Agile Team Composition: Generalists versus Specialists

Estimating levels of effort for a set of tasks by a group of individuals well qualified to complete those tasks can efficiently and reliable be determined with a collaborative estimation process like planning poker. Such teams have a good measure of skill overlap. In the context of the problem set, each of the team members are generalist in the sense  it’s possible for any one team member to work on a variety of cross functional tasks during a sprint. Differences in preferred coding language among team members, for example, is less an issue when everyone understands advanced coding practices and the underlying architecture for the solution.

With a set of complimentary technical skills it’s is easier agree on work estimates. There are other benefits that flow from well-matched teams. A stable sprint velocity emerges much sooner. There is greater cross functional participation. And re-balancing the work load when “disruptors” occur – like vacations, illness, uncommon feature requests, etc. – is easier to coordinate.

Once the set of tasks starts to include items that fall outside the expertise of the group and the group begins to include cross functional team members, a process like planning poker becomes increasingly less reliable. The issue is the mismatch between relative scales of expertise. A content editor is likely to have very little insight into the effort required to modify a production database schema. Their estimation may be little more than a guess based on what they think it “should” be. Similarly for a coder faced with estimating the effort needed to translate 5,000 words of text from English to Latvian. Unless, of course, you have an English speaking coder on your team who speaks fluent Latvian.

These distinctions are easy to spot in project work. When knowledge and solution domains have a great deal of overlap, generalization allows for a lot of high quality collaboration. However, when an Agile team is formed to solve problems that do not have a purely technical solution, specialization rather than generalization has a greater influence on overall success. The risk is that with very little overlap specialized team expertise can result in either shallow solutions or wasteful speculation – waste that isn’t discovered until much later. Moreover, re-balancing the team becomes problematic and most often results in delays and missed commitments due to the limited ability for cross functional participation among team mates.

The challenge for teams where knowledge and solution domains have minimal overlap is to manage the specialized expertise domains in a way that is optimally useful, That is, reliable, predictable, and actionable. Success becomes increasingly dependent on how good an organization is at estimating levels of effort when the team is composed of specialists.

One approach I experimented with was to add a second dimension to the estimation: a weight factor to the estimator’s level of expertise relative to the nature of the card being considered. The idea is that with a weighted expertise factor calibrated to the problem and solution contexts, a more reliable velocity emerges over time. In practice, was difficult to implement. Teams spent valuable time challenging what the weighted factor should be and less experienced team members felt their opinion had been, quite literally, discounted.

The approach I’ve had the most success with on teams with diverse expertise is to have story cards sized by the individual assigned to complete the work. This still happens in a collaborative refinement or planning session so that other team members can contribute information that is often outside the perspective of the work assignee. Dependencies, past experience with similar work on other projects, missing acceptance criteria, or a refinement to the story card’s minimum viable product (MVP) definition are all examples of the kind of information team members have contributed. This invariably results in an adjustment to the overall level of effort estimate on the story card. It also has made details about the story card more explicit to the team in a way that a conversation focused on story point values doesn’t seem to achieve. The conversation shifts from “What are the points?” to “What’s the work needed to complete this story card?”

I’ve also observed that by focusing ownership of the estimate on the work assignee, accountability and transparency tend to increase. Potential blockers are surfaced sooner and team members communicate issues and dependencies more freely with each other. Of course, this isn’t always the case and in a future post we’ll explore aspects of team composition and dynamics that facilitate or prevent quality collaboration.

Story Points and Fuzzy Bunnies

The scrum framework is forever tied to the language of sports in general and rugby in particular. We organize our project work around goals, sprints, points, and daily scrums. An unfortunate consequence of organizing projects around a sports metaphor is that the language of gaming ends up driving behavior. For example, people have a natural inclination to associate the idea of story points to a measure of success rather than an indicator of the effort required to complete the story. The more points you have, the more successful you are. This is reflected in an actual quote from a retrospective on things a team did well:

We completed the highest number of points in this sprint than in any other sprint so far.

This was a team that lost sight of the fact they were the only team on the field. They were certain to be the winning team. They were also destine to be he losing team. They were focused on story point acceleration rather than a constant, predictable velocity.

More and more I’m finding less and less value in using story points as an indicator for level of effort estimation. If Atlassian made it easy to change the label on JIRA’s story point field, I’d change it to “Fuzzy Bunnies” just to drive this idea home. You don’t want more and more fuzzy bunnies, you want no more than the number you can commit to taking care of in a certain span of time typically referred to as a “sprint.” A team that decides to take on the care and feeding of 50 fuzzy bunnies over the next two weeks but has demonstrated – sprint after sprint – they can only keep 25 alive is going to lose a lot of fuzzy bunnies over the course of the project.

It is difficult for people new to scrum or Agile to grasp the purpose behind an abstract idea like story points. Consequently, they are unskilled in how to use them as a measure of performance and improvement. Developing this skill can take considerable time and effort. The care and feeding of fuzzy bunnies, however, they get. Particularly with teams that include non-technical domains of expertise, such as content development or learning strategy.

A note here for scrum masters. Unless you want to exchange your scrum master stripes for a saddle and spurs, be wary of your team turning story pointing into an animal farm. Sizing story cards to match the exact size and temperament from all manner of animals would be just as cumbersome as the sporting method of story points. So, watch where you throw your rope, Agile cowboys and cowgirls.

(This article cross-posted at LinkedIn)


Image credit: tsaiproject (Modified in accordance with Creative Commons Attribution 2.0 Generic license)

Autopilot Agile

There is a story about a bunch of corporate employees that have been working together for so long they’ve cataloged and numbered all the jokes they’ve told (and re-told) over the years. Eventually, no one need actually tell the joke. Someone simply yells out something like “Number Nine!” and everyone laughs in reply.

As Agile methodologies and practices become ubiquitous in the business world and jump more and more functional domain gaps, I’m seeing this type of cataloging and rote behavior emerge. Frameworks become reinforced structures. Practices become policies. “Stand-up” becomes code for “status meeting.” “Sprint Review” becomes code for “bigger status meeting.” Eventually, everyone is going through the motions and all that was Agile has drained from the project.

When you see this happening on any of your teams, start introducing small bits of randomness and pattern interruptions. In fact, do this anyway as a preventative measure.

  • One day a week, instead of the usual stand-up drill (Yesterday. Today. In the way.), have each team member answer the question “Why are you working on what today?” Or have each team member talk about what someone else on the team is working on.
  • Deliberately change the order in which team members “have the mic” during stand-ups.
  • Hold a sprint prospective. What are the specific things the team will be doing to further their success? What blockers or impediments can they foresee in the next sprint? Who will be dependent on what work to be completed by when?
  • Set aside story points or time estimates for several sprints. I guarantee the world won’t end. (And if it does, well, we’ve got bigger problems than my failed guarantee.) How did that impact performance? What was the impact on morale?
  • During a backlog refinement session, run the larger story cards through the 5 Whys. Begin with “Why are we doing this work?” This invariably ends up in smaller cards and additions to the backlog.

There’s no end to the small changes that can be introduced on the spur of the moment to shake things up just a bit without upsetting things a lot. The goal is to keep people in a mindset of fluidity, adaptability, and recalibration to the goal.

It’s more than a little ironic and somewhat funny to see autopilot-type behavior emerge in the name of Agile. But if you really want funny…Number Seven!

Responding to change over following a plan

Welcome changing requirements, even late in
development. Agile processes harness change for
the customer’s competitive advantage.

Agile Manifesto Principle #2

Following from the Agile Manifesto value that is the title of this post, Principle #2 may be the most mis-interpreted and misunderstood principle among the set of twelve. Teams frequently behave as if this principle was prefaced with the word “always.”

Constantly shifting requirements leads to a frustrating and unsatisfying environment in which to work. It feeds burn-out and loss of morale. The satisfaction of a job well done depends on the opportunity to actually finish the job, no matter how small. Consider the effects on a finish carpenter who has just spent several days installing and trimming a full set of kitchen cabinets when the homeowner declares they want to change the kitchen design such that all those new cabinets will need to be ripped out and work begun on a new design. Or a film editor who has just worked 21 days straight to pare down an hour’s worth of video to fit into 7 minutes only to learn the scene has to be re-shot from scratch in order to match a change in the storyline.

Of course, the second principle does not state we should “always welcome changing requirements.” Nor does anyone I know claim that it does. But that doesn’t stop people from behaving as if it did. The rationale offered for agreeing to change requests from the stakeholders may be “We’re an agile shop and agile welcomes changing requirements” when, in fact, the change was agreed to because the product owner didn’t challenge the value of the change or make clear the consequences to the stakeholders. Or the original design was, and remains, needlessly ambiguous. Or the stakeholders have changed without renegotiating the contract or working agreements. Or any number of reasons that are conveniently masked with “welcoming changing requirements.” At some point, welcoming changing requirements is about as attractive as welcoming a rabid dog into the house. This won’t end well.

So, what kind of change is the Agile Manifesto referring to? There are several key scenarios that embody the need for flexibility around requirements.

  • The change that results from periods of deliberate design, such as during design sprints.
  • The change that is driven by the lessons learned from exploration and prototyping. If it is understood that the work being “completed” is for the purposes of testing a hypothesis and the expectation is that the work will most likely be thrown away, there can still be a great deal of satisfaction derived from the effort as the actual deliverable wasn’t working software, but the lessons from the experiment (usually in the form of a wireframe or prototype.)

So what is it that locks out the option for additional change? It’s a simple event, really. A decision is made.

Each of these scenarios where adapting to lessons and discovery is essential nonetheless end in a decision, a leverage point from which progress can be made toward a final deliverable. Each of these decisions can themselves form the basis of a series of experiments which, depending on the eventual outcome, may change.  Often, a single decision point may look good but when several decisions are evaluated together they may suggest a new direction and therefore impact the requirements. If the cumulative insight from a series of decisions results in the need to change direction, that shift is usually more substantial and on the scale of a project plan pivot rather than a simple response to a single change in a single requirement. The need to pivot cannot reliably be revealed if the underlying decisions do not coalesce into some sort of stable understanding of the emerging design.

Changing requirements cannot go on indefinitely or a final product will never be delivered. Accepting change for the sake of change is what gets teams into trouble.

Much like the forces on evolution, there will always be some external force that seeks to change the project requirements so that the delivered product can be stronger, faster, better, taller, smarter, etc.  This must be countered by clear definitions of “minimum viable” and “good enough” relative to what the customer is expecting.

In addition, product owners would serve their teams well by vigorously challenging any proposed changes to the requirements.

  • What is the source of the change?
  • Is it random change or triggered by some agent that does not announce its arrival ahead of time?
  • Was the change in requirements a surprise? If so, why was it a surprise?
  • Will this (or something like it) happen again? With what frequency? At what probability?

 

Remote Teams: Non-verbal Communication

Scrum mastering remote teams demands an extra set of skills than those required for co-located teams. The non-verbal cues we’ve learned growing up and throughout our careers are often not available with remote teams. Consequently, we have to train our ears to listen more attentively and follow-up to verify any assumptions regarding meaning from conference call, email, or instant message communications.

As scrum masters, we also need to coach team members to deliberately introduce practices that accommodate the lack of non-verbal cues during scrum meetings. For example, there are two practices I implement during remote stand-ups that facilitate the feel of co-located stand-ups.

  1. I call out the name of the team member who’ll kick off the stand-up conversation. When they’ve completed informing the team what they’ve worked on yesterday, what they’re working on today, and anything in the way of success the delivery team member calls out the next team member to take the conversation. I’ve found this keeps the rest of the team focused on the conversation better as they won’t know when they’ll be called.  Everyone will have to track who has already presented to the team. In the past I would randomly call out names until everyone on the team had their chance to speak. While they didn’t know when their name would be called they could still count on me to make sure everyone had their turn. Frequently, however, I’d have to call out a name several times to get that person’s attention away from whatever it was they were “multitasking” on. Having the team call out the next person to present has helped resolve this issue.
  2. After the team member has presented and before they pass the conversation to the next team member, I coach them to pause and ask if there are any questions from the team. In addition to signaling the end of their presentation, this makes the remote stand-up a little less mechanical and puts the thought “Do I have any questions?” in the minds of the rest of the team. More specifically, I coach the team with some version of the following: “Pause after your presentation and ask the team if there are any questions, observations, suggestions, comments, or clever remarks.”

Using techniques like this with remote teams does not replace the richness of co-located scrum meetings. They do, however, move the two a little closer.