Here’s my shot at comparing the two currently most popular frameworks for large-scale agile, SAFe and LeSS. Looking beneath the surface, how do they differ?
(updated 2022-05-24)

– Agile, Scrum, xP, Kanban, Lean: the same elephant, different points of view
-Ron Jeffries 

Having looked at the R&D scene since 1999, I’ve worked with many organizations which have tried to adopt some form of multi-team agile with planning horizons beyond the next two weeks. I was also, back in 2001, one of the authors of the first framework that attempted to capture elements common to lightweight methods – as they were called before the second and more famous Snowbird meeting.

More recently,  I’ve been stymied how many evangelists who teach scaling agile tend to ignore, or at least disregard, the existence of “the other frameworks”.

When asked to compare, most proponents mostly say that they don’t know much of ”the other ones”. Or, they simply refuse to do an analysis of the similarities and differences of the frameworks as the other ones are “something completely different” (although nowadays exceptions of a reasonable quality do exist, such as this, this, this, this and that post/podcast). 

In 2018, I had the chance to obtain both the SAFe Program Consultant as well as the LeSS Practitioner certificates. After having conducted some two-digit number trainings of Leading SAFe and the SAFe Product Owner/Product Manager courses, as well as putting together a non-framework -based product owner training of my own I’ve started to get an eerie feeling.

SAFe and LeSS actually are quite close to each other. At least in terms of essence, if not in terms of emphasis, presentation, and packaging.

To me it seems the stances are a bit like in the case of Scrum versus Kanban in the 2000’s – a silly thing already then – being brought back to the present. And funnily enough, the discussion of Kanban vs. Scrum is still ongoing, though it’s mostly carried on by tool vendors, PMI folks and those practitioners whose understanding of both Scrum and Kanban is a bit off.

Perhaps, if there’s a wall between the frameworks, it has risen as a side-effect of the commercial aspects, misunderstandings, and a tad of ethical dissonance?

In any case, the prevailing dichotomy does little to serve the industry. And based on what history teaches us, it is not going to be dismantled any time soon – unless we who are less vested in a particular framework take action.

A comparison of SAFe and LeSS

So, enter my version of the comparison!

Yes, there are other comparisons out there, better, worse, list-like and those which are a nice read but remain on a superficial level (another recent example of that here). But simply saying for example that “LeSS has no portfolio management” does not quite hit the mark. There are deeper aspects and differences – as well as essential similarities – which deserve attention.

Before delving deeper, let’s first look at the ‘why’ behind both of the frameworks’ existence.

As put forward by Scaled Agile Inc.’s president (2019) Chris James, SAFe’s approach is to collect all “proven good practices and patterns” and from there you can “tailor down according to your needs”.

In turn, according to the co-creator of LeSS Bas Vodde, LeSS attempts to offer “a barely sufficient” methodology and suggests to build up your methodology, as, quoting Barry Boehm,  “tailoring down does not work in practice”.

In the sections below I’ve compared and contrasted some aspects in SAFe and LeSS. I have attempted to focus on the most interesting ones, as a run-through of all the elements in SAFe and reciting that ”LeSS does not contain such a thing but of course you could add it” would hardly be meaningful.

In particular, I’ve discussed:

• Principles
• Organization design
• Team and organization size
• Adoption steps
• Cadence
• Requirement meta-model
• Content management
• Cross-team coordination, and
• Portfolio management

If you’re curious about a particular aspect I have not addressed, feel free to reach out and I’ll try to add, or at least share some comment about it.

Principles

SAFe: Take an economic view; Apply systems thinking; Assume variability, preserve options; Build incrementally with fast, integrated learning cycles; Base milestones on objective evaluation of working systems; Visualize and limit WiP, reduce batch sizes and manage queue lengths; Apply cadence, synchronize with cross-domain planning; Unlock the intrinsic motivation of knowledge workers; Decentralize decision-making, Organize around value

LeSS: LeSS is Scrum; Empirical process control; Transparency; More with less; Whole-product focus; Customer-centric; Continuous improvement towards perfection; Systems thinking; Lean thinking; Queuing theory

SAFe’s principles are largely based on Don Reinertsen’s book on product development flow. Still, the principles of both of the frameworks, with the exception of “LeSS is Scrum” and “More with less” seem – at least to me – essentially the same, with SAFe’s version being more verbose.  

The main difference seems to be that two of LeSS’s principles – whole-product focus and customer-centricity – are explicitly concerned with organizing around customer value. SAFe’s principles nowadays contain that as well, but before SAFe version 4, it could not have been discerned by just looking at the “headlines”.

Organization design

SAFe: Mapping the value streams and identifying Agile Release Trains

LeSS: Identifying product owners and restructuring the organization into feature teams.

SAFe implies organizing around customer value delivery. However, SAFe remains somewhat implicit about this. For example, there’s no mention of feature teams in the big picture, and one can find material which describes trains organized around subsystems as “architecturally robust”, adding that in such a case “there will be many dependencies and lots of Work-in-Progress”.

Interestingly enough, rather many SAFe adoptions I’ve seen have ’agile release trains’ organized around subsystems and are incapable of releasing to production.

I had a chat about this with a Certified SAFe Program Coach Trainer who at the time was employed at Scaled Agile Inc. Like I had suspected, the idea behind this rather ambivalent stance is to get a foot into the door in order to start helping organizations at the level where they currently are. 

While SAFe’s material on value streams is still at points slightly superficial, these concepts from lean were first presented in the context of software development in books by Mary and Tom Poppendieck and you can read more about them there.

LeSS emphasises the importance of changing the structure of the organization into feature teams and eliminating all outside-of-the-team roles except the product owner. As an example, DevOps is considered to be to be a harmful misnomer, as the “original idea was to eliminate ops”. In fact, Bas Vodde rather refers to LeSS as ‘an organization design framework’ than a ‘scaling framework’. While in large organizations the change in organizational structure can happen gradually, organizations with 50 people or less can and should be flipped in a single go.

As for LeSS adoptions … I have yet to see them. And yes, it is quite easily imagined that a LeSS consultant, after rubbing the total structural changes needed, the abolishment of titles, removal of career paths and dismantling the reward systems in the management’s face, might get shown the door.

LeSS does, however, has a concept which would be useful in improving your typical SAFe adoption: Undone Work and the Undone Department.

Team and organization size

SAFe: Teams are 5-11 people, and an agile release train 5-12 teams + the other needed roles (50-125 people)

LeSS: Teams are 5-9 people, and the dev org 3-8 teams + product owner (16-73 people)

For those development organizations which are larger than those stated above, SAFe employs multiple trains for the same solution. In similar fashion, LeSS employs multiple requirement areas (called “LeSS Huge”). In the large solution case, SAFe’s solution management corresponds to the LeSS product owner, whereas program level product managers match LeSS’s area product owners.

Looking for differences, while the team size in both of the frameworks is based on Scrum, the overall numbers in LeSS are smaller. Likewise, the split into multiple requirement areas and area product owners is recommended in the range where according to SAFe, a single train would still be enough.

Otherwise, the approaches match each other quite closely.

Adoption steps

SAFe: a) Train lean-agile change agents; train executives, managers & leaders b) Identify value streams and ARTs c) Prepare and launch ARTs d) Coach and launch more ARTs e) Extend to the portfolio

LeSS: a) Educate everyone involved in the transformation b) Define the product, define done, have appropriately structured teams c) Only the product owner gives work to the teams; keep project managers away from the teams d) Repeat until entire organization transformed

As you can see, both of the frameworks start from training everyone and both emphasize the importance of training the top management. SAFe talks about value stream identification, whereas this is essentially the same thing as defining the whole product in LeSS. Then, the notion of forming ARTs (SAFe) and restructuring teams (LeSS) are very close to each other, and both start with a part of an organization and repeat until done.

The difference is that while LeSS suggests transforming a part of the organization at a time (end thus, creating implicit portfolio management for that area), SAFe “extends to the portfolio” only after launching all the trains.

Cadence

SAFe: Synchronized 2 week sprints and 8-12 week program increments

LeSS: Synchronized sprints; does not dictate length (but 2 weeks is often implied). Emphasizes that “the sprint is for the product”, not the organization

In SAFe, teams can also “operate in kanban”, but “adhering to SAFe specific rules” where teams plan, demo and do retros together. This does in practice make it quite similar to operating in sprints.

At least when first starting with LeSS, you can do “release planning” in a very similar fashion to SAFe’s program increments. And what’s to say it should be dropped later on?

To quote my LeSS certification course teacher Ran Nyman: “Sure you can add a construct similar to SAFe’s program increment to your methodology – but only do so if you’re persistently in great pain without it”.

As the goal in both frameworks is to be able to ship the working and tested solution (roughly) every two weeks, their take on cadence is very much the same. At least in theory, for in practice the concept of PI planning tends to drive batch sizes up. Compared with sticking to plain two-week Sprints, that is.

Requirement meta-model

SAFe: Epics (do not fit into a Program Increment), Features (should fit into a program increment but not into a 2-week iteration) and Stories (should fit into a two-week iteration).

LeSS: No explicit requirements meta-model; try to use a flat list, and if you can’t, stop at three levels maximum

The notion of requirement meta-models dates to somewhere around 2005 in the work of a group of Swedish researchers (see publications 57-59). While around 2010 other models were also introduced, SAFe’s three-level Epic-Feature-Story model, based on a white paper from Nokia written by Juha-Markus Aalto, has emerged as the most popular one.

LeSS advises to avoid backlog structures with many levels of splitting and recommends that one should definitely “stop at three levels maximum”. This is because having many nested levels increases complexity, as well as tends to result in diverting from customer-centric requirements.

While SAFe and LeSS differ slightly, I think they both are a bit off here – at least when it comes to tree-like splitting.

I’m inclined to think that most of the challenges in dealing with nested levels of requirements actually have to do with inadequate tooling, which in turn stems from physical boards, index cards, and considering the backlog as a flat list.

My two cents is that if you go for tree-like splitting, you should allow for infinite levels as well as abolish explicit taxonomies. Otherwise, you end up driving up batch size in subtle ways which in turn lead to very tangible problems.

Content management

SAFe: Product manager owns the program backlog and team product owners own the sprint backlogs. In addition, there are program-level PI objectives, summed up from the team PI objectives which are in PI planning scored by the Business

LeSS: Product owner owns the product backlog, the team owns the sprint backlog. Optional Sprint goal, devised by the team and the product owner

I’ve divided the discussion into two sections: backlogs and content ownership and goal setting.

Backlogs and content ownership

Despite SAFe’s distinct portfolio level, the ultimate decision on what goes into the program increments resides with the Product Manager role. This holds true for LeSS’s product owner as well.

Overall, SAFe’s product manager and LeSS’s product owner roles are quite similar. While SAFe explicates further content owner roles such as Business owners and Epic owners, I interpret this as a way of actually making the product owner more specific – and similar to the role as originally defined in Scrum. LeSS leaves such details out and talks about product ownership being a deeply collaborative activity with the stakeholders.

But the real differences come at the sprint level.

SAFe recommends that each team should have a product owner, and that at least most of the sprint level work items (stories) should be connected to parent work items (features). LeSS, in turn, advises against both of these things. The creators of of LeSS consider that having a product owner per team promotes local optimization.

In LeSS, Product and Sprint Backlogs are also intended as separate and independent artifacts. The teams should be able to choose their own way of keeping track of sprint-level work. They should also  be trusted to understand and communicate about their progress without explicitly using a tool to tie sprint content to product backlog items.

Goal setting

In terms of goal setting, aside from the vision, SAFe has PI objectives and iteration goals, whereas LeSS has sprint goals.

The obvious difference here most likely stems from the differing cadences put forward by the frameworks. As a Program Increment contains several sprints by several teams, and each team has a set of their own PI objectives, summarizing those into program level PI objectives is only natural.

The collection of LeSS’s Sprint Goals (one for each team) are essentially the same, but for a shorter time period. Thus, summarizing is not needed.

But a less obvious, and to me a rather interesting aspect here is that SAFe has the construct of PO objectives in the first place. Also, there is a degree formality related to their use (compared to e.g. the rather vague definitions of sprint/iteration goals which have lingered around since the early 2000s).

Team level PI objectives are scored by the business people, and are then used to calculate the PI predictability measure at the end of a program increment.

Let’s take a moment to discuss this. The original intent in the manifesto for agile software development was to have the business and development work together daily. Also, user stories, as originally intended, did contain the expected benefits in terms that the business understands.

Now, in your typical real-life large-scale setting, the business people are hardly participating in development decision-making at all – at least before “the transformation”. They have too much important management stuff to do.

Also the use of stories at the team level has surprisingly often degenerated into something akin to “As the system, I want to have a button so that I can press it to print” silliness.

The PI objectives in SAFe seem to me like a tailor-made mechanism to pull the business into the discussion at least every quarter or so, without having to force them completely out of their comfort zone and join the discussion of these “agile stories” on a bi-weekly – or God forbid – daily basis. Interestingly enough, in the cases where I’ve seen PI objectives used by-the-book, they very much resemble product backlog items as they were originally intended.

Whether having – in addition to the backlog(s) – such a scoring wrapper in the long run is the safest (pun intended) route to take – as opposed to actually pursuing daily collaboration, spreading the knowledge about the proper use of a product backlog, collaborating with user stories and learning to do vertical splitting together with the teams, I’ll leave aside for now.

Having said that, the PI predictability metric is good in the sense that it’s harder to game than for example measuring velocities, function points, or some other silliness.

Cross-team coordination

SAFe: The Release Train Engineer role and Agile Release Train sync meetings

LeSS: The teams are responsible for cross-team coordination; in addition, you can have “town hall meetings”, “problem solving open space meetings”, “scrum of scrums” and whatever you need

According to SAFe, “agile release trains won’t steer themselves on autopilot” and the release train engineer role is there to facilitate cross-team coordination.

LeSS does not have an explicit coordinating role, because its creators considered that having such a role would unnecessarily take away responsibility from the teams.

Portfolio management

SAFe: Explicit strategic themes, portfolio canvas, rolling-wave funding of value streams, budgeting guard rails, a kanban for prioritizing and managing Epics, and the Epic owner role

LeSS: Portfolio management happens via backlog prioritization

Understanding LeSS’s stance on portfolio management would require a bit of explanation, but a piece about this is already out there.

Essentially, LeSS suggests that in the case of a correctly structured organization and a broad enough product definition, portfolio management is de facto reduced to backlog management. In the case of LeSS Huge, ‘portfolio management’ also includes shifting teams from one requirement area to another. And the demand for such shifts comes from…  yes, backlog prioritization.

On the surface, SAFe portfolio management looks quite different from that in LeSS. Despite the added number of elements and artifacts, I find it essentially the same. For example, if value stream funding changes, surely the number of teams working in the trains – or the number of trains – are the variables which change as well.

Having said that, limiting the number of work-in-progress on the portfolio level is the most effective way to improve an organization’s performance – even without changing the structures and practices in the development organization.

To look at this from the perspective of offering an organization an easier path to transform its portfolio management, SAFe does, by describing a ready-made set of artifacts and roles offer better novice-level guidance here. Again, whether such a path is on the long run safer and faster is unknown to me.

What about the other scaling frameworks?

You might be wondering why I haven’t included other scaling frameworks to the comparison? First of all, SAFe and LeSS seem today to be the most popular, as well as best described.

To scratch the surface of the other approaches out there, Ken Schwaber’s Nexus is very close to LeSS with a bit more structure around how to do cross-team coordination. The so-called “Spotify model”, as originally described – I have no clue what Spotify’s doing today – was structure-wise also very close to LeSS.  Likewise, Jeff Sutherland’s Scrum@Scale is quite close to LeSS – but actually has even less structure to it. On the surface it seems to simply recommend that everybody in the company should do Scrum.

Perhaps in the  future I might take a deeper look into Nexus and Scrum@Scale.

The kettle and the pot

I’ll end with quotes from both frameworks’ proponents:

“SAFe is based on the Lean-Agile principles and the agile manifesto. […] It would be great if big companies who build important systems could start from scratch and start with a team of five, ten or fifteen and build it. But often they already have thousands of people in place and SAFe provides a bigger picture of how they could operate with a different mindset and what the principles, the practices and the roles could be.” (Chris James, COO of Scaled Agile Inc. @ Panel on Agile Scaling Frameworks And Their Ecosystem – Boon or Bane at #AgileIndia2017)

“LeSS is true to agile development and the origins of Scrum and is about creating the bare minimum and more ownership for the team. It is about moving away from heavy-weight processes and roles within organizations. Complex organizations are slow, and in LeSS you want to create a simple organization, which can better make the product(s).” (Bas Vodde, co-creator of LeSS, @ The Agile Standup Podcast)

Perhaps one of these resonates with your transformation efforts? Or perhaps not? Remember that you don’t have to – or perhaps even should not “choose” either!

As it happens, both frameworks have strong roots in Finland, from companies such as both of the Nokias, F-Secure, and Ericsson – among others.

And not-so-coincidentally, Nitor’s Transformation Engineers – myself, Maarit Laanti, Rami Sirkiä, Kirsi Mikkonen, Rauno Kosamo, Marko Setälä, Juha Itkonen, Antti Tevanlinna and Kati Laine – just to mention a few – have, since early 2000s, been involved in the work which has since resulted in both SAFe and LeSS. 

So whether you pick one framework, the other, both – or wish to go your own way, we can help you transform your organization.

Did you know that having a fixed number of levels for story splitting – such as the “Epic-Feature-Story” model popularized by SAFe – has an inherent tendency to drive batch size up? In this post, I present a short history of story splitting taxonomies in agile and demonstrate why three levels of splitting is not really enough. I also propose a remedy for the problem: allow for tree-like splitting for the highest level items, but go for cell-like splitting whenever “inside” a time-box.

– Avoid a complex requirements meta-model (Larman & Vodde, 2010)

In the later part of 2000s, authors and thought leaders in the field of agile software development started applying agile beyond the context of a single team, and at the same time, proposing requirements meta-models to better structure planning for a longer term than a sprint.

Some would say it all went south from there.

But for the sake of not hiding our head in the sand and pretending tree-like work item splitting isn’t already being practiced in every other company striving to become more agile, let’s suppose it would make sense.

Let’s first recount how the idea came about.

A short history of work item splitting

In the beginning, there was the product backlog. A flat list of what was seen as potentially useful for a team to do, with smaller and better understood items at the top, and bigger, more vague items at the bottom. The product backlog was taken care of by the product owner, refined together with the team, and with the team, the contents of the next sprint were selected.

Tracing back, before the notion of requirement abstraction models in agile software development, there came the notion of levels of planning. Rautiainen et al.  (2002) presented the first attempt at generalizing levels of planning beyond the context of a single agile approach (such as xP or Scrum). However, it wasn’t until 2005 until levels of planning in agile were popularized by Mike Cohn’s planning onion in the book Agile Estimating and Planning.

As an example, the picture below depicts different levels of planning. That particular picture is from 2012 and drawn by yours truly. In it I combined ideas from Smits 2007 and Cohn 2005. Based on a quick googling it has, verbatim, spread to become a popular picture to depict planning levels:

Progressive refinement of work items has of course been part and parcel of agile all along, But planning levels models do add structure to better understand work item splitting. In progressive refinement, as development proceeds, the bigger and still vague work items are split into smaller and smaller – according to the planning horizon in question. Often, large items split into smaller items that have “mixed priority”. Thus, when possible, splitting should proceed to identify just those small bits that add the most value. Then, only the most valuable “bits” should be implemented.

Tree-like vs. cell-like splitting

SAFe, the most popular scaling framework today – as well as many other authors on the topic before SAFe – propose a tree-like splitting model. In tree-like splitting you retain the original work items as well as the trace to the resulting work items.

To contrast that, early agile thought leaders such as the manifesto authors seemed to pay little attention to the notion of tree-like splitting. This is particularly well exemplified by the following excerpt from Mike Cohn’s book Succeeding with Agile (2009, p. 178)

After an epic is split into smaller stories, I recommend that you get rid of the epic. Delete it from the tool you’re using or rip up the index card. You may choose to retain the epic to provide traceability, if that is needed. Or you may choose to retain the epic because it can provide context for the smaller stories created from it. In many cases, the context of the smaller user stories is obvious because the epics should be split in a just-in-time manner.

Like Cohn, Larman and Vodde (2010) also prefer cell-like splitting. They propose that loss of context and ancestor information in cell-like splitting (where you get rid of the parent item) may be a speculative rather than a real problem.

Whatever the case may be, tree-like splitting has, largely because of SAFe, ended up popular enough to warrant a deeper discussion.

Tree-like splitting and work item taxonomies

With tree-like splitting often comes the idea that it could be useful to have a taxonomy – or a meta-model, whichever name you prefer – to refer to the different sizes of work items on the different levels.

The first such taxonomy I’ve come across – and coining of the term requirements abstraction model – was in a research paper by Gorschek et al. in 2005. In the years that followed, many different abstraction models by different authors, among them Dean Leffingwell’s Epic-Feature-Story, were proposed.

While for example Mike Cohn warns of the pitfalls of using “complicated” requirements abstraction models, it is not difficult to accept the idea that at least in some situations, having a taxonomy for discussing the items on the different planning levels would indeed be useful. Also, the little empirical research out there on the matter (for example the work of Gorschek et al. and Lehtola et al.) supports the usefulness of such taxonomies in the context of product development.

How many levels of splitting is enough?

SAFe’s requirement abstraction model has three levels: Epics (which do not fit into a program increment), Features (which should fit into a program increment but take more than a single iteration to complete) and Stories (which should fit into an iteration). While SAFe does not talk about having hierarchy inside these levels – perhaps to keep it simple – it has an additional term, ‘Capability’, to refer to a group of related features.

The authors behind LeSS, Larman and Vodde have recommended two levels at most, and in their 2014 book they were very clear on the matter: if you go for tree-like splitting, “a maximum of three levels is enough”.

But where does this number three come from? Why not two? Or four? Or five? How many levels are enough, and when?

To me it seems that sticking to three levels stems from historical reasons.

In the physical world of walls, post-its and index cards – where it all started – the notion of many levels of work item splitting certainly does not seem feasible. Indeed, a key goal of the manifesto authors – including those who came up with the concept of the product backlog in the first place – was to make a programmer’s life simpler. Perhaps because of that most of them implicitly advocate cell-like splitting.

In the realm of electronic support for work item management, tree-like splitting would certainly be feasible. However, implementing infinite work item hierarchies presents a considerable amount of usability as well as technical challenges. As a result, an overwhelming majority of electronic tools for work item management has not tried to actively divert from the flat list / cell-like splitting approach. Also, in those tools which have some sort of work item hierarchy, the higher levels are, instead of a true hierarchy, either like ‘glued’ on top of the existing model (think of JIRA’s Epics) or simply have a pre-set number of levels (for example AgileCraft).

Does fixed-level splitting drive batch size up?

It’s fair to propose that ‘three levels’ of splitting may be a legacy notion. Thus, the fact of the matter in how many levels of splitting would be enough remains an unexplored territory.

I personally question the need to limit the levels in the breakdown. This is because in my experience, fixed level splitting drives batch size up. And keeping the batch size small is undeniably one of the pillars for rapid feedback – which in turn is the heart of agile.

With fixed-level splitting, what happens is that you easily end up having items that are too big on the higher level(s) (the case where “nothing moves”) and/or items that are too small on the lower level(s) (the case where “business loses sight”). In my experience, you will end up with either scenario – or both of them. And they both effectively undermine the benefits being sought for with tree-like splitting.

Another, a more subtle dynamic which I’ve seen take place is getting ‘attached’ to the tree-like breakdown, and ignoring emerging new and possibly more direct ways to tackle the original problem. In such a case, tree-like splitting effectively drives towards waterfall-like thinking. It may also be that the “original problem” is discovered to be no more relevant, but because of the work breakdown and the attached governance mechanisms there is a tendency to simply keep going at it.

A tale of progressive refinement

But perhaps an example would illustrate this better? Take a look at this white paper: it presents a real-life tale of progressive refinement, which explains the dynamics taking place in detail. 

What to do about it?

Throughout the tale you were able to read of all the details that go on under the hood. While a three-level breakdown would have looked clean and simple, the progress made would remain invisible even though a lot of work both necessary and valuable was being carried out beneath the surface. Still,  with three levels, even the lowest, 3rd level items would in the example seem immobile. 

In the context of product development this dynamic most often manifests so that the gap between abstraction levels gets so wide that those ‘in charge’ of the higher level will lose grasp how the contents of the lower level relate to the overall goals.

In the same way, those in charge of implementing the lower level items may lose sight of “the why” – and missing that, it may affect “the how”, leading to sub-optimal solutions that would have been avoided had the big picture been in place.

What about metrics?

You may wonder that as the Story tree gets pruned and reshaped, isn’t information about what has been achieved in the previous PIs lost? If you reformulate the story tree in such a manner that the past achievements melt into each other or disappear, what happens to the possibility to draw burn-ups, burndowns, measuring epics’ and features’ lead time, progress and so on?

While most of the tools out there are not very good in supporting the merging and splitting of work items, there are tools which can retain the past to anguishing detail. Just last week in a workshop of a corporation’s RTE and their #1 tool expert, we tried to straighten out the configurations of a 5000 item story tree (done using JIRA Structure) to act so that when new items are created anywhere in the tool, they’d be sucked into the story tree to the correct place when the correct  ‘child-parent’ link is added.

Nearing the end of the time we had at our disposal, it was decided that the best course of action would be to ‘forget the past’ and rebuild a new story tree from scratch taking only the important items which are now or in the very near future to be acted along. There may be sentimental value in all the garbage collected over the years, but I’ve yet to see a case where it would have been needed later. Likewise, any possible metrics drawn from a heap of garbage items hold no value either.

Instead of progress metrics, aim for daily collaboration and value delivery

The key to successful iterative refinement – and indeed, agile – is in rapid feedback, value delivery and the daily collaboration of development and business.

When that works, detailed history, metrics and graphs – as well as the taxonomy for the items on different levels in the story tree ultimately matter very little.

Tree-like splitting needs more than three levels

The example in the white paper, while real, most likely a straw-man compared to the challenges you face in real-life product and service development. After all, while the domain here could be considered equally challenging, we can in theory deliver an end-to-end solution with a single person, and we already know what the end result should look like. We merely don’t know the exact steps to get there or how long it will take.

Just like tree-like item splitting helps you to avoid variability and batch size problems you’d have with a flat list, if you don’t allow for item splitting of arbitrary depth you’ll just run into the same problems a little later.

Allow tree-like splitting for work items outside a time-box

For tree-like splitting you need is easy reformulation of the story tree and as many levels you think you need whenever you need them. Most electronic tools don’t do a good job of supporting you there, so if you are going for an electronic tool, choose carefully.

But you don’t have to go for an electronic tool. If you allow yourself to ‘drop the past’ and focus on what is the plan right now, you can well do that with pen, paper and two walls. But how exactly, that will be the subject of a future post.

But still, in this straw-man example, using more than three levels seems very useful. This is why resorting to a fixed number levels will not be optimal in all but the most trivial cases. In fact is never has been optimal. I believe that is one of the reasons why the original signers of the manifesto for agile software development did not venture into that direction at all but swept it under the rug of ‘the product owner should take care of it’. Their goal was to make the life of developers simpler, and the only way they could see that happening was by fostering Business-Development collaboration on a daily basis.

And that’s what I have seen working as well. If you don’t have that in place, you are dealing with alleviating managerial phantom limb pain. And for that, fake metrics are just as good as the ones you could with a great deal of effort draw from the mess that is the stuff in your tool-of-choice.

Sure, you can in retrospect prune the story tree and force it into only a few levels. But during the process and in the collaboration, you need room to think and discuss. Constraining that discussion with a fixed set of levels and taxonomy of names and roles in charge of the levels will only be a hindrance and level s is hardly useful.

As you probably will have to deal with tree-like splitting, a final word of advice: what I’ve found useful is to allow for tree-like splitting for those items which are not supposed to be completed in a particular time-box. Using SAFe as an example, you’d allow tree-like splitting for Epics, but whenever Features or Stories are split, you go for cell-like splitting. Don’t go making a taxonomy for your Epics-on-top-of-Epics, it is hardly useful in reality. Too big is too big, and more gemba is what you really need.

After all, it makes little sense to have Features which are supposed to fit in a Program Increment – which have sub-Features which also should fit into the same Program Increment.

Or what do you think? As always, comments and experiences are most welcome.

Backlog tools are seldom the first-order problem in an organization. And even the best ones can’t solve the first-order problems for you. However, bad tools do get directly in the way of your transformation efforts. That’s why it’s useful to tell one from the other.

 

– God bless me, but the backlog, is very like a list! (adapted from John Godfrey Saxe)

Having been involved in the development of a backlog tool (that’s Agilefant, nowadays known also as Nektion) since 2004, I’ve been a long time dismayed by the quality of the tool reviews out there.

I know, it’s individuals and interactions over processes and tools but bear with me here. Tools are seldom the first-order problem and even the best tools can’t save you. However, bad tools do get directly in the way of your transformation efforts. That’s why it’s useful to tell one from the other.

Unfortunately, most tool reviews seem to be camouflaged marketing, huge tables or lists consisting of extremely shallow observations of the tools’ capabilities and/or copy-paste from the vendor’s sites. I honestly don’t know why these are done in the first place! Perhaps virtual name-dropping gets you traffic?

Gartner’s magic quadrant reports seem to come the closest, but they, too, suffer from staying at a superficial level.

Another confounding factor is that as SAFe and the like spread further, the vendors’ marketing folk pick up that this is something their product should be able to do as well. And they go and change their website to say that surely their product supports SAFe whether or not that actually is evenclosely the case in reality. Of course similar things tend to happen to everything which has demand – like it has for Agile, Scrum, Lean or Kanban.

If there was a clear upside to doing good tool reviews, surely someone would have done so already. And kept at it, because whenever I have found something that might be useful, it’s cut short after some two posts.

So, while producing useful tool reviews will probably prove to be a futile effort in ways I don’t yet foresee, I’m willing to take my chances and try it.

But before going into the actual reviews, in this post I’ll lay some necessary groundwork.

SO, WHAT MAKES A TOOL GOOD?

In my experience, the “goodness” of a tool really comes down to three things:

1. The conceptual strength of the tool
2. How easy it is to get started
3. To what degree you can tailor and adapt the tool as you learn more of what you need

I’ll try to elaborate a bit on what I mean by these below.

1. THE CONCEPTUAL STRENGTH OF THE TOOL

At the heart of the challenge is the concept of ‘product backlog’ and being able to support how it’s supposed to work. While that might sound simple – “just list the most important items” – taking a closer look at what has been said about it will reveal a vast landscape of needs.

Exploring that further would be a subject of another post itself, but you can get a taste of what I mean by skimming through chapter 2 of “Towards Agile Product and Portfolio Management”.

2. EASE OF GETTING STARTED

The ease of getting started is in direct contradiction to the conceptual strength of the tool. This makes things challenging.

I’ve seen cases where people want to start by getting a board-like view for the company’s high-level initiatives (a ‘portfolio kanban’, if you will). But equally crucial is the need to support a single team in its daily work.

While Trello might, with individual boards, cater to both of these needs, its conceptual strength stops short when people start wanting to combine these views into a coherent whole.

From the portfolio perspective this can expand into wanting swim-lanes for ‘strategic themes’, roll-upped progress metrics based on the epics’ breakdown and so on.

Likewise, on the level of the individual team, being able to tie the team-level work items to the big audacious hairy goals of the company is something that may help guide the decisions. As expert work such as programming is essentially problem-solving, and there are many ways to solve problems, an understanding of the big picture helps the team align their solutions to the company goals.

Either way, you have to start somewhere, and if the conceptual strength gets in the way of just jotting things down as you would on post-it notes or a paper notebook, it will cripple the drive.

3. TAILORING TO YOUR NEEDS

To be able to combine both the easiness of getting started and the conceptual strength, you need to be able to adapt and grow the tool as you need to, creating new concepts and relationships and renaming the old ones.

This makes it possible for the tooling to grow with you. Otherwise, you have to force your way of working to the model enforced by the tool. This could be a “big hairy proven framework” which incarnates the latest version of the Unified Software Development Processes or Capability Maturity Models of late 1990s – or something else which doesn’t quite fit your reality.

No matter how enlightened, if a big model is forced on the organization too soon, the result will be co-optation: your system projects will be cast as ‘release trains’, your component teams as ‘feature teams’, and your non-customer facing business units as ‘value streams’. In such a scenario, the tooling wille become a strait jacket. In such a case, if you are going through with your transformation, not only will you have to change the organization, but also dismantle the tooling.

An important but fairly simple as well as often overlooked part of tailoring is being able to rename the concepts in the tool.

While choice of names will matter in the long-run (think of for example, ‘projects’ vs #noprojects), in a transformation you want to be able to pick your fights.

Will you, from the get-go, have to convince your C-level managers to talk of Epics, Sagas, Novels and Steam Trains or simply Business Value Proposals and Projects like they’ve used to?

THE CANDIDATE TOOLS

At the time of writing this, I’m considering to take the following tools under a closer scrutiny; in alphabetical order, these are:

• Agilecraft – the self-claimed leader which to date has not lent itself for easy sign-up and tire-kicking
• Agilefant – the open source version from 2014 – as a baseline
• Favro – the offspring of Hansoft from Sweden
• Google Sheets – not because spreadsheets are that good but because they just might be better than anything else
• Leankit– I’ve heard good things about this, though nowadays it has been acquired by the more traditional vendor Planview
• CA Agile Central (formerly known as Rally) – first IPO, then going to CA to die?
• Taiga – the other open source tool worth mentioning
• Targetprocess – long-standing original thinking from Belarus
• VersionOne – besides Rally, the other U.S. based ‘enterprise agile’ vendor; nowadays acquired by CollabNet, which already many years ago swalloved an early player, ScrumWorks

Of the obvious possible choices, I’m skipping JIRA, at least for now. This is because of my customer engagements. I am anyhow in the process of writing a separate thread of posts covering it.

I’m also skipping big software houses’ such as HP’s, IBM’s and Microsoft’s offerings, even though nowadays they, too, claim to support “agile”. I may be wrong in doing so, but for some reasons I can’t quite verbalize, I don’t feel it’s relevant to address them. And you can read how they by some strange mechanism get put up as leaders anyway from any Gartner or Forrester report.

So that’s it for the groundwork, and stay tuned for the first review. I will be backlinking the results to this post, and following Nitor on Twitter you’ll hear about it among the first.

If you have suggestions for tools which I should take a closer look at, or want to affect the order in which I go through the candidates, get in touch!

– Culture is the product of the system; change the system and behavior changes
(John Seddon)

As a community, advocates of agile often seem preoccupied with the notions of culture and mindset. Even when people who have been involved in successful transformations actually talk about structural changes, they tend to refer to it as “changing the culture” – for example in these presentations by Mirette Kangas and Fred George.

This emphasis on culture paints the picture where “if you just change hearts & minds and train everyone, self-organization happens and things fall into place”.

My journeys in enterprises have taken me to places where seemingly everyone was trained in “agile” but as the key structures remained unchanged, the impediments persisted.

In one organization, “Done” did not mean that something was deployed and running in production. Done merely meant that the feature had been handed off to the Q&A and release organization. And as there was no easy way to measure the time in the Q&A and release phase, they measured the time spent in the development phase and called it the ‘lead time’. As we pointed this out and went on to explore this further, we discovered that for features that had been developed in 1-2 months, the total lead time could be as long as 18 months.

Another common example of a structural problem comes from contractual issues. In one organization, the people were excited about the new ways of working, and most had been trained as well. But upon asking if they could mix the current, component based teams to form cross-functional feature teams, the answer was a disheartened sigh.

After a bit of prodding, it was revealed that because of the outsourcing contracts in place, this was considered impossible. Moreover, the outsourcing had resulted in a considerable amount of offshoring. This had led into people on different sites specializing further into certain kinds of tasks. Because everybody had to have something to work on, prioritizing according to highest customer value was not possible.

And as the people who were responsible for the contracts did not feel the pain, nothing was done about these issues when the contracts were eventually renewed.

You cant’ change structure bottom-up

Organizations tend to grow so that when problems occur, specialists are hired to take care of them. Over time this results in organizing such specialists into their own resource pools. Then work gets done by handing it over from one pool to another. Such structures are in direct contrast with the notion of cross-functional feature teams and organizing around delivering value to the customers.

In my experience, the drive to adopt agile often arrives at organizations at the level of development managers and team leads. However, the prevailing structures can only be changed by C-level executives, and hiring a “VP of agile” will not be enough.

Take it from the thought leaders

It doesn’t help that currently the most popular framework for scaling agile, SAFe, is not that explicit (at least compared to the total amount of material in the framework) of the need to change the structures. Examining the structures lurks under the notion of “applying systems thinking”.

To me SAFe has seemed almost surprisingly agnostic about the matter as it allows “development value streams” and says that “there is no one right answer”. The fine print does warn though that with development value streams you will end up with a lot of dependencies.

I had the chance of discussing this with folks from Scaled Agile Inc. They consider it a conscious choice: it’s better to get a foot in the door and then proceed to help the client from there instead of getting completely turned down as a result of proposing radical changes up front.

While that may be true, there are thought leaders who criticize SAFe from SAFe from the point of view that because of the sheer amount of material, it can easily turn into scaffolding for the legacy organization to hide behind.

Also some thought leaders have taken the notion of changing the structure as a central part of their teaching. In fact, they consider the preoccupation with culture as failure demand caused by the inability to change structures.

They articulate this so well that I’ll step aside here and provide a few pointers so you can delve deeper into the matter.

The ones I’ve raised here work quite well even if you only listen to the audio, so you can explore them while for example commuting. These speakers have also lot of other presentations available on Youtube which further deepens the point. Here’ I’ve tried to pick those presentations that most directly cover the point I’m trying to convey and put them into an order they are most easily approachable. Enjoy!

Four presentations worth checking out

 

Author	Presentation	Quote
Mike Cottmeyer (2017) @mcottmeyer	Is culture really the issue? (Youtube, podcast)	“Most organizations are deeply flawed from the perspective of delivering value. Teaching them to want something is not enough. At some point you have to do the work of removing the impediments. And if the impediment is 2M lines of legacy mainframe code in a key business system, you just fix by the next sprint”
Craig Larman (2016) www.craiglarman.com	More with LeSS: a decade of descaling with LeSS @ Agile Munich meetup (Youtube)	“I can quickly spot a young naive change person when they say you have to change culture; you can’t change culture”
Jason Little (2017) @jasonlittle	Rethinking agile transformation (Youtube) @ Agile Montreal	“Co-optation is the most common mode I see. A VP of agile is hired, the structures persist, we do things as we always did them, and the agile is put in front of everything.”
Dan North (2017) @tastapod	How to break the rules @ Goto 2017 (Youtube)	“In companies we have a huge number of rules to cope with the limitations of the old way of working. In a transformation we not only have to dismantle them but also come up with the new and mostly very different kinds of rules to manage the new limitations”