to “think like the startups” or “be more agile”.  You cannot transplant a culture.  Size alone is not their advantage, strength alone is not their advantage, tenacity alone – as much we love a good underdog story – is not their advantage.  To emulate any ONE  attribute of the lean-agile startup on the rise is foolish.

Stop talking about enterprise at-scale agility like you’re trying to be that kindergartener veering into the street unexpectedly. 

It’s more than being lean, or gaining experience or agility. At scale you need to build repertoire of enterprise-grade DevOps Athleticism!  It’s one thing to have an impressive vertical jump but quite another to jump over a fence, hurdle over a tackling safety, or parkour up a building,

Training for Obstacles

For the support engineer team, kanban looks a lot like an Olympic marathon team.  You constrain WIP (focus/movement pattern), create a sustainable pace, and fuel as you go – you train for the long haul by (basically always) running for distance.  It may be fragile spaghetti code built over the decades, but you your crack team knows it inside out.  But that’s not the majority of your at-scale enterprise.  As you get further from a continuous flow of relatively similar requests and move toward innovation and greenfield disruption efforts, kanban and even scrum are going to fail unless you include the assumption of uncertainty and churn in your overarching process.

This is like the difference between a New York marathon versus Tough Mudder or another obstacle-rich competition.  If you don’t build your capacity for speed-strength and coordination against unexpected obstacles, you’re likely fall short. The long and short of it is, if you can count on a marathon, kanban your way to glory.  If unpredictable obstacles and risk-taking for glory are fundamental, stop whining and start training. Look for extra opportunities to beat down tough challenges instead insisting on a slow and steady pace.  Speed and sustainability need to be loosely coupled in a strong DevOps process.

Jumping the Fence

I can tell you from experience that maximizing raw strength in the barbell squat does not correlate to jumping higher.  If you need to jump higher to make a layup, you do things like box jumps.  If your really daring, leverage your box jump into jumping over a 3-4′ fence (or hurdle) from a standing position.  Raw strength on the one hand and sprint speed on the other don’t give you the actual agility, coordination, and explosive power you’d need.

Similarly, coordination of multiple teams is more complex than strengthening, quickening, or improving communication with each team individually.  Establishing a cadence of synchronization and opportunities for cross-pollination of ideas – even as you increase the independence of each team  

This extended metaphor has a great caveat – go find a 3’ tall picket fence, stand in front of it, and try to jump over.  Assuming you haven’t been practicing, I bet your body stops you.  The same is true of a healthy DevOps system – when you try to launch into a painful bout of stupidity, the developers stop you.  If you’re smart, you don’t force yourself into a giant failure.  Instead, you practice a bit and ramp up your agility to get your entire body confident you won’t end up in the hospital.

Throwing a Punch

You don’t throw a punch with your arm.  You throw it from the ground up, leveraging the perfect twisting launch of one square inch of fist powered by your entire body.  If you’re the square inch that gets to land the winning knock-out blow, don’t get cocky.  You’d be nothing without the support and power of the entire body.