Locking Cadences to Optimize the Whole Scaled System – Not Really…

I had a reminder through some recent comments that people view locking cadences in step as a means for optimizing the whole of the system and not for individual teams (by allowing them to choose the cadences at which they wish to deliver).  this is used to justified in the case of when you have a need for a program.  I think this is missing the point, so I am going to go through some explanations.  I really like how Jurgen Appelo has applied David Snowden’s Cynefin framework to work systems so I am going to illustrate my rationale using some of his work.

So let us start with a team:

Programs_Explained_in_Mgmt3.0_speak-1Teams are simple to understand, predominantly because of their simple structure with few people; however they are  complex in nature because we are dealing with humans.  Sometimes we can’t even predict our own behavior, much less a whole team’s.  Next, let’s think of where most policies and processes wind up…Programs_Explained_in_Mgmt3.0_speak-2Good processes (and their accompanying policies), try to add order into systems; this is particularly true of many of the scaling systems out there (SAFe, DAD, to some degree LeSS) where structure and process is imposed on the ‘program’ system in order to achieve more predictability.  Unfortunately most of these are quite complicated in nature; some have helped by providing well diagrammed (some even animated) pictures, but there is still no denying the complicated nature of their arrangements to attempt to get predictability.

This is very well intentioned, yet what happens in reality is the following:

Programs_Explained_in_Mgmt3.0_speak-3The complicated-ordered process thrown on a simple-complex team yields a complicated-complex result.  This isn’t achieving what we wanted… and we’re just talking about a single team! And if we expand this to many teams such as we would have in a program, this is the best case we can hope to achieve.  It may become complicated and chaotic as the additive results yield less predictable results. Programs_Explained_in_Mgmt3.0_speak-4So why is this happening?

It’s because we humans create complex social systems.  There’s a reason why we value individuals and interactions over processes and tools; the latter can be complicated in nature perhaps and yet they are ordered in nature, while people systems can be either simple or complicated, yet are always at best complex.  People aren’t robots, so our behavior is never entirely predictable.

And yet… we try and put systems in place that have unintended consequences, such as imposing cadences on teams to get more order (predictability) out of them.  Think about the last time you had something forced on you that you disdained; it probably had you at best working at less than motivated – it sucked the motivation out of you, so you didn’t perform as predictably as desired. And at worst case, you went and found a new job and now the team was thrown into reforming and restorming to get back to renorming and performing.

Each team and its individuals will be different, perhaps some won’t care that much about the ‘normalization’ of cadence.  But some will have deep negative impacts that will occur.

So I ask you what ‘system’ are we trying to optimize? The process or the people?  Imposing a process to de-optimize how humans perform seems to me have many potential negative longterm effects; besides losing good people or demotivating people, even if this happens to only one team out of ten, it sends a signal that people don’t control their work system at all, that any element can be changed on a whim. Basically apply the pants principle and let teams adopt as simple a process as possible, including the orchestration.  As Saint-Exupery said, simplicity is not achieved by deciding on not when there is more to add, but deciding on when there is not more to take away.

Programs_Explained_in_Mgmt3.0_speak-6 Does this mean that locking cadences can’t ever be adopted? Not at all… Facilitate teams to select a good cadence within themselves firstand then collaborate with other teams to find how to best orchestrate delivery.  This may result in lockstep cadences or perhaps a creative branching and merging strategy. This could be done during team chartering by holding a futurespective. Regular intra-team retrospectives could help teams identify when changes need to occur. Simply installing a locked cadence at the beginning may result in a sub-optimal approach as it overlooks the people part of the equation.

The Dimensions of Choosing a Scaling Approach


From Issue 26 of Compute! magazine, July 1982

As many folks know, I have been exploring what scaling means in various discussions. I am no fan of the Scaled Agile Framework (SAFe); I got and let lapse my SAFe Agilist certification. I chose to get it mostly as it was offered to me at extremely low cost AND it allowed me to hear about what it was about straight from someone certified in it. I am not here to bash it though; it has its place. It’s not for EVERYWHERE you need to scale as it is portrayed though. This post will explore the scaling approaches available to you and when to apply them.

Let’s start with some “definition” of what is meant by scaling first…

Generally, when folks say they want to scale something, it means they want to expand its use or its capacity. So to now to fill in the ‘it’, to expand Agile’s use is to replicate Agile teams over more of the organization and to expand Agile’s capacity is to allow what is currently working to do more. These are different classes of needs. The act of replicating Agile teams (and more importantly its benefits) is solved by “scaling out” and requires thoughts on cultural change, choices of approaches and practices, and how these teams should be instantiated and organized. The act of expanding capacity of current Agile teams to accomplish more is “scaling up”. Here the choices are how to help existing teams work together effectively and gain more product throughput. The confusion on which of these apply stems from the fact that both expand overall organizational capacity.

So I’d like to provide a means for thinking along a couple of dimensions to determine which one applies as you decide to scale up. People in an organization may be choosing different approaches based on what their needs are at any one time, but I want folks to understand when and why to choose specific approaches. I plan to apply the Cynefin framework to classify problem spaces as simply a means of determining what types of approaches may be more effective. Lastly, I want this to focus on the end result of your organization’s value stream and what it needs, not on simply making choices for your organization in a vacuum.

To do this, let’s look at the following graph; it has two dimensions, both attribute of the end product lines of a value stream. I actually use the term product lines (could also be service lines) to indicate that these have an inter-relationship. So the vertical dimension is one of interdependency among products, which formulate a product line. Let’s take a concrete example: an Enterprise Resource Planning system. There is a core product and a set of product modules; this is a product line produced by a value stream. The company may have a different product line totally unrelated; say machinery control software used in factories that may be its own product line – the end result of a different value stream.

The second dimension is how responsive a value stream (and the products produced by it) may need to be to the market. (For organizations not driven by a market, say government agencies, replace market with mission.) As the market changes, so does the needs of the resulting products (or services) the organization is providing.


These two dimensions can define the ‘space’ for our organization’s business agility needs. So let’s explore this space now to understand how and when to apply scaling….

If our market (or mission) is slow to change (i.e. our demand for market responsiveness is low) AND we have few products with interdependencies, then we are in the Obvious domain (this used to be called the Simple domain in Cynefin terminology). In this space, we have a simple, stable product line. We are probably the market leaders with little competition to worry about. If this is our domain, we don’t need to worry about scaling; if we are transitioning to use Agile/Lean approaches, we are probably doing this to remain ahead of our competition as a proactive component in our strategy (or maybe we have always been Agile or Lean). The key here is few products and the need to respond to external market forces is low; our need for agility is low.

So what if the market is rapidly changing or the mission is rapidly evolving? Our need to respond is high… This is where start-ups generally find themselves; they are constantly reacting. This is the Chaotic domain. If our organizations are still exploring how to fit customer needs, there may be several competitors trying to do this as well. There are no market leaders yet. Or maybe we have a small product line and have found ourselves facing new and stiff competition. This demands agility, but not a need to scale as the product line inter-relatedness is low.

As the number of our product lines increases, so does our need to scale our Agile capacity. This may be able to first be accomplished by simply using some lightweight activities like a Scrum of Scrums to help coordinate interdependencies. Eventually though, we’ll need to think more formally about how we want to scale and when we look at interdependent product lines and whether a scale up or a scale out approach is more appropriate.

So let’s return where our now interdependent product lines have market stability; the demand to respond to market changes is low. The primary driver now for any agility is to coordinate product line activities together into cohesive releases. We may be a market leader across most, if not all, of the interdependent products that make up our line. A scale up approach can handle this need for cohesiveness via coordination. We can roll the products into a program and use it to coordinate activities, thus a hierarchical approach to organizing will work. Approaches like the Scaled Agile Framework (SAFe), Disciplined Agile Delivery (DAD), and the lesser-known Enterprise Agility framework can be applied. We can take time to analyze the situation and provide a means for gathering product needs and rolling them out to the product teams; this is the Complicated domain.

If the need to respond to the market though is high, each individual product (within the product line) needs to evolve fairly rapidly so that it can meet customer needs. This does not mean that there should not be some form of congruency among teams. Our scaling approach should be one of scaling out teams that are networked together to maintain this congruency; there needs to be allowable deviations so that we can keep pace with the market (or mission) needs. Each deviation needs evaluation to ensure this isn’t a new path for the entirety of the interdependent product line. This is where probe-sense-respond comes into play, the Complex domain.

One thing to remember here is that the organizational structure and its communication paths will create the coupling of the products. This is Conway’s Law. The result for most hierarchical approaches will have product lines that are tightly coupled, while for most networked organizations, loosely coupled product lines will result.

I’ll close this post with a final thought; regardless of the scaling need, who is choosing it? Is it your people in the organization or is it someone dictating how and when you need to scale? This is the difference I see happening is that people are not exploring how they themselves can scale, but they are being told how to do it. Use this as a tool to help your people figure out what will work for them…

ACC US Session: How to Practice Agile Scaling w/o a Condom: un-SAFe Agility

I held a provocatively titled session to explore some of the issues surrounding SAFe, DAD, and other Agile scaling frameworks that prescriptively define the structure in how they work.  I personally don’t feel it useful attacking frameworks, but understanding the context around them so that one can judge for themselves whether they will apply or not.  The path I took was to explore the problems, then the why we are scaling, then finally the assumptions these hierarchical and rigid frameworks make.  I did this through time boxed brain-writing portions and then discussion on the results.  This was to eliminate the possibility for undo influence between participants.

We had several people come and go, but my core group was Karen Spencer, Kristen Tavelli, Dave Rooney, Brett Palmer, Susan Strain, Diana Wiliams, Darren Terrell, Sameli Zeid, Patrick Wojtak, and myself of course.  Brett in particular stated he found the session useful; he had just completed his SPC and was struggling with some of the rationale behind how to apply it.

Problems created when introducing SAFe (or other hierarchical scaling approach)

The following are the problems folks have seen when implementing these hierarchical approaches. (NOTE: we are talking about actual implementations seen and/or the way the framework is being prescribed to apply.)

  • unknown needs for why certain measures or metrics are required – most of the metrics these frameworks seem to roll-up seem to be to ensure that the same items are measured across teams and not necessarily what may be needed for the individual team itself
  • these metrics also seem to be used to compare team performance in a negative manner (and thus lead to team’s gaming their metrics to keep from being viewed negatively)
  • it also seems to prescribe the same process across all teams (mostly around Scrum rituals)
  • often times the organization begins implementing SAFe without executive buy-in, in particular from the business side of the organization
  • it tends to make too many decisions upfront with the product management/program level making decisions around how work will be done and not just about the how, sometimes well before any team(s) will begin solving it
  • it also removes decisions from the team around cadences and architecture, and constrains what improvements or experiments a team may do
  • after getting agile teams to drop formal roles and promote T-shaped people (generalizing specialists); most of these frameworks and SAFe in particular, introduces unneeded roles again
  • SAFE seems to focus at driving a release (train – get that damn train off my runway says the aviator!) at the team level; they are still left to simply struggle on their own (in fact there seems no one that they can truly turn to for impediment removal either)
  • with all these new roles and early decisions, this introduces unneeded coordination overhead
  • it reintroduces big upfront requirements again, sometimes using lighter models, but sometimes favoring back towards heavier ones
  • it reinvents Gantt charts with post-its
  • for teams starting their implementation of this sort of framework, it begins to force common processes and tools onto teams that may have evolved to a different set
  • also when beginning implementation, there seems ot be a lack of communication to the teams why such changes are needed, it just begins to impose them without explaining the rationale behind them
  • and there may be some possible unsound assumptions being made as to the need to scale in the first place

Whew! That’s a lot of problems, but there must be a reason for scaling?

Why Are We Scaling? (What do organizations want…?)

So we turned our attention to why we are doing this in the first place.  Understanding the reason(s) may help us make more useful decisions on approaches and such.  Here’s our take on the why’s organizations we’ve encountered are doing so…

  • there’s a silver bullet mentality; there must be a one right way to getting consistent result from all teams
  • there is a desire to help large programs adopt Agile across the enterprise with an approach that can be easily visualized
  • the above two reasons also seem to be a means for simply trying to organize a large number of teams and the people within them
  • for programs with large technical products, it can help them coordinate their activities, dependencies, and constraints
  • there may be multiple teams with multiple dependencies
  • often ‘programs’ are defined by the organizational structure that already exists or the budget that is provided to fund the work (it’s easier to sell large programs for large budgets that will produce large benefits that than a collection of smaller products that may collectively and more loosely accomplish the same results)
  • there is a belief it will remove impediments more easily (remove an impediment for one team will remove it for all teams)
  • there is a desire on management’s part to see consistency and predictability across all teams
  • and lastly in many Agile approaches, middle managers don’t see where they fit; they feel a loss of power – these hierarchical approaches show where they retain power and control

In particular, we discussed how some of these desires to retain hierarchy for coordination produce results that follow Conway’s Law.  The resulting development may have rigid and brittle interfaces.

Underlying Assumptions

So lastly we turned our attention to the assumptions these approaches seem to be based on…

  •  belief that management has limited insight into what teams are doing; our discussion on this revealed two parts to this – management expects information to be pushed to them as opposed to pulling for it and secondly management has a belief all data coming to them should be identical for easy consumption
  • a fundamental belief that process is more important; essentially it is process that helps interactions between people
  • a belief that this is how one should scale/coordinate Scrum teams and not through simpler mechanisms such as Scrum of Scrums
  • along with the organization and budget above, BIG Budgets = Importance = Easy Approval over having to ponder each smaller need/budget request on its merit
  • that management believes they will be able to see better productivity and identify where teams need to improve their performance
  • there is a fundamental belief that all development work is the same and thus should follow the same process
  • it assumes that organizations will customize the approach and not adopt it as-is
  • for organizations where they have removed these roles, introducing new roles will be easy (or having people swap from one role to a new one will be easily done)
  • it assumes all teams can standardize on a cadence
  • it assumes we must manage complexity from a central location; I mentioned that a wonderful book that explores where complexity can be managed in a decentralized fashion is Organizing for Complexity by Niels Pflaeging
  • there is a belief that effectiveness is derived via consistency or that efficiency yields effectiveness (or that they are the same)
  • the trade space (trade-offs being made) between autonomy and measurement around effectiveness is (are) obvious
  • management should be able to continue as-is; as Agile moves out from teams, management should not be expected to change in its role
  • the architectural stuff that needs to be done does not equate to business value or is too hard to equate to business value, so we’ll manage it as separate items of work
  • and lastly hierarchies are a natural way for people to organize; people coming together for common purpose would naturally choose it as their preferred structure
  • one I mentioned at the end was that organizations (management) must start with an end structure in sight and that they don’t need to just evolve to a structure

Sameli also had an item that came up that organizations can easily change their structure to match what SAFe has.

I hope you found what we discussed useful and that it will help guide you in your decisions on whether SAFe is right for you and/or how to customize it.  Start with this latter assumptions part to help you avoid the problems that may arise, regardless of whether you use SAFe or a similar approach, how to customize it, or decide on another approach altogether.