My January 2010 DDJ Agile Update, Tragic Mistakes When Adopting Test Driven Development (TDD)
, is now online. In the article I summarize what I consider to be common, and tragic, mistakes that I'm seeing organizations make when they attempt to adopt TDD.
These mistakes include:
The article also goes into potential benefits of TDD as well as potential challenges that you're face when adopting it.
When you’re inside, safe in the warmth of your home watching snow fall on your driveway outside, all snowflakes look the same. But, when you look at a snowflake up close, particularly when you do so under a microscope, you quickly discover that all snowflakes are in fact unique.
It’s the same with IT projects.
When you look at them from afar, particularly
from a very high level, they all look the same.
However, when you look at them up close, you quickly discover that they too
The agile scaling factors
, which are really just general scaling factors applicable to all types of IT
project regardless of paradigm, help to make this very clear.
For example, when it comes to team size some teams
are small, less than ten people perhaps, some are medium sized, and some are very
large (with hundreds of people).
comes to distribution some teams are co-located in the same room, some teams
have team members in different cubicles in the same building, some have people
working in different buildings, and some even have people working in different
Many agile teams work in
regulatory environments, in fact the July 2009 DDJ State of the IT Union survey reports that one third of agile teams must
comply to industry regulations, although clearly many agile teams do not have
this as a concern. That’s only three
scaling factors. The point is that a
small, co-located team working in a non-regulatory environment will work much
differently than a fifty-person team working in three different locations,
which in turn works differently than a two hundred person team in the same
building working in a regulatory situation.
Different teams, facing different scaling issues will work in different
ways – unique snowflakes from a process point of view.
The SEMAT vision
has recently been posted online. SEMAT is short for Software Engineering and Method and Theory (SEMAT) and I am one of several signatories and a provider of input into the effort.
There are several reasons why I'm involved with SEMAT:
- The industry clearly needs something like this. Ivar Jacobson has been writing and speaking for awhile now about how our industry behaves in a similar manner to the fashion industry
-- we lurch from one cool idea (the fashion) to another and few of us
observe that the current fashion is often just a rehash of fashion(s) from the
- The right people are involved. The SEMAT initiative has
attracted a wide range of industry experts, including both the old
guard, the new "agile guard", and people in between. Arguably we may
be short a few people, the data community isn't well represented and
I'm not sure we have the systems community covered well, but we can
address those challenges in time.
We'll achieve something. We may not pull of the entire vision, but we
are going to produce something of value and I hope that it has a
positive impact on the industry. Time will tell.
I have several thoughts about the SEMAT vision
which I'd like to share with you:
- The vision is coherent. A lot of reasoned effort went into it's development as you can see when you read it.
- It will be a challenge to identify a non-trivial kernel. Even developing a kernel language will be hard as people will often stick to their preferred terms. For example, is it an iteration, a sprint, or a time box?
- Practitioners may not notice. It will also be a significant challenge to get practitioners interested in the SEMAT effort and more importantly to leverage the material. For example, the patterns community has a long history of producing great work which for the most part is ignored by the vast majority of practitioners, with the exception of a handful of the hundreds of patterns out there. So, although SEMAT is likely to produce some great ideas, will anyone care?
- Academics may not notice. I suspect that this will be less of a problem than practitioners not noticing, but it's still a possibility.
- Position papers from many of the signatories, including myself, will soon be published at the SEMAT site. Several non-signatories have been invited to submit papers as well.
- A workshop is being held in the third week of March in Zurich. At this workshop the people who published position papers will flesh out our ideas.
- I'll blog about these things as they occur.
My new paper Scaling Agile: An Executive Guide
is now available. As the title suggests the paper overviews how to scale agile strategies to meet your organization's unique needs. The executive summary:
Agile software development is a highly collaborative, quality-focused approach to software and systems delivery, which emphasizes potentially shippable working solutions produced at regular intervals for review and course correction. Built upon the shoulders of iterative development techniques, and standing in stark contrast to traditional serial or sequential software engineering methods, agile software delivery techniques hold such promise that IBM has begun to adopt agile processes throughout its Software Group, an organization with over 25,000 developers. But how can practices originally designed for small teams (10-12) be “scaled up” for significantly larger operations? The answer is what IBM calls “agility@scale.”
There are two primary aspects of scaling agile techniques that you need to consider. First is scaling agile techniques at the project level to address the unique challenges individual project teams face. This is the focus of the Agile Scaling Model (ASM).
Second is scaling your agile strategy across your entire IT department, as appropriate. It is fairly straightforward to apply agile on a handful of projects, but it can be very difficult to evolve your organizational culture and structure to fully adopt the agile way of working.
The Agile Scaling Model (ASM) defines a roadmap for effective adoption and tailoring of agile strategies to meet the unique challenges faced by a software and systems delivery team. Teams must first adopt a disciplined delivery lifecycle
that scales mainstream agile construction techniques to address the full delivery process, from project initiation to deployment into production. Then teams must determine which agile scaling factors
– team size, geographical distribution, regulatory compliance, domain complexity, organizational distribution, technical complexity, organizational complexity, or enterprise discipline, if any — are applicable to a project team and then tailor their adopted strategies accordingly to address their specific range of complexities.
When scaling agile strategies across your entire IT organization you must effectively address five strategic categories — the Five Ps of IT
: People, principles, practices, process, and products (i.e., technology and tooling). Depending on your organizational environment the level of focus on each area will vary. What we are finding within many organizations, including IBM, is that the primary gating factor for scaling agile across your entire organization is your organization’s ability to absorb change.
Rolf Nelson recently recorded a short (5 min) podcast about IBM Rational
(RTC). RTC is a complete agile collaborative development
environment providing agile planning, source code management, work item
management, build management, and project health, along with integrated
reporting and process support. I've worked with RTC for a couple of years now and have been truly impressed with it. What should be of interest to many people is the Express-C version which is a free, fully-featured, 10-license version of RTC which can be easily downloaded from www.jazz.net
Yesterday I was involved with a workshop around agile development at scale. At one point in the conversation we started talking about the relationship between cost and quality. Some of the people in the workshop were relatively new to agile and still believed the traditional theory that to build in high quality it costs more, sometimes substantially more. This does appear to be true on traditional waterfall projects, but some people were making the mistake that this was an "natural law of IT" which also must apply to agile project teams. I naturally jumped on that idea and described how agile developers have found that writing high quality code leads to lower development costs and shorter time to value, in direct contradiction to traditional theory. A few people struggled with the idea for a bit, and one was pretty adamant that in some cases the need for very high quality does in fact lead to greater cost and time. He talked about his experiences on large-scale Rational Unified Process(RUP)
projects and in particular how some URPS (usability, reliability, performance, and supportability) requirements can increase your cost. At this point Per Kroll, co-author of Agility and Discipline Made Easy: Practices from OpenUP and RUP
, jumped into the conversation and pointed out although higher quality does lead to lower cost in most cases, using Toyota's lean approach to manufacturing as an example, that the agile community didn't completely have the relationship between quality and cost completely correct. My spidey sense told me that a learning opportunity was coming my way.
Per and I had an offline discussion about this to explore what he'd been observing in practice. In most situation it appears to be the case that higher quality does in fact lead to lower costs and shorter time for delivery, something that Per and I had observed numerous times. This happens because high quality code is much easier to understand and evolve than low quality code -- the agile community has found that it is very inexpensive to write high quality code by following practices such as continuous integration
, developer regression testing [or better yet test-driven development(TDD)
], static code analysis
, following common development conventions, and agile modeling strategies
. When you "bake in" quality from the start through applying these techniques, instead of apply traditional techniques such as reviews
and end-of-lifecycle testing (which is still valid for agile projects, but should not be your primary approach to testing) which have long feedback cycles
and therefore prove costly in practice. But, as we've learned time and again, when you find yourself in more complex situations of Agility@Scale sometimes the mainstream agile strategies fall down. For example, in situations where the regulatory compliance scaling factor is applicable, particularly regulations around protecting human life (i.e. the FDA's CFR 21 Part 11), you find that some of the URPS requirements require a greater investment in quality which can increase overall development cost and time. This is particularly true when you need to start meeting 4-nines requirements (i.e. the system needs to be available 99.99% of the time) let alone 5-nines requirements or more. The cost of thorough testing and inspection can rise substantially in these sorts of situations.
In conclusion, it does seem to be true in the majority of situations, which is what the level 1 rhetoric focuses on, that higher quality leads to lower development costs. But at scale this doesn't always seem to hold true.
PS -- Sorry for the corny title, but a couple of days ago at the Rational Software Conference I had the pleasure of interviewing Jamie Hyneman and Adam Savage from the Discovery Channel's Mythbuster's show as part of the conference keynote. They're great guys, BTW, who have had a really positive impact on motivating children to be interested in science (apparently kids like to see stuff get blown up, go figure).[Read More
The Scrum community has adopted a different set of terms than the other agile methodologies. This is done on purpose to help people realize that Agile approaches are different than traditional approaches, which can help in their adoption, but it can also hinder people's understanding because some of the terminology is not only non-standard it really doesn't make much sense. Because of this I'm often asked by people that I'm coaching to convert back and forth between terms, and recently wrote a detailed article on the subject. The following summarizes the mapping:
- Daily Scrum Meeting ==> Daily Stand-up Meeting
- Product Backlog ==> Work Item List
- Scrum Master ==> Team Lead or Team Coach
- Sprint ==> Iteration or Time Box
For more details read my article Translating Scrum Terminology
which includes explanations of a wider range of Scrum terms and discussions of why some of them really are questionable. Further reading:
Recently I visited a customer who had adopted Scrum. They were a few sprints, what Scrum calls iterations, into the project and were running into some difficulties. Although I was primarily brought in to educate senior management on disciplined agile software development, I was also asked to sit in on the team’s daily stand-up meeting so that I could hopefully provide some suggestions as to how to address the problems they were running into.
Their work area was fairly typical. They had some whiteboards which they were using for project planning and tracking, with sticky notes to indicate what work had been taken on by each team member. The current status of the task (not yet started, in progress, and completed) was indicated by putting each sticky note in a corresponding column for the status and corresponding column for the team member. This allowed everyone on the team to easily share their status and to see the status of everyone else. On the sides were sketches of the architecture as well as some business oriented models. In addition to Scrum the team had adopted several practices from Agile Modeling, in this case they had done some initial requirements envisioning
and architecture envisioning
, as well as practices from Extreme Programming (XP) for construction. In short, they had followed a fairly common strategy of combining practices from various agile methods.
This would have worked perfectly fine if they had tailored the practices to reflect the situation that they were in, but instead they adopted them "straight out of the book". First, the team was distributed, with most of the team in the location that I was visiting but some people located in two other distant cities. Therein was the source of most of their problems. The people at the other two locations weren’t getting much value out of the daily stand-up meetings, even though they would dial in, because they couldn’t see the project status information. Although people at this location were trying their best to represent these distant people in the daily stand-ups it wasn’t working well – their status information wasn’t being kept up to date and for some people it was a bit of mystery as to what they were actually working on at all.
This team also had 30 people in it, which isn’t a big deal although it can stretch the limits of the simple modeling and planning tools (in this case paper and whiteboards) that they were using. Because the team was larger they were investing a fair bit of time creating burn down charts at both the iteration/sprint and project levels. One of the unfortunate implications of using manual tools for project management is that any associated metric/status reporting in turn becomes manual as well. Considering how the agile community is so concerned with working efficiently, I find it comical that we have a tendency to overlook our own potentially unnecessary bureaucracy such as this.
The problem was that the team was applying strategies, in this case using sticky notes and whiteboards to capture the detailed iteration plan, applying similar strategies to capture key models, and were verbally relaying of status information between sub-teams. There are perfectly fine strategies for smaller co-located teams, but not so good for large or distributed teams. The solution was to recognize that they were in an Agility@Scale situation and needed to tailor their approach to reflect this fact. In this case they needed to forgo some of the manual tools and instead use electronic tooling such as Rational Team Concert (RTC) to share information across disparate locations, in particular the work assignment and corresponding status information. RTC also creates common agile reports such as burn-down charts based on the activities of the developers, providing accurate (nearly) real-time information while removing the burden of status reporting. The RTC project dashboard does more than just this, to see an actual example of one visit www.jazz.net
to see the dashboard for the RTC development team itself. You can also see their actual work item list too, a more advanced version of Scrum’s product and sprint backlogs.[Read More
It's customary to start a blog by describing the vision for it. Although this vision will undoubtedly evolve over time, it's always good to put a stake in the ground to get things started. Agile software development is clearly taking off and in my opinion is becoming the dominant development paradigm. Furthermore it appears that Agile approaches enjoy a higher success rate, providing better value for your IT investment, than do traditional approaches. Although organizations are succeeding at simpler projects with agile, many are struggling when applying Agile in more complex situations. They're finding that the "Agile rhetoric" doesn't always live up to its promises once you move into these complex situations. My goal with this blog is to share strategies for applying Agile techniques at scale.
When applying Agile strategies at scale you are likely to run into one or more of the following complexity factors:1. Geographical distribution. Is your team, including stakeholders, in different locations? Even being in different cubicles within the same building can erect barriers to communication, let alone being in different cities or even on different continents.2. Regulatory compliance. Regulations, including the Sarbanes-Oxley act, BASEL-II, and FDA statutes, to name a few, can increase the documentation and process burden on your projects. Complying to these regulations while still remaining as agile as possible can be a challenge.3. Entrenched policies, people, and processes. Most agile teams need to work within the scope of a larger organization, and that larger organization isn't always perfectly agile. Hopefully that will change in time, but we still need to get the job done right now. Your existing culture and organization can really hinder your ability to scale agile approaches, then a few "simple" changes can really help your efforts.4. Legacy systems. Although the politically correct term would be "proven assets" the reality is that it can be very difficult to leverage existing code and data sources due to quality problems. The code may not be well written, documented, or even have tests in place, yet that doesn't mean that your agile team should rewrite everything from scratch. Some legacy data sources are questionable at best, or the owners of those data sources difficult to work with, yet that doesn't given an agile team license to create yet another database.5. Organizational distribution. When your teams are made up of people working for different divisions, or if you have people from different companies (such as contractors, partners, or consultants), then your management complexity rises.6. Degree of governance. If you have one or more IT projects then you have an IT governance process in place. How formal it is, how explicit it is, and how effective it is will be up to you. IBM has been doing a lot of work in this topic over the past few years, and just recently Per Kroll and I have done some work around Lean Governance strategies. 7. Team size. Large teams will be organized differently than small teams, and they'll work differently too.8. System complexity. The more complex the system the greater the need for a viable architectural strategy. An interesting feature of the Rational Unified Process (RUP) is that it's Elaboration phase's primary goal is to prove the architecture via the creation of an end-to-end, working skeleton of the system. This risk-reduction technique is clearly a concept which Extreme Programming (XP) and Scrum teams can clearly benefit from.
It is definitely possible to scale Agile software development to meet the real-world complexities faced by modern organizations. Based on my experiences, I believe that over the next few years we'll discover that Agile scales better than traditional approaches. Many people have already discovered this, but as an industry I believe that there isn't yet sufficient evidence to state this as more than opinion. My goal with this blog is to provide advice for scaling Agile so as to increase your chances of success.
So, it looks like I have my work cut out for me. My strategy will be to address common questions which I get when working with customers and with internal IBM development teams. I have the privilege to work with a variety of software development teams worldwide, helping them to become more agile. They're all struggling with the same basic issues although don't recognize it because they're too focused on their own situation. So hopefully I'll be able to spread the word about what's actually working in practice.
I hope that you stay tuned.
- Scott[Read More
Test-driven development (TDD) is a common agile programming technique which has both specification and validation aspects. With TDD, you specify your software in detail on a just-in-time (JIT) basis via executable tests that are run in a regression manner to confirm that the system works to your current understanding of what your stakeholders require.
TDD is the combination of test-first development (TFD) and refactoring. With TFD, you write a single test (at either the requirements level with customer/acceptance tests or the design level with developer tests) and then you write just enough software to fulfill that test. Refactoring is a technique where you make a small change to your existing code to improve its design without changing its semantics.
TDD offers several benefits:1. It enables you to take small, safe steps during development, increasing programmer productivity.2. It increases quality. Agile developers are doing more testing, and doing it more often, than ever before. We're also fixing the problems that we find right on the spot.3. It helps to push validation activities early in the lifecycle, decreasing the average cost to fix defects (which rises exponentially the longer it takes you to detect them).4. Through single sourcing information, by treating tests as both specifications and as tests, we reduce the work required, increasing productivity.5. We leave behind valuable, up-to-date, detailed specifications for the people who come after us. Have you ever met a maintenance programmer who wouldn't want a full regression test suite for the code that they're working with?
But TDD isn't perfect. Although TDD is great at specifying code at a fine-grain level, tests simply don't scale to address higher level business process and architectural issues. Agile Model Driven Development (AMDD) enables you to scale TDD through initial envisioning of the requirements and architecture as well as just-in-time (JIT) modeling at the beginning and during construction iterations. To scale requirements-level TDD, you must recognize that customer tests are very good at specifying the details, but not so good at providing overall context. High-level business process models, conceptual domain models, and use cases are good at doing so, and these work products are often created as part of your initial requirements envisioning and iteration modeling activities. Similarly, to scale design-level TDD you must recognize that developer tests are very finely grained but once again do not provide overall context. High-level architecture sketches created during envisioning activities help set your initial technical direction. During each construction iteration, you'll do more detailed design modeling to think through critical issues before you implement them via TDD.
You also need to scale the validation aspects of TDD. TDD is in effect an approach to confirmatory testing where you validate the system to the level of your understanding of the requirements. The fundamental challenge with confirmatory testing, and hence TDD, is that it assumes that stakeholders actually know and can describe their requirements. Therefore you need to add investigative testing practices which explore issues that your stakeholders may not have thought of, such as usability issues, system integration issues, production performance issues, security issues, and a multitude of others.
For further reading, I suggest:1. My article "Introduction to TFD/TDD" at http://www.agiledata.org/essays/tdd.html which overviews TDD.2. My February 2008 column in Dr. Dobb's Journal entitled "Scaling TDD" at http://www.ddj.com/architect/205207998 which explores this issue in detail. 3. Andrew Glover's article "In pursuit of code quality: Adventures in behavior-driven development" at http://www.ibm.com/developerworks/java/library/j-cq09187/ which describes a new-and-improved take on TDD called BDD.[Read More
The popular Agile literature can often seam naive when it comes to how Agilists work with project stakeholders:- Extreme Programming (XP) has a practice called On-Site Customer where one or more people work closely with your team to provide information and to make decisions in a timely manner.- Scrum has the role of Product Owner who is the one single person that the development team goes to for decisions about requirements. - Agile Modeling (AM) has the practice of Active Stakeholder Participation which extends On-Site Customer to get the stakeholder(s) actively involved with the modeling effort through the use of inclusive tools and techniques.
These are great strategies for small, co-located teams doing straightforward development, but they quickly fall apart at scale. This occurs for several reasons:1. Stakeholders are a diverse group. Your stakeholders include end users, business management, project funders, enterprise architects, operations staff, support staff, other system development teams, and many others. Different people have different, and often contradictory, requirements and they certainly have different priorities. It's questionable whether a single person, or a handful of persons, can adequately represent this diverse group.2. One person becomes a bottleneck. Even with a small co-located team this is a problem, let alone one that is geographically distributed or one that is very large. There's no way that a single person can be available 24/7 in a responsive manner to support distributed teams.3. It's a difficult role. The Product Owner/Customer (POC) is responsible for representing the business to the development team. They're making important decisions on a regular basis, decisions which they'll be held accountable for.4. One person becomes a serious project risk. Not only is it questionable whether a single person can fairly represent all stakeholders, even if they could what happens if you lose that person? They effectively become a single point of failure for your team.
To scale this role, consider the following strategies:1. Recognize the true scope of the POC role. Not only are they stakeholder proxies they also are a development team representative to the stakeholder community as a whole. As stakeholder proxies they'll make decisions and prioritize the work, they'll run requirements elicitation sessions, they'll negotiate priorities, and they'll put the development team in contact with stakeholders who have expertise in specific aspects of the domain. As team representatives they'll often demo the current version of the system to other stakeholders, communicate the status of the project to people, and respond to various requests for information from the stakeholders.2. Have multiple people in it. A single POC works well for small, co-located teams developing simple software. At scale you'll soon discover that you need multiple people in this role so that they don't become a bottleneck. For distributed teams it's common to see each subteam have one or more POCs who are managed by a primary/chief POC. The primary POC typically works on the coordinating team with the chief architect (I'll talk about this role in a future blog posting) and the program manager (also a topic for a future blog posting).3. Train them in business analysis skills. The person(s) in the POC role need good business analysis skills. If fact, it's common for people who were formerly BAs for traditional teams to step into the POC role, particularly with BAs who originally come from the business side of your organization. This strategy has its advantages and disadvantages. As a BA they've likely got solid business knowledge but their instincts may motivate them to take a documentation-driven approach to providing information to the development team instead of a collaboration-based approach. Be careful.4. Consider the full system development lifecycle. There's far more to the POC role than supporting the development team during Construction iterations. During "Iteration 0", the Inception phase for an Agile RUP project or the warm-up phase for an Eclipse Way project, the POC(s) will often lead the initial requirements envisioning efforts. The product backlog, or better yet your work item list, needs to come from somewhere after all. During the release iteration(s), the Transition phase for RUP or the End-Game phase for Eclipse Way, the POC(s) will focus on communicating the upcoming release to the stakeholder community, will be actively involved with any final user acceptance testing (UAT), and may even be involved with training end users.
In my January 2008 column in Dr Dobb's Journal, posted at http://www.ddj.com/architect/204801134 , I provide detailed advice about how to scale the way that you work with stakeholders on Agile projects by applying the practices of Agile Model Driven Development (AMDD). There's no magic solution, you just need to choose to organize yourself effectively. The good news is that you can easily work with stakeholders at scale.[Read More
When adopting agile software development
techniques across a large number of teams within your organization it is important to provide a definition for what agile software development is, in addition to criteria
for what it means to be agile. Many people will point to the four values of the Agile Manifesto
and claim that's a good definition. Well... it might be a good definition for the visionaries and early adopters among us, but for people on the right-hand side of the technology adoption chasm (the early majority, late majority and the laggards) this isn't enough. Don't get me wrong, I'm a firm believer in the agile values but I like to cast them as philosophies instead of as a definition.
At IBM Software Group, the definition of disciplined agile software delivery which we have been sharing with our customers is:Disciplined agile software delivery is an evolutionary (iterative and incremental) approach to delivery which regularly produces high quality software in a cost effective and timely manner. It is performed in a highly collaborative and self-organizing manner, with active stakeholder participation to ensure that the team understand and addresses the changing needs of its stakeholders. Disciplined agile delivery teams provide repeatable results by adopting just the right amount of ceremony for the situation which they face.
I think that this is a pretty good definition, although I have no doubt that we'll evolve it over time.
I also suspect that the agile community will never settle on a common definition for what agile is and more than likely are smart enough not to even try. ;-)Further reading:
I just wanted to share with you the Manifesto for Software Craftsmanship
which extends the Agile Manifesto
. The Manifesto for Software Craftsmanship states:As aspiring Software Craftsmen we are raising the bar of professional software development by practicing it and helping others learn the craft. Through this work we have come to value:
- Not only working software, but also well-crafted software
- Not only responding to change, but also steadily adding value
- Not only individuals and interactions, but also a community of professionals
- Not only customer collaboration, but also productive partnerships
That is, in pursuit of the items on the left we have found the items on the right to be indispensable.
I view this manifesto as an important step in the maturation of software development. More on this in a future blog posting.[Read More
I recently wrote an "e-book" for Internet Evolution overviewing agile software development at scale. The goal of the Agility at Scale: Become as Agile as You Can Be
ebook is to get people thinking outside of the box a bit when it comes to agile development strategies and see that they really are ready for primetime.
When you are first adopting agile techniques in your organization a common strategy is to run one or more pilot projects. When organizing these projects you typically do as much as you can to make them successful, such as finding:
- Projects where the stakeholders are willing to actively work with you.
- IT people who are flexible, willing to try new things, and willing to collaborate with one another.
- IT people who are generalizing specialists, or at least willing to become so.
- Finding a project which is of medium complexity (therefore it's "real" in the sense that it's significant to your organization) but not one where it can make or break your organization (therefore it's safe to experiment with).
In North America we refer to this as "cherry picking" because you're picking the cherry/best situation that you can find.
- Being agile may not have been the primary determinant of success. You set up an environment where you have a good relationship with your stakeholders, where you have good people who want to work together, and the project is challenging but not impossible. Oh, and by the way you adopted a few agile techniques as well. Sounds to me that situation you could have adopted a few not-so-agile techniques instead and still succeed. Although my various project success surveys, see my IT surveys page for details, have shown time and again that agile project teams are more successful than traditional project teams I haven't been able to tease out (yet) whether this success is attributable to agile or just attributable to improved project initiation efforts.
- When adopting agile/lean widely across your organization, you can't cherry pick any more. For the past few years I've been working with IT organizations that are in the process of adopting agile/lean strategies across their entire organization, not just across a few pilot projects. What these organizations are finding is that they need to find ways to adopt agile where the business isn't as willing to work with IT, where some of the people aren't so flexible or collaborative, where some of the people are narrowly specialized and not as willing to expand their skills, or where the project exhibits scaling factors which motivates you to tailor your agile approach. It's harder to succeed with agile in these situations because they're not as "cherry" as what you've experienced previously. Luckily, if you've been successful previously then you now have some agile experienced people, you have successes to reference, and you've likely overcome some problems even in the cherry situations which you have learned from. So, your cherry successes will hopefully improve your ability to succeed even in "non cherry" situations.
- You need to work smarter, not harder. If the source of your success was actually from improved project initiation practices and not from agile, then recognize that and act accordingly. Realistically part of your success was from that and part was from agile, and the organizations that adopt a measured improvement approach potentially have the data to determine which practices lead to success and which didn't. Without the metrics you're effectively flying blind when it comes to deciding how to improve. There is clearly a mandate for smarter work practices within IT, within your organization as a whole for that matter.
If you want to gain more insight into some of the issues that you'll face when adopting agile across your organization, I suspect that you'll find my recent paper Scaling Agile: An Executive Guide
to be interesting. I've got a more detailed paper in the works, so stay tuned to this blog.
Modified by ScottAmbler
I just wanted to round out my discussion about agile approaches to geographically distributed development (GDD) with a few important words of advice:1. Get some experience. Worry less about enterprise adoption and instead get started with a small project, or better yet a series of increasingly more complex projects. There will be learning experiences as you build a relationship with the offshore service provider. This advice is applicable whether you’re working with your own offshore division or with an independent service provider.2. Have a long-term staffing strategy. It may be great in the short term to have work done in a lower cost country, but how are you going to transfer the necessary skills to the maintenance and support team. Outsourcing that work is also an option, but it can be a risky one as you would need to build up expertise in “your” systems if you ever decide to insource that work again.3. Be concerned about intellectual property (IP). The rules are different around the world, and you may inadvertently be financing the creation of a new international competitor if you don’t have a clear division of ownership. And yes, this may mean that some components of your systems are still built internally by your own organization.4. Show off locally before you go global. GDD makes things harder to manage, so if you’re struggling to manage local teams you’re really going to struggle managing teams at a distance. Make sure you have local success first and are good at agile development in general. Furthermore, if your agile GDD projects run into trouble, don’t end your local agile adoption just because of difficulties with distributed projects.5. Let your offshore partners lead. The offshore partner likely has more experience than you at successful distributed development, and this is particularly true when you’re dealing with an established service provider.6. Do some reading. There’s a great IBM Redbook entitled “Global Development and Delivery in Practice: Experiences of the IBM Rational India Lab” which can be downloaded free of charge from http://www.redbooks.ibm.com/abstracts/sg247424.html7. Do some viewing. We recorded a Rational Chat a few months ago entitled "Being Agile in a Global Development Environment" which is posted at https://www14.software.ibm.com/webapp/iwm/web/reg/acceptSignup.do?lang=en_US&source=dw-c-wcsdpr&S_PKG=120607&S_TACT=105AGX23&S_CMP=TALKS&cp=UTF-8 . I also gave a keynote on Agile approaches to GDD at Software Development Practices 2007 held in Boston in the Autumn of 2007. The video can be downloaded free of charge from http://www.life20.net/video/scottambler.mov .[Read More
A common question that I keep running into with customers is whether you can take an agile approach to service oriented architecture (SOA). The quick answer is yes, because Agile is orthogonal to the implementation technologies used. You can take an agile approach developing COBOL applications running on mainframes, fat-client Java applications, multi-tier J2EE applications, and yes, even services. Granted, it's easier to do with some technologies than others, either because of the nature of the technology or because of the supporting tools.
The long answer is "yes, but". You don't adopt an SOA approach for the sheer joy of doing so, instead you very likely want to improve the level of reuse within your organization. To succeed at SOA-driven reuse you need an enterprise focus, something that doesn't appear to be very common on many agile teams. Therein lies the challenge. Several strategies for improving your chances with Agile SOA, and SOA in general, follows:1. Invest in some initial enterprise architecture modeling. You don't need to identify all of the details up front, that would take too long and actually put the effort at risk, but you do need to set a starting point to guide development teams. Identifying the technical architecture is critical, and identifying a few basic services which would provide immediate business value to one or more teams is critical. Involve people from several application project teams to ensure that you get a wide range of input. See http://www.agiledata.org/essays/enterpriseArchitecture.html for a streamlined approach to enterprise architecture modeling. Creating big, detailed models often proves to be a waste of time because development teams are rarely motivated to read mounds of documentation.2. Build out the initial infrastructure on a real application development project. This proves that your SOA strategy actually works and puts the technical foundation in place for future teams. During this period you'll be tempted to try to support several development teams, which is feasible but dramatically increases your risk. It's also tempting to focus simply on getting the infrastructure in place without delivering any business functionality, but this risks producing an ivory-tower architecture that nobody is interested in.3. Spread the service architects out onto application development teams. The people that formulated and then proved your SOA should be actively involved on the development teams that are working with it to ensure that the teams use it appropriately and to ensure that the architects get concrete feedback which they can use to evolve the architecture. When working on agile teams, these people will need to work in a collaborative and evolutionary approach just like other team members.4. Fund reuse separately. I've lost track of the number of organizations that I've run into that fail at reuse because their development teams never have the resources to develop reusable assets. That's simply the nature of the beast -- project teams will always be more interested in addressing their own specific requirements than they are in investing the time and effort to make something reusable. The real problem here is that you expect them to act differently. A better strategy is to have a separate reuse engineering team that has the resources to monitor existing projects to look for potentially reusable assets. When they find said assets this team does the work to harvest the asset, to reengineer it to make it reusable, and then to integrate back into the original source project. The goal is to make it as painless as possible to produce reusable assets such as services. If you expect project teams to do this work out of the goodness of their hearts then you're effectively punishing them when they do the right thing. That's not a very good governance strategy, IMHO.5. The reuse team now owns the asset. Any reusable asset, including services, will need to be maintained, evolved over time, and supported. This isn't free nor is it viable for project teams to do so.
If you're interested, I provide agile strategies for both enterprise architecture and strategic reuse in the book "Enterprise Unified Process". Although written under the assumption that you're taking a RUP-based approach to development, the reality is that the EUP can extend any evolutionary/agile software development process so that it addresses the larger-scale needs of modern IT organizations.
- Scott[Read More
I've been getting a lot of questions lately about applying the acceleration metric
in practice. So, here's some answers to frequently asked questions:
1. How do I monetize acceleration?
This is fairly straightforward to do. For example, assume your acceleration is 0.007 (0.7%), there are five people on the team, your annual burdened cost per person is $150,000, and you have two week iterations. All these numbers are made up, but you know how to calculate acceleration now and IT management had darn well better know the average burdened cost (salary plus overhead) of their staff. So, per iteration the average burdened cost per person must be $150,000/26 = $5,770. Productivity improvement per iteration for this team must be $5,770 * 5 * .007 = $202. If the acceleration stayed constant at 0.7% the overall productivity improvement for the year would be (1.007)^26 (assuming the team works all 52 weeks of the year) which would be 1.198 or 19.8%. This would be a savings of $148,500 (pretty much the equivalent of one new person). Of course a 20% productivity increase over an entire year is a really aggressive improvement, regardless of some of the claims made by the agile snake oil salesman out there, although at 10-15% increase is a reasonable expectation. What I'd really want to do is calculate the acceleration for the year by comparing the velocity from the beginning of the year to the end of the year (in Western cultures I'd want to avoid comparing iterations near to the holidays). So, if the team velocity the first week of February 2008 was 20 points, now the same team's velocity the first week of February 2009 was 23 points, that's an acceleration of (23-20)/20 = 15% over a one year period, for a savings of $112,500.
2. Is acceleration really unitless?
For the sake of comparison it is. The "units" are % change in points per iteration, or % change in points per time period depending on the way that you want to look at it. Because it's a percentage I can easily monetize it, as you see above, and use it as a basis of comparison.
3. How do I convince teams to share their data?
This can be difficult. Because acceleration is easy to calculate for agile teams, and because it's easy to use to compare teams (my team has .7% acceleration whereas other teams down the hall from mine have accelerations of .3% and -.2% of teams), people are concerned that this metric will be used against them. OK, to be fair, my team might be OK with this. ;-) Seriously though, this is a valid fear that will only be addressed by an effective governance program
based on enablement, collaboration, and trust instead of the traditional command-and-control approach. Management's track record regarding how they've used measurements in the past, and how they've governed in general, have a great effect on people's willingness to trust them with new metrics such as acceleration. The implication is that you need to build up trust, something that could take years if it's possible at all.
4. Why does this work for agile teams?
Agile teams are self organizing, and an implication of that is that they will be held accountable for their estimates. Because of this accountability, and because velocity is a vital input into their planning and estimation efforts, agile teams are motivated to calculate their velocity accurately and to track it over time. Because they're eager to get their velocity right, and because acceleration is based on velocity, there's an exceptionally good chance that it's accurate.
5. What about function points or similar productivity measures?
Function points can be calculated for projects being developed via an agile approach, or other approaches for that matter, but it's a very expensive endeavor compared to calculating acceleration (which is essentially free) and likely will be seen as a bureaucratic overhead by the development team. My rule of thumb is that if you're not being explicitly paid to count function points (for example the US DoD will often pay contracting companies to create estimates based on function point counts) then I wouldn't bother with them.
6. What about calculating acceleration for iterative project teams?
Iterative project teams, perhaps following Rational Unified Process (RUP)
, can choose to calculate and track their velocity and thereby their acceleration. The key is to allow the team to be self organizing and accountable for their estimates, which in turn motivates them to get their velocity right just like agile teams (RUP can be as agile as you want to make it, don't let anyone tell you differently).
7. What about calculating acceleration for traditional project teams?
In theory this should work, in practice it is incredibly unlikely. Traditional teams don't work in iterations where working software is produced on a regular basis, they're typically not self organizing, and therefore there really isn't any motivate to calculate velocity (even if they do, there is little motivation to get it right). Without knowing the velocity you can't calculate acceleration. If you can't trust the velocity estimate, and I certainly wouldn't trust a traditional team's velocity estimate, then you can't trust your acceleration calculation. So, my fall back position to calculate productivity improvement would be to do something like function point counting (which is expensive and difficult to compare between teams due to different fudge factors used by different FP counters) and then looking at change in FPs delivered over time.
8. How can I apply this across a department?
It is fairly straightforward to roll up the acceleration of project teams into an overall acceleration measure for a portfolio of teams simply by taking a weighted average based on team size. However, this is only applicable to teams that are in a position to report an accurate acceleration (the agile and iterative teams) and of course are willing to do so.
9. What does a negative acceleration tell me?
If the acceleration is negative then productivity on the team is going down, likely an indicator of quality and/or team work problems. However, you don't want to manage by the numbers so you should talk to the team to see what's actually going on.
10. What does a zero acceleration tell me?
This is an indication that the team's productivity is not increasing, and that perhaps they should consider doing retrospectives at the end of each iteration and then acting on the results from those retrospectives. Better yet they can "dial up" their process improvement efforts by adopting something along the lines of IBM Rational Self Check
One of the scaling factors
of the Agile Scaling Model (ASM)
is technical complexity.
The fundamental observation is that the underlying technology of solutions varies and as a result your approach to developing a solution will also need to vary.
It’s fairly straightforward to achieve high-levels of quality if you’re building a new system from scratch on a known technology platform, but not so easy when there are several technologies, the technologies are not well known, or legacy assets are involved.
There are several potential technical complexities which a Disciplined Agile Delivery (DAD) team may face:
- New technology platforms. Your team may choose to work with a technology platform which is either new to the team or sometimes even new to the industry. In the past few years new technology platforms include the Android operating system, Apple’s iPad platform, and various cloud computing (http://www.ibm.com/ibm/cloud/) platforms. Working with these platforms may require you to adopt new development tools and techniques, not to mention the need to train and mentor your staff in their usage. Furthermore, your team may need to allocate time for architectural spikes to explore how to use the new technology and to prove the overall architecture with working code early in the project lifecycle (this is a DAD milestone).
- Multiple technology platforms. IT solutions often run on multiple platforms. For example, a system’s user interface (UI) could run in a browser, access business logic implemented using J2EE on Websphere which in turn invokes web services implemented in COBOL running on a Z-series mainframe, and stores data in an Oracle database, a DB2 database, and in several XML files. Implementing new business functionality, or updating existing functionality, could require changes made on several of these platforms in parallel. The implication is that you’ll need to adopt tools and strategies which enable your team to develop, test, and deploy functionality on all of these platforms. Testing and debugging in particular will become more difficult as the number of technology platforms increases, potentially requiring you to adopt the practice of parallel independent testing. The Agility at Scale survey found that 34% of respondents indicated that their agile teams were working with multiple technology platforms.
- Legacy data. IT solutions should leverage existing, legacy data wherever possible to reduce the number of data sources and thereby increase data quality within your organization. Also, using existing data sources can potentially speed up development, assuming your team has a good relationship with the owners of the legacy data sources (sadly, this often isn’t the case as the Data Management Survey found). Working with legacy data sources may require improved database regression testing, practices, database refactoring practices, and agile approaches to data administration. The Agility at Scale survey found that 42% of respondents indicated that their agile teams were working with legacy data sources (personally, I’m shocked that this figure is so low, and fear that many agile teams are contributing to data quality problems within their organization as a result).
- Legacy systems. There are several potential challenges with legacy systems. First, the code quality may not be the best either because it was never really that good to begin with or because it’s degraded over the years as multiple people worked with it. You know you’ve got a quality problem if you’re either afraid to update the code or if when you do so you have to spend a lot of time debugging and then fixing problems revealed when doing the update. If the legacy system is a true asset for your organization you will want to pay off some of this technical debt by refactoring the code to make it of higher quality. Second, you may not have a full regression test suite in place, making it difficult to find problems when you do update the code let alone when you refactor it. Third, your development tools for your legacy code may be a bit behind the times. For example, I often run across mainframe COBOL developers still working with basic code editors instead of modern IDEs such as Rational Developer for System Z. Some of the strategies to deal effectively with legacy systems are to adopt a modern development toolset if you haven’t already done so (better yet, if possible adopt a common IDE across platforms and thereby reduce overall licensing and support costs) and to adopt agile practices such as static code analysis, dynamic software analysis, and continuous integration (CI). The Agile Project Initiation Survey found that 57% of respondents were integrating their new code with legacy systems and 51% were evolving legacy systems.
- Commercial off-the-shelf (COTS) solutions. COTS solutions, also called package applications, can add in a few complexities for agile teams. The packages rarely come with regression test suites, they often have rules about what you can modify and what you shouldn’t (rules that are ignored at your peril), and they’re often architected with the assumption that they’re the center of the architectural universe (which is a valid assumption if they’re the only major system within your organization). As I describe in my article Agile Package Implementations it is possible to take an agile approach to COTS implementations, although it may require a significant paradigm shift for the people involved. The Agility at Scale survey found that 15% of respondents indicated that their agile teams were working with COTS solutions.
- System/embedded solutions. For the sake of simplicity, if your team is developing a solution with both hardware and software aspects to it then you’re a systems project. Embedded systems are a specialization where the system has a few dedicated functions often with real-time constraints. Bottom line is that systems/embedded projects are typically more challenging than software-only projects – it gets really interesting when laws of physics starts to kick in, such as when you’re building satellites or space probes. I highly suggest Bruce Douglass’s book Real-Time Agility if you are interested in taking an agile approach to systems/embedded solution delivery.
The technical complexity faced by a project team is contextual – Working with four technology platforms is straightforward for someone used to dealing with seven, but difficult for someone used to dealing with just one. Recommended Reading:
- Does the team regularly produce value for their stakeholders?
- Does the team validate its own work to the best of its ability?
- Are stakeholders actively involved?
- Is the team self organizing?
- Does the team strive to improve their process?
Some interesting results include:
94% of teams which are claiming to be agile are providing value to stakeholders on a regular basis.
87% of teams which are claiming to be agile are validating their own work.
95% of teams which are claiming to be agile are working closely with stakeholders.
56% of teams which are claiming to be agile are self organizing.
88% of teams which are claiming to be agile are improving the process that they follow throughout the lifecycle.
Teams which are claiming to be agile often aren't. 53% of "agile teams" meet the five criteria, although 72% meet all but the self-organization criteria.
Teams which are moving towards agile but aren't there yet are reasonably close. 39% of those teams meet all five criteria and 63% meet all but self-organization.
I believe that there are several important implications:
- Whenever someone claims to be on an agile team you may want to explore that claim a bit deeper.
The low level of self organization may be an indicator of cultural challenges with organizations in that their project managers aren't giving up sufficient control. The Agility at Scale survey
in November 2009 found that 59% of respondents who indicated that their organization hadn't adopted agile techniques yet that a rigid culture was hampering their efforts. The IT Governance and Project Management
survey in July 2009 discovered that "questionable behaviors", many of which were ethically questionable (I'm being polite), were far too common within IT project management.
Although "agile teams" may not be as agile as they claim, they're still doing better than traditional V-model teams, as revealed (again) by the 2010 IT Project Success
If there was some sort of consensus within the agile community as to the criteria for determining whether a team is agile, I highly suspect that the agileness ratings would increase over time. What gets measured often improves.
However, how agile you are isn't anywhere near as important as getting better at what you're doing. So perhaps I'm barking up the wrong tree on this issue. ;-)