Modified by ScottAmbler
One of the scaling factors called out in the Software Development Context Framework 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.
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.
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.
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.
Modified by ScottAmbler
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.
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:
Modified by ScottAmbler
One of the scaling factors called out in the Software Development Context Framework (SDCF) 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.
Modified by ScottAmbler
This article has been replaced by an official "Disciplined Agile Manifesto".
The text of the original article remains below.
I've recently been working with Mark Lines of UPMentors and we've had some interesting discussions around evolving the Agile Manifesto which I thought I would share here to obtain feedback. Note that this is not any sort of official position of IBM, nothing in my blog is by the way (unless explicitly stated so), nor is it some sort of devious plot to take over the agile world (although if we did have some sort of devious plot, we'd make the exact same claim). What we hope to accomplish is to put some ideas out there in the hopes of getting an interesting conversation going.
Over the past decade we’ve applied the ideas captured in the Agile Manifesto and have learned from our experiences doing so. What we’ve learned has motivated us to suggest changes to the manifesto to reflect the enterprise situations which we have applied agile and lean strategies in. We believe that the changes we’re suggesting are straightforward:
Where the original manifesto focused on software development, a term which too many people have understood to mean only software development, we suggest that it should focus on solution delivery.
Where the original focused on customers, a word that for too many people appears to imply only the end users, we suggest that it focus on the full range of stakeholders instead.
Where the original manifesto focused on development teams, we suggest that the overall IT ecosystem and its improvement be taken into consideration.
Where the original manifesto focused on the understanding of, and observations about, software development at the time there has been some very interesting work done within the lean community since then (and to be fair there was very interesting work done within that community long before the Agile Manifesto was written). We believe that the Agile Manifesto can benefit from lean principles.
Our suggested rewording of the Agile Manifesto follows, with our suggested changes in italics.
Updating the Values of the Agile Manifesto
We are uncovering better ways of developing software by doing it and helping others do it. Through this work we have come to value:
Individuals and interactions over processes and tools
Working solutions over comprehensive documentation
Stakeholder collaboration over contract negotiation
Responding to change over following a plan
That is, while there is value in the items on the right, we value the items on the left more.
Updating the Principles behind the Agile Manifesto
Our highest priority is to satisfy the customer through early and continuous delivery of valuable solutions.
Welcome changing requirements, even late in the solution delivery lifecycle. Agile processes harness change for the stakeholder’s competitive advantage.
Deliver working solutions frequently, from a couple of weeks to a couple of months, with a preference to the shorter timescale.
Stakeholders and developers must work together daily throughout the project.
Build projects around motivated individuals. Give them the environment and support they need, and trust them to get the job done.
The most efficient and effective method of conveying information to and within a delivery team is face-to-face conversation.
Quantified business value is the primary measure of progress.
Agile processes promote sustainable development. The sponsors, developers, and users should be able to maintain a constant pace indefinitely.
Continuous attention to technical excellence and good design enhances agility.
Simplicity--the art of maximizing the amount of work not done--is essential.
The best architectures, requirements, and designs emerge from self-organizing teams.
At regular intervals, the team reflects on how to become more effective, then tunes and adjusts its behavior accordingly.
Leverage and evolve the assets within your organizational ecosystem, and collaborate with the people responsible for those assets to do so.
Visualize workflow to help achieve a smooth flow of delivery while keeping work in progress to a minimum.
The organizational ecosystem must evolve to reflect and enhance the efforts of agile teams, yet be sufficiently flexible to still support non-agile or hybrid teams.
We’re agile – things evolve, including manifestos. Looking forward to your feedback (add a comment).
Updates Since this Was First Published:
When it comes to testing on agile projects it is common practice for agile teams to adopt a "whole team testing
" approach where the team itself does its own testing. To accomplish this agile teams will often embed testers in the development team. Programmers will work closely with the testers, often via non-solo development
strategies such as pair programming, to pick up their valuable testing skills. The testers will in turn pick up new skills from the programmers, and in effect both groups will move away from being just specialists (testers or programmers) to being what's called generalizing specialists
. Whole team testing can be very different from traditional approaches where programmers may do some testing, often unit testing of their own code, and then throw it over the wall to testers and quality assurance (QA) professionals for verification and validation.
The types of testing that the parallel independent test team performs may include:
Pre-production system integration testing. Does the solution work within your overall organizational ecosystem? Importantly, if this is one of several teams currently developing new solutions, does this team's solution work with what will be in production (including the work in progress of other teams) when they go to release? In mid-to-large organizations the only economical way to do this sort of testing is via an independent, centralized team.
. Although it's possible to do usability testing on the development team, the reality is that usability testing is a specialized skill that few people have (although could pick up via non-solo development). Furthermore, particularly for solutions with many potential users, you may want to invest in a usability testing
lab. This is a centralized resource, or an outsourced resource these days, which is shared across many teams.
. Security testing is also a specialized skill, albeit one well supported with sophisticated security testing tools such as the Rational Appscan
suite which can be included in your continuous integration (CI) strategy. Many organizations will centralize their security testing efforts.
Exploratory testing. The fundamental goal of exploratory testing is to discover where the solution breaks, as opposed to confirmatory testing which focuses on showing that the solution conforms to the requirements (this is the type of testing the development team typically focuses on). Exploratory testing is also a skill, a good one which everyone should strive to pick up, but exploratory testers are often few in number in many organizations. So, to leverage their skills effectively you may want to have some of them on the independent test team while they mentor others while doing so.
Non-functional testing. Non-functional requirements have a tendency to fall through the cracks on some development teams. Knowing this the independent test team will often "test to the risk" and focus on non-functional issues.
And much more. The above points are just exemplars, not an exact list. Please follow some of the links above for greater detail.
I'd like to leave you with several important thoughts:
The developers still do the majority of the testing. Just because there's an independent test team it doesn't imply that they are the ones doing all the testing. In fact, nothing could be further from the truth. They should be doing the minority of the testing effort, albeit the more difficult forms of it.
An independent test team will support multiple dev teams. For example, a test team of 5-6 people could support several development teams totalling 70 to 80 people. I typically look for a 15:1 or 20:1 ratio of developers to independent testers, hopefully even higher than that.
- You need to consider better tooling. Although the development team will still be using common agile testing tools such as the xUnit and FIT frameworks the independent test team (ITT) will need more sophisticated tooling. First, the ITT will need to be able to report defects back to the team easily. When the development team is using a Jazz-based tool such as Rational Team Concert (RTC) then this can easily be done using either RTC (the web interface may be sufficient) or another Jazz-enabled product such as Rational Quality Manager (RQM). Second, the ITT will likely need more sophisticated testing tools, such as Rational Appscan for static and dynamic security testing and Rational Performance Tester (RPT) for performance testing (just two of several software quality management tools you should consider).
Independent testing is economical. Although I listed several tools in my previous point (hey, I do work for a vendor after all) an "unfortunate" implication of my advice (unfortunate for IBM at least) is that you can reduce the number of licenses that you require and still get this critical testing done by centralizing their use.
It may be a bit more complicated in regulatory environments. In a strict regulatory environment the independent test team may need to repeat, or at least validate, the testing efforts of the development team. In regulatory environments my fundamental advice is always this -- Have practical people, including yourself, read and interpret the regulations. If you leave it to the bureaucrats you'll get a bureaucratic solution.
This is an important scaling technique. Parallel independent testing, when done in an agile manner, is an important technique which you should consider when scaling agile strategies to meet the uniques needs of the situation that you find yourself in.
Modified by ScottAmbler
IBM Rational recently published an update to my Agility@Scale e-book, which can be downloaded free of charge. The e-book is a 21 page, 2.3 meg PDF (sorry about the size, guess the graphics did it) . It overviews the Agile Scaling Model (ASM) (which has since been replaced by the Software Development Context Framework (SDCF) ), Disciplined Agile Delivery (DAD), the scaling factors of agility at scale, and ends with some advice for becoming as agile as you can be. In short it's a light-weight coverage of some of the things I've been writing about in this blog the past couple of years. Could be a good thing to share with the decision makers in your organization if they're considering adoption agile strategies.
I'm happy to announce that a revised version of the Lean Development Governance
white paper which I co-wrote with Per Kroll is now available. This version of the paper reflects our learnings over the past few years helping organizations to improve their governance strategies.
There's a more detailed description of the paper here