One of the scaling factors
called out in the Agile Scaling Model (ASM)
is domain complexity. The general idea is that agile teams will find themselves in different situations where some teams are developing fairly straightforward solutions, such as an informational website, whereas others are addressing very complex domains, such as building an air-traffic control system (ATCS). Clearly the team building an ATCS will work in a more sophisticated manner than the one building an informational website. I don't know whether agile techniques have been applied in the development of an ATCS, although I have to think that agile's greater focus on quality and working collaboratively with stakeholders would be very attractive to ATCS delivery teams, I do know that agile is being applied in other complex environments: The 2009 Agility at Scale Survey
found that 18% of respondents indicated that their organizations had success at what they perceived to be very complex problem domains,.
Increased domain complexity may affect your strategy in the following ways:
- Reaching initial stakeholder consensus becomes difficult. One of the risk reduction techniques called out in Disciplined Agile Delivery (DAD) is to come to (sufficient) stakeholder consensus at the beginning of the project during the Inception phase (called Sprint 0 in Scrum or Iteration 0 in other agile methods). Stakeholder consensus, or perhaps "near concensus" or "reasonable agreement" are better terms, can be difficult to come to the more complex the problem domain is because the stakeholders may not fully understand the implications of what they're making decisions about and because there is likely a greater range of stakeholders with differing goals and opinions. The implication is that your project initiation efforts may stretch out, increasing the chance that you'll fall back on the old habits of big requirements up front (BRUF) and incur the costs and risks associated with doing so.
- Increased prototyping during inception. It is very common for disciplined agile teams to do some light-weight requirements envisioning during inception to identify the scope of what they're doing and to help come to stakeholder consensus. The greater the complexity of the domain, and particularly the less your team understands about the domain, the more likely it is that you'll benefit from doing some user interface (UI) prototyping to explore the requirements. UI prototyping is an important requirements exploration technique regardless of paradigm, and it is something that you should consider doing during both initial requirements envisioning as well as throughout the lifecycle to explore detailed issues on a just in time (JIT) manner.
- Holding "all-hands reviews". One strategy for getting feedback from a wide range of people is to hold an "all hands review" where you invite a large group of people who aren't working on a regular basis with your team to review your work to date. This should be done occasionally throughout the project to validate that the input that you're getting from your stakeholder represenatives/product owners truly reflects the needs of the stakeholders which they represent. The 2010 How Agile Are You? Survey found that 42% of "agile teams" reported running such reviews.
- Increased requirements exploration. Simple modeling techniques work for simple domains. Complex domains call for more complex strategies for exploring requirements. The implication is that you may want to move to usage scenarios or use cases from the simpler format of user stories to capture critical nuances more effectively. A common misunderstanding about agile is that you have to take a "user story driven approach" to development. This is an effective strategy in many situations, but it isn't a requirement for being agile.
- The use of simulation. You may want to take your prototyping efforts one step further and simulate the solution. This can be done via concrete, functional prototypes, via simulation software, via play acting, or other strategies.
- Addition of agile business analysts to the team. Analysis is so important to agile teams we do it every day. In situations where the domain is complex, or at least portions of the domain is complex, it can make sense to have someone who specializes in exploring the domain so as to increase the chance that your team gets it right. This is what an agile business analyst can do. There are a few caveats. First, even though the domain is complex you should still keep your agile analysis efforts as light, collaborative, and evolutionary as possible. Second, this isn't a reason to organize your team as a collection of specialists and thereby increase overall risk to your project. The agile analyst may be brought on because their specialized skills are required, but the majority of the people on the team should still strive to be generalizing specialists. This is also true of the agile analyst because their may not be eight hours a day of valuable business analysis work on the team, and you don't want the BA filling in their time with needless busy work.
The important thing is to recognize that the strategies which work well when you're dealing with a simple domain will not work well for a complex domain. Conversely, techniques oriented towards exploring complex domains will often be overkill for simple domains. Process and tooling flexiblity is key to your success.
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:
I'm happy to announce that A Practical Guide to Distributed Scrum
by Elizabeth Woodward, Steffan Surdek, and Matthew Ganis is now in print. I've been talking this book up in presentations and with customers the past few months and promised that I would let everyone know once it was available. I was one of several people who wrote forewords for the book, Ken Schwaber, Roman Pichler, and Matthew Wang also did so, and I've modified my foreword below to help you to understand a bit better what the book is about.
If you’re thinking about buying this book, you’re probably trying to answer one or more of the following questions: “What will I learn?”, “Should I spend my hard earned money on this book?”, “Will it be worth my valuable time to read it?”, and “Is this a book that I’ll refer to again and again?” To help you answer these questions, I thought I’d list a few user stories which I believe this book clearly fulfills:
As a reader I want:
- a book that is well-written and understandable
real-world examples that I can relate to
- quotes from actual people doing this in the field
- to understand the challenges that I’ll face with distributed agile development
As someone new to agile I want to:
- learn the fundamentals of Scrum
- understand the fundamentals of agile delivery
- learn about what actually works in practice
- discover how extend Scrum into an agile delivery process
As an experienced agile practitioner I want to learn:
- how to scale agile approaches for distributed teams
- how to overcome the challenges faced by distributed teams
- how to tailor existing agile practices to reflect the realities of distribution
- bout “new” agile practices which we might need to adopt
- techniques so that distributed team members can communicate effectively
- how to extend Scrum with proven techniques from Extreme Programming, Agile Modeling, and other agile methods
- how to address architectural issues on a distributed agile team
- how agile teams address documentation
- how agile teams can interact effectively with non-agile teams
As a Scrum Master I want to learn how to:
- lead a distributed agile team
- facilitate a distributed “Scrum of Scrums”
- facilitate the successful initiation of a distributed agile project
- facilitate communication and collaboration between distributed team members
As a Product Owner I want to learn:
- how to manage a product backlog on a distributed team
- about different categories of stakeholders whom I will need to represent
- about techniques to understand and capture the goals of those stakeholders
- how to manage requirements with other product owners on other sub-teams
- what to do during an end-of-sprint review
- how I can streamline things for the delivery team that I’m working with
As an agile skeptic I want to:
- see examples of how agile works in practice
- hear about the challenges faced by agile teams
- hear about where agile strategies don’t work well and what to do about it
I work with organizations around the world helping them to scale agile strategies to meet their real-world needs. Although this book is focused on providing strategies for dealing with geographical distribution, it also covers many of the issues that you’ll run into with large teams, complex problem domains and complex technical domains. An important aspect of scaling agile techniques is to first recognize that’s there’s more to scalability than dealing with large teams, something which this book clearly demonstrates.
At the risk of sounding a bit corny, I’ve eagerly awaited the publication of this book for some time. I’ve known two of the authors, Elizabeth and Matt, for several years and have had the pleasure of working with them and learning from them as a result. Along with hundreds of other IBMers I watched this book get written and provided input where I could. The reason why I’m so excited about it is that I’ve wanted something that I could refer the customers to that I work with and honestly say, “yes, we know that this works because this is what we do in practice”.
IBM is doing some very interesting work when it comes to scaling agile. We haven’t published enough externally, in my opinion, due to a preference for actively sharing our experiences internally. This book collects many of our experiences into a coherent whole and more importantly shares them outside the IBM process ecosystem. Bottom line is that I think that you’ll get a lot out of this book.
In Implementing Lean Software Development
, Mary and Tom
Poppendieck show how the seven principles of lean manufacturing can be applied
to optimize the whole IT value stream. These principles are:
- Eliminate waste. Lean thinking advocates regard any activity
that does not directly add value to the finished product as waste. The three
biggest sources of waste in software development are the addition of unrequired
features, project churn and crossing organizational boundaries (particularly
between stakeholders and development teams). To reduce waste it is critical
that development teams be allowed to self organize and operate in a manner that
reflects the work they’re trying to accomplish. Walker Royce argues in “Improving Software Economics” that the primary benefit of modern iterative/agile
techniques is the reduction of scrap and rework late in the lifecycle.
- Build in quality. Your process should not allow defects to
occur in the first place, but when this isn’t possible you should work in such
a way that you do a bit of work, validate it, fix any issues that you find, and
then iterate. Inspecting after the fact,
and queuing up defects to be fixed at some time in the future, isn’t as
effective. Agile practices which build
quality into your process include test driven development (TDD) and non-solo
development practices such as pair programming and modeling with others.
- Create knowledge. Planning is useful, but learning is essential.
You want to promote strategies, such as iterative development, that help teams
discover what stakeholders really want and act on that knowledge. It’s also
important for a team to regularly reflect on what they’re doing and then act to
improve their approach.
- Defer commitment. It’s not necessary to start software
development by defining a complete specification, and in fact that appears to
be a questionable strategy at best. You can support the business effectively
through flexible architectures that are change tolerant and by scheduling
irreversible decisions to the last possible moment. Frequently, deferring
commitment requires the ability to closely couple end-to-end business scenarios
to capabilities developed in multiple applications by multiple projects.
- Deliver quickly. It is possible to deliver high-quality
systems quickly. By limiting the work of a team to its capacity, which is
reflected by the team’s velocity (this is the number of “points” of
functionality which a team delivers each iteration), you can establish a
reliable and repeatable flow of work. An effective organization doesn’t demand
teams do more than they are capable of, but instead asks them to self-organize
and determine what they can accomplish. Constraining these teams to delivering potentially
shippable solutions on a regular basis motivates them to stay focused on
continuously adding value.
- Respect people.
The Poppendiecks also observe that sustainable advantage is gained from
engaged, thinking people. The implication is that you need a lean governance
strategy that focuses on motivating and enabling IT teams—not on controlling
- Optimize the whole. If you want to be effective at a solution you
must look at the bigger picture. You need to understand the high-level business
processes that individual projects support—processes that often cross multiple
systems. You need to manage programs of interrelated systems so you can deliver
a complete product to your stakeholders. Measurements should address how well
you’re delivering business value, because that is the sole reason for your IT
Lean thinking is important for scaling agile in several ways:
- Lean provides an explanation for why many of the agile
practices work. For example, Agile
Modeling’s practices of light weight, initial requirements envisioning followed
by iteration modeling and just-in-time (JIT) model storming work because they
reflect deferment of commitment regarding what needs to be built until it’s
actually needed, and the practices help eliminate waste because you’re only modeling
what needs to be built.
Lean offers insight into strategies for improving your
software process. For example, by
understanding the source of waste in IT you can begin to identify it and then
Lean principles provide a philosophical foundation for
scaling agile approaches.
- It provides techniques for identifying waste. Value stream mapping, a technique common within the lean
community whereby you model a process and then identify how much time is spent
on value-added work versus wait time, helps calculate overall time efficiency
of what you’re doing. Value stream maps are
a straightforward way to illuminate your IT processes, providing insight into
where significant problems exist. I’ve
created value stream maps with several customers around the world where we
analyzed their existing processes which some of their more traditional staff
believed worked well only to discover they had efficiency ratings of
20-30%. You can’t fix problems which you
are blind to.
Timo Tenhunen has recently published his master's thesis, Challenges in Scaling Agile Software Development
, and has been kind enough to make it available online. I suspect you'll find it to be an interesting read.
One of the scaling factors
called out in the Agile
Scaling Model (ASM)
is “geographic distribution". As with the other scaling factors the level of geographic distribution is a range, with co-located teams at one extreme and far-located at the other. When your team is co-located the developers and the primary stakeholders are all situated in the same work room. If you have some team members in cubicles or in separate offices then you're slightly distributed, if you're working on different floors in the same building you're a bit more distributed, if you're working in different buildings within the same geographic area (perhaps your team is spread across different office buildings in the same city or some people work from home some days) then your team is more distributed, if people are working in different cities in the same country you're more distributed, and finally if people are working in different cities around the globe you're even more distributed (I call this far located).
As your team becomes more distributed your project risk increases for several reasons:
- Communication challenges. The most effective means of communication between two people is face-to-face around a shared sketching space such as a whiteboard, and that requires you to be in the same room together. As you become more distributed you begin to rely on less effective communication strategies.
- Temporal challenges. When people are in different time zones it becomes harder to find common working times, increasing the communication challenges. One potential benefit, however, is the opportunity to do "follow-the-sun" development where a team does some work during their workday, hands off the work to another team in a significantly different time zone, who picks up the work and continues with it. This strategy of course requires a high degree of sophistication and discipline on the part of everyone involved, but offers the potential to reduce overall calendar time.
- Cultural challenges. As the team becomes more distributed the cultural challenges between sites typically increases. Different cultures have different work ethics, treat intellectual property differently, have different ideas about commitment, have different holidays, different approaches to things, and so on.
As you would imagine, because the project risk increases the more distributed your team is, the lower the average success rates of agile projects decrease as they become more distributed. The 2008 IT Project Success Survey
found that co-located agile teams has an average success rate of 79%, that near located teams (members were in same geographic area) had a success rate of 73%, and that far-located agile teams had a success rate of 55%. The success rate decreases similarly for project teams following other paradigms.
The practices that you adopt, and the way that you tailor the agile practices which you follow, will vary based on the level of geographic distribution of your team. For example, a co-located team will likely do initial architecture envisioning
on a whiteboard and keep it at a fairly high-level. A far-located team will hopefully choose to fly in key team members at the beginning of the project, at least the architecture owners
on the various sub-teams, to do the architecture envisioning together. They will likely go into greater detail because they will want to identify, to the best of their ability, the interfaces of the various subsystems or components which they'll be building. They'll also likely use a modeling tool such as Rational Rhapsody
to capture this information (note that it is very possible to use CASE tools in an agile manner, and that some agile teams in fact do so as the 2008 Modeling and Documentation Survey
Geographically distributed agile teams, at least the effective ones, will also use tools which reflect the realities of agile geographically distributed development (GDD). The Jazz platform
tools, particularly Rational Team Concert (RTC)
, are developed with agile GDD in mind. In fact, the RTC team itself is an agile GDD and they use RTC to develop RTC. Although index cards are a great way for co-located agile teams to capture high-level requirements such as user stories, you need an electronic strategy for a GDD team. RTC also supports communication between team members, distributed debugging, and many other features which distributed teams will find useful.
Interestingly, the Agility at Scale 2009 survey
found that it was quite common for agile teams to be geographically distributed in some manner:
- 45% of respondents indicated that some of their agile teams were co-located
- 60% of respondents indicated that some of their agile teams had team members spread out through the same building
- 30% of respondents indicated that some of their agile teams were working from home
- 21% of respondents indicated that some of their agile teams had people working in different offices in the same city
- 47% of respondents indicated that some of their agile teams had team members that were far located
The bottom line is that some organizations, including IBM, have been very successful applying agile techniques on geographically distributed teams. In fact, agile GDD is far more common than mainstream agile discussion seem to let on. Recommended Resources:
One of the scaling factors
called out in the Agile Scaling Model (ASM)
is “regulatory compliance”. This name is a bit of a misnomer because this scaling factor really addresses two issues: complying to regulations imposed upon you from external sources and choosing to adhere to internal regulations willingly adopted by your organization. It is relatively common for agile teams to find themselves in such situations. For example, in the 2009 Agile Practices Survey
one third of respondents said that they were applying agile on projects where one or more industry regulations applied.
First let’s consider external regulatory compliance. In these situations you may face the need to undergo an audit by an external regulatory body with consequences for non-compliance ranging from anywhere to a warning to a fine or even to legal action. Sometimes even a warning may be a grave thing. A few years ago I was working with a pharmaceutical company which had discovered that a warning from the FDA for non-compliance with their CFR 21 Part 11 regulation, when reported in major newspapers, resulted on average in a half-billion dollar loss to their market capitalization as the result of a dip in their stock price. There are financial regulations such as Sarbanes-Oxley and Basel II, informational regulations such as HIPAA which focuses on health information privacy, technical regulations such as ISO 27002 for security practices, and even life-critical regulations such as some of the FDA regulations.
External regulations are typically managed by a government organization or industry watchdog will range in complexity and can have a myriad of effects on project teams. For example, you may need to be able to prove that you had a documented process and that you followed it appropriately; you may need to produce extra artifacts, or more detailed artifacts, than you normally would; you may need to add extra features to your solution, such as tracking financial information, that you wouldn’t have normally implemented; you may need to produce specific reports to be submitted to the regulatory body; or you may even need to submit your team to audits, sometimes scheduled and sometimes not, to ensure regulatory compliance. Interestingly, even though many of those requirements go against the agile grain, the 2009 Agility at Scale Survey
found that organizations were successfully applying agile techniques while still conforming to external regulations. So yes, it is possible to scale your agile strategy to address regulatory compliance.
Second, let’s consider compliance to internally adopted, or sometimes even developed, “regulations” which you will be potentially evaluated/appraised against. Perfect examples of these are process improvement frameworks such as CMMI and ISO 900x. Similar to external regulations, the 2009 Agility at Scale Survey
found that some agile teams are succeeding in situations where they have chosen to adopt such frameworks. It’s important to note that frameworks such as CMMI aren’t primarily about ensuring the compliance of development teams to a standard process, regardless of what CMMI detractors may claim, but instead about process improvement. Process improvement at the IT department (or beyond) is an enterprise discipline issue from the point of view of ASM, implying that frameworks such as CMMI affect more than one scaling factor.
When you find yourself in a regulatory situation, whether those regulations are imposed or willingly adopted, the best advice that I can give is to read the regulations and develop a strategy to conform to them in the most agile manner possible. If you let bureaucrats interpret the regulations you’ll likely end up with a bureaucratic strategy, but if you instead choose to take a pragmatic approach you will very likely end up with a very practical strategy. Part of that strategy is to treat the regulatory representative(s) within your organization as important stakeholders whom you interact with regularly throughout the project.
People who are new to agile are often confused about how agile teams address architecture, but luckily we're seeing more discussion around agile architecture
now in the community so this problem is slowly being addressed from what I can tell. But, what I'm not seeing enough discussion about, at least not yet, is how is enterprise architecture addressed in the overall agile ecosystem. So I thought I'd share some thoughts on the subject, based on both my experiences over the years (see the recommended resources at the bottom of this posting) as well as on an enterprise architecture survey
which I ran in January/February 2010.
My belief is that effective enterprise architecture, particularly in an agile environment, is:
- Business driven. Minimally your EA effort should be driven by your business, not by your IT department. Better yet it should be business owned, although this can be a challenge in many organizations because business executives usually aren't well versed in EA and view it as an IT function. Yes, IT is clearly an important part of EA but it's not the entirety of EA nor is it the most critical part. In many organizations the IT department initiates EA programs, typically because the business doesn't know to do so, but they should quickly find a way to educate the business in the need to own your organization's EA efforts.
- Evolutionary. Your enterprise architecture should evolve over time, being developed iteratively and introduced incrementally over time. An evolutionary approach enables you act on the concrete feedback that you receive when you try to actually implement it, thereby enabling you to steer its development successfully.
- Collaborative. The EA survey clearly pointed to "people issues" being critical determinants of success, and of failure, of EA programs. My experience is that the best enterprise architects, just like the best application architects, work closely with the intended audience of their work, both on the business side of things as well as on the IT side. They will "roll up their sleeves" and become active members of development teams, often in the role of Architecture Owner on agile teams or Architect on more traditional teams. Their mission is to ensure that the development teams that they work with leverage the EA, to mentor developers in architecture skills, and to identify what works and what doesn't in practice so that they can evolve the EA accordingly. Enterprise architects, architects in general, who don't participate actively on development teams (holding architecture reviews isn't active participation) run the risk of being thought of as "ivory tower" and thus easy to ignore.
- Focused on producing valuable artifacts. The most valuable artifacts are useful to the intended audience, are light weight, and ideally are executable. Many EA programs run aground when the enterprise architects focus on artifacts that they've always wanted but that development teams really aren't very excited about -- yes, it might be interesting to have a comprehensive comparison of cloud technologies versus mainframe technologies, but a collection of reusable services would be fare more interesting to them. A detailed enterprise data model indicating suggested data attributes would be intellectually interesting to develop, but a list of legacy data sources with a high-level description of their contents would be immediately valuable to many development teams. A detailed model depicting desired web services would be useful, but an actual collection of working services that I can reuse now would be even better.
- An explicit part of development. In Disciplined Agile Delivery (DAD) architectural activities are an explicit part of the overall delivery process. Part of the architectural advice is that delivery teams should work closely with their organization's enterprise architects so that they can leverage the common infrastructure, and sometimes to help build it out, effectively. Disciplined agile teams realize that they can benefit greatly by doing so.
The Agile Scaling Model (ASM)
calls out addressing enterprise disciplines, such as enterprise architecture, as one of eight scaling factors which may apply to a given project. The interesting thing about this scaling factor is that it's the only one where things get potentially easier for development teams when we move from the simple approach, having a project focus, to the more complex approach, where we have an enterprise focus. By having a common infrastructure to build to, common guidelines to follow, and valuable artifacts to reuse project teams can benefit greatly. So, I guess my advice is to seriously consider adding enterprise disciplines to your agile strategy.Recommended Resources:
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.
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.