The scaling of software and systems agility is still very much in the early stages of evolution, such that there doesn’t seem to be any clear consensus on exactly what is meant by scaling, or rather, where that starts and ends.
In this post, I’ll use Scrum as my “baseline” and reference agile way of working since that is by far my biggest experience, but you can substitute other agile paradigms.
Scalability in this context refers to the innate ability to apply single team-based agile techniques in successively larger and interdependent organisational units. I often think of this as having two dimensions:
- Teams working on the same product, project or programme. Typically, one or two teams (and at maximum three) will work on a product owned by a single Product Owner, and Scrum works entirely native in that situation. But where several products within a project or programme have dependencies between each other, a degree of coordination is required between them to ensure overall project/programme/system integrity. This can be to minimise waste, for example in ensuring that dependent components are developed just-in-time for when they are needed (no sooner, and obviously no later). It can also be to satisfy technical dependencies (especially in component-based development teams), part of the very essence of project, product and programme development.
- Teams working on disparate products but within the same organisation.It may also be highly desirable to be able to use broadly similar agile practices across many (or all) parts of the development organisation. For example, this reduces ‘learning curve’ overheads when teams are formed or rearranged. It also helps contain and manage the cost of operational and tool support in large organisations, an important consideration for any business, even though we should beware of the tail wagging the dog.
There is no question that Scrum can be applied to a large number of teams. In small products, projects and programmes, there are typically a “handful” of teams that need to collaborate and the original concept of Scrum-of-Scrums works perfectly well. To some extent, this is also further scalable, in both dimensions described above. Things start to get a lot more tricky however as you start to get beyond 6-12 teams. This is partly because there has never really been much in terms of detail of how Scrum-of-Scrums should work that I have come across, and that isn’t also bespoke to a particular organisation or scenario. However, it’s an even bigger headache in terms of how to manage an ever-increasing number of teams that need to ‘cross-coordinate’. Examples of Scrum-of-Scrum-of-Scrums (and beyond) have been tried and made to work (or so I have been led to believe) so this might handle a limit of up to 50 teams, at its best, but this is introducing hierarchies of ‘reporting’ and function that generally have pretty severe disadvantages too.
This returns me to the original question of what we mean by scaling agility. To many organisations, scalability to 50 teams would indeed seem ambitious and round about the upper limit. My experience has been with organisations like Nokia and Symbian, where we were dealing with a phone product development of 200+ teams, at peak. This can truly be called Enterprise Agility. Scrum-of-Scrums begins to look a little lightweight in this context.
Without some method of scaling for the enterprise, it will be pretty well impossible to achieve a coordinated system (or enterprise or system-of-systems etc) that always runs, that delivers value to stakeholders in small increments, that is responsive to change, delivers just in time (only) and minimises the Cost of Delay.
Unsurprisingly, businesses that I have worked with over the years have all placed great importance to the predictability of schedule and predictability of quality (whether they are using agile methods or not). After all, these characteristics are the basis of survival in an ever-increasingly fierce and competitive marketplace.
In a highly complex product being built using changing/emergent technology and having frequently changing priorities for features, it is still reasonable to set business deadlines based on forecasts of market need , economic value, and quantified Cost of Delay. It isn’t realistic to expect dozens (or hundreds) of teams to self-organise; it’s a risky approach almost bound to fail. The need for a way to combine Scrum with higher-level release and portfolio planning becomes vital if we want to preserve the benefits that agile can bring (e.g. small increments of value at product quality, fast feedback, ability to react to change).
Shown here is a picture summarising the model for scaling agility defined by Dean Leffingwell; you can read about in many sources including his blog. This was the basis of the model in use at Nokia. In a later post, I intend to talk about the details of the model with some modifications and minor enhancements we adopted. For example, the model allows for just enough planning (and at the right level) to be able to define the next release, and beyond in an increasingly less detailed way.
It quickly becomes clear that any adoption of scaled agile practices requires commitment from more parts of the organisation than small-scale Scrum does. This raises a number of questions for the enterprise aspiring to reap agile benefits. Some of these arise for any ‘size’ of agile adoption but require even clearer answers in an enterprise agile transformation:
- Will all affected parts of the product development chain adopt agile behaviour? It is so often the case that, at best, senior executives endorse the practice of agile techniques, but do not consider that it is something that will (or even should) affect their own behaviour. It can be regarded by leaders as something ‘they’ do but obviously we, as the decision-makers, need not be constrained by its patterns.A little knowledge is dangerous (in the wrong hands). Having learnt that agile practices embrace change (changing priorities and product scope), there can be a tendency to assert too many changes on the development organisation and assume there is no associated cost at all. Some change is of course healthy but too much change (let’s call it ‘churn’) has a high cost and also is indicative of a business in chaotic mode.
- What are the business objectives in adopting agile practices?
- What does it mean for the enterprise to be agile?
- What is the initial willingness of the workforce to become agile?
- Will it be acceptable for the product architecture to emerge or is there a light (but significant) steering design required?
- How should large product teams be organised? In sufficiently large and complex products, is it feasible to have feature-based teams, or does component-based teams become a necessity in practice?
- Does the enterprise have an organisational structure that will support scaled agility? For example, how collaborative are those parts of the organisation dealing with system/product testing, requirements definition, code-line integration (configuration management)?
How robust are the underlying Technical Practices (for designing, building and testing)? Scrum itself quickly reveals flaws in how teams actually develop software, but these become magnified exponentially when scaling agile practices.
In subsequent posts, I hope to tackle a number of these issues in more detail.