One of the scaling factors
of the Agile Scaling Model (ASM)
is technical complexity.
The fundamental observation is that the underlying technology of solutions varies and as a result your approach to developing a solution will also need to vary.
It’s fairly straightforward to achieve high-levels of quality if you’re building a new system from scratch on a known technology platform, but not so easy when there are several technologies, the technologies are not well known, or legacy assets are involved.
There are several potential technical complexities which a Disciplined Agile Delivery (DAD) team may face:
- New technology platforms. Your team may choose to work with a technology platform which is either new to the team or sometimes even new to the industry. In the past few years new technology platforms include the Android operating system, Apple’s iPad platform, and various cloud computing (http://www.ibm.com/ibm/cloud/) platforms. Working with these platforms may require you to adopt new development tools and techniques, not to mention the need to train and mentor your staff in their usage. Furthermore, your team may need to allocate time for architectural spikes to explore how to use the new technology and to prove the overall architecture with working code early in the project lifecycle (this is a DAD milestone).
- Multiple technology platforms. IT solutions often run on multiple platforms. For example, a system’s user interface (UI) could run in a browser, access business logic implemented using J2EE on Websphere which in turn invokes web services implemented in COBOL running on a Z-series mainframe, and stores data in an Oracle database, a DB2 database, and in several XML files. Implementing new business functionality, or updating existing functionality, could require changes made on several of these platforms in parallel. The implication is that you’ll need to adopt tools and strategies which enable your team to develop, test, and deploy functionality on all of these platforms. Testing and debugging in particular will become more difficult as the number of technology platforms increases, potentially requiring you to adopt the practice of parallel independent testing. The Agility at Scale survey found that 34% of respondents indicated that their agile teams were working with multiple technology platforms.
- Legacy data. IT solutions should leverage existing, legacy data wherever possible to reduce the number of data sources and thereby increase data quality within your organization. Also, using existing data sources can potentially speed up development, assuming your team has a good relationship with the owners of the legacy data sources (sadly, this often isn’t the case as the Data Management Survey found). Working with legacy data sources may require improved database regression testing, practices, database refactoring practices, and agile approaches to data administration. The Agility at Scale survey found that 42% of respondents indicated that their agile teams were working with legacy data sources (personally, I’m shocked that this figure is so low, and fear that many agile teams are contributing to data quality problems within their organization as a result).
- Legacy systems. There are several potential challenges with legacy systems. First, the code quality may not be the best either because it was never really that good to begin with or because it’s degraded over the years as multiple people worked with it. You know you’ve got a quality problem if you’re either afraid to update the code or if when you do so you have to spend a lot of time debugging and then fixing problems revealed when doing the update. If the legacy system is a true asset for your organization you will want to pay off some of this technical debt by refactoring the code to make it of higher quality. Second, you may not have a full regression test suite in place, making it difficult to find problems when you do update the code let alone when you refactor it. Third, your development tools for your legacy code may be a bit behind the times. For example, I often run across mainframe COBOL developers still working with basic code editors instead of modern IDEs such as Rational Developer for System Z. Some of the strategies to deal effectively with legacy systems are to adopt a modern development toolset if you haven’t already done so (better yet, if possible adopt a common IDE across platforms and thereby reduce overall licensing and support costs) and to adopt agile practices such as static code analysis, dynamic software analysis, and continuous integration (CI). The Agile Project Initiation Survey found that 57% of respondents were integrating their new code with legacy systems and 51% were evolving legacy systems.
- Commercial off-the-shelf (COTS) solutions. COTS solutions, also called package applications, can add in a few complexities for agile teams. The packages rarely come with regression test suites, they often have rules about what you can modify and what you shouldn’t (rules that are ignored at your peril), and they’re often architected with the assumption that they’re the center of the architectural universe (which is a valid assumption if they’re the only major system within your organization). As I describe in my article Agile Package Implementations it is possible to take an agile approach to COTS implementations, although it may require a significant paradigm shift for the people involved. The Agility at Scale survey found that 15% of respondents indicated that their agile teams were working with COTS solutions.
- System/embedded solutions. For the sake of simplicity, if your team is developing a solution with both hardware and software aspects to it then you’re a systems project. Embedded systems are a specialization where the system has a few dedicated functions often with real-time constraints. Bottom line is that systems/embedded projects are typically more challenging than software-only projects – it gets really interesting when laws of physics starts to kick in, such as when you’re building satellites or space probes. I highly suggest Bruce Douglass’s book Real-Time Agility if you are interested in taking an agile approach to systems/embedded solution delivery.
The technical complexity faced by a project team is contextual – Working with four technology platforms is straightforward for someone used to dealing with seven, but difficult for someone used to dealing with just one. Recommended Reading:
When you are first adopting agile techniques in your organization a common strategy is to run one or more pilot projects. When organizing these projects you typically do as much as you can to make them successful, such as finding:
- Projects where the stakeholders are willing to actively work with you.
- IT people who are flexible, willing to try new things, and willing to collaborate with one another.
- IT people who are generalizing specialists, or at least willing to become so.
- Finding a project which is of medium complexity (therefore it's "real" in the sense that it's significant to your organization) but not one where it can make or break your organization (therefore it's safe to experiment with).
In North America we refer to this as "cherry picking" because you're picking the cherry/best situation that you can find.
- Being agile may not have been the primary determinant of success. You set up an environment where you have a good relationship with your stakeholders, where you have good people who want to work together, and the project is challenging but not impossible. Oh, and by the way you adopted a few agile techniques as well. Sounds to me that situation you could have adopted a few not-so-agile techniques instead and still succeed. Although my various project success surveys, see my IT surveys page for details, have shown time and again that agile project teams are more successful than traditional project teams I haven't been able to tease out (yet) whether this success is attributable to agile or just attributable to improved project initiation efforts.
- When adopting agile/lean widely across your organization, you can't cherry pick any more. For the past few years I've been working with IT organizations that are in the process of adopting agile/lean strategies across their entire organization, not just across a few pilot projects. What these organizations are finding is that they need to find ways to adopt agile where the business isn't as willing to work with IT, where some of the people aren't so flexible or collaborative, where some of the people are narrowly specialized and not as willing to expand their skills, or where the project exhibits scaling factors which motivates you to tailor your agile approach. It's harder to succeed with agile in these situations because they're not as "cherry" as what you've experienced previously. Luckily, if you've been successful previously then you now have some agile experienced people, you have successes to reference, and you've likely overcome some problems even in the cherry situations which you have learned from. So, your cherry successes will hopefully improve your ability to succeed even in "non cherry" situations.
- You need to work smarter, not harder. If the source of your success was actually from improved project initiation practices and not from agile, then recognize that and act accordingly. Realistically part of your success was from that and part was from agile, and the organizations that adopt a measured improvement approach potentially have the data to determine which practices lead to success and which didn't. Without the metrics you're effectively flying blind when it comes to deciding how to improve. There is clearly a mandate for smarter work practices within IT, within your organization as a whole for that matter.
If you want to gain more insight into some of the issues that you'll face when adopting agile across your organization, I suspect that you'll find my recent paper Scaling Agile: An Executive Guide
to be interesting. I've got a more detailed paper in the works, so stay tuned to this blog.
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
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.
It's customary to start a blog by describing the vision for it. Although this vision will undoubtedly evolve over time, it's always good to put a stake in the ground to get things started. Agile software development is clearly taking off and in my opinion is becoming the dominant development paradigm. Furthermore it appears that Agile approaches enjoy a higher success rate, providing better value for your IT investment, than do traditional approaches. Although organizations are succeeding at simpler projects with agile, many are struggling when applying Agile in more complex situations. They're finding that the "Agile rhetoric" doesn't always live up to its promises once you move into these complex situations. My goal with this blog is to share strategies for applying Agile techniques at scale.
When applying Agile strategies at scale you are likely to run into one or more of the following complexity factors:1. Geographical distribution. Is your team, including stakeholders, in different locations? Even being in different cubicles within the same building can erect barriers to communication, let alone being in different cities or even on different continents.2. Regulatory compliance. Regulations, including the Sarbanes-Oxley act, BASEL-II, and FDA statutes, to name a few, can increase the documentation and process burden on your projects. Complying to these regulations while still remaining as agile as possible can be a challenge.3. Entrenched policies, people, and processes. Most agile teams need to work within the scope of a larger organization, and that larger organization isn't always perfectly agile. Hopefully that will change in time, but we still need to get the job done right now. Your existing culture and organization can really hinder your ability to scale agile approaches, then a few "simple" changes can really help your efforts.4. Legacy systems. Although the politically correct term would be "proven assets" the reality is that it can be very difficult to leverage existing code and data sources due to quality problems. The code may not be well written, documented, or even have tests in place, yet that doesn't mean that your agile team should rewrite everything from scratch. Some legacy data sources are questionable at best, or the owners of those data sources difficult to work with, yet that doesn't given an agile team license to create yet another database.5. Organizational distribution. When your teams are made up of people working for different divisions, or if you have people from different companies (such as contractors, partners, or consultants), then your management complexity rises.6. Degree of governance. If you have one or more IT projects then you have an IT governance process in place. How formal it is, how explicit it is, and how effective it is will be up to you. IBM has been doing a lot of work in this topic over the past few years, and just recently Per Kroll and I have done some work around Lean Governance strategies. 7. Team size. Large teams will be organized differently than small teams, and they'll work differently too.8. System complexity. The more complex the system the greater the need for a viable architectural strategy. An interesting feature of the Rational Unified Process (RUP) is that it's Elaboration phase's primary goal is to prove the architecture via the creation of an end-to-end, working skeleton of the system. This risk-reduction technique is clearly a concept which Extreme Programming (XP) and Scrum teams can clearly benefit from.
It is definitely possible to scale Agile software development to meet the real-world complexities faced by modern organizations. Based on my experiences, I believe that over the next few years we'll discover that Agile scales better than traditional approaches. Many people have already discovered this, but as an industry I believe that there isn't yet sufficient evidence to state this as more than opinion. My goal with this blog is to provide advice for scaling Agile so as to increase your chances of success.
So, it looks like I have my work cut out for me. My strategy will be to address common questions which I get when working with customers and with internal IBM development teams. I have the privilege to work with a variety of software development teams worldwide, helping them to become more agile. They're all struggling with the same basic issues although don't recognize it because they're too focused on their own situation. So hopefully I'll be able to spread the word about what's actually working in practice.
I hope that you stay tuned.
- Scott[Read More
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
Rolf Nelson recently recorded a short (5 min) podcast about IBM Rational
(RTC). RTC is a complete agile collaborative development
environment providing agile planning, source code management, work item
management, build management, and project health, along with integrated
reporting and process support. I've worked with RTC for a couple of years now and have been truly impressed with it. What should be of interest to many people is the Express-C version which is a free, fully-featured, 10-license version of RTC which can be easily downloaded from www.jazz.net
My new paper Scaling Agile: An Executive Guide
is now available. As the title suggests the paper overviews how to scale agile strategies to meet your organization's unique needs. The executive summary:
Agile software development is a highly collaborative, quality-focused approach to software and systems delivery, which emphasizes potentially shippable working solutions produced at regular intervals for review and course correction. Built upon the shoulders of iterative development techniques, and standing in stark contrast to traditional serial or sequential software engineering methods, agile software delivery techniques hold such promise that IBM has begun to adopt agile processes throughout its Software Group, an organization with over 25,000 developers. But how can practices originally designed for small teams (10-12) be “scaled up” for significantly larger operations? The answer is what IBM calls “agility@scale.”
There are two primary aspects of scaling agile techniques that you need to consider. First is scaling agile techniques at the project level to address the unique challenges individual project teams face. This is the focus of the Agile Scaling Model (ASM).
Second is scaling your agile strategy across your entire IT department, as appropriate. It is fairly straightforward to apply agile on a handful of projects, but it can be very difficult to evolve your organizational culture and structure to fully adopt the agile way of working.
The Agile Scaling Model (ASM) defines a roadmap for effective adoption and tailoring of agile strategies to meet the unique challenges faced by a software and systems delivery team. Teams must first adopt a disciplined delivery lifecycle
that scales mainstream agile construction techniques to address the full delivery process, from project initiation to deployment into production. Then teams must determine which agile scaling factors
– team size, geographical distribution, regulatory compliance, domain complexity, organizational distribution, technical complexity, organizational complexity, or enterprise discipline, if any — are applicable to a project team and then tailor their adopted strategies accordingly to address their specific range of complexities.
When scaling agile strategies across your entire IT organization you must effectively address five strategic categories — the Five Ps of IT
: People, principles, practices, process, and products (i.e., technology and tooling). Depending on your organizational environment the level of focus on each area will vary. What we are finding within many organizations, including IBM, is that the primary gating factor for scaling agile across your entire organization is your organization’s ability to absorb change.
When you’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.
Modified by ScottAmbler
I was recently involved in an online discussion about how to calculate the benefits realized by software development teams. As with most online discussions it quickly devolved into camps and the conversation didn’t progress much after that. In this case there was what I would characterize as a traditional project camp and a much smaller agile/lean product camp. Although each camp had interesting points, the important thing for me in the conversation was the wide cultural and experience gap between the people involved in the conversation.
The following diagram summarizes the main viewpoints and the differences between them. The traditional project camp promoted a strategy where the potential return on investment (ROI) for a project would be calculated, a decision would be made to finance the project based (partly) on that ROI, the project would run, the solution delivered into production, and then at some point in the future the actual ROI would be calculated. Everyone was a bit vague on how the actual ROI would be calculated, but they agreed that it could be done although would be driven by the context of the situation. Of course several people pointed out that it rarely works that way. Even if the potential ROI was initially calculated it would likely be based on wishful thinking and it would be incredibly unlikely that the actual ROI would be calculated once the solution was in production. This is because few organizations are actually interested in investing the time to do so and some would even be afraid to do so. Hence the planned and actual versions of the traditional strategy in the diagram.
The agile/lean camp had a very different vision. Instead of investing in upfront ROI calculation, which would have required a fair bit of upfront requirements modelling and architectural modelling to get the information, the idea was that we should instead focus on a single feature or small change. If this change made sense to the stakeholders then it would be implemented, typically on the order of days or weeks instead of months, and put quickly into production. If your application is properly instrumented, which is becoming more and more common given the growing adoption of DevOps strategies, you can easily determine whether the addition of the new feature/change adds real value.
Cultural differences get in your way
The traditional project camp certainly believed in their process. In theory it sounded good, and I’m sure you could make it work, but in practice it was very fragile. The long feedback cycle, potentially months if not years, pretty much doomed the traditional approach to measuring benefits of software development to failure. The initial ROI guesstimate was often a work of fiction and rarely would it be compared to actuals. The cultural belief in bureaucracy motivated the traditional project camp to ignore the obvious challenges with their chosen approach.
The agile/lean camp also believed in their strategy. In theory it works very well, and more and more organizations are clearly pulling this off in practice, but it does require great discipline and investment in your environment. In particular, you need investment in modern development practices such as continuous integration (CI), continuous deployment (CD), and instrumented solutions (all important aspects of a disciplined agile DevOps strategy). These are very good things to do anyway, it just so happens that they have an interesting side effect of making it easy (and inexpensive) to measure the actual benefits of changes to your software-based solutions. The cultural belief in short feedback cycles, in taking a series of smaller steps instead of one large one, and in their ability to automate some potentially complex processes motivated the agile/lean camp to see the traditional camp as hopeless and part of the problem.
Several people in the traditional project camp struggled to understand the agile/lean approach, which is certainly understandable given how different that vision is compared with traditional software development environments. Sadly a few of the traditionalists chose to malign the agile/lean strategy instead of respectfully considering it. They missed an excellent opportunity to learn and potentially improve their game. Similarly the agilists started to tune out, dropping out of the conversation and forgoing the opportunity to help others see their point of view. In short, each camp suffered from cultural challenges that prevented them from coherently discussing how to measure the benefits of software development efforts.
How Should You Measure the Effectiveness of Software Development?
Your measurement strategy should meet the following criteria:
Measurements should be actioned. Both the traditional and agile/lean strategies described above meet this criteria in theory. However, because few organizations appear willing to calculate ROI after deployment as the traditional approach recommends, in practice the traditional strategy rarely meets this criteria. It is important to note that I used the word actioned, not actionable. Key difference.
There must be positive value. The total cost of taking a measure must be less than the total value of the improvement in decision making you gain. I think that the traditional strategy falls down dramatically here, which is likely why most organizations don’t actually follow it in practice. The agile/lean strategy can also fall down WRT this criterion but is much less likely to because the feedback cycle between creating the feature and measuring it is so short (and thus it is easier to identify the change in results to the actual change itself).
The measures must reflect the situation you face. There are many things you can measure that can give you insight into the ROI of your software development efforts. Changes in sales levels, how often given screen or function is invoked, savings incurred from a new way of working, improved timeliness of information (and thereby potentially better decision making), customer retention, customer return rate, and many others. What questions are important to you right now? What measures can help provide insight into those questions? It depends on the situation that you face, there are no hard and fast rules. For a better understanding of complexity factors faced by teams, see The Software Development Context Framework.
The measures should be difficult to game. Once again, traditional falls down here. ROI estimates are notoriously flakey because they require people to make guesses about costs, revenues, time frames, and other issues. The measurements coming out of your instrumented applications are very difficult to game because they’re being generated as the result of doing your day-to-day business.
The strategy must be compatible with your organization. Once again, this is a “it depends” type of situation. Can you imagine trying to convince an agile team to adopt the traditional strategy, or vice versa? Yes, you can choose to improve over time.
Not surprisingly, I put a lot more faith in the agile/lean approach to measuring value. Having said that, I do respect the traditional strategy as there are some situations where it may in fact work. Just not as many as traditional protagonists may believe.