Lean Software Engineering

This is part 4 of 10 Pitfalls of Agility on Large Projects. In part 3, we talked about how we can’t afford to trust everyone on large teams, and what to do about it.

Frequent releases, which are central to both agile and lean methods, sometimes draw a visceral reaction because people fear we can’t keep the product that close to release quality at all times, while still delivering as much innovation.

That is a real challenge of agile/lean methods. But making this argument against short cycles is difficult, so the most common argument ends up being “the customer doesn’t want a release every month (or every 6 months, or every year …) anyway.”

Unfortunately on any project with many customers, while no customer wants a release every month, there is always one wanting a release right now.

We can deal with that to some extent by having tiers of releases: the single-customer quick fix, the multi-customer patch, the service release, and maybe minor and major releases. But each of these tiers involves extraordinary cost and waste from duplicate efforts — waste that can often be avoided if the main release cycle is short enough that customers can get their needs met.

It’s better to embrace the challenge and compelling benefits of feedback on short cycles. Here’s a rough diagram of a typical three-tier set of daily, weekly, and monthly release cycles.

The heart of it is a per-change or, at worst, a daily build (continuous integration). This build is picked up only by people who are in close contact with the project. This discipline keeps everyone in sync, and keeps the project from wandering into a broken state.

The weekly build (or some equivalent) is important whether at a large organization (where many remote teams share dependencies) or at a smaller startup (where the salespeople and management interact with the product daily). Tightening up the feedback loop of these internal customer proxies creates transparency, builds trust, and keeps the product from evolving off-track feature-wise.

Releasing something to customers every month can seem daunting in some large organizations. The biggest of the software beasts (Microsoft) has had challenges but also great benefits in doing so. And if you think you have a great plan set in stone (a very detailed set of requirements), all the feedback these releases will generate would seem to be just a source of endless distraction.

Don’t be foolish. Unless you’re delivering a 1-1 functional replacement for some existing product (and how often do we do that?), you desperately need that feedback. It keeps the team connected with the customer, motivated by the customer, doing right by the customer. Concerned about opening your kimono to competitors? Limit your audience to a trusted subset, like Apple’s AppleSeed program and most others do.

Once the team gets used to a cadence of regular releases, the practice becomes the heartbeat of the organization, keeping everyone on track, in touch with reality, and constantly learning.

This is part 3 of 10 Pitfalls of Agility on Large Projects. In part 2, we talked about how effective small teams need coordination to make an effective large organization, and what to do about it.

When cycles get shorter and our teams become more empowered to react to change, one fear is that accountability will get lost in all those changes.

Specifically, when something goes wrong, what is the root cause? Are my people failing? our processes failing? our plans unrealistic? How can management learn how to head off these failures in the future, if we aren’t making commitments and measuring progress against them?

Step one is to take some of this pressure off — in fact, to embrace failure as a path to learning, and taking a statistical approach to making the most of it.

Like a pharmaceutical firm screening new compounds, or venture capitalist building a portfolio of investments — a manager in a high-risk domain needs strategies to spread the bets to maximize opportunity while minimizing overall risk. This is basically Set-Based Design (Toyota’s Set-Based Concurrent Engineering).

Software development, in particular, is a research and development activity suited more to this approach, and much less of a traditional production activity.

Step two is creating an environment with much more transparency — it’s not about trusting people to execute to plan, rather it’s about trusting people to be transparent about the true progress and status of the project, so that everyone can adjust accordingly.

One mechanism is a public kanban board like the kind Corey has been exploring on this blog (from work with David Anderson at Corbis). By watching the board over time, throughput of the team and bottlenecks within the team become clear.

An electronic version is important if there are people (dependent teams, remote teams, or upper management) that can’t huddle around the board.

A Cumulative Flow Diagram is an electronic alternative that can be a great way to both summarize the flow of value, gain visibility into the history, and see important management events (like estimation troubles, or WIP getting out of hand, or new priorities causing the plan to grow out of control). This CFD is again from David Anderson, as described in his 2004 BorCon presentation.

In a future post, we’ll look at a way to create and manage by CFDs, even when each kanban (or feature) is not similarly sized — this involves also collecting time data (which then has other uses).

And, of course, if rework and bugs are tracked separately (as they usually are today), then traditional bug charts are critical to management.

Should a small team of 4-6 developers with a strong process like Extreme Programming layer this kind of data collection on to their process? Probably not. But as teams grow to 15, 50, or beyond — this kind of transparency is critical glue to keep management and teams coordinated, even while allowing each individual and each small group to work on short cycles and be highly responsive to change.

On your projects, have you seen other forms of data collection that are both lightweight, keep everyone in touch with reality, and help build trust?

This is part 2 of 10 of the 10 Pitfalls of Agility on Large Projects. In part 1, we talked about how planning a month or less ahead is not enough on a very large project, and what to do about it.

Here’s some of why people say that long-term, full-detail plans are essential:

1. You need the detailed work breakdown structure through the end of the project to produce estimates.
2. And you need estimates to schedule handoffs, deliverables, and other dependences between teams.
3. And as things do change, you need a plan through which to communicate those changes.

How can we satisfy these needs while still allowing small teams latitude to adapt and be agile?

Concern #1 is a red herring of sorts. Estimates constructed from a detailed WBS are not the most accurate, if you’re in a domain with significant unknowns (like most new product development). In these domains, you’ll get much better estimates from other methods like an experienced expert or group of experts using a technique like Wideband Delphi. For more, see a book like McConnell’s Software Estimation: Demystifying the Black Art

#2 is a dominant concern for organizations with long internal lead times. The motivation and techniques for attacking this problem in other ways is what lean thinking is all about. In short, agile/lean teams are much better equipped to handle changes in other teams’ plans, so they don’t need those plans to be as firm. It’s a self-reinforcing benefit of shorter cycles that pays off in spades.  The trick is keeping the peace during the (often long) transition period where an organization has a mix of long-cycle and short-cycle teams. These solutions to #3 can help during this transition.

Concern #3 speaks to allowing your high and low level plans to evolve as you progress and learn. But how do you keep them in sync?

• Have top-down goals and priorities that are clear about the customer and business need, but that don’t over-anticipate the technology to best fulfill that need.
• Be prepared to take top-down input and provide bottom-up feedback as part of your regular planning cycle (e.g. Scrum’s monthly sprint planning).
  • For inputs, the Scrum Product Backlog and processes around it are an effective way to turn top-down priorities into actionable technical workitems.
  • For feedback, provide actuals. In order to keep the trust of the organization, some kind of actuals in terms of feature throughput, earned value, or time data, etc. are essential. If agile teams “go dark” on a large organization, it becomes harder maintain trust when things go bad (as they invariably will from time to time on a large project).
  • For feedback, provide new estimates on the larger goals, based on this last cycle’s progress on specific workitems. To make this feasible, use a fast group estimation method like planning poker or its elder kin, wideband delphi.
• As the size of the team goes up and dependencies between teams get more tangled, coordination on just a monthly basis isn’t enough. Getting information more frequently than your usual planning cycle (or getting your planning cycle down to one or two week sprints) may become essential. The diagram above says weekly (which might match an org with more than 6-8 Scrum teams).

  This might also be the threshold where project management specialists are called for — don’t distract your project leads with sub-sprint communication and coordination between teams. But also don’t lose Scrum’s designed benefit of protecting teams from constant interrupts — the team controls whether their plan changes within a sprint. Project Managers can help make sure status and communication flow between teams even during a sprint, but they (like all stakeholders) should be prepared to hold new work and priority changes until teams plan their next sprint.

If you’re adopting short-cycle methods in a (long-cycle) large organization — what are your pain points that weren’t covered here. And how have you adapted?

This is part 1 of 10 of the 10 Pitfalls of Agility on Large Projects.

One of the most common, valid critiques of agile or lean processes is the time horizon of planning. Scrum focuses on one month sprints. XP advises shorter iterations (2 week, typical). Lean focuses on a single piece (one feature, in the case of design projects), delivered in the shortest possible time.

To many organizations and many people — especially when they first manage projects — these kinds of planning horizons are crazy and negligent. Rather, they strive to plan in as much detail as possible, out to the end of the project. They want to identify critical paths, plan resources, etc. It’s obvious, right? Ah, but I see you’re smiling.

Unfortunately, what you may know (but isn’t obvious to everyone) is this over-planning can be disastrous when there is any level of risk or significant unknowns. Almost any non-trivial software development project would fall in this category.

Usually, this highly detailed initial plan falls quickly out of touch with reality, and must be ignored by the team after a certain point. Good project managers will try to adapt the plan, but if they built in too much detail initially, they’ll find keeping it up to date impossible. Either way, this all can be damaging, as now the team often feels like they’re confused and failing, and management or stakeholders can quickly get dangerously out of touch — they’re still looking at and expecting that initial plan.

Beyond that, there are a host of other harms. First among them that you’re trying hard to lock down your plan at the earliest possible stage of the project, when you have the least understanding of what customers want, what the technology is capable of, and how quickly your team will be able to deliver it. You’ve not explored or mitigated any of the risks yet. You’ve basically committed to be as unresponsive as possible to the new things you learn as the project unfolds.

This is such a common problem — so much pain and so many failed projects could be avoided if it could be solved. And a simple conceptual solution is widely known, but is under-adopted.

It’s called Rolling Wave Planning. And it’s one effective way to unify the worlds of agile/lean and traditional project planning. Here’s a crude diagram illustrating how plans are detailed in the short term, but get progressively more generalized and flexible in the longer term.

How does this work?

• Identify just a few strategic, long-term product line and product goals. If they don’t fit on one side of one sheet of paper, they’re probably too long. These might look 1-2 years out for a large organization.
• Expand that into a short, prioritized list of near-term problems for your team to solve in the coming year.
• Bring in your more technical people to produce a short list of functionality the organization is capable of delivering in the coming months to make progress towards solving those problems. There should be lots of room to scale bells and whistles up or back, and especially to make technical choices about how to implement the functionality — you will reap significant efficiencies if your team can adjust as they learn more about the technologies involved and how long things will take to implement.
• Involve the whole team to do a detailed work-item level just a few weeks ahead. If you have a low-risk, well-understood domain, you could choose to approach this as a work breakdown structure with gantt chart and analysis. If you’re in a higher-risk domain (like new product development), use Scrum-style monthly sprints or, even better, a lean production flow. This is the schedule people can rally around for day to day work.
• At the end of that shortest planning cycle, percolate your learnings from the small, granular work through to the larger grained goals, then back into your next short-term planning cycle. The key to making this doable is again to not allow too much detail into the larger goals. Keep them high-level, meaningful, and always flexible.

In short, you match the level of detail to (1) how far out in time you’re planning and (2) how risky your domain is.

By doing so, you’ll gain a host of benefits, many of which relate to lean — reducing work in progress, making decisions at the last responsible moment (when you have the most information), pushing responsibility down and empowering the people who are closest to the problem, and generally being open to feedback and agile in response to the changing forces around your project.

Most of these pitfalls don’t apply to very small projects. They reflect some of the feedback you’d get when trying to drive agility at a large company with a lot of inertia behind existing ways of working (this list was born from experiences trying to drive mix of Scrum, XP, and lean concepts at Microsoft). They also embody some of the common trade-offs or dualities of projects.

We’ll keep it short (thus perhaps cryptic) in this post — but then each pitfall/solution pair will be expanded upon in future posts. Any pitfalls that simply don’t make sense, or any you’d add to the list?

Pitfall #1: Planning a month or less ahead is not enough.
Use rolling wave planning to create an evolving big picture.

Pitfall #2: Effective small teams need coordination to make an effective large organization.
Combine bottom-up (scrum-style) and top-down (traditional) planning.

Pitfall #3: We can’t afford to trust everyone on larger teams.
Turn up the knob on transparency (especially time and quality data).

Pitfall #4: The customer doesn’t want a release every month.
Release early and often internally, with longer cycles for expanded audiences.

Pitfall #5: Hundreds of people can’t check directly into “main” every day.
Separate dependent sub-projects and use incremental integration with branches.

Pitfall #6: Not all activities are best handled by generalists.
Apply lean techniques to more effectively handle specialization.

Pitfall #7: Our team/management expects to plan, and execution to plan.
Making firm commitments to something we don’t yet understand is counter-productive. As they come in, actuals have to trump estimates.

Pitfall #8: We are already in the dark. We need more documentation, not less.
On large projects, there are usually reams of wasted documentation. But it may be that “just enough” documentation and status-taking is still a lot.

Pitfall #9: Large teams will reject big changes in how we work.
Start with the way the team works today. Reflect and adapt towards agility.

Pitfall #10: Being agile on a large project is unrealistic and impossible to sustain.
There is no surer strategy for large-scale failure than large projects without empowered teams, short cycles, strong feedback, and a culture which embraces change and adaptation. All we can do is have the patience, persistence, and thoughtfulness to always keep driving in the right direction.