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 on 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.
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.
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
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.
Modified on by ScottAmbler
An imporant step in scaling your agile strategy is to adopt a Disciplined Agile Delivery (DAD)
approach instead of one which is just focused on agile construction. One aspect of adopting a DAD approach it to mature your focus from just producing software to instead providing a solution which meets the needs of its stakeholders within the appropriate economic, cultural, and technical constraints. The fundamental observation is that as IT professionals we do far more than just develop software. Yes, this is clearly important, but in addressing the needs of our stakeholders we will often:
Provide new or upgraded hardware
Change the business/operational processes which stakeholders follow
Change the organizational structure in which our stakeholders work
Update supporting documentation
And yes, develop high-quality software
Although delivery of high-quality, working software is important it is even more important that we deliver high-quality working solutions to our stakeholders. Minimally IT professionals should have the skills and desire to produce good software, but what they really need are the skills and desire to provide good solutions. We need strong technical skills, but we also need strong "soft skills" such as user interface design and process design to name just two.
The shift to a solution-oriented focus from a software-oriented focus requires your agile teams to address some of the software-oriented prejudices which crept into the Agile Manifesto
. The people who wrote the manifesto (which I fully endorse) were for the most part software developers, consultants, and in many cases both. It is little wonder that this group would allow a bias towards software development creep into the language of their manifesto.
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.
activities are evolutionary (iterative and incremental) and highly collaborative in nature. Initially requirements are explored at a high level via requirements envisioning
at the beginning of the project and the details are explored on a just-in-time (JIT) basis via iteration modeling
and model storming
activities. The way that you perform these agile practices, and the extent to which you do so, depends on the situation in which a project team finds itself. The Agile Scaling Model (ASM)
is a contextual framework for effective adoption and tailoring of agile practices to meet the unique challenges faced by a system delivery team of any size. To see how this works, let's apply the concepts of the ASM to see how we would scale our agile approach to requirements.
First, let's consider how a small, co-located team would work. The first two categories of the ASM are core agile development and disciplined agile delivery
, the focus of both are small co-located teams in a fairly straightforward situation. In these situations simple techniques such as user stories
written on index cards and sketches on whiteboards
work very well, so the best advice that I can give is to stick with them. Some teams will take a test-driven development
(TDD) approach where they capture their requirements and design in the form of executable specifications
, although this sort of strategy isn't as common as it should be (yet!), likely because of the greater skill and discipline that it requires. Traditionalists often balk at this approach, believing that they need to document the requirements in some manner. But, for a small co-located team working in a collaborative manner, requirements documentation proves to be little more than busy work, often doing nothing more than justifying the existence of a business analyst who hasn't made the jump to agile yet. Don't get me wrong, there are good reasons to write some requirements documentation, and we'll see this in a minute, but you should always question any request for written specifications and try to find more effective ways to address the actual goal(s) motivating the request. Never forget that written documentation
is the least effective communication
option available to you.
Although inclusive tools
such as whiteboards and paper work well for requirements, for development activities you will need electronic tools. You will either put together an environment from point-specific tools or adopt something more sophisticated such as IBM Rational Team Concert (RTC)
which is already fully integrated and instrumented. RTC is a commercial tool, but luckily you can download a 10-license environment free of charge, which is just perfect for a small team. Larger teams, of course, will need to purchase licenses. One of the things that a disciplined agile delivery approach adds to core agile development is it addresses the full delivery life cycle, which is important because it explicitly includes pre-construction activities such as requirements envisioning. The first step in scaling agile techniques is to adopt a full delivery life cycle which covers the full range of activities required to initiate a project, produce the solution, and then release to solution to your end users.
More interesting is the third category of the ASM, Agility@Scale, and how its eight agile scaling factors
affect the way that you tailor your process and tooling strategy. Let's explore how each one could potentially affect your agile requirements strategy:
- Geographical distribution. The majority of agile teams are distributed in some manner -- some people are working in cubicles or private offices, on different floors, in different buildings, or even in different countries -- and when this happens your communication and coordination risks goes up. To counter this risk you will need to perform a bit more requirements envisioning up front to help ensure that everyone is working to the same vision, although this doesn't imply that you need to write detailed requirements speculations which would dramatically increase the risk to your project. Remember, agilists do just barely enough modeling and are prepared to iteratively elicit the details when they need to do so. The more distributed the team is the more likely they will need to adopt software-based requirements modeling tools such as IBM Rational Requirements Composer (RRC) which supports streamlined, agile requirements elicitation throughout the delivery life cycle. Index cards and whiteboards are great, but they're difficult to see if you're outside the room where they're posted. I've written a fair bit about distributed agile development in this blog.
- Team size. Some organizations, including IBM, are successfully applying agile techniques with teams of hundreds of people. A team of one hundred people will naturally work much differently than a team of ten people, or of one thousand people. Large teams are organized into collections of smaller teams, and the requirements for the overall project must be divvied up somehow between those teams. The implications are that as the team size grows you will need to invest a bit more time in initial requirements envisioning, and in initial architecture envisioning for that matter; you will need to use more sophisticated tools; and may need to use more sophisticated modeling techniques such as use cases and functional user interface prototypes. See large agile teams for more advice.
- Compliance requirement. When regulatory issues – such as Sarbanes Oxley, ISO 9000, or FDA CFR 21 – are applicable you are likely going to be required to capture requirements specifications in some manner and to enact traceability between those requirements. However, I highly recommend that you read the actual regulations yourself and don't let bureaucrats interpret them for you (doesn't it always seem that their interpretation always results in an onerous, documentation heavy solution?) because I have yet to run into a regulation which required you to work in an ineffective manner. Managing your requirements as work items in RTC can often more than meet your regulatory requirements for documentation and traceability, although you may want to consider a tool such as IBM Rational RequisitePro for complex regulatory situations.
- Domain complexity. The manner in which you elicit requirements for a data entry application or an informational web site will likely be much simpler than for a bio-chemical process monitoring or air traffic control system. More complex domains will require greater emphasis on exploration and experimentation, including but not limited to prototyping, modeling, and simulation. Although user stories may be effective as a primary requirements artifact in simple domains, in more complex domains you are likely to find that you need to drive your requirements effort with more sophisticated modeling techniques.
- Organization distribution. Sometimes a project team includes members from different divisions, different partner companies, or from external services firms. In these cases, particularly where the work is strictly organized between the various organizations (perhaps for security concerns), you may need a more sophisticated approach to managing the requirements. RTC enables you to organize the requirements between teams, and then to automatically track progress in real time via the RTC project dashboard.
- Technical complexity. The technical complexity of a solution can vary widely, from a single platform silo application to a multi-platform application working with legacy systems and data to a full-blown systems engineering effort. Complex technical domains, just like complex business domains, require more complex strategies for requirements elicitation and management. The requirements for your legacy systems are likely to have been captured using tools and techniques appropriate for that platform, for example the requirements for your COBOL application may have been captured using data flow diagrams and data models, whereas the requirements for your Java legacy application where captured using UML diagrams. The subteam working on the COBOL system might be using IBM Rational Application Developer (RAD) and RTC for Z whereas the Java subteam may use Eclipse with RTC. Because systems engineering projects can stretch on for years, particularly when the hardware is being developed in parallel to the software, sophisticated tooling such as IBM Rational DOORS is often used in these situations. For more information about systems engineering, see the IBM Rational Harmony process.
- Organizational complexity. Your approach to requirements elicitation and management will be affected by a host of organizational complexities, including your corporate culture. When the culture is flexible and collaborative you can be very agile in your approach to requirements, but as it becomes more rigid you become more constrained in what is considered acceptable and thus take on greater project risk. For example, many organizations still struggle with their approach to funding projects, often demanding that the project team provides an "accurate" estimate up front to which they will be held to. This in turn motivates risky behavior on the part of the development, including a "big requirements up front (BRUF)" approach where a detailed requirements speculation is developed early in the project. This is just one example of how questionable corporate culture can impact the way in which an agile team works.
- Enterprise discipline. Some organizations have enterprise-level disciplines, such as enterprise architecture, enterprise business modeling, strategic reuse, and portfolio management in place. These disciplines can easily be agile and from what I can tell the more successful efforts appear to lean more towards the agile end of the spectrum rather than the traditional end. Having an enterprise business modeling effort underway will affect your project-level requirements strategy -- you'll be able to leverage existing models, have access to people who understand the domain at an enterprise level, and will likely need to map your project efforts back to your enterprise models. The enterprise modelers will likely be using tools such as IBM Rational System Architect or IBM Websphere Business Modeler.
It is important to note that the way that you tailor the agile practices that you follow, and the tools that you use, will reflect the situation that you find yourself in. In other words, you need to right size your process and the Agile Scaling Model (ASM) provides the context to help you do so. As you saw above, in simpler situations you will use the simpler tools and techniques which are commonly promoted within the core agile development community. But, when things become a bit more complex and one or more of the scaling factors applies you need to modify your approach -- just don't forget that you should strive to be as agile as you can be given the situation that you find yourself in.
Modified on by ScottAmbler
In 2009 I wrote a white paper entitled The Agile Scaling Model (ASM): Adapting Agile Methods for Complex Environments for IBM Rational. Apparently it's been taken down, which I think is unfortunate as it contains some interesting ideas that your organization may be able to benefit from.
The original white paper addresses several key issues:
It provides and explains a definition for disciplined agile delivery. A more up to date discussion of DAD can be found on the Disciplined Agile Delivery site.
It describes criteria to determine is a team is agile. I've explored this issue via several surveys over the years since then. See the January 2013 How Agile Are You? results.
It describes the ASM, which distinguishes between core agile development techniques, disciplined agile delivery strategies, and agility at scale. The ASM was superceded in early 2013 by the Software Development Context Framework (SDCF). Perhaps this is why the ASM paper was taken down??
It overviews the eight scaling factors which a delivery team may face, scaling factors which motivate changes in the process that you will follow and the tools that you will adopt. The SDCF provides my recent thoughts regarding scaling factors. I have also run various IT Surveys over the years exploring how well organizations fare at scaling agile.
It describes the implications of the ASM. My blog posting Scaling Agile: Start with a Disciplined Foundation covers this very well.
It argues that you should strive to be as agile as you need to be, and that will be driven by the situation that you face.
On Tuesday, Dec 1, 2009 Philippe Kruchten
, Bruce MacIsaac
, and myself participated on two virtual panels about the future of the Unified Process (we did two to support callers from around the globe) for the Global Rational User's Group (GRUG)
. During the panel sessions we discussed a bit of the history of the Unified Process, some of the misconceptions people have with it, some of the common mistakes people made implementing it (instantiating it to be documentation heavy and/or serial) due to those misconceptions, how it can be very agile if you choose to instantiate it that way, the OpenUP
, the AUP
, how UP relates to the IBM Practices
, and other topics.
The links to the recordings are:
Hope you find it interesting. As I've written in the past, the RUP can be as agile as you want to make it. Furthermore, there are a lot of really good ideas in the RUP that the agile community can and should choose to mine, although sadly I see far too many teams doing things the hard way and reinventing the process wheel on their own. I hope they're enjoying themselves, because it clearly isn't a very efficient way for them to go about process improvement.
The Agile Scaling Model (ASM) is a contextual framework for effective adoption and tailoring of agile practices to meet the unique challenges faced by a system delivery team of any size.
The ASM distinguishes between three scaling
- Core agile development. Core agile methods, such as Scrum and Agile Modeling, are self governing, have a value-driven system development lifecycle (SDLC), and address a portion of the development lifecycle. These methods, and their practices, such as daily stand up meetings and requirements envisioning, are optimized for small, co-located teams developing fairly straightforward systems.
- Disciplined agile delivery. Disciplined agile delivery processes, which include Dynamic System Development Method (DSDM) and Open Unified Process (OpenUP), go further by covering the full software development lifecycle from project inception to transitioning the system into your production environment (or into the marketplace as the case may be). Disciplined agile delivery processes are self organizing within an appropriate governance framework and take both a risk and value driven approach to the lifecycle. Like the core agile development category, this category is also focused on small, co-located teams delivering fairly straightforward systems. To address the full delivery lifecycle you need to combine practices from several core methods, or adopt a method which has already done so.
- Agility at Scale. This category focuses on disciplined agile delivery where one or more scaling factors are applicable. The eight scaling factors are team size, geographical distribution, regulatory compliance, organizational complexity, technical complexity, organizational distribution, domain complexity, and enterprise discipline. All of these scaling factors are ranges, and not all of them will likely be applicable to any given project, so you need to be flexible when scaling agile approaches to meet the needs of your unique situation. To address these scaling factors you will need to tailor your disciplined agile delivery practices and in some situations adopt a handful of new practices to address the additional risks that you face at scale.
The first step in scaling agile approaches is to move from partial methods to a full-fledged, disciplined agile delivery process. Mainstream agile development processes and practices, of which there are many, have certainly garnered a lot of attention in recent years. They’ve motivated the IT community to pause and consider new ways of working, and many organizations have adopted and been successful with them. However, these mainstream strategies (such as Extreme Programming (XP) or Scrum, which the ASM refers to as core agile development strategies) are never sufficient on their own; as a result organizations must combine and tailor them to address the full delivery life cycle. When doing so the smarter organizations also bring a bit more discipline to the table, even more so than what is required by core agile processes themselves, to address governance and risk.
The second step to scaling agile is to recognize your degree of complexity. A lot of the mainstream agile advice is oriented towards small, co-located teams developing relatively straightforward systems. But once your team grows, or becomes distributed, or you find yourself working on a system that isn’t so straightforward, you find that the mainstream agile advice doesn’t work quite so well – at least not without sometimes significant modification. Each of the scaling factors introduces their own risks, and when addressed effectively can actually reduce project risk, and for your project team to succeed you will want to identify the scaling factors applicable to the situation that you face and act accordingly. Unfortunately, this is a lot easier said (OK, in this case blogged about) than done.
IBM Rational advocates disciplined agile delivery as the minimum that your organization should consider if it wants to succeed with agile techniques. You may not be there yet, still in the learning stages. But our experience is that you will quickly discover how one or more of the scaling factors is applicable, and as a result need to change the way you work.
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.
At IBM Rational we define disciplined agile delivery as:
Disciplined agile delivery is an evolutionary (iterative and incremental) approach which regularly produces high quality solutions in a cost effective and timely manner via a risk and value driven life cycle. It is performed in a highly collaborative, disciplined, and self-organizing manner within an appropriate governance framework, with active stakeholder participation to ensure that the team understands and addresses the changing needs of its stakeholders to maximize business value provided. Disciplined agile delivery teams provide repeatable results by adopting just the right amount of ceremony for the situation which they face.
Let’s explore the key points in this definition:
- Full delivery life cycle. Disciplined agile delivery processes have life cycles which are serial in the large and iterative in the small. Minimally they have a release rhythm which recognizes the need for start up/inception activities, construction activities, and deployment/transition activities. Better yet, they include explicit phases as well. It is very important to note that these are not the traditional waterfall phases – requirements, analysis, design, and so on – but instead different “seasons” of a project. The point is that we need to look beyond agile software development and consider the full complexities of solution delivery. Adopting a full delivery life cycle, not just a construction life cycle, is arguably the “zeroth” agile scaling factor.
- Evolutionary. Agile strategies are both iterative and incremental in nature. Iterative means that you are working in a non-serial manner, on any given day you may do some requirements analysis, some testing, some programming, some design, some more testing, and so on. Incremental means that you add new functionality and working code to the most recent build, until such time as the stakeholder determines there is enough value to release the product.
- Regularly produces high quality solutions. Agilists are said to be quality focused. They prefer to test often and early, and the more disciplined ones even take a test-first approach where they will write a single test and the just enough production code to fulfill that test (then they iterate). Many agile developers have adopted the practice of refactoring, which is a technique where you make simple changes to your code or schema which improves its quality without changing its semantics. Adoption of these sorts of quality techniques seems to work – it appears that agile teams are more likely to deliver high quality systems than traditional teams (according to the DDJ 2008 Project Success survey). Within IBM we take it one step further and focus on consumability, which encompasses quality and other features such as ease of deployment and system performance. Furthermore, although some agile methods promote the concept of producing “potentially shippable software” on a regular basis, disciplined agile delivery teams produce solutions: a portion of which may be software, a portion of which may be hardware, and a portion of which will be the manner in which the system is used.
- Cost effective and timely manner. Agile teams prefer to implement functionality in priority order [http://www.agilemodeling.com/essays/prioritizedRequirements.htm], with the priority being defined by their stakeholders (or a representative thereof). Working in priority order enables agile teams to maximize the return on investment (ROI) because they are working on the high-value functionality as defined by their stakeholders, thereby increasing cost effectiveness. Agile teams also prefer to produce potentially shippable solutions each iteration (an iteration is a time-box, typically 2-4 weeks in length), enabling their stakeholders to determine when they wish to have a release delivered to them and thereby improving timeliness. Short iterations reduce the feedback cycle, improving the chance that agile teams will discover problems early (they “fail fast”) and thereby enable them to address the problems when they’re still reasonably inexpensive to do so. The DDJ 2008 Project Success survey found that agile teams are in fact more likely to deliver good ROI than traditional teams and more likely to deliver in a timely manner.
- Value driven life cycle. One result of building a potentially shippable solution every iteration is that agile teams produce concrete value in a consistent and visible manner throughout the life cycle.
- Risk and value driven life cycle. Core agile processes are very clear about the need to produce visible value in the form of working software on a regular basis throughout the life cycle. Disciplined agile delivery processes take it one step further and actively mitigate risk early in the life cycle – during project start up you should come to stakeholder concurrence regarding the project’s scope, thereby reducing significant business risk, and prove the architecture by building a working skeleton of your system, thereby significantly reducing technical risk. They also help with transition to agile, allowing traditional funding models to use these milestones before moving to the finer grained iteration based funding that agile allows.
- Highly collaborative. People build systems, and the primary determinant of success on a development project is the individuals and the way that they work together. Agile teams strive to work closely together and effectively as possible. This is a characteristic that applies to both engineers on the team, as well as their leadership.
- Disciplined. Agile software development requires greater discipline on the part of practitioners that what is typically required by traditional approaches.
- Self organizing. This means that the people who do the work also plan and estimate the work.
- Self-organization within an appropriate governance framework. Self-organization leads to more realistic plans and estimates which are more acceptable to the people implementing them. At the same time these self-organizing teams must work within an appropriate governance framework which reflects the needs of their overall organizational environment. An “appropriate governance framework” explicitly enables disciplined agile delivery teams to effectively leverage a common infrastructure, to follow organizational conventions, and to work towards organizational goals. The point is that project teams, regardless of the delivery paradigm they are following, need to work within the governance framework of their organization. More importantly, effective governance programs should make it desirable to do so. Our experience is that traditional, command-and-control approaches to governance where senior management explicitly tells teams what to do and how to do it don’t work very well with agile delivery teams. We’ve also found that lean development governance, an approach which is based on collaboration and enablement, is far more effective in practice. Good governance increases the chance that agile delivery teams will build systems which fit into your overall organizational environment, instead of yet another stand-alone system which increases your overall maintenance burden and data quality problems.
- Active stakeholder participation. Agile teams work closely with their stakeholders, who include end users, managers of end users, the people paying for the project, enterprise architects, support staff, operations stuff, and many more. Within IBM we distinguish between four categories of stakeholder: principles/sponsors, partners (business partners and others), end users, and insiders These stakeholders, or their representatives (product owners in Scrum, or on-site customers in Extreme Programming, or a resident stakeholder in scaling situations), are expected to provide information and make decisions in a timely manner.
- Changing needs of stakeholders. As a project progresses your stakeholders will gain a better understanding of what they want, particularly if you’re showing them working software on a regular basis, and will change their “requirements” as a result. Changes in the business environment, or changes in organization priority, will also motivate changes to the requirements. There is a clear need for agile requirements change management [http://www.agilemodeling.com/essays/changeManagement.htm] on modern IT projects.
- Repeatable results. Stakeholders are rarely interested in how you delivered a solution but instead in what you delivered. In particular, they are often interested in having a solution which meets their actual needs, in spending their money wisely, in a high-quality solution, and in something which is delivered in a timely manner. In other words, they’re interested in repeatable results, not repeatable processes.
- Right amount of ceremony for the situation. Agile approaches minimize ceremony in favor of delivering concrete value in the form of working software, but that doesn’t mean they do away with ceremony completely. Agile teams will still hold reviews, when it makes sense to do so. DDJ’s 2008 Modeling and Documentation Survey found that agile teams will still produce deliverable documentation, such as operations manuals and user manuals, and furthermore are just as likely to do so as traditional teams. The DDJ September 2009 State of the IT Union survey found that the quality of the documentation delivered by agile teams was just as good as that delivered by traditional teams, although iterative teams (e.g. RUP teams) did better than both agile and traditional.
At Agile 2009 in August Sue McKinney, VP of Development Transformation with IBM Software Group, was interviewed by DZone's Nitin Bharti about IBM's experiences adopting agile techniques. There are over 25,000 developers within IBM Software Group alone. Follow the link to the interview
to view it online (there is also a text transcript posted there. There's some great insights into the realities of scaling agile in large teams, in distributed agile development, and in particular how to transform a large organization's development staff.
Modified on by ScottAmbler
When I talk to people about scaling agile techniques, or about agile software development in general, I often put describe strategies in terms of various risks. I find that this is an effective way for people to understand the trade-offs that they're making when they choose one strategy over another. The challenge with this approach is that you need to understand these risks that you're taking on, and the risks that you're mitigating, with the techniques that you adopt. Therein lies the rub, because the purveyors of the various process religions ( oops I mean methodologies) rarely seem to coherently the discuss the risks which people take on (and there's always risk) when following their dogma (oops, I mean sage advice).
For example, consider the risks associated with the various strategies for initially specifying requirements or design. At the one extreme we have the traditional strategy of writing initial detailed speculations, more on this term in a minute, and at the other extreme we have the strategy of just banging out code. In between are Agile Modeling (AM) strategies such as requirements envisioning and architecture envisioning (to name a few AM strategies). Traditionalists will often lean towards the former approach, particularly when several agile scaling factors apply, whereas disciplined agile developers will lean towards initial envisioning. There are risks with both approaches.
Let's consider the risks involved with writing detailed speculations (there's that term again):
You're speculating, not specifying. There is clearly some value with doing some up-front requirements or architecture modeling, although the data regarding the value of modeling is fairly slim (there is a lot of dogma about it though), but that value quickly drops off in practice. However, the more you write the greater the chance that you're speculating what people want (when it comes to requirements) or how you're going to build it (when it comes to architecture/design). Traditionalists will often underestimate the risks that they're taking on when they write big requirements up front (BRUF) , or create big models up front (BMUF) in general, but in the case of BRUF the average is that a large percentage of the functionality produced is never used in practice -- this is because the detailed requirements "specifications" contained many speculations as to what people wanted, many of which proved to be poor guesses in practice.
You're effectively committing to decisions earlier than you should. A side effect of writing detailed speculations is that by putting in the work to document, validate, and then update the detailed speculations the decisions contained in the speculations become firmer and firmer. You're more likely to be willing to change the content of a two-page, high-level overview of your system requirements than you are to change the content of a 200-page requirements speculation that has been laboriously reviewed and accepted by your stakeholders. In effect the decision of what should be built gets "carved in stone" early in the process. One of the principles of lean software development is to defer decisions as late as possible, only making them when you need to, thereby maximizing your flexibility. In this case by making requirements decisions early in the process through writing detailed speculations, you reduce your ability to deliver functionality which meets the actual needs of your stakeholders, thereby increasing project risk.
You're increasing communication risk. We've known for decades that of all the means of communication that we have available to us, that sharing documentation with other people is the riskiest and least effective strategy available to us for communicating information (face-to-face communication around a shared sketching environment is the most effective). At scale, particularly when the team is large or the team geographically distributed, you will need to invest a little more time producing specifications then when the team is co-located, to reduce the inherent risks associated with those scaling factors, but that doesn't give you license to write huge tomes. Agile documentation strategies still apply at scale. Also, if you use more sophisticated tooling you'll find it easier to promote collaboration on agile teams at scale.
You're traveling heavy. Extreme Programming (XP) popularized the concept of traveling light. The basic idea is that any artifact that you create must be maintained throughout the rest of the project (why create a document if you have no intention of keeping it up to date). The implication is that the more artifacts you create the slower you work due to the increased maintenance burden.
There are also risks involved with initial envisioning:
You still need to get the details. Just because you're not documenting the details up front doesn't imply that you don't need to understand them at some point. Agile Modeling includes several strategies for exploring details throughout the agile system development life cycle (SDLC), including iteration modeling performed at the beginning of each iteration as part of your overall iteration planning activities, just in time (JIT) model storming throughout the iteration, and test-driven development (TDD) for detailed JIT executable specification.
You need access to stakeholders. One of the fundamental assumptions of agile approaches is that you'll have active stakeholder participation throughout a project. You need to be able to get information from your stakeholders in a timely manner for the previously listed AM techniques to work effectively. My experience is that this is fairly straightforward to achieve if you educate the business as to the importance of doing so and you stand up and fight for it when you need to. Unfortunately many people don't insist on access to stakeholders and put their projects at risk as a result.
You may still need some documented speculations. As noted previously you may in fact need to invest in some specifications, particularly at scale, although it's important to recognize the associated risks in doing so. For example, in regulatory compliance situations you will find that you need to invest more in documented speculations simply to ensure that you fulfill your regulatory obligations (my advice, as always, is to read the regulations and then address them in a practical manner).
The ways that you approach exploring requirements, and formulating architecture/design, are important success criteria regardless of your process religion/methodology. No strategy is risk free, and every strategy makes sense within given criteria. As an IT professional you need to understand the risks involved with the various techniques so that you can make the trade-offs best suited for your situation. One process size does not fit all.
My final advice is to take a look at the Disciplined Agile Delivery (DAD) framework as it provides a robust strategy for addressing the realities of agile software development in enterprise settings.
Recently I spent some time in the UK with Julian Holmes of Unified Process Mentors
. In one of our conversations we deplored what we were seeing in the agile community around certification, in particular what the Scrum community was doing, and he coined the term “integrity debt” to describe the impact it was having on us as IT professionals. Integrity debt is similar to technical debt
which refers to the concept that poor quality (either in your code, your user interface, or your data) is a debt that must eventually be paid off through rework. Integrity debt refers to the concept that questionable or unprofessional behavior builds up a debt which must eventually be paid off through the rebuilding of trust with the people that we interact with.
The agile community has been actively increasing their integrity debt through the continuing popularity of Scrum Certification, in particular the program around becoming a Certified Scrum Master (CSM). To become a CSM you currently need to attend, and hopefully pay attention during, a two-day Scrum Master Certification workshop taught by a Certified Scrum Trainer (CST). That’s it. Granted, some CSTs will hold one or more quizzes which you need to pass, an optional practice which isn’t done consistently, to ensure that you pay attention in the workshop.
Scrum Masters, as you know, take the leadership position on a Scrum team. The idea that someone can master team leadership skills after two entire days of training is absurd. Don’t get me wrong, I’m a firm supporter of people increasing their skillset and have no doubt that many of the CSTs deliver really valuable training. However, there is no possible way that you can master a topic, unless it
is truly trivial, in only two days of training. From what I can tell the only thing that is being certified here is that your check didn’t bounce.
The CSM scheme increases the integrity debt of the IT industry by undermining the value of certification. When someone claims that they’re certified there’s an assumption that they had to do something meaningful to earn that certification. Attending a two-day course, and perhaps taking a few quizzes where you parrot back what you’ve heard, clearly isn’t very meaningful. The problem with the term Certified Scrum Master is two-fold: not only does the term Certified imply that the holder of the certification did something to earn it, the term Master implies that they have significant knowledge and expertise gained over years of work.
It is very clear that people are falling for the Scrum certification scheme.
A quick search of the web will find job ads requiring that candidates be CSMs, undoubtedly because they don’t realize that there’s no substance behind the certification. Whenever I run into an organization that requires people to be CSMs I walk them through the onerous process of earning the designation and suggest that they
investigate the situation themselves. Invariably, once they recognize the level of deception, the customer drops the requirement that people be CSMs.
Another quick search of the web will find people bragging about being a CSM, presumably being motivated by the employment opportunities within the organizations gullible enough to accept Scrum certification at face value. My experience is that the people claiming to be CSMs are for the most part decent, intelligent people who 99.99% of the time have far more impressive credentials to brag about than taking a two-day course. Yet, for some reason they choose to park their integrity at the door when it comes to Scrum certification. I suspect that this happens in part because they see so many other people doing it, in part because they’re a bit desperate to obtain or retain employment in these tough economic times, and in part because the IT industry doesn’t have a widely accepted code of ethical conduct. These people not only embarrass themselves when they indicate on their business cards or in their email signatures that they’re Certified Scrum Masters they also increase the integrity debt of the agile community as a whole.
Yet another search of the web will find people bragging about being Certified Scrum Trainers (CSTs), the people whom have been blessed by the Scrum Alliance to deliver Scrum master certification courses. Once again, my experience is that these are intelligent, skilled people, albeit ones who have also parked their integrity at the door in the pursuit of a quick buck. Surely these people could make a decent living via more ethical means? I know that many of them have done so in the past, so I would presume that they could do so in the future. The actions of the CSTs increase our integrity debt even further.
The group of people who have most embarrassed themselves, in my opinion, are those whom we consider thought leaders within the agile community. Leaving aside the handful who are directly involved with the Scrum certification industry, the real problem lies with those who have turned a blind eye to all of this. The Scrum certification scheme was allowed to fester within our community because few of our thought leaders had the courage to stand up and publicly state what they were talking about in private. This of course is all the more galling when you consider how much rhetoric there is around the importance of courage on software development projects. As Edmund Burke once observed, all that is necessary for evil to triumph is for good men to do nothing.
There are several things that we can do today to start paying off some of our integrity debt:
- Be discerning, not deceptive. If you’re going to list credentials on your email signature or business card then only choose to list the ones that actually mean something.
- Educate human resources people. Make them aware of what “Certified Scrum Master” really means and let them think for themselves. I highly suspect that if HR people realized what was going on the demand for CSMs would plummet, and in turn people wouldn’t be tempted by Scrum certification.
- Act professional, don’t just claim to be certified. Instead of signing up for every easy certification that comes your way why not simply do a good job and let the people you work with be your claim to fame? The good news is that for the past few years the agile community has tried to pay down some of the IT industry’s integrity debt that we have with our stakeholders by providing better return on investment (ROI), delivering systems which are more effective at addressing the needs of your stakeholders, by working in a more timely manner, and by producing greater quality work. All of these claims are borne out by the 2008 Software Development Project Success Rate Survey by the way.
- Recognize that adding a test doesn’t address the underlying problems. For the past year there’s been a move afoot to have people pass a test as part of earning their CSM (apparently it’s been a challenge to create a non-trivial test to validate your understanding of a topic that you can master by taking a two-day training course). This is something that should have been done from the very beginning, along with some sort of peer review, not years later when the damage has been done. Adding a test at this late date isn’t going to remove the stink that’s built up over the years, but sadly it will fool a few people into believing that they’ve covered it up.
- Recognize that there is a demand for certification. The agile community needs to put together a decent certification program, something that the Scrum Alliance has clearly failed at doing. My article Coming Soon: Agile Certification provides some thoughts as to what we need to do. The good news is that people such as Ron Jeffries and Chet Hendrickson, and others, are putting together a developer certification program. The really good news is that these are the right people to do this. The really bad news is that they’re doing it under the aegis of the Scrum Alliance, so whatever they accomplish will unfortunately be tainted by the fallout of the CSM debacle.
If we're going to scale agile software development strategies to meet the range of challenges faced by modern organizations, we need to be trustworthy. Is claiming to be a certified master after taking a two-day course an act which engenders trust? I don't think so. As individuals we can choose to do better. As a community we need to.Suggested Reading
- Agile Certification -- A humorous look at certification.
- IT Surveys -- A great resource for statistics about what IT people are actually doing in practice.
I was recently in Bangalore speaking at the Rational Software Conference, which was really well done this year, and visiting customers. In addition to discussing how to scale agile software development approaches, particularly when the team is distributed geographically and organizationally, I was also asked about what I thought about a software factory approach to development. My instinctual reaction was negative, software factories can result in lower overall productivity as the result of over specialization of staff (I prefer generalizing specialists
), too many hand-offs between these specialists (I find close collaboration to be far more effective), and too much bureaucratic overhead to coordinate these activities. I initially chalked it up to these people still believing that software development was mostly a science, or perhaps an engineering domain, whereas my experiences had made me come to believe that software development is really more art than it is a science. Yet, the consistent belief in this strategy by very smart and experienced people started me thinking about my position.
Just let me begin by saying that this blog posting isn't meant to be yet another round in the age old, and relatively inane, "art vs. science" debate within the software development community. That debate is a symptom of versusitis
, a dread disease which particularly plagues the IT industry and which can any of us at any time. There is no known cure, although the combination of experience, open-mindedness, and critical thought are the best inoculation against versusitis that we have so far. In that vein, let me explore the issues as I see them and I will let you think for yourself.
On the one hand software development has aspects of being an art for several reasons. First, the problem definition is never precise, nor accurate, and even when we have detailed specifications the requirements invariably evolve
anyway. The lack of defined, firm requirements requires us to be flexible and to adjust to the situation that we find ourselves in. Second, teams typically find themselves in unique situations, necessitating a unique process and tool environment to reflect this (assuming that you want to be effective, otherwise there's nothing stopping you from having a "repeatable process" and consistent tool environment). Third, software is built by people for people, requiring that the development team have the ability to build a system with a user interface which meets the unique needs of their end users. One has only to look at the myriad UI designs out there to see that surely there is a bit of art going on. Fourth, if software development wasn't at least partially art then why hasn't anyone succeeded at building tools which take requirements as inputs and produce a viable solution that we can easily deploy? It's been over four decades now, so there's been sufficient time and resources available to build such tooling. Fifth, regardless of how much of a scientific/business facade we put over it, our success rate at producing up front detailed cost estimates and schedules speak for itself (see Funding Agile Projects
for links to articles).
On the other hand software development has aspects of being a science for several reasons. First, some aspects of software development have in fact been automated to a significant extent. Second, there is some mathematical basis to certain aspects of software development (although in the case of data-oriented activities the importance of relational theory
often gets blown way out of proportion and I have yet to see a situation where formal methods proved to be of practical value).
What does this have to do with Agility@Scale. As you know, one of the agile scaling factors
is Organizational Complexity, and cultural issues are the hardest to overcome. Whether your organization believes that software development is mostly an art or mostly a science is a cultural issue which will be a major driver in you choice of methods and practices. Organizations which believe that software development is more of a science will prefer strategies such as software factories, model-driven architecture (MDA),
and master data management (MDM)
. And there is ample evidence to support the claims that some organizations are succeeding at these strategies. Although you may not agree with these strategies, you need to respect the fact that many organizations are making them work in their environments. Similarly, organizations which believe that software development is more of an art will find that agile and lean strategies are a better fit, and once again there is ample evidence that organizations are succeeding with these approaches (there's also evidence that agile projects are more successful
than traditional projects, on average). Once again, you may not agree with these strategies but you need to respect the fact that other people are making them work in practice.
Trying to apply agile approaches within an organization that believes software development is mostly a science will find it difficult at best, and will likely need to embark on a multi-year program to shift their culture (likely an expensive endeavor which won't be worth the investment). Similarly, trying to apply a software factory strategy in an organization that believes that software development is mostly an art will also run aground. The bottom line is that one size does not fit all, that one strategy is
not right for all situations and that you need to understand the trade-offs of various strategies, methodologies, techniques, and practices and apply them appropriately given the situation that you face. In other words, it depends! If you are embarking on a software process initiative, and you don't have the broad experience required to effective choose between strategies (very few organizations do, although many believe otherwise), then you should consider Measured Capability Improvement Framework (MCIF)
to help increase your chance of success.
Modified on by ScottAmbler
For several years now I've written various articles and newsletters on the topics of estimating and funding strategies for software development projects, and in particular for agile software development projects. Whenever I talk to people about agile software development, or coach them in how to succeed at it, some of the very first questions that I'll be asked, particularly by anyone in a management role, is how to fund agile software development projects. Apparently a lot of people think that you can only apply agile strategies on small, straightforward projects where it makes sense to do a time and materials (T&M) approach. In fact you can apply agile strategies in a much greater range of situations, as the various surveys
that myself and others are showing time and again. My goal with this blog posting is to summarize the various strategies for, and issues surrounding, the funding of agile software development projects.
There are three basic strategies for funding projects, although several variations
clearly exist. These strategies are:
- "Fixed price". At the beginning of the project develop, and then commit to, an initial estimate based on your up-front requirements and architecture modeling efforts. Hopefully this estimate is given as a range, studies have shown that up-front estimating techniques such as COCOMO II or function points are accurate within +/- 30% most of the time although my July 2009 State of the IT Union survey found that on average organizations are shooting for +/- 11% (their actuals come in at +/- 19% on average, but only after doing things such as dropping scope, changing the estimate, or changing the schedule). Fixed-price funding strategies are very risky in practice because they promote poor behavior on the part of development teams to overcome the risks foisted upon them as the result of this poor business decision. It is possible to do agile on a fixed budget but I really wouldn't recommend it (nor would I recommend it for traditional projects). If you're forced to take a fixed-price approach, and many teams are because the business hopes to reduce their financial risk via this approach not realizing that it actually increases their risk, then adopt strategies that reduce the risk.
- Stage gate. Estimate and then fund the project for given periods of time. For example, fund the project for a 3-month period then evaluate it's viability, providing funding for another period of time only to the extent that it makes sense. Note that stages don't have to be based on specific time periods, they could instead be based on goals such as to intiate the project, prove the architecture with working code, or to build a portion of the system. Disciplined agile methods such as Open Unified Process have built in stage-gate decision points which enable this sort of strategy. When the estimation technique is pragmatic, the best approaches are to have either the team itself provide an estimate for the next stage or to have an expert provide a good gut feel estimate (or better yet have the expert work with the team to develop the estimate). Complex approaches such as COCOMO II or SLIM are often little more than a process facade covering up the fact that software estimating is more of an art or a science, and prove to be costly and time consuming in practice.
- Time and materials (T&M). With this approach you pay as you go, requiring your management team to actually govern the project effectively. Many organizations believe a T&M strategy to be very risky, which it is when your IT governance strategy isn't very effective. An interesting variation, particularly in a situation where a service provider is doing the development, is an approach where a low rate is paid for their time which covers their basic costs, the cost of materials is paid out directly, and delivery bonuses are paid for working software. This spreads the risk between the customer/stakeholder and the service provider. The service provider has their costs covered but won't make a profit unless they consistently deliver quality software.
The point is that there are several strategies for funding agile software development projects, just like there are several strategies for funding traditional software development projects. My experience is that fixed-price funding strategies are incredibly poor practice which increases the risk of your software development projects dramatically. I recognize how hard it can be to change this desire on the part of our business stakeholders, but have also had success changing their minds. If you choose to perservere, which is a difficult decision to make, you can help your organization's decision makers to adopt more effective strategies. Like you they want to improve the effectiveness of your IT efforts.Further reading: (In recommended order)
- Something's Gotta Give: Argues for a flexibly approach to funding, schedule, and/or scope.
- Agile on a Fixed Budget: Describes in detail how to take a fixed-price approach on agile projects.
- The Dire Consequences of Fixed-Price IT Projects: Describes in detail the questionable behavior exhibited by IT teams when forced to take a fixed-price approach.
- Is Fixed-Price Software Development Unethical?: Questions the entire concept of fixed-price IT projects, overviewing some of the overwhelming evidence against this really poor practice.
- Reducing the Risk of Fixed-Price Projects: Describes viable strategies for addressing some of the problems resulting from the decision of fixed-price projects.
- Strategies for Funding Software Development Projects: Describes several variations on the strategies described above.
- Lies, Great Lies, and Software Development Project Plans: Summarizes some results from the July 2009 State of the IT Union survey which explored issues related to project funding (among many).