Friday, January 31, 2020

Double Queues for faster Delivery

Is your organization constantly overburdened?
Do you have an endless list of tasks, and nothing seems to get finished? Are you unable to predict how long it will take for that freshly arriving work item to get done?
Here's a simple tip: Set up a "Waiting Queue" before you put anything into progress.

The Wait Queue

The idea is as simple as it is powerful:
By extending the WIP-constraint to the preparation queue, you have a fully controlled system where you can reliably measure lead time. Queuing discipline guarantees that as soon as something enters the system, we can use historic data to predict our expected delivery time.

This, in turn, allows us to set a proper SLA on our process in a very simple fashion: WIP in the system multiplied with average service time is when the average work item will be done.
This allows us to give a pretty good due date estimate on any item that crosses the system boundary.
Plus, it removes friction within the system.

Yes, Scrum does something like that

If you're familiar with Scrum, you'll say: "But that's exactly the Product Backlog!" - almost!
Scrum attempts to implement this "Waiting Queue" with the separation of the Sprint Backlog from the Product Backlog. While that is a pretty good mechanism to limit the WIP within the system, it means we're stuck with an SLA time of "1 Sprint" - not very useful when it comes to Production issues or for optimization!
By optimizing your Waiting Queue mechanics properly, you can reduce your replenishment rate to significantly below a day - which breaks the idea of "Sprint Planning" entirely: you become much more flexible, at no cost!

The Kanban Mechanics

Here's a causal loop model of what is happening:

Causal Loops

There are two causal loops in this model:

Clearing the Pipes

The first loop is negative reinforcement - moving items out of the system into the "Waiting Queue" in front of the system will accelerate the system! As odd as this may sound: keeping items out of the system as long as possible reduces their wait time!

As an illustration, think of the overcrowded restaurant - by reducing the amount of guests in the place and having them wait outside, the waiter can reach tables faster, there's less stress on the cook - which means you'll get your food faster than if you were standing between the tables, blocking the waiter's path!

Flushing Work

The second loop is positive reinforcement - reducing queues within the system reduces wait time within the system (which increases flow efficiency) - which in turn increases our ability to get stuff done - which reduces queues within the system.

How to Implement

This trick costs nothing, except having to adjust our own mental model about how we see the flow of work. You can implement it today without any actual cost in terms of reorganization, retraining, restructuring, reskilling - or whatever.
By then setting the work you permit within your system (department, team, product organization - whatever) to only what you can achieve in a reasonable period of time, you gain control over your throughput rate and will thus get much better predictability into forecasts of any type.

The above is just one of many powerful examples of how #TameFlow deals with our pre-conceived mental models in order to enable us to create better systems - at no cost, with no risk.

Tuesday, January 28, 2020

The six terminal diseases of the Agile Community

The "Manifesto for Agile Software Development" was written highly talented individuals seeking for "better ways of developing software and helping others do it." Today, "Agile" has become a 
playground for quacks of all sorts. While I am by no way saying that all agilists are like this, Agile's openness to "an infinite number of practices" has allowed really dangerous diseases to creep in. They devoid the movement of impact, dilute its meaning and will ultimately cause it to become entirely useless.

The six terminal diseases of "Agile"

In the past decade, I've seen six dangerous diseases creep into the working environment, proliferated and carried in through "Agile". Each of these diseases is dangerous to mental health, productivity and organizational survival:

Disease #1 - Infantilization of Work

"Hey, let's have some fun! Bring out the Nerf Guns! Let's give each other some Kudos cards for throwing out the trash - and don't forget to draw a cute little smilie face on the board when you've managed to complete a Task. And if y'all do great this week, we'll watch a Movie in the Office on Friday evening!" Nope. Professionals worth their salt do not go to work to do these things, and they don't want such distractions at work. They want to achieve significant outcomes, and they want to get better at doing what they do. Work should be about doing good work, and workers should be treated like adults, not like infants.
An agile working environment should let people focus on doing what they came for doing, and allow them to bring great results. While it's entirely fine to let people decide by themselves how they can perform best, bringing kindergarten to work and expecting people to join the merry crowd is a problem, not a solution!

Once we have mastered disease #1, we can introduce ...

Disease #2 - Idiocracy

Everything is easy. Everything can be learned by everyone in a couple days. Education, scholarism and expertise are worth nothing. Attend a training, read a blog article or do some Pairing - and you're an expert. There's a growing disdain for higher education, because if that PhD would mean anything, it'd only be that the person has got a "Fixed Mindset" and isn't a good cultural fit: Flexible knowledge workers can do the same job just as well, they'll just need a Sprint or two to get up to speed! 

And since we're dealing with idiots now, we can set the stage for the epic battle of ...

Disease #3 - Empiricism vs. Science

I've written about this many times - There's still something like science, and it beats empiricism hands down. We don't need to re-invent the Wheel. We know how certain things, like thermodynamics, electricity and data processing work. We don't need to iterate our way there to figure out how those things work in our specific context.

Empiricism is the idiocratic answer to ignorance, and it's increasingly replacing scientific  knowledge. Coaches don't just not point their teams to existing bodies of knowledge - they question scientifically valid practices with "Would you want to try something else, it might work even better?" The numbers don't mean anything - "In a VUCA world, we don't know until we tried." - so who needs science or scientifically proven methods? Science is just a conspiracy of people who are unwilling to adapt.

Which brings us into the glorious realm of ...

Disease #4 - Pseudoscience

There are a whole number of practices and ideas rejected by the scientific community, because they  have either failed to meet their burden of proof, or failed the test of scrutiny. Regardless, agile coaches and trainers "discover", modify - or even entirely re-invent these ideas and proclaim them as "agile practices" that are "at least worth trying". They add them into their coaching style or train others to use them. And so, these practices creep into Agile workplaces, get promoted as if they were scientifically valid, and further dilute the credibility and impact of methods that are scientifically valid.
NLP, MBTI and the law of attraction are just some of these practices growing an audience among agilists.

And what wouldn't be the next step if not ...

Disease #5 - Esoterics

Once we've got the office Feng Shui right, a Citrine crystal should be on your desk all the time to stimulate creativity and help your memory. Remember to do some Transcendental Meditation and invoke your Chakras. It will really boost your performance! If you have access to all these wonderful Agile Practices, your Agile Coach has truly done all they can!

(If you think I'm joking - you can find official, certified trainings that combine such practices with Agile Methods!)

Even though it's hard, we can still top this with ...

Disease #6 - Religion

I'll avoid the obvious self-entrapment of starting yet another discussion whether certain Agile approaches or the Agile Movement itself have already become a religion, and take it where it really hurts.
Some agile coaches use "Agile" approaches to promote their own religion - a blog article nominates their own deity as "The God of Agile" (which could be considered a rather harmless cases) - and some individuals are even bringing Mysticism, Spiritism, Animism or Shamanism into their trainings or coaching practice!

Religion is a personal thing. It's highly contentious. It doesn't help us in doing a better job, being more productive or solving meaningful problems. It simply has no place in the working environment.

The Cure

Each of these six diseases is dangerous, and in combination, their harmful effect grows exponentially. At best, consider yourself inoculated now and actively resist against letting anyone induce them into your workplace. At worst, your workplace has already contracted one or more of them.

Address them. Actively.

If you're a regular member (manager / developer etc.) of the organization that suffers from such diseases: figure out where it comes from and confront those who brought in the disease. Actively stop further contamination and start cleansing the infection from your organization.

If you're a Scrum Master or Coach and you think introducing these practices is the right thing to do: if this article doesn't make you rethink your course of action, for the best of your team: please pack your bags and get out! And no, this isn't personal - I'm not judging you as a person, just your practice.

Saturday, January 25, 2020

You shape culture - one way or the other!

Culture is the buzzword. Everyone wants a good company culture - but: how do we get that?
In complex cyber-social systems, cause and effect are often hard to separate.

The biggest problem with Culture: it's "self-healing". When someone behaves in ways that are not in line with the existing culture, that culture will "fix" the "problem" by removing the unexpected behaviour, either through assimilation (conforming the person exhibiting that behaviour to existing culture) or ostracization (eliminating the person exhibiting the behaviour from the system).

Hence, changing culture requires constant, active effort until the culture no longer responds to the change like the human body would respond to a disease.

Shaping signals

Culture is shaped through the signals sent by leaders. We can take any of the following stances on any given, newly arising or potential cultural element - which could be a behaviour, idea or even a mix thereof:

"This is not a problem" 

If the element is negative, the signal is: "You may continue". Culture is shaped to accept the element.
If the element is positive, the signal is: "It doesn't matter". It will only prevail if it doesn't conflict with an existing cultural element.

"This is a problem" 

The signal is: "You should not continue". Culture is shaped to eliminate the element.
Do this a few times to a positive element, and you can be certain that it will never pop up again.

"We are looking for this" 

If the element is negative, the signal is "The end justifies the means". Culture will shaped by those who benefit not only from this negative element, but also from other negative elements which generate similar outcomes.
If the element is positive, there's still going to be a struggle with incumbent negative cultural elements that conflict with the positive element: The message won't stick if clashing negative elements aren't actively discouraged and the positive element reinforced.

Mixed signals

If management is sending different signals on the same cultural element, this can quickly turn into an "Everything goes" mindset. People no longer care either way - which is absolutely fatal when positive cultural elements start to get ignored and people learn to take personal advantage from exploiting negative cultural elements.
Sending mixed signals is an absolute no-go: consistency is key!

Culture as a consequence of signals

Hence, to form a positive culture, top down leadership must actively and continuously take a stance:
- Reinforce positive elements
- Reject negative elements

Everything else will eventually breed cultural toxicity.

Feedback Culture

Management needs to respond to feedback, both directly and across hops.

No Feedback

The absence of feedback poses a huge risk that culture doesn't turn out as desired - at a minimum, it's already a sign that there's no sound level of transparency.

Conflicting Feedback

When there's conflicting feedback, there's a problem. And that needs to have a root cause, which needs to be explored. There must be a negative cultural element hidden somewhere causing clashes with the desired state.

Negative Feedback

When feedback is negative, then a stronger negative element is overriding the signals - and that element needs to become priority 1 focus.

Positive Feedback

If management receives positive feedback, that needs to be reinforced. The fly in the ointment: How do you know it's honest and unfiltered? Make sure that you hear what you need to hear, not what you want to hear!

Culture as a consequence of feedback

Leaders have the opportunity to deal with feedback in a number of ways. We need to be aware that our reception of feedback is as important in shaping a culture as the way we address the behaviour itself. The way we handle feedback either creates or breaks reinforcement loops.

Negative culture as a result of feedback handling

  • Entirely disregarding feedback encourages a "Free for All" culture where people do whatever suits them best and transparency gets lost.
  • Rejecting negative feedback will lead to confirmation bias, where leaders lose touch with reality.
  • Ignoring positive feedback may lead to an abolishment of existing progress as people learn "it's not that important".

Positive culture as a result of feedback handling

  • Acting upon mixed or negative feedback reinforces the idea that "someone cares", which will lead to more efforts put into improving the situation to open a way for the cultural element.
  • Acting upon positive feedback reinforces the cultural element itself.

Down the line

Pervasive top-down leadership is the key to shaping culture - because top management are the only people with the positional power to stop the proliferation of negative cultural elements and to anchor in positive cultural elements.

Top management sets the direction. Their sphere of control on the culture reaches exactly as far as their active involvement in culture. When managers inbetween send mixed or conflicting signals with the message from above, culture in their immediate sphere of control will adapt to their local influence.

Hence, it's essential for top management to ensure consistency of signals both with their immediate staff, as well as across the organization. They need to sense and respond to the signals sent by their staff on every level.

You can't not lead

"As an manager, can't I just remain neutral? I want my teams to self-organize and don't want to impose myself on them!"
The problem with neutrality is: we can't not communicate. 
Not actively acknowledging positive cultural elements sends the signal that these are not important - hence, that's actively "not shaping a positive culture".
The same goes for not actively rejecting negative cultural elements - which is actively "shaping a negative culture".

"Evil triumphs when good men do nothing" (Image source: AZ Quotes)

Make your choice - and take a stance!

Sunday, January 12, 2020

Teams: Slices, components, features - and false dichotomies

There's a massive confusion about what is a "feature team", what is a "component team" - and what is a good strategy to proceed. Consequently, many organizations follow the advice of "Agile Gurus" without reflecting on their reality. Let me bring a little bit of light into the topic.

The flawed model

You've probably seen this kind of model - the idea that "Cross-functional feature teams are able to deliver vertical slices of value". So, basically, you'd design a team where at least one team member can tick the box in each of the quadrants:

Does "Vertical slicing" mean you can do all  things on the horizontal domain on the vertical domain?
If you believe that this means you will have independent teams who can "deliver business value autonomously" - sorry to say, you've been taken for a ride! The mental model is flawed.

Here's why:
The model makes a massive assumption: that a "product" has only these dimensions. That may be a developer's (or IT person's) point of view. But - is that really true?

The hidden third dimension

Yeah, the Business - who cares about the business? Is that even important?
Yes - we forgot the business! There's a hidden third dimension in the model that adds another level of complexity. The response you'd elicit from a lawyer if you'd tell them that the Legal domain is "simple and easy to learn" would probably be quite interesting - the business domain is at least as complex as the technical domain - moreso when we're talking about international operations and get into multilateral agreements, cultural and language differences. Indeed, when we look at traditional sales organizations, we realize that just the single domain of sales often gets split across different lines.
Typical Sales splitting lines could be products, channels, markets or regions or customer segments. So, even each of the single business domains could turn out to have multiple sub-dimensions.

In large enterprises, the model is no longer two dimensional, "horizontal or vertical slices", it's multi-dimensional with a potentially incomprehensibly large amount of dimensions!
As such, we're not even making "slices" - the delivery of value would mean that we have to cut across n dimensions!

Defining your Product

Once we realize that we're crossing borders in more than two dimensions, we need to answer the question of "What is the product we're working on?"
Crossing what?
If we define "cross-functional team" as "a single team that can deliver end to end value", we need to be cross-functional in all dimensions!
Let me take, for example - a company that wants to add Widgets to their portfolio.
Widgets need to appear in search engines, on commercials, linked to the Online Shop so that people can buy them - Widget contracts need to be bullet proof both in procurement and fulfilment - Widgets need to get shipped to the buyers, who need to get charged correctly for their Widgets - have the amount collected from their account - and finally, customer service may need to settle disputes on Widget purchases. The simple "Widget" may thus require changes to a whole boatload of technical platforms, across a wide range of business processes - and there is no "end to end customer value" until all of these functions are implemented!

This, of course, begs the question:
Can a single team of developers manage all of this?
If the business processes, technology landscape and development processes are sufficiently simple, the answer may be "Yes".

And what if they aren't?
What if there are independent technical solutions for Online Shopping, retail, B2B sales, wholesale?
What if ERP doesn't happen in the CRM solution? And what if fulfilment is outsourced to a third party? All these conditions are normal in Large Enterprises.

Organizing Teams

Especially when transitioning towards an agile organization, it's important to accept current reality and learn to understand where we are, then move from there.
"You go to war with the army you have -
not with the one you'd wish to have at a later time."
- Donald Rumsfeld
Most traditional organizations are set up to optimize IT for utilization - that is, there are different departments, groups and teams to do fragmented work:

The Classic IT Model

Classic IT is typically specialized with "project groups" where an IT project manager oversees teams specialized in a subset of technical Engineering domains, and -depending on project size- also specialized in a subset of technologies.
These teams are cross-functional in no dimension and can not deliver "full slices" of anything. They do piecemeal work and depend on other teams for everything.

From here, we get into the question: "Which direction do we want to go?"

Cross-Functional Development Teams

Scrum, among other models, assumes cross-functional teams - but what Scrum actually means is "cross functional in engineering", that is - analysis, development, test, deployment and operation are done within the same team.
Re-organizing especially smaller projects into one or two cross-functional development teams who have full control over their development process "from requested to Done" across the entire project's tech stack is a simple exercise. Breaking the team boundaries also opens the door to DevOps and thus offers some performance benefits.

Technical Component Teams

The clarification of "technical component" is important for later - because there are also business components.
An alternative approach in highly fragmented organizations is to bring together teams that can do end-to-end work on technical components. Breaking the barriers between analysis, test and development for certain technologies (e.g., a Database) can already be a quantum leap forward.
The downside is that such technical component teams need to constantly communicate and synchronize with other technical component teams to deliver anything that works.

The reason why technical component teams might actually make sense: If we have monolithic components used by multiple business processes and other technical components, then we may have nobody except these component specialists who can actually work with this component.

An example would be a centralized Enterprise Database which serves as single source of truth for Campaign Management, Sales, Customer Service, ERP and Revenue Assurance.
Such components are a pain to work with, but if that's what you have - you need to work with it.
Typically, these technical components become the bottleneck in most development efforts, so regardless of the size of the technical component team, there will always be a lot of coordination, stress and blaming going on.

Business Component Teams

While certainly preferable to technical components, Business Components are the same as technical components, on a different level of abstraction: Consider, for example, an out-of-the-box CRM platform that serves as a central customer database, and provides a frontend for typical business user processes.
While IT may claim that this CRM is a "vertical slice" and "provides end to end customer value", this only works when we have an extremely narrow definition of "end to end", "customer" and "value".

A CRM company can create an entire business model out of providing a standard product with a standard User Interface and standard functions like "create user, administer account, CRUD customer, CRUD product, CRUD order" - so the CRM company can "provide end to end customer value" to their customers, that is, companies buying their solution.

The picture looks different when an enterprise buys the CRM solution and integrates it into their business landscape: a new product is configured in the Product Management Tool, product information is provided to the CRM via API, and the CRM has to offer business insight information via API to ERP, DWH - and even business partner platforms!
In this case, the entire CRM solution is merely a component of a larger ecosystem - making the CRM team not a product team, but a component team - by nothing other than a change of perspective!

End to End Value Delivery Teams

Is it feasible to simply assume that someone who was formerly a Java coding specialist for a CRM system to take coding responsibility for the python product management and ABAP ERP as well? That's not universal to answer - yet if the answer is "No", then having business component teams with end to end responsibility for a single component's stack and processes is probably already the limit.

Given this scenario, an "end to end value delivery team" would need the ability and expertise to work across a wide range of business processes, technologies and development functions. Using the initial 3D model, such a team doesn't deliver "vertical slices" - it serves "multidimensional cubes"!

While this may be a very fascinating perfection vision, when asking the question, "How do we work today - and how do we want to work tomorrow?" - most organizations are not even remotely at a level where it's a feasible option to immediately regroup into small teams that combine all development, technology and content expertise of the entire company!

The False Dichotomy of Feature Teams

Some agilists have very strong opinions about whether we should do "Feature Teams or Component Teams" - promoting the advantages of "feature teams" and listing the disadvantages of "component teams". Yet, when taking all the previous factors into play, we quickly realize that "feature team vs. component team" is a false dichotomy.

Cross-Functionality vs. Specialization

Feature Teams are Cross-Functional and Component Teams are specialized - that's easy to proclaim. What's assumed, yet never pronounced: "Feature Teams are cross-functional in development process and technology, but specialized in the business content domain."
If we look at development from different perspectives, the statement boils down to "feature teams are specialists from a business perspective - component teams are specialists from a technical perspective." Therefore, "teams are specialists" poses a false dichotomy. All teams specialize in something.

Component work vs. end-to-end customer value

Component Teams deliver piecemeal that needs to be integrated, whereas Feature Teams can deliver end-to-end customer value. Again, we have a hidden assumption: the "customer". If we consider "the customer" to be a project, then a database operations team can well claim to deliver end-to-end customer value: from installation over configuration to access management and service requests, the team does everything.

Would we agree that AWS is a component of software systems? As an Enterprise application developer, yes. As a member of Amazon, working in the AWS development unit, this component is the product! Does Amazon deliver a product with features - or are they delivering piecemeal that needs to be integrated?
We end up at the same problem as before: by assuming a different perspective, one person's "component team" may be another person's "end to end customer value delivery team". Therefore, "teams deliver end to end customer value" is yet another false dichotomy. Depending on how the customer is defined, all teams (or: no teams) deliver end-to-end customer value.

Levels of abstraction

Component Teams work only on a small portion of the Value Stream, whereas Feature Teams can deliver a Feature across the Value Stream. There's another hidden assumption: that the "Value Stream" is an absolute, and has only one definition.

Returning to our AWS example - the AWS platform is merely the technical platform of an Enterprise Platform. Suppose that Enterprise Platform spans a business process, then that platform is just a component of an Enterprise Process. And if that process is part of a Value Stream, then that process is again just a component. And that value stream may be a component of a Value Chain, ... again: component. And if that value chain is used by another company: again: component.

The bigger we perceive the system, everything we previously considered "end to end" becomes a component on the next level of abstraction. As the complexity of an Enterprise grows, there may be a myriad of abstraction layers. Eventually, it becomes impossible for any single person to even understand how many technical changes need to be made in order to provide "end to end customer value", or: vice versa - how much new "end to end customer value" can be generated by a single technical change.

Therefore: claiming that a team "delivers end to end customer value" poses even a second another false dichotomy: it assumes an organization without abstraction layers. Only when a single team has direct access both to the low-level tech stack of all components and the end customers of the value chain - only then will any team ever deliver end to end customer value.

Aligning mental models

In the dispute of "feature teams or component teams", we need to clarify some terminology, concepts and expectations - otherwise, we get nowhere.


We have explored in depth the different potential domains of specialization: development specialists, technology specialists - and content specialists. By now adding the question of abstraction layers, we need to also answer the question of layer specialization. The term "full stack developer" assumes a developer working on the tech stack of a single business platform - not a potentially infinite array of business platforms with a potentially infinite array of tech stacks. At some point, the "full stack developer" would become a "Master of (almost) none." - and whether they'd actually be a "Jack of all trades" becomes increasingly doubtful as the stack grows.
We need to agree on what we call "specialization" and in what context we expect "generalization", lest we're potentially talking about "being everything for everyone".

"We can't do everything for everyone everywhere, but we can do something for someone somewhere."
Richard L. Evans

End to End Work

When we talk about end-to-end, we have different concepts, and things become difficult from there.
A really obvious example is the difference in definitions of "lead time". Whereas the common Lean understanding is that it's the time between initiation and completion of a process - this gets defined differently. While most IT project managers would calculate "lead time" as the time between when a development project gets approved and closed, the book "Accelerate" defines "lead time" as the time between "code committed" and "code deployed on Production".
Returning from the specific idea of "lead time" - one person may define "end to end" as "from customer to customer", another as "from request to delivery", another as "from development to deployment", and yet another as "from build to production".
We need to agree on the definition of "end to end", to make any discussion around "end to end teams" meaningful.


We have already exhausted the subject of abstraction levels. While Software Vendors deliver certain Products, these products are just components of bigger enterprise architectures. Software Integrators do nothing other than customize and integrate one of more of these "products" into a software landscape. And even an entire array of vendor products, fully integrated into a business process - may be seen as but a component of a larger value stream.
It's irrelevant of how many layers of abstraction we have in an organization - everything one layer below is a "component". By adding one abstraction layer, every "product" turns into a "component".
We need to agree on the abstraction level we're talking about, otherwise every discussion around "component vs. product" is entirely futile.


I have painstakingly avoided the term "system" wherever possible here. The reason: everyone has a different understanding of what "The System" is supposed to be!
When we're talking about "The System", do we mean a piece of software? Do we mean the larger architectural context within which this piece of software operates, its integration context? Or do we mean the development organization developing (and integrating) said software? How about abstraction layers? How would "the system" look like at another abstraction layer?
It's common that a developer means "the piece of code that's running on a server" when they use the term "the system" - whereas a business user might consider a complex, b2b mesh of services encapsulated by a single frontend to be "the system". A systems thinker would abhor both ideas, and would equally include processes, rules and people into "the system".
We need to agree on a common understanding of "the system", lest different understandings generate confusion and misunderstanding.


When deciding whether a team is doing simple, complicated or complex work - we're quickly falling into the trap of category errors, because "complexity", like "end to end", depends on the domains we consider. Software development is pretty simple for a single piece of content and in a single technology. As we cross technology boundaries, a simple feature can quickly become a monstrosity of technical complexity - and as we cross content boundaries, possibly even organizational boundaries - even technically simple changes can become infinitely complex.
The problem: Until we have decided the dimensions in which we assume linearity and the dimensions in which we have variation, we do not understand how much complexity we're actually dealing with!
Whereas common sense dictates that "complexity" needs to consider all relevant dimensions, these dimensions can become infinite - making everything so complex that the very word becomes meaningless!
We need to agree to what we call "complexity" - and what we don't.

Bringing the right people together

After much philosophical ado, we can use all of the above to determine how to organize teams.

A team is able to work with minimal constraints if it is:
  1. Appropriately specialized, i.e. they don't rely on third parties for knowledge
  2. Doing end-to-end work, i.e. don't have handovers as part of their process
  3. Able to work on all relevant components, i.e. don't give or receive "orders" for component work
  4. Autonomous within the overarching System, i.e. team performance depends on the team and not outside factors.
  5. Feasibly complex, i.e. given the complexity of all relevant domains and the cumulative skills of all team members, there's a realistic learning curve
Will the outcome of these five factors be a "feature team" or a "component team"?
Back to square one - that's a false dichotomy. And it's the wrong question.
In most organizations, it will be a huge struggle and steep learning journey to form such teams, and it's entirely moot to discuss how we label them. 

Before even considering whether we should re-organize, we should ponder whether any of the above five factors is currently the hindering constraint in organizational performance.

If, instead of all of these, the performance constraint rests outside the current teams - for example, in policies and procedures, in politics or processes, in budget or timelines - then it's entirely irrelevant how teams are organized, as even the "ideal feature team" would still suffer from the same constraints.


The entire discussion of "feature teams or component teams" is a red herring.

Reorganizing teams is only relevant if it elevates the current constraint - and the question is not whether it should be a "proper Feature Team" or whether "component teams have dependencies". 
The right question is: "will the reorganization elevate the constraint on the current system?" - only if that is the case, then will the new team structure generate any better outcomes than the previous structure! 

Hence: Work on your systemic constraints. Bring those people together who can elevate the constraint. Just let people work until the team structure is the constraint! And don't assume it is until you have supporting evidence!

Thursday, January 2, 2020

10 signs you should fire your developers

Good developers are worth their weight in gold, and quite literally so. On the downside, bad software will eventually kill your business. In this article, I will describe - from a management perspectice - ten surefire signs that you're better off firing your developers than keeping them.

At the same time, if you're a developer and you see these signs in yourself or your coworkers, today may be a great day to hand in your two weeks' notice and find a proper developer job. You're doing yourself a favor by taking the first step!

The following list are epitomes of an organizational culture which will eventually result in a steaming pile of garbage that is both worthless and expensive rather than software which lets the company flourish. Systems generated in such a culture are parasites - they suck the very life essence out of everyone who has to deal with them, and the longer you let them fester, the bigger the problems will become.

Ten signs you should fire your developers

#1 - Working 9 to 5

Creative work can't be clocked. When developers always start at a fixed time and always drop the pen at the same fixed time, never taking work home, that's a huge red flag. Sometimes, the best ideas happen while jogging, under the shower or even while playing a game. Most work doesn't happen at work - solutions created exclusively on the clock just plain suck.

#2 - Copy Paste Solutions

Software development is creating new solutions and optimizing existing solutions. By copying and modifying the same thing all the time, complexity grows over time and simple changes eventually become extremely difficult. This way of working is unsustainable, and by the time this becomes obvious, it may be economically impossible to change course.

#3 - Need for supervision

Developers need to think by themselves. When developers only do what they have explicitly been assigned to do, only work when someone is checking on them and outcomes need to be monitored before they can be released, you have a serious problem.

#4 - Closed groups

The world is bigger than we think. When developers dig trenches to the business, can't even give you the name of a single user, much less having a professional relationship with any of them - how can they build the right product? A sense of "stranger danger" where developers perceive every new face as a threat means that they have already lost touch with reality.

#5 - One Trick Ponies

"If the only tool you know is a hammer, every problem looks like a nail".
When developers see technical diversity as a threat, can only work within a single paradigm and start to frame business problems in terms of what they know rather than expanding their knowledge to suit the business domain, you have the wrong people. Combined with a "my way or the highway" attitude, you can be certain that the money you sink into development exceeds the value generated.

#6 - Learning passivity

Knowledge work is all about knowledge. A continuous hunger for new knowledge allows developers to excel in their field. When developers resist new ideas, need to be told when they need to learn something new and shy away from experimenting, they lose their edge - and so does your software!

#7 - Limits to responsibility

Great people care for what they do, and want their work to make an impact. Statements like "Works as Designed", "Works as Requested", "Quality is a tester's job" or a pervasive mindset that users are just too stupid to use the software properly imply that developers have locked themselves into an ivory tower and try to shelter themselves from reality.

# 8 - Frameworks frame thoughts

If there were a standard framework for your business, someone else would be doing it better and cheaper than you could. Be very suspicious when the answer to every question is, "<this framework> can do it", especially when the solution always looks like the framework says it has to. Once developers have a standard of standards for developing new solutions, you know they're solving the wrong problems.

#9 - Enamored with code

Nobody cares what happens "under the hood", as long as the engine runs. When developers esteem good-looking code higher than the business utility of said code, they waste time and money. Combined with an attitude that the code would look much better if it wasn't for constantly changing business demands, you know that eventually, the house of cards will collapse - and your business might tumble down with it.

#10 - Caught in the past

The marginal value of every technology is Zero. Yesterday's great solution is often just barely useful today, and last decade's state of art is today's liability. If your newest technology is half a decade old, and the "never change a running system" mindset pervades the organization, you're riding a dead horse already. If on top of that, developers feel emotionally attached to "their baby" and aren't willing to let go, you'll be stuck between a rock and a hard place.

Toxic culture

Encouraging and reinforcing the behaviours above creates a devastating culture. If you encourage behaviours that fall into any of the above ten categories, you are creating a culture where high performance isn't even possible. You may likewise inadvertently be shaping culture by not stopping these behaviours, not calling them out or just tagging along with them. As such, it's always a people problem, that is - a problem created by management.
You can't close a blind eye to these. You have to call them out, you have stop them, and you have to actively work against them. There's a reason why people do these things - and rarely is the reason that people want to hurt the business or their own career. Explore the root cause, and eliminate it!

Organizations where development works as above are career dead ends. They take the purpose out of the work and make IT as a whole a massive liability. The faster developers leave such a place, the better it is for them. If they no longer have the will to take this step by themselves, do them a favor and help them move towards a better future.