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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).
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)
, Disciplined Agile Delivery (DAD), the scaling factors of Agility@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.
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.
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.
A common misunderstanding about agile software development approaches are that they're only applicable to small, co-located teams. Yes, it's much easier to be successful with small teams, and with co-located teams, and as a result agilists being smart people prefer to work this way. After all, why take on extra risk when you don't need to do so? But, sometimes reality gets in the way and you find yourself in a situation where you need a large team, or you need to distribute your team (see previous blog postings for strategies for distributed agile development), and you would still like to be as agile as possible. The good news is that it's still possible to be agile with a large team, although you will need to go beyond some of the popular "agile in the small" strategies to succeed.
Here are some disciplined agile strategies to succeed at large-team agile:
- Question the need for a large team. Many times an organization will believe that they need a large team because their process is overly complex, because they're still organized for waterfall development, or simply because that's what they're used to. I've seen teams of 80 people doing the work of 20 as the result of over-specialization of job roles and all the bureaucracy required to organize and validate their work.
- Do some initial envisioning. In order to succeed the team must work together towards the same goals. This is true for small teams but doubly true for larger ones -- without a common vision chaos will quickly ensue. You must gain this common vision on two fronts: you need a common business vision and a common technical vision. To gain the common business vision you must do some initial, high-level requirements envisioning and to gain the common technical vision some common architecture envisioning. This isn't to say that you need to take on the risk of detailed, up-front specifications but you must at least have a high-level understanding of the scope and technical solution in order to move forward effectively. So, expect to spend the first few weeks of your project doing this initial modeling.
- Divide and conquer. You never have a team of 200 people, instead you have a collection of subteams that add up to 200 people. This is called having a team of teams.
- Align team structure with architecture. The most effective way to organize the subteams is to have each one implement one or more components, and thereby to build your overall system as a "system of systems". This reduces the coordination required because the majority of the communication will be within the subteams themselves. You'll still need to coordinate the subteams, that will never go away, but you can reduce the overhead (and the risk) by being smart about the way that you organize the people. A common mistake is to organize around job function (e.g. having architects in Toronto, developers in Raleigh, testers in Bangalore, and so on). This increases communication overhead and risk because these people need to work together closely to get something built.
- Project management coordination. Each subteam will have a team lead/coach, and these people will need to coordinate their work. There is often an overall project manager who leads this group. To coordinate the work within their subteam the team lead/coach will often have a daily meeting, in the Scrum method this is called a scrum meeting, where people share their current status and identify any problems they may be running into. To scale this effectively the team lead/coach attends a daily team coordination meeting, a scrum of scrums, where the same sort of information is shared at the overall team level.
- Product owner coordination. Similarly, each subteam has a product ownder, also referred to as an "on-site customer", who is responsible for making decisions about the requirements and for providing information to the team in a timely manner. Sometimes a single product owner will work with several subteams. The product owners will get together at the beginning of the project to do some requirements envisioning to identify the initial scope and to start portioning the requirements between the subteams. Because the requirements between the subsystems are interrelated and should be reasonably consistent, the product owners will need to meet on a regular basis to share information, to negotiate priorities, and to resolve requirements-related disputes.
- Architecture coordination. Each subteam will have an architecture owner, often a senior technical person and sometimes also in the role of the team lead/coach. These architecture owners will get together at the beginning of the project to do some initial architecture envisioning, based on the requirements envisioning efforts of the product owners. They will identify the major subsystems, and their interfaces, enabling the effective organization of the team into smaller subteams corresponding to the architecture. They will also get together regularly to evolve the architecture and to resolve any major technical issues.
- System integration team. For complex systems, which is often what large teams work on, an effective system integration effort is critical to your success. Although this may be easy at first, as the overall system evolves the need for a subteam focused solely on this quickly becomes apparent. This not only supports the development efforts of the subteams, it also supports independent investigative testing.
- Independent testing team. An independent testing team is common on mid-to-large size agile projects to enhance the testing efforts of the development subteams. This testing team will work in parallel to the developers, they get a new build on a regular basis (minimally each iteration, although more often is desirable), which they test in more advanced ways than what is typical with Test-Driven Development (TDD). For example, they often validate non-functional, quality of service (QoS) type requirements as well as technical constraints, things that often aren't captured well via user stories. They'll also do investigative testing to try to break the system by using it in ways not thought of by the product owners.
- Some specialties reappear. On larger teams it can make sense to have some people be a bit more specialized than what we normally see on small agile teams. For example, it's common to see people in the role of agile DBA, tech writer, build master, or user experience (UE) professional. More complex systems often require people in these roles, although it still behooves these poeple to not be pure specialists but instead to be generalizing specialists with a wider range of skills. Also, recognize that the reintroduction of specialists can be a slippery slope back to the bureaucracy of traditional software development.
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.
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
During 2007 Per Kroll and myself invested a significant amount of time development a framework for lean development governance. This effort resulted in a series of three articles that were published in Rational Edge and a recently published white paper. The articles go into the various practices in detail whereas the paper provides an overview aimed at executives. I also recently did a webcast which is now available online. The URLs are at the bottom of this blog posting.
Development governance isn’t a sexy topic, but it critical to the success of any IT department. I like to compare traditional, command-and-control approaches to governance to herding cats – you do a bunch of busy work which seems like a great idea in theory, but in the end the cats will ignore your efforts and stay in the room. Yet getting cats out of a room is easy to accomplish, as long as you know what motivates cats. Simply wave some fish in front of their noses and you’ll find that you can lead them out of the room with no effort at all. Effective governance for lean development isn’t about command and control. Instead, the focus is on enabling the right behaviors and practices through collaborative and supportive techniques. It is far more effective to motivate people to do the right thing than it is to try to force them to do so.
This framework is based on the philosophical foundation provided by the 7 principles proposed in the book “Lean Software Development” by Mary and Tom Poppendieck. The 7 principles are:1. Eliminate Waste. The three biggest sources of waste in software development are the addition of extra features, churn, and crossing organizational boundaries. Crossing organizational boundaries can increase costs by 25% or more because they create buffers which slow down response time and interfere with communication. It is critical that development teams are allowed to organize themselves, and run themselves, in a manner which reflects the work that they’re trying to accomplish. 2. Build Quality In. If you routinely find problems with your verification process then your process must be defective. When it comes to governance, if you regularly find that developers are doing things that you don’t want them to do or are not doing things that they should be then your approach to governance must be at fault. The strategy is not to make governance yet another set of activities that you layer on top of your software process but instead should embed into your process to make it as easy as possible for developers to do the right thing. 3. Create Knowledge. Planning is useful, but learning is essential. 4. Defer Commitment. You do not need to start software development by defining a complete specification, but instead work iteratively. You can support the business effectively through flexible architectures that are change tolerant and by scheduling irreversible decisions to the last possible moment. This also requires the ability to closely couple end-to-end business scenarios to capabilities developed in potentially several different applications by different projects. 5. Deliver Fast. It is possible to deliver high-quality systems fast and in a timely manner. By limiting the work of a team to their capacity, by not trying to force them to do more than they are capable but instead ask them to self-organize and thereby determine what they can accomplish, you can establish a reliable and repeatable flow of work. 6. Respect People. Sustainable advantage is gained from engaged, thinking people. The implication is that you need a human resources strategy which is specific to IT, that you need to focus on enabling teams not on controlling them. 7. Optimize the Whole. If you want to govern your development efforts effectively you must look at the bigger picture, not just individual project teams. You need to understand the high-level business process which the individual systems support, processes which often cross multiple systems. You need to manage programs of interrelated systems so that you can deliver a complete product to your stakeholders. Measurements should address how well you’re delivering business value, because that is the raison d’etre of your IT department.
Based on our experiences, and guided by the 7 principles, Per Kroll and I identified 18 practices of lean development governance. We've organized these practices into 6 categories:1. The Roles & Responsibilities category: - Promote Self-Organizing Teams. The best people for planning work are the ones who are going to do it. - Align Team Structure With Architecture. The organization of your project team should reflect the desired architectural structure of the system you are building to streamline the activities of the team.
2. The Organization category: - Align HR Policies With IT Values. Hiring, retaining, and promoting technical staff requires different strategies compared to non-technical staff. - Align Stakeholder Policies With IT Values. Your stakeholders may not understand the implications of the decisions that they make, for example that requiring an “accurate” estimate at the beginning of a project can dramatically increase project risk instead of decrease it as intended.
3. The Processes category: - Adapt the Process. Because teams vary in size, distribution, purpose, criticality, need for oversight, and member skillset you must tailor the process to meet a team’s exact needs. - Continuous Improvement. You should strive to identify and act on lessons learned throughout the project, not just at the end. - Embedded Compliance. It is better to build compliance into your day-to-day process, instead of having a separate compliance process that often results in unnecessary overhead. - Iterative Development. An iterative approach to software delivery allows progressive development and disclosure of software components, with a reduction of overall failure risk, and provides an ability to make fine-grained adjustment and correction with minimal lost time for rework. - Risk-Based Milestones. You want to mitigate the risks of your project, in particular business and technical risks, early in the lifecycle. You do this by having throughout your project several milestones that teams work toward.
4. The Measures category: - Simple and Relevant Metrics. You should automate metrics collection as much as possible, minimize the number of metrics collected, and know why you’re collecting them. - Continuous Project Monitoring. Automated metrics gathering enables you to monitor projects and thereby identify potential issues so that you can collaborate closely with the project team to resolve problems early.
5. The Mission & Principles category: - Business-Driven Project Pipeline. You should invest in the projects that are well-aligned to the business direction, return definable value, and match well with the priorities of the enterprise. - Pragmatic Governance Body. Effective governance bodies focus on enabling development teams in a cost-effective and timely manner. They typically have a small core staff with a majority of members being representatives from the governed organizations. - Staged Program Delivery. Programs, which are collections of related projects, should be rolled out in increments over time. Instead of holding back a release to wait for a subproject, each individual subprojects must sign up to predetermined release date. If the subproject misses it skips to the next release, minimizing the impact to the customers of the program. - Scenario-Driven Development. By taking a scenario-driven approach, you can understand how people will actually use your system, thereby enabling you to build something that meets their actual needs. The whole cannot be defined without understanding the parts, and the parts cannot be defined in detail without understanding the whole.
6. The Polices & Standards category: - Valued Corporate Assets. Guidance, such as programming guidelines or database design conventions, and reusable assets such as frameworks and components, will be adopted if they are perceived to add value to developers. You want to make it as easy as possible for developers to comply to, and more importantly take advantage of, your corporate IT infrastructure. - Flexible Architectures. Architectures that are service-oriented, component-based, or object-oriented and implement common architectural and design patterns lend themselves to greater levels of consistency, reuse, enhanceability, and adaptability. - Integrated Lifecycle Environment. Automate as much of the “drudge work”, such as metrics gathering and system build, as possible. Your tools and processes should fit together effectively throughout the lifecycle.
The URLs for the 3 articles:Principles and Organizations: http://www.ibm.com/developerworks/rational/library/jun07/kroll/Processes and Measures: http://www.ibm.com/developerworks/rational/library/jul07/kroll_ambler/Roles and Policies: http://www.ibm.com/developerworks/rational/library/aug07/ambler_kroll/
The URL for the white paper:https://www14.software.ibm.com/webapp/iwm/web/preLogin.do?lang=en_US&source=swg-ldg
The URL for the webcast:https://www14.software.ibm.com/webapp/iwm/web/preLogin.do?lang=en_US&source=dw-c-wcsdpr&S_PKG=112907C[Read More
I just wanted to share with you the Manifesto for Software Craftsmanship
which extends the Agile Manifesto
. The Manifesto for Software Craftsmanship states:As aspiring Software Craftsmen we are raising the bar of professional software development by practicing it and helping others learn the craft. Through this work we have come to value:
- Not only working software, but also well-crafted software
- Not only responding to change, but also steadily adding value
- Not only individuals and interactions, but also a community of professionals
- Not only customer collaboration, but also productive partnerships
That is, in pursuit of the items on the left we have found the items on the right to be indispensable.
I view this manifesto as an important step in the maturation of software development. More on this in a future blog posting.[Read More
The Scrum community has adopted a different set of terms than the other agile methodologies. This is done on purpose to help people realize that Agile approaches are different than traditional approaches, which can help in their adoption, but it can also hinder people's understanding because some of the terminology is not only non-standard it really doesn't make much sense. Because of this I'm often asked by people that I'm coaching to convert back and forth between terms, and recently wrote a detailed article on the subject. The following summarizes the mapping:
- Daily Scrum Meeting ==> Daily Stand-up Meeting
- Product Backlog ==> Work Item List
- Scrum Master ==> Team Lead or Team Coach
- Sprint ==> Iteration or Time Box
For more details read my article Translating Scrum Terminology
which includes explanations of a wider range of Scrum terms and discussions of why some of them really are questionable. Further reading: