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.
Modificado por 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.
Modificado por 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).
I recently wrote an "e-book" for Internet Evolution overviewing agile software development at scale. The goal of the Agility at Scale: Become as Agile as You Can Be
ebook is to get people thinking outside of the box a bit when it comes to agile development strategies and see that they really are ready for primetime.
Recently I visited a customer who had adopted Scrum. They were a few sprints, what Scrum calls iterations, into the project and were running into some difficulties. Although I was primarily brought in to educate senior management on disciplined agile software development, I was also asked to sit in on the team’s daily stand-up meeting so that I could hopefully provide some suggestions as to how to address the problems they were running into.
Their work area was fairly typical. They had some whiteboards which they were using for project planning and tracking, with sticky notes to indicate what work had been taken on by each team member. The current status of the task (not yet started, in progress, and completed) was indicated by putting each sticky note in a corresponding column for the status and corresponding column for the team member. This allowed everyone on the team to easily share their status and to see the status of everyone else. On the sides were sketches of the architecture as well as some business oriented models. In addition to Scrum the team had adopted several practices from Agile Modeling, in this case they had done some initial requirements envisioning
and architecture envisioning
, as well as practices from Extreme Programming (XP) for construction. In short, they had followed a fairly common strategy of combining practices from various agile methods.
This would have worked perfectly fine if they had tailored the practices to reflect the situation that they were in, but instead they adopted them "straight out of the book". First, the team was distributed, with most of the team in the location that I was visiting but some people located in two other distant cities. Therein was the source of most of their problems. The people at the other two locations weren’t getting much value out of the daily stand-up meetings, even though they would dial in, because they couldn’t see the project status information. Although people at this location were trying their best to represent these distant people in the daily stand-ups it wasn’t working well – their status information wasn’t being kept up to date and for some people it was a bit of mystery as to what they were actually working on at all.
This team also had 30 people in it, which isn’t a big deal although it can stretch the limits of the simple modeling and planning tools (in this case paper and whiteboards) that they were using. Because the team was larger they were investing a fair bit of time creating burn down charts at both the iteration/sprint and project levels. One of the unfortunate implications of using manual tools for project management is that any associated metric/status reporting in turn becomes manual as well. Considering how the agile community is so concerned with working efficiently, I find it comical that we have a tendency to overlook our own potentially unnecessary bureaucracy such as this.
The problem was that the team was applying strategies, in this case using sticky notes and whiteboards to capture the detailed iteration plan, applying similar strategies to capture key models, and were verbally relaying of status information between sub-teams. There are perfectly fine strategies for smaller co-located teams, but not so good for large or distributed teams. The solution was to recognize that they were in an Agility@Scale situation and needed to tailor their approach to reflect this fact. In this case they needed to forgo some of the manual tools and instead use electronic tooling such as Rational Team Concert (RTC) to share information across disparate locations, in particular the work assignment and corresponding status information. RTC also creates common agile reports such as burn-down charts based on the activities of the developers, providing accurate (nearly) real-time information while removing the burden of status reporting. The RTC project dashboard does more than just this, to see an actual example of one visit www.jazz.net
to see the dashboard for the RTC development team itself. You can also see their actual work item list too, a more advanced version of Scrum’s product and sprint backlogs.[Read More
In the early days of agile, the applications where agile development was applied were smaller in scope and relatively straightforward. Today, the picture has changed significantly and organizations want to apply agile development to a broader set of projects. Agile hence needs to adapt to deal with the many business, organization, and technical complexities today’s software development organizations are facing. This is what Agility@Scale is all about – explicitly addressing the complexities which disciplined agile delivery teams face in the real world.These agile scaling factors which we've found to be important are:
- Team size. Mainstream agile processes work very well for smaller teams of ten to fifteen people, but what if the team is much larger? What if it’s fifty people? One hundred people? One thousand people? Paper-based, face-to-face strategies start to fall apart as the team size grows.
- Geographical distribution. What happens when the team is distributed, perhaps on floors within the same building, different locations within the same city, or even in different countries? Suddenly effective collaboration becomes more challenging and disconnects are more likely to occur.
- Compliance requirement. What if regulatory issues – such as Sarbanes Oxley, ISO 9000, or FDA CFR 21 – are applicable? These issues bring requirements of their own that may be imposed from outside your organization in addition to the customer-driven product requirements.
- Enterprise discipline. Most organizations want to leverage common infrastructure platforms to lower cost, reduce time to market, and to improve consistency. To accomplish this they need effective enterprise architecture, enterprise business modeling, strategic reuse, and portfolio management disciplines. These disciplines must work in concert with, and better yet enhance, your disciplined agile delivery processes.
- Organizational complexity. Your existing organization structure and culture may reflect traditional values, increasing the complexity of adopting and scaling agile strategies within your organization. To make matters worse different subgroups within your organization may have different visions as to how they should work. Individually the strategies can be quite effective, but as a whole they simply don’t work together effectively.
- Organization distribution. Sometimes a project team includes members from different divisions, different partner companies, or from external services firms. This lack of organizational cohesion can greatly increase the risk to your project.
- Technical complexity. Some applications are more complex than others. It’s fairly straightforward to achieve high-levels of quality if you’re building a new system from scratch, but not so easy if you’re working with existing legacy systems and legacy data sources which are less than perfect. It’s straightforward to build a system using a single platform, not so easy if you’re building a system running on several platforms or built using several disparate technologies. Sometimes the nature of the problem that your team is trying to address is very complex in its own right.
Each factor has a range of complexities, and each team will have a different combination and therefore will need a process, team structure, and tooling environment tailored to meet their unique situation. Further reading:
I've been getting a lot of questions lately about applying the acceleration metric
in practice. So, here's some answers to frequently asked questions:
1. How do I monetize acceleration?
This is fairly straightforward to do. For example, assume your acceleration is 0.007 (0.7%), there are five people on the team, your annual burdened cost per person is $150,000, and you have two week iterations. All these numbers are made up, but you know how to calculate acceleration now and IT management had darn well better know the average burdened cost (salary plus overhead) of their staff. So, per iteration the average burdened cost per person must be $150,000/26 = $5,770. Productivity improvement per iteration for this team must be $5,770 * 5 * .007 = $202. If the acceleration stayed constant at 0.7% the overall productivity improvement for the year would be (1.007)^26 (assuming the team works all 52 weeks of the year) which would be 1.198 or 19.8%. This would be a savings of $148,500 (pretty much the equivalent of one new person). Of course a 20% productivity increase over an entire year is a really aggressive improvement, regardless of some of the claims made by the agile snake oil salesman out there, although at 10-15% increase is a reasonable expectation. What I'd really want to do is calculate the acceleration for the year by comparing the velocity from the beginning of the year to the end of the year (in Western cultures I'd want to avoid comparing iterations near to the holidays). So, if the team velocity the first week of February 2008 was 20 points, now the same team's velocity the first week of February 2009 was 23 points, that's an acceleration of (23-20)/20 = 15% over a one year period, for a savings of $112,500.
2. Is acceleration really unitless?
For the sake of comparison it is. The "units" are % change in points per iteration, or % change in points per time period depending on the way that you want to look at it. Because it's a percentage I can easily monetize it, as you see above, and use it as a basis of comparison.
3. How do I convince teams to share their data?
This can be difficult. Because acceleration is easy to calculate for agile teams, and because it's easy to use to compare teams (my team has .7% acceleration whereas other teams down the hall from mine have accelerations of .3% and -.2% of teams), people are concerned that this metric will be used against them. OK, to be fair, my team might be OK with this. ;-) Seriously though, this is a valid fear that will only be addressed by an effective governance program
based on enablement, collaboration, and trust instead of the traditional command-and-control approach. Management's track record regarding how they've used measurements in the past, and how they've governed in general, have a great effect on people's willingness to trust them with new metrics such as acceleration. The implication is that you need to build up trust, something that could take years if it's possible at all.
4. Why does this work for agile teams?
Agile teams are self organizing, and an implication of that is that they will be held accountable for their estimates. Because of this accountability, and because velocity is a vital input into their planning and estimation efforts, agile teams are motivated to calculate their velocity accurately and to track it over time. Because they're eager to get their velocity right, and because acceleration is based on velocity, there's an exceptionally good chance that it's accurate.
5. What about function points or similar productivity measures?
Function points can be calculated for projects being developed via an agile approach, or other approaches for that matter, but it's a very expensive endeavor compared to calculating acceleration (which is essentially free) and likely will be seen as a bureaucratic overhead by the development team. My rule of thumb is that if you're not being explicitly paid to count function points (for example the US DoD will often pay contracting companies to create estimates based on function point counts) then I wouldn't bother with them.
6. What about calculating acceleration for iterative project teams?
Iterative project teams, perhaps following Rational Unified Process (RUP)
, can choose to calculate and track their velocity and thereby their acceleration. The key is to allow the team to be self organizing and accountable for their estimates, which in turn motivates them to get their velocity right just like agile teams (RUP can be as agile as you want to make it, don't let anyone tell you differently).
7. What about calculating acceleration for traditional project teams?
In theory this should work, in practice it is incredibly unlikely. Traditional teams don't work in iterations where working software is produced on a regular basis, they're typically not self organizing, and therefore there really isn't any motivate to calculate velocity (even if they do, there is little motivation to get it right). Without knowing the velocity you can't calculate acceleration. If you can't trust the velocity estimate, and I certainly wouldn't trust a traditional team's velocity estimate, then you can't trust your acceleration calculation. So, my fall back position to calculate productivity improvement would be to do something like function point counting (which is expensive and difficult to compare between teams due to different fudge factors used by different FP counters) and then looking at change in FPs delivered over time.
8. How can I apply this across a department?
It is fairly straightforward to roll up the acceleration of project teams into an overall acceleration measure for a portfolio of teams simply by taking a weighted average based on team size. However, this is only applicable to teams that are in a position to report an accurate acceleration (the agile and iterative teams) and of course are willing to do so.
9. What does a negative acceleration tell me?
If the acceleration is negative then productivity on the team is going down, likely an indicator of quality and/or team work problems. However, you don't want to manage by the numbers so you should talk to the team to see what's actually going on.
10. What does a zero acceleration tell me?
This is an indication that the team's productivity is not increasing, and that perhaps they should consider doing retrospectives at the end of each iteration and then acting on the results from those retrospectives. Better yet they can "dial up" their process improvement efforts by adopting something along the lines of IBM Rational Self Check
I'm happy to announce Rational's Agility at Scale poster which is currently available free of charge from the Rational poster order page
Although I'm obviously biased as I was involved with its creation, the poster includes some really good information about how to scale agile software development practices effectively. It summarizes the scaling factors, such as large teams, distribution, regulatory compliance, application complexity, and so on that you should be concerned with. It also presents a full agile software development lifecycle that goes beyond the construction focused lifecycles of common "agile in the small" processes. It also summarizes the practices of lean development governance, giving you some insight into how to govern your IT environment more effectively.
I think it's a pretty good poster that's worth checking out. It's free, so it's hard to argue with the price. Most importantly, it would look pretty good hanging on your office wall.
The explicit phases of the Unified Process -- Inception, Elaboration, Construction, and Transition -- and their milestones are important strategies for scaling agile software development to meet the real-world needs of modern organizations. Yes, I realize that this is heresy for hard-core agilists who can expound upon the evils of serial development, yet these very same people also take a phased approach to development although are loathe to admit it. The issue is that the UP phases are like seasons of a project: although you'll do the same types of activities all throughout a project, the extent to which you do them and the way in which you do them change depending on your goals. For example, at the beginning of a development project if you want to be effective you need to do basic things like identify the scope of the project, identify a viable architecture strategy, start putting together your team, and obtain support for the project. Towards the end of a project your focus is on the activities surrounding the deployment of your system into production, including end-of-lifecycle testing efforts, training, cleaning up of documentation, piloting the system with a subset of users, and so on. In between you focus on building the system, including analysis, design, testing, and coding of it. Your project clearly progresses through different phases, or call them seasons if the term phase doesn't suit you, whether your team is agile or not.
The UP defines four phases, each of which address a different kind of risk:1. Inception. This phase focuses on addressing business risk by having you drive to scope concurrence amongst your stakeholders. Most projects have a wide range of stakeholdres, and if they don't agree to the scope of the project and recognize that others have conflicting or higher priority needs you project risks getting mired in political infighting. In the Eclipse Way this is called the "Warm Up" iteration and in other agile processes "Iteration 0".2. Elaboration. The goal of this phase is to address technical risk by proving the architecture through code. You do this by building and end-to-end skeleton of your system which implements the highest-risk requirements. Some people will say that this approach isn't agile, that your stakeholders should by the only ones to prioritize requirements. Yes, I agree with that, but I also recognize that there are a wide range of stakeholders, including operations people and enterprise architects who are interested in the technical viability of your approach. I've also noticed that the high-risk requirements are often the high-business-value ones anyway, so you usually need to do very little reorganization of your requirements stack.3. Construction. This phase focuses on implementation risk, addressing it through the creation of working software each iteration. This phase is where you put the flesh onto the skeleton.4. Transition. The goal of this phase is to address deployment risk. There is usually a lot more to deploying software than simply copying a few files onto a server, as I indicated above. Deployment is often a complex and difficult task, one which you often need good guidance to succeed at.
Each phase ends with a milestone review, which could be as simple as a short meeting, where you meet with prime stakeholders who will make a "go/no-go" decision regarding your project. They should consider whether the project still makes sense, perhaps the situation has changed, and that you're addressing the project risks appropriately. This is important for "agile in the small" but also for "agile in the large" because at scale your risks are often much greater. Your prime stakeholders should also verify that you have in fact met the criteria for exiting the phase. For example, if you don't have an end-to-end working skeleton of your system then you're not ready to enter the Construction phase. Holding these sorts of milestone reviews improves your IT governance efforts by giving senior management valuable visibility at the level that they actually need: when you have dozens or hundreds of projects underway, you can't attend all of the daily stand up meetings of each team, nor do you even want to read summary status reports.
These milestone reviews enable you to lower project risk. Last Autumn I ran a survey via Dr. Dobb's Journal (www.ddj.com) which explore how people actually define success for IT projects and how successful we really were. We found that when people define success in their own terms that Agile has a 71% success rate compared with 63% for traditional approaches. Although it's nice to that Agile appears to be lower risk than traditional approaches, a 71% success rate still implies a 29% failure rate. The point is that it behooves us to actively monitor development projects to determine if they're on track, and if not either help them to get back on track or cancel them as soon as we possibly can. Hence the importance of occasional milestone reviews where you make go/no-go decisions. If you're interested in the details behind the project, they can be found at http://www.ambysoft.com/surveys/success2007.html .
Done right, phases are critical to your project success, particularly at scale. Yes, the traditional community seems to have gone overboard with phase-based approaches, but that doesn't mean that we need to make the same mistakes. Let's keep the benefit without the cost of needless bureaucracy.[Read More
The popular Agile literature can often seam naive when it comes to how Agilists work with project stakeholders:- Extreme Programming (XP) has a practice called On-Site Customer where one or more people work closely with your team to provide information and to make decisions in a timely manner.- Scrum has the role of Product Owner who is the one single person that the development team goes to for decisions about requirements. - Agile Modeling (AM) has the practice of Active Stakeholder Participation which extends On-Site Customer to get the stakeholder(s) actively involved with the modeling effort through the use of inclusive tools and techniques.
These are great strategies for small, co-located teams doing straightforward development, but they quickly fall apart at scale. This occurs for several reasons:1. Stakeholders are a diverse group. Your stakeholders include end users, business management, project funders, enterprise architects, operations staff, support staff, other system development teams, and many others. Different people have different, and often contradictory, requirements and they certainly have different priorities. It's questionable whether a single person, or a handful of persons, can adequately represent this diverse group.2. One person becomes a bottleneck. Even with a small co-located team this is a problem, let alone one that is geographically distributed or one that is very large. There's no way that a single person can be available 24/7 in a responsive manner to support distributed teams.3. It's a difficult role. The Product Owner/Customer (POC) is responsible for representing the business to the development team. They're making important decisions on a regular basis, decisions which they'll be held accountable for.4. One person becomes a serious project risk. Not only is it questionable whether a single person can fairly represent all stakeholders, even if they could what happens if you lose that person? They effectively become a single point of failure for your team.
To scale this role, consider the following strategies:1. Recognize the true scope of the POC role. Not only are they stakeholder proxies they also are a development team representative to the stakeholder community as a whole. As stakeholder proxies they'll make decisions and prioritize the work, they'll run requirements elicitation sessions, they'll negotiate priorities, and they'll put the development team in contact with stakeholders who have expertise in specific aspects of the domain. As team representatives they'll often demo the current version of the system to other stakeholders, communicate the status of the project to people, and respond to various requests for information from the stakeholders.2. Have multiple people in it. A single POC works well for small, co-located teams developing simple software. At scale you'll soon discover that you need multiple people in this role so that they don't become a bottleneck. For distributed teams it's common to see each subteam have one or more POCs who are managed by a primary/chief POC. The primary POC typically works on the coordinating team with the chief architect (I'll talk about this role in a future blog posting) and the program manager (also a topic for a future blog posting).3. Train them in business analysis skills. The person(s) in the POC role need good business analysis skills. If fact, it's common for people who were formerly BAs for traditional teams to step into the POC role, particularly with BAs who originally come from the business side of your organization. This strategy has its advantages and disadvantages. As a BA they've likely got solid business knowledge but their instincts may motivate them to take a documentation-driven approach to providing information to the development team instead of a collaboration-based approach. Be careful.4. Consider the full system development lifecycle. There's far more to the POC role than supporting the development team during Construction iterations. During "Iteration 0", the Inception phase for an Agile RUP project or the warm-up phase for an Eclipse Way project, the POC(s) will often lead the initial requirements envisioning efforts. The product backlog, or better yet your work item list, needs to come from somewhere after all. During the release iteration(s), the Transition phase for RUP or the End-Game phase for Eclipse Way, the POC(s) will focus on communicating the upcoming release to the stakeholder community, will be actively involved with any final user acceptance testing (UAT), and may even be involved with training end users.
In my January 2008 column in Dr Dobb's Journal, posted at http://www.ddj.com/architect/204801134 , I provide detailed advice about how to scale the way that you work with stakeholders on Agile projects by applying the practices of Agile Model Driven Development (AMDD). There's no magic solution, you just need to choose to organize yourself effectively. The good news is that you can easily work with stakeholders at scale.[Read More