We recently posted a new page titled Tool Support for DAD which you may find interesting.
At the end of July I spoke at the Agile 2014 conference in Orlando about what it means to be an agile enterprise. Part way through that presentation I spoke about the differences between producing potentially shippable software, one of the mantras of the Scrum community, and potentially consumable solutions as promoted by DAD. To do this I walked people through what I call the glass of water analogy. Here’s how it went:
I had a glass of drinking water. I took a sip from the glass to verify that the water was clean and the right temperature for drinking. The water was very refreshing and was something that I thought others would enjoy. It was my opinion that this glass of water was potentially shippable. I took another sip and then offered the water to the audience, there was over 200 people in the room, yet nobody was willing to drink from my glass. Shocking! I even singled someone out and tried to bully him into drinking my water (oops, I mean I aggressively marketed the wonderfulness of the water to him). Still, nobody wanted to drink the water. I took another sip and verified that it was in fact still refreshing. It was clear to me that my glass of water was potentially shippable. I could very easily have walked over to anyone in the room and they could easily have drunk from the glass. But everyone chose not to. It was potentially shippable from my point of view, but from the point of view of every single audience member it wasn’t consumable. In a venue where drinks are easily available, not a single person was willing to drink from my water glass (I assume due to a fear of catching my cooties). Had the venue been different, perhaps a desert with no other sources of drinkable liquids, someone might have been interested.
The point is that creating potentially shippable software isn’t sufficient. It needs to be something that people actually want to use, to consume. It must be a true solution that adds real value for them given their current situation. Cootie-laden water isn’t attractive when other drinks are readily available. Similarly, software that is difficult to use compared to other options, that isn’t well supported as other options, or that doesn’t enhance the way that people want to work isn’t going to be very attractive either.
Disciplined agilists focus on producing potentially consumable solutions. High-quality software is clearly part of this, but that software needs to be usable and something that people want to use. It needs to be supported with sufficient documentation. It needs to be supported with adequate hardware. It may even be part of an overall change to the business process and even organizational structure of the people using that software.
“Potentially shippable software” is a wonderful slogan, but we need to do a lot better than that.
I just posted a session idea for the Toronto Agile and Software 2014 conference. The title of the session is The Disciplined Agile Enterprise: Harmonizing Agile and Lean. The URL for the idea is http://agiletoronto.ideascale.com/a/dtd/The-Disciplined-Agile-Enterprise-Harmonizing-Agile-and-Lean/125226-30411 and I was hoping to get some feedback about it. I gave this presentation a few weeks ago at Agile 2014 to a packed room.
The conference organizers are taking an interesting approach this year by crowdsourcing the CFP process. I think it’s a really great experiment to run, so we’ll have to see how it goes.
Also, if your organization is interested, I’m happy to do this presentation as a webcast to you. Feel free to contact me directly.
Like it or not, functional dependencies occur between requirements. This can happen for many reasons, as we discussed in Managing Requirements Dependencies Between Teams, and there are several strategies for resolving such dependencies. In this blog posting we explore what happens when a functional dependency between two requirements exists AND one requirement is implemented by an agile/lean team and another by a traditional/waterfall team.
In our example requirement X depends on requirement Y. Neither requirement has been implemented yet (if requirement Y had already been implemented, and better yet deployed into production, the point would be moot). When we refer to the “agile team” this team may be following any one of the lifecycles supported by DAD (Basic/Agile, Advanced/Lean, Continuous Delivery, or Exploratory/Lean Startup).
Scenario 1: An Agile/Lean Team Depends on a Traditional Team
In this scenario X is being implemented by an agile team and Y is being implemented by a traditional team. From the point of view of the agile team, this is very risky for the following reasons:
- The traditional team is likely working on a longer time frame. Disciplined agile teams produce a potentially consumable solution (potentially shippable software in Scrum parlance) on a regular basis, at least every few weeks. A traditional team typically delivers a working solution over a much longer time frame, often measured in quarters. The implication is that because Y is being developed by a traditional team it may be many months until it is available, compared to several weeks if it was being developed by an agile team. This potentially adds schedule risk to the agile team.
- The traditional team may not make their deadline. According to the Standish Group’s Chaos Report, the average traditional team comes it at almost twice their original estimate (e.g. a project originally estimated at 6 months of work takes almost a year). Similarly, the December 2010 State of the IT Union survey found that traditional teams were much more likely than agile teams to miss their deadlines. By having a dependency on the deliverable of a traditional team, an agile team effectively increases their schedule risk.
- The traditional team may struggle to deliver something that is “agile friendly”. Agile teams routinely develop well written, high-quality software that is supported by a robust regression test suite and where needed concise supporting documentation. Although traditional teams can also choose to deliver similar artifacts very often their code isn’t as well supported by regression tests and their documentation may be overly detailed (and thereby more likely to be out of date and difficult to maintain). In other words, there is potential for quality risk being injected into the agile team.
- The traditional team may not deliver. There is always the risk that the traditional team doesn’t implement Y, traditional teams often need to reduce the scope of their deliveries in order to meet their commitments, or if they do implement Y it is done too late to be useful any more.
There are several strategies the agile team may decide to take:
- Negotiate a delivery date with the traditional team. Once the agile team has identified the dependency they should collaborate with the traditional team to determine the implementation schedule for Y. The agile team now has a release/schedule dependency on the traditional team which is a risk and should be treated as such. The agile team’s high-level release plan should show a dependency on the delivery of Y and their risk log (if they have one) should also capture this risk. The agile team should stay in contact with the traditional team throughout construction to monitor the progress of the development of Y. The agile team should also attempt to negotiate early delivery of Y so that they may integrate with it, and test appropriately, as soon as possible.
- Collaborate to develop Y. One way for the agile team to make it attractive for the traditional team to implement Y earlier than they normally would is to pitch in and help to do the work.
- Rework X to remove the dependency. One of the general strategies discussed in Managing Requirements Dependencies Between Teams was to rework X so that it no longer depended on Y. This may mean that you reduce the scope of X or it may mean that you deliver part of X now and wait to deliver the rest of X once Y is available.
- Reschedule the implementation of X. Another general strategy is to deprioritize X and implement it after Y is eventually deployed. This is a realistic option if Y is about to be implemented soon, say in the next few months, but often unrealistic otherwise.
- Implement Y. When the lead time is substantial, the agile team may choose to do the work themselves to implement the functionality. This can be viable when the agile team has the skills, experience, and resources to do the work. This strategy runs the risk of Y being implemented twice, once by each team, potentially inconsistently. To avoid this sort of waste the agile team will want to negotiate with the traditional team to take the work over from them.
Scenario 2: A Traditional Team Depends on an Agile/Lean Team
In this scenario X is being implemented by a traditional team and Y by an agile team. From the point of view of the traditional team, this might be seen as risky for the following reasons:
- They may not understand how a disciplined agile team actually works. Many traditional teams are still concerned about the way that they believe agile teams work. This is often because they perceive agile to be undisciplined or ad-hoc in nature, when the exact opposite is true. The implication is that the agile team will need to describe to the traditional team how they work, why they work that way, and describe the types of deliverables they will produce.
- They may want traditional deliverables from the agile team. Disciplined agile teams will produce high quality code, a regression test suite for that code, and concise supporting documentation. Traditional teams may believe that they also want detailed requirements and design specifications, not realizing that the tests produced by the agile team can be considered as executable specifications for the production code. The implication is that the two teams will need to negotiate what the exact deliverable(s) will be.
- They may struggle with any changes to the interface. Agile teams are used to working in an evolutionary manner where the requirements, design, and implementation change over time. Traditional teams, on the other hand, will often strive to define the requirements and design up front, baseline them, and then avoid or prevent change to them from that point onwards. These different mindsets towards change can cause anxiety within the traditional team, the implication being that the agile team may need to be a bit more strict than they usually would be when it comes to embracing change.
The fact is that scenario 2, a traditional team relying on a disciplined agile team, is very likely an order of magnitude less risky than the opposite (scenario 1). Either scenario will prove to be a learning experience for the two teams, particularly the one that relies on the other team. Going into the situation with an open mind and a respectful strategy will greatly increase the chance that you’ll work together effectively.
Sometimes functional dependencies occur between requirements that are being implemented by different teams. For example, requirement X depends on requirement Y and X is being worked on by team A and Y is being worked on by team B. This generally isn’t a problem when requirement Y is implemented before requirement X, is a bit of an annoyance if they’re being implemented in parallel (the two teams will need to coordinate their work), and an issue if X is being implemented before Y. For the rest of this posting we will assume that X depends on Y, X is just about to be implemented, and Y has not yet been implemented. Previously in Managing Dependencies in Agile Teams we discussed strategies for addressing such dependencies, including reordering the work or mocking out the functionality to be provided by Y. In this posting we explore the implications of managing requirements dependencies between an agile team and a lean team.
Managing requirements dependencies between an agile and lean team is similar to that of managing dependencies between two agile teams, although there are important nuances. These nuances stem from differences in the ways that agile and lean teams manage their work. Figure 1 depicts how agile teams do so, organizing work items (including requirements) as a prioritized stack (called a product backlog in Scrum). Work is pulled off the stack in batches that reflect the amount of work they can do in a single iteration/sprint. With agile teams the entire stack is prioritized using the same strategy, Scrum teams will prioritize by business value but disciplined agile teams are more likely to consider a combination of business value and risk. Figure 2 shows that lean teams manage their work as an options pool, pulling one work item out of the pool at a time. Lean teams will prioritize work items on a just in time (JIT) basis, determining which work is the highest priority at the point in time that they pull the work into their process. As you can see in Figure 2, they will consider a variety of factors when determining what work is the most important right now.
Figure 1. Agile work management strategy.
Figure 2. Lean work management strategy.
When an agile team depends on a lean team challenge is relatively straightforward. Because lean teams take on work in very small batches, one item at a time, it gives them much more granular control over when they implement something. As long as the agile team lets them know in a timely manner that the functionality needs to be implemented it shouldn’t be a problem. For example, if the agile team is disciplined enough to do look-ahead modelling (an aspect of Scrum’s backlog grooming efforts) then they should be able to identify an iteration or two in advance that they have a dependency on the lean team. At that point the product owner of the agile team should talk with the appropriate person(s) on the lean team to let them know about the dependency so that the lean team can prioritize that work appropriately (perhaps treat it as something to be expedited).
When a lean team depends on an agile team it’s a bit harder, but not much, to address. This time the challenge is with the batch sizes of the work that the teams take in. The lean team is taking in work in a very granular manner, one at a time, whereas the agile team is taking in work in small batches (perhaps two weeks worth of work at a time). From a lean point of view this injects wait time into their process, even though it may just be two weeks, but this wait time is still considered to be waste (muda). Once again the solution would be for the lean team to identify the dependency ahead of time via look-ahead modelling and negotiate with the agile team.
To summarize, requirements dependencies do in fact occur. There are strategies to minimize their impact, in particular implementing and better yet deploying the functionality that is being depended upon before the dependent functionality is implemented, but sometimes it just doesn’t work out that way. So your team will need to be prepared to manage the requirements dependencies that it has on other teams, and similarly be prepared to support other teams with dependencies on them. In this series of blog postings we’ve seen how Agile<=>Agile and Agile<=>Lean dependencies can be managed, next up is Agile/Lean<=>Traditional.
We recently posted four new posters, one for each of the four lifecycles currently supported by the Disciplined Agile Delivery (DAD) framework, on the Disciplined Agile Consortium site. The picture above shows what the Basic lifecycle poster looks like. These four lifecycles are:
- Basic/Scrum-based lifecycle
- Advanced/Lean lifecycle
- Continuous Delivery/DevOps lifecycle
- Exploratory/Lean Startup lifecycle
Click here to go to the download page for all currently available posters. We’re using PDF for the file format. As with the other posters you are able to download them free of charge. We hope you find them useful and welcome any ideas that you may have for other posters.
Although we strive to avoid functional dependencies between requirements, the fact is that they occur in practice. They certainly occur between requirements that are being addressed by a single team and they will even occur between requirements being addressed by different development teams. This is particularly true between the subteams within a program (a large development team organized into a “team of teams”).
The following diagram depicts a simple situation where there is an agile program organized into five subteams (A thru E). The way you read the diagram is that the arrows between requirements represent functional dependencies. In this case the requirement fourth from the top on A’s backlog (A4) depends on the one that is second from the top (A2) and on B3 (the requirement third from the top on team B’s backlog). B3 in turn depends on C7, which depends on D3. D3 depends on E4, which depends on D10, which depends on C12, which depends on D14. There could very well be dependencies between other requirements, but for this example we’re only worried about the dependencies originating from A4.
Figure 1: Example of functional dependencies between requirements.
Where Do Functional Dependencies Come From?
Functional dependencies occur between requirements for several reasons:
- End-user driven. Functional dependencies occur naturally in the business domain as the result of end user activities. For example, when a customer opens a bank account there is a functional dependency between the customer and bank account business entities. Furthermore, functionality such as being able to withdraw from a bank account depends on their being the ability to open a bank account for a customer to begin with.
- Requirements decomposition. When a large requirement is decomposed into smaller ones there are dependencies from the original large requirement to the smaller sub-requirements. An example of this is decomposing an epic, a large story, into several smaller stories.
- Technology driven. Some teams will choose to identify requirements for a given platform, subsystem, or architectural layer. For example, you may identify requirements for systems of engagement, such as applications running on mobile devices, and for systems of record, such as a back-end ERP system. A requirement for a mobile application may have a dependency on a requirement for a backend system to provide certain behaviors (such as the ability to create, read, update, and delete data). An example of requirements dependencies driven by architectural layering would be that you may choose to identify user interface (UI) requirements, business rules, and data requirements (via data models perhaps). A UI requirement depends on the implementation of a business rule which in turn depends on several data-oriented requirements.
Of the three reasons for why functional dependencies exist, the first two are clearly within the purview of a Product Owner (PO). The third one, technology driven dependencies, can be trickier because many POs will not be familiar with the underlying technologies. This is one reason why Disciplined Agile Delivery (DAD)’s Architecture Owner (AO) role is so important. The AO and the PO on a disciplined agile team work very closely together. AOs will help POs to better understand the implications of the technologies being used as well as to understand potential implications of the technologies (including technology-driven functional dependencies). These sorts of discussions will occur throughout the lifecycle, although they are particularly important during initial release planning during Inception and during iteration planning and look-ahead planning throughout Construction.
How do You Resolve Functional Dependencies?
Functional dependencies are addressed via three basic strategies:
- Reprioritize one or both of the requirements. When requirement X depends on requirement Y you ideally want to implement Y before, or at least in parallel, to implementing X. The advantage of reprioritization is that it requires the least amount of work by the development team. The disadvantage is that when a requirement is reprioritized in this manner the team is no longer working on the highest priority functionality by business value, potentially decreasing the return on investment (ROI) provided by the team.
- Mock out the missing functionality until it is available. Requirement X depends on requirement Y and Y will not be available in time (e.g. X is being worked on right now and Y will be developed in a future iteration). In this case the development team will implement X to the best of their ability, but will mock out (simulate or stub out) the functionality of Y until it is available. The advantage of this approach is that it is now possible to demo X so as to get feedback about it. The disadvantages are that your solution isn’t shippable until the mocked out functionality is implemented (or removed) and that there is the additional work to be done to mock it out.
- Rework the requirements to remove the dependency. If X depends on Y, then one solution might be to refactor X into X1 and X2, where X2 has the functionality dependent on Y but X1 has no dependency. X1 would be implemented now, and X2 at the same time or after Y is implemented. For example, a new screen has a dependency on data services being available. The screen includes five fields, four of which already have data services available but one of which is brand new. In this case X1 would be to do the work to implement the screen with the four fields and X2 would be the requirement to add the new field once the data was available on the back end. Another solution would be to not add the new data field at all, something you would need to discuss with your stakeholders.
Within an agile environment, functional dependencies are managed by Product Owners. When the dependencies are between requirements, or more accurately work items, that are being addressed by a single agile team this is fairly straightforward because it’s within the purview of the single product owner.
Now let’s consider how a Product Owner team would manage requirements dependencies within a program, as in the diagram above. In this case let’s assume that each team has it’s own product owner (PO) whom we’ll refer to as PO-A, PO-B, and so on. There are three scenarios to consider when managing requirements dependencies:
- Within the same sub-team. An example of this is A4 depends on A2. This is straightforward as a single person, in this case PO-A, is responsible for managing this dependency.
- On previously developed functionality. An example of this is C7 depends on D3. This should also be straightforward as D3 was implemented in iteration N so it should be available when C7 is implemented during iteration N+1.
- On future functionality. An example of this is B3 depends on C7. The problem is that we want to implement B3 during iteration N but we currently plan to implement C7 during iteration N+1. The two product owners, PO-A and PO-B, will need to work together to determine a strategy for resolving the dependency. They’ll do this via a combination of the strategies described earlier. They may also need to work closely with the Chief Product Owner to ensure that their reprioritization choices reflect the overall needs of the program.
How would the entire requirements dependency map for A4, as depicted in the diagram above, be resolved? It depends on what the product owner team decides. At the present moment the overall requirements dependency chain is to be implemented during iterations N through N+3. This may in fact be acceptable and the product owners will decide to live with the impact of mocking out functionality until it is available. Or they may decide to reprioritize the functionality so that it is implemented in a more effective order (perhaps during iteration N+1). The point is that the product owners will engage in negotiation amongst themselves to determine the best order in which the sub teams will implement the functionality.
How do You Manage Functional Dependencies?
Functional dependencies are managed by the Product Owner, or in the case of a program, the Product Owner team. The goal is to do just enough work to maintain the dependencies and no more. When you do not sufficiently maintain the dependencies, perhaps you forget to record that a sub-requirement was created as the result of decomposing a larger parent requirement, then it becomes difficult to ensure that a requirement is properly implemented. When you invest too much effort into maintaining functional dependencies any extra effort beyond the point of sufficiency is a waste. In short, your dependency map should be just barely good enough (JBGE) for the situation you find yourself in.
There are several options available to you for maintaining a functional dependencies:
- Physical dependency map. With this strategy requirements, such as user stories or features, are captured on paper (typically via index cards or sticky notes) and placed on a whiteboard, corkboard, or table. On physical boards dependencies can be indicated via physical placement, for example the cards capturing the sub-requirements of a large requirement are placed immediately to the right of the large requirement card. On a corkboard strings representing requirements could be placed from one card to another and on a whiteboard lines could be drawn to represent the dependencies. Or IDs could be given to each requirement and any dependencies simply captured on the cards via writing down the appropriate IDs. An example of a physical map include user story maps, see Figure 2 below, that indicate the epic or theme that a story is part of (this is a rudimentary form of dependency mapping). Another example includes a program plan board, an idea promoted by SAFe, where requirements are mapped to iterations/sprints (columns on the board), to implementation teams (rows on the board), and dependencies indicated via strings or lines.
- Simple electronic tool. Dependencies can be managed using tools such as spreadsheets, word processors, or wikis.
- Backlog/work item management tools. This includes products such as Trello, Atlassian’s JIRA, Rally and VersionOne. Some of these tools will have native support for managing dependencies where others do not (if the solution is to add a text reference into a freeform notes field then that’s not native support).
- Requirements management tools. This includes products such as Blueprint, Enterprise Architect, or DOORS NG. Be aware that some of these tools will have native, and more importantly effective, support for agile requirements artifacts such as user stories and acceptance criteria. Sometimes they will not.
Figure 2. Example of a simple story map.
Which approach should you take? Our advice is always to keep it simple and use physical tools if your situation permits. Having said that, there are advantages and disadvantages to each strategy:
- Physical dependency maps work well when teams are geographically close (working on the same floor or at least nearby floors in the same building). When you find yourself with a lot of dependencies to manage, or in a regulatory environment when traceability is mandated, or your team is geographically distributed (even if you just have a few people working from home), you’ll find that you’ll want to consider using electronic tools.
- Simple electronic tools work well when the team is small to medium sized (say less than 30 people), when the team is geographically distributed in some way, and the dependencies aren’t very complex.
- Backlog management tools are an effective option if you’re already using them for other reasons (such as managing your work), they natively support dependency mapping, and when physical dependency maps haven’t worked out for you.
- Requirements management tools are appropriate when you find yourself in complex situations, often at scale. This includes geographically distributed teams, complex domains, and regulatory situations.
Earlier we said that the diagram represents a “simple” situation. It is simple in that all five teams are following the same sort of lifecycle, in this case the basic/agile DAD lifecycle. Furthermore the velocities of the teams are roughly the same, which we did for the convenience of the example. Usually the team velocities are very different, due to a combination of different team sizes and different levels of productivity. In a future blog posting we’ll discuss the challenges that arrive when the subteams are following different lifecycles (for example a lean or continuous delivery lifecycle or even a waterfall lifecycle).
Several of the strategies described in the blog posting were first identified in Complex Requirements on an Agile Project (Dr. Dobbs Journal, October 2008).