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:
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.
Modified by ScottAmbler
In 2009 I wrote a white paper entitled The Agile Scaling Model (ASM): Adapting Agile Methods for Complex Environments for IBM Rational. Apparently it's been taken down, which I think is unfortunate as it contains some interesting ideas that your organization may be able to benefit from.
The original white paper addresses several key issues:
It provides and explains a definition for disciplined agile delivery. A more up to date discussion of DAD can be found on the Disciplined Agile Delivery site.
It describes criteria to determine is a team is agile. I've explored this issue via several surveys over the years since then. See the January 2013 How Agile Are You? results.
It describes the ASM, which distinguishes between core agile development techniques, disciplined agile delivery strategies, and agility at scale. The ASM was superceded in early 2013 by the Software Development Context Framework (SDCF). Perhaps this is why the ASM paper was taken down??
It overviews the eight scaling factors which a delivery team may face, scaling factors which motivate changes in the process that you will follow and the tools that you will adopt. The SDCF provides my recent thoughts regarding scaling factors. I have also run various IT Surveys over the years exploring how well organizations fare at scaling agile.
It describes the implications of the ASM. My blog posting Scaling Agile: Start with a Disciplined Foundation covers this very well.
It argues that you should strive to be as agile as you need to be, and that will be driven by the situation that you face.
activities are evolutionary (iterative and incremental) and highly collaborative in nature. Initially requirements are explored at a high level via requirements envisioning
at the beginning of the project and the details are explored on a just-in-time (JIT) basis via iteration modeling
and model storming
activities. The way that you perform these agile practices, and the extent to which you do so, depends on the situation in which a project team finds itself. The Agile Scaling Model (ASM)
is a contextual framework for effective adoption and tailoring of agile practices to meet the unique challenges faced by a system delivery team of any size. To see how this works, let's apply the concepts of the ASM to see how we would scale our agile approach to requirements.
First, let's consider how a small, co-located team would work. The first two categories of the ASM are core agile development and disciplined agile delivery
, the focus of both are small co-located teams in a fairly straightforward situation. In these situations simple techniques such as user stories
written on index cards and sketches on whiteboards
work very well, so the best advice that I can give is to stick with them. Some teams will take a test-driven development
(TDD) approach where they capture their requirements and design in the form of executable specifications
, although this sort of strategy isn't as common as it should be (yet!), likely because of the greater skill and discipline that it requires. Traditionalists often balk at this approach, believing that they need to document the requirements in some manner. But, for a small co-located team working in a collaborative manner, requirements documentation proves to be little more than busy work, often doing nothing more than justifying the existence of a business analyst who hasn't made the jump to agile yet. Don't get me wrong, there are good reasons to write some requirements documentation, and we'll see this in a minute, but you should always question any request for written specifications and try to find more effective ways to address the actual goal(s) motivating the request. Never forget that written documentation
is the least effective communication
option available to you.
Although inclusive tools
such as whiteboards and paper work well for requirements, for development activities you will need electronic tools. You will either put together an environment from point-specific tools or adopt something more sophisticated such as IBM Rational Team Concert (RTC)
which is already fully integrated and instrumented. RTC is a commercial tool, but luckily you can download a 10-license environment free of charge, which is just perfect for a small team. Larger teams, of course, will need to purchase licenses. One of the things that a disciplined agile delivery approach adds to core agile development is it addresses the full delivery life cycle, which is important because it explicitly includes pre-construction activities such as requirements envisioning. The first step in scaling agile techniques is to adopt a full delivery life cycle which covers the full range of activities required to initiate a project, produce the solution, and then release to solution to your end users.
More interesting is the third category of the ASM, Agility@Scale, and how its eight agile scaling factors
affect the way that you tailor your process and tooling strategy. Let's explore how each one could potentially affect your agile requirements strategy:
- Geographical distribution. The majority of agile teams are distributed in some manner -- some people are working in cubicles or private offices, on different floors, in different buildings, or even in different countries -- and when this happens your communication and coordination risks goes up. To counter this risk you will need to perform a bit more requirements envisioning up front to help ensure that everyone is working to the same vision, although this doesn't imply that you need to write detailed requirements speculations which would dramatically increase the risk to your project. Remember, agilists do just barely enough modeling and are prepared to iteratively elicit the details when they need to do so. The more distributed the team is the more likely they will need to adopt software-based requirements modeling tools such as IBM Rational Requirements Composer (RRC) which supports streamlined, agile requirements elicitation throughout the delivery life cycle. Index cards and whiteboards are great, but they're difficult to see if you're outside the room where they're posted. I've written a fair bit about distributed agile development in this blog.
- Team size. Some organizations, including IBM, are successfully applying agile techniques with teams of hundreds of people. A team of one hundred people will naturally work much differently than a team of ten people, or of one thousand people. Large teams are organized into collections of smaller teams, and the requirements for the overall project must be divvied up somehow between those teams. The implications are that as the team size grows you will need to invest a bit more time in initial requirements envisioning, and in initial architecture envisioning for that matter; you will need to use more sophisticated tools; and may need to use more sophisticated modeling techniques such as use cases and functional user interface prototypes. See large agile teams for more advice.
- Compliance requirement. When regulatory issues – such as Sarbanes Oxley, ISO 9000, or FDA CFR 21 – are applicable you are likely going to be required to capture requirements specifications in some manner and to enact traceability between those requirements. However, I highly recommend that you read the actual regulations yourself and don't let bureaucrats interpret them for you (doesn't it always seem that their interpretation always results in an onerous, documentation heavy solution?) because I have yet to run into a regulation which required you to work in an ineffective manner. Managing your requirements as work items in RTC can often more than meet your regulatory requirements for documentation and traceability, although you may want to consider a tool such as IBM Rational RequisitePro for complex regulatory situations.
- Domain complexity. The manner in which you elicit requirements for a data entry application or an informational web site will likely be much simpler than for a bio-chemical process monitoring or air traffic control system. More complex domains will require greater emphasis on exploration and experimentation, including but not limited to prototyping, modeling, and simulation. Although user stories may be effective as a primary requirements artifact in simple domains, in more complex domains you are likely to find that you need to drive your requirements effort with more sophisticated modeling techniques.
- Organization distribution. Sometimes a project team includes members from different divisions, different partner companies, or from external services firms. In these cases, particularly where the work is strictly organized between the various organizations (perhaps for security concerns), you may need a more sophisticated approach to managing the requirements. RTC enables you to organize the requirements between teams, and then to automatically track progress in real time via the RTC project dashboard.
- Technical complexity. The technical complexity of a solution can vary widely, from a single platform silo application to a multi-platform application working with legacy systems and data to a full-blown systems engineering effort. Complex technical domains, just like complex business domains, require more complex strategies for requirements elicitation and management. The requirements for your legacy systems are likely to have been captured using tools and techniques appropriate for that platform, for example the requirements for your COBOL application may have been captured using data flow diagrams and data models, whereas the requirements for your Java legacy application where captured using UML diagrams. The subteam working on the COBOL system might be using IBM Rational Application Developer (RAD) and RTC for Z whereas the Java subteam may use Eclipse with RTC. Because systems engineering projects can stretch on for years, particularly when the hardware is being developed in parallel to the software, sophisticated tooling such as IBM Rational DOORS is often used in these situations. For more information about systems engineering, see the IBM Rational Harmony process.
- Organizational complexity. Your approach to requirements elicitation and management will be affected by a host of organizational complexities, including your corporate culture. When the culture is flexible and collaborative you can be very agile in your approach to requirements, but as it becomes more rigid you become more constrained in what is considered acceptable and thus take on greater project risk. For example, many organizations still struggle with their approach to funding projects, often demanding that the project team provides an "accurate" estimate up front to which they will be held to. This in turn motivates risky behavior on the part of the development, including a "big requirements up front (BRUF)" approach where a detailed requirements speculation is developed early in the project. This is just one example of how questionable corporate culture can impact the way in which an agile team works.
- Enterprise discipline. Some organizations have enterprise-level disciplines, such as enterprise architecture, enterprise business modeling, strategic reuse, and portfolio management in place. These disciplines can easily be agile and from what I can tell the more successful efforts appear to lean more towards the agile end of the spectrum rather than the traditional end. Having an enterprise business modeling effort underway will affect your project-level requirements strategy -- you'll be able to leverage existing models, have access to people who understand the domain at an enterprise level, and will likely need to map your project efforts back to your enterprise models. The enterprise modelers will likely be using tools such as IBM Rational System Architect or IBM Websphere Business Modeler.
It is important to note that the way that you tailor the agile practices that you follow, and the tools that you use, will reflect the situation that you find yourself in. In other words, you need to right size your process and the Agile Scaling Model (ASM) provides the context to help you do so. As you saw above, in simpler situations you will use the simpler tools and techniques which are commonly promoted within the core agile development community. But, when things become a bit more complex and one or more of the scaling factors applies you need to modify your approach -- just don't forget that you should strive to be as agile as you can be given the situation that you find yourself in.
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.
People who are new to agile are often confused about how agile teams address architecture, but luckily we're seeing more discussion around agile architecture
now in the community so this problem is slowly being addressed from what I can tell. But, what I'm not seeing enough discussion about, at least not yet, is how is enterprise architecture addressed in the overall agile ecosystem. So I thought I'd share some thoughts on the subject, based on both my experiences over the years (see the recommended resources at the bottom of this posting) as well as on an enterprise architecture survey
which I ran in January/February 2010.
My belief is that effective enterprise architecture, particularly in an agile environment, is:
- Business driven. Minimally your EA effort should be driven by your business, not by your IT department. Better yet it should be business owned, although this can be a challenge in many organizations because business executives usually aren't well versed in EA and view it as an IT function. Yes, IT is clearly an important part of EA but it's not the entirety of EA nor is it the most critical part. In many organizations the IT department initiates EA programs, typically because the business doesn't know to do so, but they should quickly find a way to educate the business in the need to own your organization's EA efforts.
- Evolutionary. Your enterprise architecture should evolve over time, being developed iteratively and introduced incrementally over time. An evolutionary approach enables you act on the concrete feedback that you receive when you try to actually implement it, thereby enabling you to steer its development successfully.
- Collaborative. The EA survey clearly pointed to "people issues" being critical determinants of success, and of failure, of EA programs. My experience is that the best enterprise architects, just like the best application architects, work closely with the intended audience of their work, both on the business side of things as well as on the IT side. They will "roll up their sleeves" and become active members of development teams, often in the role of Architecture Owner on agile teams or Architect on more traditional teams. Their mission is to ensure that the development teams that they work with leverage the EA, to mentor developers in architecture skills, and to identify what works and what doesn't in practice so that they can evolve the EA accordingly. Enterprise architects, architects in general, who don't participate actively on development teams (holding architecture reviews isn't active participation) run the risk of being thought of as "ivory tower" and thus easy to ignore.
- Focused on producing valuable artifacts. The most valuable artifacts are useful to the intended audience, are light weight, and ideally are executable. Many EA programs run aground when the enterprise architects focus on artifacts that they've always wanted but that development teams really aren't very excited about -- yes, it might be interesting to have a comprehensive comparison of cloud technologies versus mainframe technologies, but a collection of reusable services would be fare more interesting to them. A detailed enterprise data model indicating suggested data attributes would be intellectually interesting to develop, but a list of legacy data sources with a high-level description of their contents would be immediately valuable to many development teams. A detailed model depicting desired web services would be useful, but an actual collection of working services that I can reuse now would be even better.
- An explicit part of development. In Disciplined Agile Delivery (DAD) architectural activities are an explicit part of the overall delivery process. Part of the architectural advice is that delivery teams should work closely with their organization's enterprise architects so that they can leverage the common infrastructure, and sometimes to help build it out, effectively. Disciplined agile teams realize that they can benefit greatly by doing so.
The Agile Scaling Model (ASM)
calls out addressing enterprise disciplines, such as enterprise architecture, as one of eight scaling factors which may apply to a given project. The interesting thing about this scaling factor is that it's the only one where things get potentially easier for development teams when we move from the simple approach, having a project focus, to the more complex approach, where we have an enterprise focus. By having a common infrastructure to build to, common guidelines to follow, and valuable artifacts to reuse project teams can benefit greatly. So, I guess my advice is to seriously consider adding enterprise disciplines to your agile strategy.Recommended Resources:
One of the scaling factors
called out in the Agile Scaling Model (ASM)
is “regulatory compliance”. This name is a bit of a misnomer because this scaling factor really addresses two issues: complying to regulations imposed upon you from external sources and choosing to adhere to internal regulations willingly adopted by your organization. It is relatively common for agile teams to find themselves in such situations. For example, in the 2009 Agile Practices Survey
one third of respondents said that they were applying agile on projects where one or more industry regulations applied.
First let’s consider external regulatory compliance. In these situations you may face the need to undergo an audit by an external regulatory body with consequences for non-compliance ranging from anywhere to a warning to a fine or even to legal action. Sometimes even a warning may be a grave thing. A few years ago I was working with a pharmaceutical company which had discovered that a warning from the FDA for non-compliance with their CFR 21 Part 11 regulation, when reported in major newspapers, resulted on average in a half-billion dollar loss to their market capitalization as the result of a dip in their stock price. There are financial regulations such as Sarbanes-Oxley and Basel II, informational regulations such as HIPAA which focuses on health information privacy, technical regulations such as ISO 27002 for security practices, and even life-critical regulations such as some of the FDA regulations.
External regulations are typically managed by a government organization or industry watchdog will range in complexity and can have a myriad of effects on project teams. For example, you may need to be able to prove that you had a documented process and that you followed it appropriately; you may need to produce extra artifacts, or more detailed artifacts, than you normally would; you may need to add extra features to your solution, such as tracking financial information, that you wouldn’t have normally implemented; you may need to produce specific reports to be submitted to the regulatory body; or you may even need to submit your team to audits, sometimes scheduled and sometimes not, to ensure regulatory compliance. Interestingly, even though many of those requirements go against the agile grain, the 2009 Agility at Scale Survey
found that organizations were successfully applying agile techniques while still conforming to external regulations. So yes, it is possible to scale your agile strategy to address regulatory compliance.
Second, let’s consider compliance to internally adopted, or sometimes even developed, “regulations” which you will be potentially evaluated/appraised against. Perfect examples of these are process improvement frameworks such as CMMI and ISO 900x. Similar to external regulations, the 2009 Agility at Scale Survey
found that some agile teams are succeeding in situations where they have chosen to adopt such frameworks. It’s important to note that frameworks such as CMMI aren’t primarily about ensuring the compliance of development teams to a standard process, regardless of what CMMI detractors may claim, but instead about process improvement. Process improvement at the IT department (or beyond) is an enterprise discipline issue from the point of view of ASM, implying that frameworks such as CMMI affect more than one scaling factor.
When you find yourself in a regulatory situation, whether those regulations are imposed or willingly adopted, the best advice that I can give is to read the regulations and develop a strategy to conform to them in the most agile manner possible. If you let bureaucrats interpret the regulations you’ll likely end up with a bureaucratic strategy, but if you instead choose to take a pragmatic approach you will very likely end up with a very practical strategy. Part of that strategy is to treat the regulatory representative(s) within your organization as important stakeholders whom you interact with regularly throughout the project.
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: