7 Agile Best Practices that You Don’t Need to Follow

There are many good ideas and practices in Agile development, ideas and practices that definitely work: breaking projects into Small Releases to manage risk and accelerate feedback; time-boxing to limit WIP and keep everyone focused; relying only on working software as the measure of progress; simple estimating and using velocity to forecast team performance; working closely and constantly with the customer; and Continuous Integration – and Continuous Delivery – to ensure that code is always working and stable.

But there are other commonly accepted ideas and best practices that aren’t important: if you don’t follow them, nothing bad will happen to you and your project will still succeed. And there are a couple that you are better off not following at all.

Test-Driven Development

Teams that need to move quickly need to depend on a fast, efficient testing safety net. With Test First Development or Test-Driven Development (TDD), there’s no excuse for not writing tests – after all, you have to write a failing test before you write the code. So you end up with a good set of working automated tests that ensure a high level of coverage and regression protection.

TDD is not only a way of ensuring that developers test their code. It is also advocated as a design technique that leads to better quality code and a simpler, cleaner design.

A study of teams at Microsoft and IBM (Realizing Quality Improvement through Test Driven Development, Microsoft Research, 2008) found that while TDD increased upfront development costs between 15-35% (TDD demands developers change the way that they think and work, which slows developers down, at least at first), it reduced defect density by 40% (IBM) or as much as 60-90% (Microsoft) over teams that did not follow disciplined unit testing.

But in Making Software Chapter 12 “How Effective is Test-Driven Development” researchers led by Burak Turhan found that while TDD improves external quality (measured by one or more of test cases passed, number of defects, defect density, defects per test, effort required to fix defects, change density, % of preventative changes) and can improve the quality of the tests (fewer mistakes in the tests, tests that are easier to maintain), TDD does not consistently improve the quality of the design. TDD seems to reduce code complexity and improve reuse, however it also negatively impacts coupling and cohesion. And while method and class-level complexity is better in code developed using TDD, project/package level complexity is worse.

People who like TDD like it a lot, so if you like it, do it. And even if you are not TDD-infected, there are times when working test first is natural – when you have to solve a specific problem in a specific way, or if you’re fixing a bug where the failing test case is already written up for you. But the important thing is that you write a good set of tests and keep them up to date and run them frequently – it doesn't matter if you write them before, or after, you write the code.

Pair Programming

According to the VersionOne State of Agile Development Survey 2012, almost 1/3 of teams follow pair programming – a surprisingly high number, given how disciplined pair programming is, and how few teams follow XP (2%) or Scrum/XP Hybrid (11%) methods where pair programming would be prescribed.

There are good reasons for pairing: information sharing and improving code quality through continuous, informal code reviews as developers work together. And there are natural times to pair developers, or sometimes developers and testers, together: when you’re working through a hard design problem; or on code that you’ve never seen before and somebody who has worked on it is available to help; or when you’re over your head in troubleshooting a high-pressure problem; or testing a difficult part of the system; or when a new person joins the team and needs to learn about the code and coding practices.

Some (extroverted) people enjoy pairing up, the energy it creates and the opportunities it provides to get to know others on the team. But forcing people who prefer working on their own or who don’t like each other to work closely together is definitely not a good idea. There are real social costs in pairing: you have to be careful to pair people up by skill, experience, style, personality type and work ethic. And sustained pair programming can be exhausting, especially over the long term – one study (Vanhanen and Lassenius 2007) found that people only pair between 1.5 and 4 hours a day on average, because it’s too intense to do all day long.

In Pair Programming Considered Harmful? Jon Evans says that pairing can have also negative effects on creativity:

Research strongly suggests that people are more creative when they enjoy privacy and freedom from interruption … What distinguished programmers at the top-performing companies wasn’t greater experience or better pay. It was how much privacy, personal workspace and freedom from interruption they enjoyed,” says a New York Times article castigating “the new groupthink”.

And in “Still Questioning Extreme Programming” Pete McBreen points out some other disadvantages and weaknesses of pair programming:

• Exploration of ideas is not encouraged, pairing makes a developer focus on writing the code, so unless there is time in the day for solo exploration the team gets a very superficial level of understanding of the code.
• Developers can come to rely too much on the unit tests, assuming that if the tests pass then the code is OK. (This follows on from the lack of exploration.)
• Corner cases and edge cases are not investigated in detail, especially if they are hard to write tests for.
• Code that requires detail thinking about the design is hard to do when pairing unless one partner completely dominates the session. With the usual tradeoff between partners, it is hard to build technically complex designs unless they have been already been worked out in a solo session.
• Personal styles matter when pairing, and not all pairings are as productive as others.
• Pairs with different typing skills and proficiencies often result in the better typist doing all of the coding with the other partner being purely passive.

And of course pairing in distributed teams doesn't work well if at all (depending on distance, differences in time zones, culture, working styles, language), although some people still try.

While pairing does improve code quality over solo programming, you can get the same improvements in code quality, and at least some of the information sharing advantages, through code reviews, at less cost. Code reviews – especially lightweight, offline reviews – are easier to schedule, less expensive and less intrusive than pairing. And as Jason Cohen points out even if developers are pair programming, you may still need to do code reviews, because pair programming is really about joint problem solving, and doesn’t cover all of the issues that a code review would.

Back to Jon Evans for the final word on pair programming:

The true answer is that there is no one answer; that what works best is a dynamic combination of solitary, pair, and group work, depending on the context, using your best judgement. Paired programming definitely has its place. (Betteridge’s Law strikes again!) In some cases that place may even be “much of most days.” But insisting on 100 percent pairing is mindless dogma, and like all mindless dogma, ultimately counterproductive.

Emergent Design and Metaphor

Incremental development works, and trying to keep design simple makes good sense, but attempting to define an architecture on the fly is foolish and impractical. There’s a reason that almost nobody actually follows Emergent Design: it doesn't work.

Relying on a high-level metaphor (the system is an "assembly line" or a "bill of materials" or a "hive of bees") shared by the team as some kind of substitute for architecture is even more ridiculous. Research from Carnegie Mellon University found that

… natural language metaphors are relatively useless for either fostering communication among technical and non-technical project members or in developing architecture.

Almost no one understands what a system metaphor is any ways, or how it is to be used, or how to choose a meaningful metaphor or how to change it if you got it wrong (and how you would know if you got it wrong), including one of the people who helped come up with the idea:

Okay I might as well say it publicly - I still haven't got the hang of this metaphor thing. I saw it work, and work well on the C3 project, but it doesn't mean I have any idea how to do it, let alone how to explain how to do it.
Martin Fowler, Is Design Dead?

Agile development methods have improved development success and shown better ways to approach many different software development problems – but not architecture and design.

Daily Standups

When you have a new team and everyone needs to get to know each other and more time to understand what the project is about; or when the team is working under emergency conditions trying to fix something or finish something under extreme pressure, then getting everyone together in regular meetings, maybe even more than once a day, is necessary and valuable. But whether everyone stands up or sits down and what they end up talking about in a meeting should be up to you.

If your team has been working well together for a while and everyone knows each other and knows what they are working on, and if developers update cards on a task board or a Kanban board or the status in an electronic system as they get things done, and if they are grown up enough to ask for help when they need it, then you don’t need to make them all stand up in a room every morning.

Collective Code Ownership

Letting everyone work on all of the code isn't always practical (because not everyone on the team has the requisite knowledge or experience to work on every problem) and collective code ownership can have negative effects on code quality.

Share code where it makes sense to do so, but realize that not everybody can – or should – work on every part of the system.

Writing All Requirements as Stories

The idea that every requirement specification can be written as User Stories in 1 or 2 lines on cards, that requirements should be too short on purpose (so that the developer has to talk to someone to explain what’s really needed) and insisting that they should all be in the same template form

“As a type of user I want some goal so that some reason…”

is silly and unnecessary. This is the same kind of simple minded orthodoxy that led everyone to try to capture all requirements in UML Use Case format with stick men and bubbles 15 years ago.

There are many different ways to effectively express requirements. Sometimes requirements need to be specified in detail (when you have to meet regulatory compliance or comply with a standard or integrate with an existing system or implement a specific algorithm or…). Sometimes it’s better to work from a test case or a detailed use case scenario or a wire frame or some other kind of model, because somebody who knows what’s going on has already worked out the details for you. So pick the format and level of detail that works best and get to work.

Relying on a Product Owner

Relying on one person as the Product Owner, as the single solitary voice of the customer and the “one throat to choke” when the project fails, doesn't scale, doesn't last, and puts the team and the project and eventually the business at risk. It’s a naïve, dangerous approach to designing a product and to managing a development project, and it causes more problems than it solves.

Many teams have realized this and are trying to work around the Product Owner idea because they have to. To succeed, a team needs real and sustained customer engagement at multiple levels, and they should take responsibility themselves for making sure that they get what they need, rather than relying on one person to do it all.

Certified Agile: The PMI-ACP Exam

I sat for the Project Management Institute’s Agile Certified Practitioner (PMI-ACP) exam earlier this week. The PMI-ACP tests your understanding of common Agile development methods, values and practices. It focuses on basic Agile principles, and on Scrum and XP in detail, as well as fundamentals of Lean and Kanban.

Unlike the PMP, there is no Book of Knowledge which defines best practices and a process framework for this certification. Instead there is a certification content outline that explains at a high level the tools, techniques, knowledge and skills that you will be expected to know and will be tested on, and a reference list of books to read which includes some of the usual suspects. Out of this list I’d recommend reading Mike Cohn’s books on Agile Estimating and Planning and User Stories - they are useful for the exam and they're worth reading regardless. If you’re not working in an XP shop you should also read Kent Beck’s Extreme Programming Explained to make sure that you understand XP, and you must read up on the basics of Lean and Kanban. And of course you need to memorize the Agile Manifesto and the Twelve Principles of Agile Software Development front to back.

But I know from writing the PMP several years ago that experience and general reading aren’t enough to prepare for a PMI certification exam. PMI wants everyone who holds a certification to know the same things, and to share the same values and to think and act the same way. There’s an emphasis on orthodoxy – you’re tested not on what you would do (based on your experience and common practical knowledge), but what you should do according to PMI's definition of what “the right way" is to do something. And PMI’s exams are as much a test of your ability to read and write an exam as they are of the subject matter, with trick questions and trip-up answers and questions which are purposefully hard to understand, and even some extra questions thrown in which don’t make sense at all. Writing a test like this is not fun, although the PMI-ACP exam is certainly not as hard as the PMP exam - you shouldn’t need the 3+ hours that you’re given to complete this test.

So like others, I decided to use an exam prep guide to finish my studying.

The PMI-ACP Exam: How to Pass on Your First Try by Andy Crowe is a quick overview of the material that you should know for the exam. Easy to read and easy to follow, it defines key terms and “doing Agile right”, roles and responsibilities and rituals and tools, and covers communication and collaboration issues, and includes some sample questions (and access to a sample online exam). This is not an especially insightful book, but I found it useful for last minute review and cramming.

I did most of my studying with Mike Griffiths’ PMI-ACP Exam Prep: A Course in a Book for Passing the PMI Agile Certified Practitioner (PMI-ACP) Exam, a much more complete study guide, and a good overview of Agile development that is worth keeping and reading on its own. This book builds on materials that Griffiths published earlier on his blog and it is especially good on Agile reporting tools.

Griffiths is one of the experts who created the PMI-ACP program and so he understands what you need to know in depth, and he is a good writer. However, his book is harder to study from than Crowe’s, because it contains a lot more details and because it is structured around the artificial domains that PMI uses to describe Agile development. This results in several discontinuities, where an idea or practice is introduced under “Value Driven Delivery” and then continues later under “Adaptive Planning” or “Continuous Improvement” or one of the other domains (it is not necessary by the way to learn the domains for the exam).

If you have solid experience with Agile development (which you need to in order to meet the qualifying bar) especially Scrum and XP, you should be able to pass the exam with the help of Griffiths’ guide and some general reading to fill in gaps.

Studying for the PMI-ACP has made me examine Agile development ideas and practices in more detail (which is why I decided to apply for the certification). But it hasn't changed how I think about Agile practices and methods or how I think you should follow them. I am just as convinced today as I was before that the key is not following some method in a pure way, but instead to build your own toolkit, to borrow what works from different methods and adapt them to your specific requirements, constraints and situation. And the more that you know and understand about Agile methods and practices, the more tools you have for your toolkit.

Design Doesn't Emerge from Code

I know a lot of people who are transitioning to Agile or already following Agile development methods. Almost all of them are using something based on Scrum at the core, mixed with common XP practices like Continuous Integration and refactoring and automated unit testing – pretty much how Mike Cohn says things should be done in his book Succeeding with Agile.

Emergent Design in Scrum and XP

But none of them are doing emergent design as Cohn describes it, or as Kent Beck explains how design is done in Extreme Programming: trying to get away without any upfront design and architecture work, coding features right away and relying on test-first development, refactoring and technical spikes to work out a design on the fly, one week or two weeks at a time.

“For the first iteration, pick a set of simple, basic stories that you expect will force you to create the whole architecture. Then narrow your horizon and implement the stories in the simplest way that can possibly work. At the end of this exercise you will have your architecture. It may not be the architecture you expected, but then you will have learned something.” Kent Beck

You don’t need upfront architecture and design?

Maybe it’s because everyone I know is working at scale – building big enterprise systems and online systems used by lots of customers, systems that have a lot of constraints and dependencies. Many of them are working on brownfield projects where you need to understand the existing system’s design and implementation first, before you can come up with a new design and before you can make any changes. Performance-critical, mission-critical systems in highly-regulated environments.

Emergent, incremental design doesn’t work for these cases. And it doesn’t scale to large projects or any project that has to be delivered along with other projects and that has specified integration points and dependencies – which is pretty much every project that I've ever worked on.

Bob Martin, another one of the people who helped define how Agile development should be done, thinks that this incremental approach to design is, well…

“One of the more insidious and persistent myths of agile development is that up-front architecture and design are bad; that you should never spend time up front making architectural decisions. That instead you should evolve your architecture and design from nothing, one test-case at a time. Pardon me, but that’s Horse Shit.”

Martin goes on to say that

“there are architectural issues that need to be resolved up front. There are design decisions that must be made early. It is possible to code yourself into a very nasty cul-de-sac that you might avoid with a little forethought.”

Architecture and Design in Disciplined Agile Delivery

The way that most people that I know approach Agile development is better described by Scott Ambler in Disciplined Agile Delivery, a model for scaling Agile to larger systems, projects and organizations. As Ambler’s research shows, almost all teams (86%) spend at least some time (on average a month or more) on upfront on planning, scoping and architecture envisioning – what he calls the “Inception Phase” (borrowing from Rational’s Unified Process) or what most others call “Sprint 0” or “Iteration 0”.

This is time spent to understand the scope of the system at a high-level at least, and the constraints and dependencies that the project needs to work within. Time to model the main chunks of the system and their interfaces, and to choose a technical direction to start with.

Upfront architectural and design work doesn't have to take a lot of time. As Ambler points out, for many teams (except for some startups), a lot of architectural decisions have already been made for you:

“In practice, it’s likely you won’t need to do much initial architectural modeling: a large majority of project teams work with technical architecture decisions that were made years earlier. Your organization will most likely already have chosen a network infrastructure, an application-server platform, a database platform, and so on. In these situations your team will need to invest the time to understand those decisions and to consider whether the existing infrastructure build-out is sufficient (and if not, identify potential improvements).”

It’s when you have a real greenfield development project, when you don’t have anything to leverage and you’re doing something completely new, that you should spend more time on upfront thinking about design – not less.

Can you “be Agile” without Emergent Design?

Of course you can. Bob Martin points out that there’s nothing in “Agile Development” that says that you shouldn't do design upfront – as much design as you need to for the size of the system that you are building and the environment that you are working in.

You can and should do iterative, incremental design and development starting with a plan of where you are going and how you think that you are going to get there. As you go along and prove out your design and respond to feedback and deal with changes in requirements, this is where incremental design actually does come into play – handling changes in direction, filling in gaps, correcting misunderstandings. The design will change and maybe become something that you didn't expect. But you need a place to start from – designs don’t just emerge from code.

Hardening Sprints. What are they? Do you need them?

For anyone who is developing software using Scrum, XP or another incremental development approach, the idea of a “hardening sprint” or a “release iteration” is bound to come up. But people disagree about what a “hardening sprint” should include, when you need to do one, and if you should do them at all. There is a deep divide between people who recognize that spending some time on hardening is needed for many environments, and people who are adamant that allocating some time for hardening is a sign that you are doing some things – or everything – wrong.

Hardening to make sure that Done means Done

In a hardening sprint, the team stops focusing on delivering new features or architecture, and instead spends their time on stabilizing the system and getting it ready to be released.

For some people, hardening sprints are for completing testing and fixing work that couldn't be done – or didn't get done – earlier. This might include UAT or other final acceptance testing if this is built into a contract or governance model.

Mike Cohn recognizes that teams may need a “release sprint” at the end of each release cycle, because the team’s definition of “done” may not be enough – that a "potentially shippable product" and a system that is actually “shippable” or ready for production aren't the same thing. He suggests that after every 3-5 feature iterations, the team may want to schedule a release sprint to do work like expensive manual system and integration testing and extra reviews, whatever is needed to make sure that what they think is done, is actually done.

Anand Viswanath, in “The end of regression, stabilisation, hardening or release sprints”, describes a common approach where teams schedule 1 or 2 stabilization sprints every 4-6 iterations to do regression testing and system testing in a staging environment, and then fix whatever bugs are found. As he points out, it’s hard to predict how much testing might be required and long it will take to fix whatever problems are found, so the idea is to time box this work and then triage the results.

Because this can be an expensive and risky and stressful way to work, Vishwanath recommends following Continuous Delivery to build an automated test pipeline through to staging in order to catch as many problems as early as possible. This is a good idea, but most large projects, especially projects starting from a legacy code base, will still probably need some kind of hardening or integration testing phase at regular points regardless of what kind of continuous testing they are doing.

Some testing, like interoperability testing with other systems and operational testing, can’t be done effectively until later, when there is enough of a working system to do end-to-end testing, and some of this testing can only be done in staging (if you have a staging environment), or in production. For some systems, load testing and stress testing and soak testing also needs to be left to later, because these teams don’t have access to a big enough test system to run high load scenarios before they get to production.

Is Hardening a sign that you aren't doing things right?

Not everyone thinks that scheduling a hardening sprint for testing and fixing like this is a good idea:

“[a hardening sprint] might take the cake for stupid things invented that has lead to institutionalized delusion and ‘Agile’ dysfunction.” Janelle Klein, Who Came up with the “Hardening Sprint”?

For many people, a hardening sprint or release sprint is a bad “process smell”: a sign that the team isn't working properly or thinking clearly:

“The problem with “hardening sprints” is that you are lying. You make believe your imaginary burndown during the initial sprints shows that you are approaching Done. But it’s a lie--you aren't getting any closer to being ready for Production until you begin your Test phase. You wrote a pile of code that you didn't test adequately. You don’t know how good it is, you don’t know how much work you have left to do, and you don’t know how much longer it will take, until you are deep into your Test phase.” Richard Kasperowski, Hardening sprints? Sorry, you’re not Agile

Ron Jeffries says that a hardening sprint for testing and fixing is a clear anti-pattern. I agree: if you need a separate sprint to fix bugs, then you’re doing something wrong. But that doesn't mean that you won’t need extra time to fix things before the system goes live – knowing that it is wrong doesn't make the bugs go away, you still have to fix them. As somebody else on this same discussion thread points out, there is a risk that your “definition of done” could fall short of what is actually needed by the customer, so you should plan for 1 or more hardening sprints before release, to double-check and stabilize things, just in case.

In these cases, the need for hardening sprints is a sign of a team’s immaturity (from a post by Paul Beavers):

1. A beginning agile team will prefer to schedule 6 hardening iterations after a 12 iteration development plan. This is “agile” to the hard core “waterfall guy”.
2. As time goes by, the team will mature a bit and you will see the seasoned agile team will shrink the number of required hardening iterations at the end, just because they understand they need to “fix” the high severity bugs as they go and QA understands they need to test closer and better early up in the release cycle.
3. Further down the road the team will notice that by adding a hardening iteration in the middle of the development cycle (and flushing out even lesser priority bugs earlier on in the process), it will help them to maintain cadence later on.
4. The final step of maturity is there when the team starts understanding “hardening is not required any more”, because they made fixing bugs part of their daily routines.

Hardening is whatever you need to do to Make the System Ready for Production

Another way of looking at hardening, is that this is when you stop thinking about features and focus all of your time on the detailed steps of deploying, installing and configuring the system and making sure that everything is working from end-to-end. In a hardening sprint, your most important customers are operations and support, the people who are going to make sure that the system is running, rather than the end users.

For some teams, this kind of hardening can come as an ugly and expensive surprise, after they understand that what they need to do is to take a working functional prototype and make it ready for the real world:

“All those things that got skipped in the first phase - error handling, monitoring, administration - need to get put into the product.” Catherine Powell, The "Hardening Myth"

But a hardening sprint can also be when when you take care of what operations calls hardening: reviewing and preparing the production environment and securing the run-time, tightening up access to production data, double-checking system and application configs, making sure that auditing is enabled properly, wiring the system in to operations monitoring and metrics collection, checking system dependencies like platform software versions and patch levels (and making sure that all of the systems are consistent, that there aren't any snowflakes), completing final security reviews and other review and release gates, and making sure that the people installing and running the software have the correct instructions.This is also when you need to prepare your roll-back plan or recovery plan if something bad happens with the release, and test your roll-back and recovery steps. Walk through and rehearse the release process and checklists, and make sure that everyone is prepared to roll out patches quickly after the release is done.

Hardening is something that you have to do

Some people see an obvious need for hardening sprints. For example, Dean Leffingwell includes hardening sprints in his “Scaled Agile Framework”, because there is some work that can only really be done in a final hardening phase:

• Final exploratory and field testing
• Checklist validation against release, QA and standards governance
• Release signoffs if you need them
• Ops documentation
• Deployment package
• Communicate release to everyone (hard to do in big companies)
• Traceability etc for high assurance and regulatory compliance

Leffingwell makes it clear that hardening shouldn't include system integration, fixing high priority bugs, automating test scripts, user documentation, regression testing and code cleanup. There is other work that should be done earlier – but in the first year or so, will probably need to be done in a late hardening phase:

• Cross-component integration, integration with third-party/customer
• Integrated system-level testing
• Final QA sign-offs
• User doc finalization
• Localization

Dan Rawsthorne explains that teams need at least one release sprint at first to get ready for release to production, because until you've actually done it, you don’t really know what you need to do. Release sprints include tasks like:

• Exploratory testing to double check that key features are working properly
• Stress testing/load testing/performance testing – testing that is expensive to setup and do
• Interoperability testing with other production systems
• Fix whatever comes out of this testing
• Review and finish off any documentation
• Train support and sales and customers on new features
• Help with press releases and other marketing material

The Software Project Manager’s Bridge to Agility anticipates that teams will need at least a short hardening iteration before the system is ready for release, even if they frontload as much testing as possible. A release iteration is not a test-fix phase – it’s when you prepare for the release: capturing screenshots for marketing materials, final tests, small tweaks, finish documentation for whoever needs it, training. The authors suggest however that if some developers have any time left over in the release iteration, they can do some refactoring and other cleanup – which I think is bad advice, given that at this point you don’t want to be introducing any new variables or risks.

Disciplined Agile Delivery, a method that was developed by Scott Ambler at IBM to scale Agile practices to large organizations and large projects, includes a Transition Phase before each release to take care of:

• Transition planning and coordination
• End-of-lifecycle testing and fixing
• Testing and rehearsing deployment
• Data setup and migration
• Pilots and beta testing (short UAT if necessary)
• Reviewing and finalizing documentation
• Preparing operations and support
• Stakeholder training

This kind of transition can take almost no time, or it can take several weeks, depending on the situation.

Hardening – taking some time to make sure that the system is really ready to be released – can’t be avoided. The longer your release cycles, the further away development is from day-to-day production, the more hardening you need. Even if you've been doing disciplined testing and reviews in stream, you’re going to find some problems at the end. Even if you planned ahead for transition, you’re going to run into operational details that you didn't know about or didn't understand until the end.

When we first launched our platform from startup, we had to do hardening and stabilization work before going live to get the system ready, and some more work afterwards to deal with operational issues and requirements that we weren't prepared for. We included time at the end of subsequent releases for extra testing, deployment and roll back planning, and release coordination.

But as we shortened our release cycle, releasing less but more often, and as we built more fail-safes into the system and as we learned more about what we needed to do in ops, and as we invested more in simplifying and automating deployment and everything else that we could, we found that we didn't need time any outside of our regular iterations for hardening. We’re still doing hardening – but now this is part of the day-to-day job of building and releasing software.

Agile’s Customer Problem

Agile methods like Scrum and XP both rely on a close and collaborative relationship and continual interaction with the customer – the people who are paying for the software and who are going to use the system. Rather than writing and reviewing detailed specifications and working through sign-offs and committees, the team works with someone who represents the interests of the customer to define business features and to decide what work needs to be done and when. One of the key problems in adopting these approaches is finding the right person to play the important role of the Customer (XP) or Product Owner (Scrum). I’ll use both terms interchangeably.

The team reviews their work with the Customer, the Customer answers any questions that they have and sets the team’s direction and priorities and makes sure that the team is focused on what is important to the business, owns and manages the requirements backlog, writes acceptance tests and decides when the software really is done.

A team’s success depends a lot on how good the Customer or Product Owner is, their knowledge and experience, their commitment to the project, how they make decisions and how good these decisions are. Mike Cohn in his book Succeeding with Agile explains that Product Owners have to be:

• committed to the team and available to answer questions, get the information that the team needs when the team needs it;


• an expert in the business: not only do they have to understand the domain, but they also need to understand what’s important strategically to the business and what’s important to the user community;


• a good communicator within the team and outside of the team;


• a good negotiator so that they can balance the needs of the team and the needs of different stakeholders;


• empowered – they must be able to make decisions on behalf of the customer – and they need to be willing to make tradeoffs and tough decisions when they have to.

An effective Product Owner also needs to be detail-oriented so that they can understand and resolve fine details of functionality and write functional acceptance tests. They should understand the basics of software development, at least the boundaries of what is and is not possible, what is hard to do and what isn’t and why so that they can appreciate technical dependencies and technical risks. They need to at least understand the rules of Scrum or XP – what’s expected of them, and how to play the game.

And they should understand the basics of project management and risk management. Because in the end, the Product Owner is the person who decides what gets done and what doesn’t.

The Product Owner is a product manager, project manager and business analyst all rolled into one.

Oh, and… they also need to be “collaborative by choice”, “agile in all things”, and…” fun and reasonable”.

Being in Two places at Once

The Product Owner has to work closely with the team, in touch with what the team is working on, to make sure that they can keep moving forward. But the Product Owner also has to stay involved in the business to understand what is going on and what is important. They have to be both inward-facing (working with the team, planning, holding reviews, attending meetings, prioritizing, helping to manage the backlog, defining requirements, answering questions and clarifying information) and outward-facing (working with the project’s sponsors and with the users of the system, making sure that the business understands what is happening in the project, making sure that they understand business priorities and competitive positioning and business trends and when any of this changes and how this could affect the project). They have to be in two places at once, which is physically impossible if the development team and the business aren’t co-located.

The Product Owner and Politics

There are political risks in the team’s relationship with the Product Owner, and in the Product Owner’s position and influence within their own organization. The Product Owner has to play politics with the team and inside the business, trying to promote the interests of the team and the project, reconciling conflicts between different stakeholders, trying to get and keep stakeholders onside, building coalitions. Their success, and the project’s success, depends on their ability to negotiate these issues.

Scrum assumes that the Product Owner is not only committed and talented and in touch with the business’s strategic priorities and with the concerns and needs of front line workers; but it also assumes that the Product Owner will always put the interests of the business ahead of their own interests. But a good Product Owner is usually an ambitious Product Owner – they are interested in the project as an opportunity to advance their career. Projects effect change, and with every change there are winners and losers. There is the real risk that the Product Owner’s success may put them in conflict with other important stakeholders in the business – by focusing on making their Product Owner happy, the team may be making enemies somewhere else in the organization without knowing it.

A Customer, or Many Customers?

Not only does the Product Owner decide what is important and what is going to get done, they are responsible for the project’s budget, and they are accountable for the project’s success. According to Ken Schwaber’s Agile Software Development with Scrum (the original definition of Scrum) the Product Owner is “the person who is officially responsible for the project”, “the one throat to choke” if the project fails or goes off the rails.

Expecting one person to take on all of this responsibility and this much work is unrealistic. It’s too much responsibility, too much risk, and too much work. For many Product Owners, it’s more than a full-time job – a direct contradiction to Agile values that put people first and emphasize realistic working hours and sustainable pace for the team.

This has been a problem since the beginning of Agile: a few months after the launch of the initial phase of C3 (the first XP project), the Customer representative quit due to burnout and stress, and could not be replaced, and the project was eventually cancelled.

Scrum still demands that the Product Owner role must be played by one person.

This doesn’t make sense, given that another fundamental underlying Agile principle is that people working together collaboratively make better decisions than one person working alone (“the Wisdom of Crowds”). If true, then why are the critical decisions about prioritization and direction and vision for the project made by one person?

The people behind XP eventually recognized that the simple idea of a Customer demanded too much from one person, that the workload and responsibility need to be shared by a Customer team. A Customer team means that you get the advantage of multiple perspectives, people with different specialties and experiences, and you have more help with answering questions and making decisions. It’s more sustainable and practical.

But this comes with its own set of problems:

• The development team has to reconcile differences in abilities, differences in understanding, different priorities, biases and political conflicts and personal conflicts within the Customer team.


• More time has to be spent explicitly keeping the Customer team itself in synch. There are more chances of mistakes and misunderstandings and dropped balls.


• Somebody still has to be in charge, make the important decisions – what Mike Cohn calls “the-buck-stops-here” person. The development team has to know that Customer decisions will not be over-ridden within the Customer team so that they can commit to getting work done.

The Customer in Maintenance

Maintenance and enhancement, where most of us will spend a lot of our careers, shows other problems with the Product Owner idea. First, it’s hard enough to get someone with the talent and drive and selflessness to represent the customer on a high-profile, strategic development project. It’s much harder to get anything close to this same level of commitment and talent for smaller projects, or for ongoing maintenance work. People with this knowledge and ability are likely to be running or supporting some important part of the business, not answering questions and helping to prioritize issues for your maintenance team.

And if you are lucky enough to find someone good, it’s hard to keep them – unlike a project, maintenance work doesn’t have a clear end date, so the team will need to get used to working with different Customers at different times, with different working styles, different agendas and different strengths.

The Product Owner is supposed to act as the single voice for the customer. But for a production system you are more likely to have too many voices, too many different people with different priorities and demands, all working for different parts of the business, all talking to different people on your team, trying to get what they need or want done. Or for some old legacy systems you may run into the opposite problem – nobody wants to take ownership of the system or its data, nobody knows enough or wants to be responsible for making business decisions.

Be your own Customer

All of these challenges don’t mean that you can’t work with the Product Owner model – obviously lots of teams are following Scrum and XP in one way or another. But you need to recognize the limitations and risks of this approach, and be prepared to fill in.

For example, many development and maintenance teams who work in a different location and especially a different timezone from the business fall back on a Customer Proxy: a business analyst or somebody else on the team who can help fill part of the Customer role, and work with people in the business to help answer questions and confirm requirements and priorities. It’s not as efficient as working directly with the business, but sometimes there isn’t a choice.

Even strong Customers need help at times. Many ScrumMasters and Product Owners find ways to split up the responsibilities more equitably and help each other out.

The Scrum Master or team lead or senior developers or senior testers, whoever is playing a technical leadership role on the team may have to step in and help fill in when the Customer isn’t available, when they are over-worked and can’t keep up, when they don’t understand, when they aren’t qualified to make a decision, or when they don’t care. To reconcile technical and business requirements and the needs of different stakeholders, and make technical and business trade-offs and long-term and short-term trade-offs. To communicate with business stakeholders. To follow-up on outstanding issues and unanswered questions and try to get answers from someone in the business. To write the acceptance tests for the customer – a common problem on Agile teams is that nobody on the business side is willing to help write acceptance tests, but they are willing to jump on the team when something is done wrong.

Be prepared to make more mistakes working this way – you will have to work with imperfect and incomplete information, sometimes you’ll have to make a best guess and go with it, and you will get requirements and priorities wrong. Test everything that you can, and get the product out to the business as quickly and as often as you can, and be prepared for negative feedback. You may not be able to build as close a relationship with the business as you could with a strong and committed Customer.

It’s a compromise, but it’s a necessary compromise that many teams have no choice but to make. As Mike Cohn points out in The Fallacy of One Throat to Choke, in the end it’s the team that fails, not just the Customer.