Getting things done is great; to get things done is why we start things in the first place and why we follow through even when presented with obstacles and setbacks. We do things because they will (hopefully) bring us to some better state. So getting these things done quickly is good because we arrive at this better state sooner. We track our rate of development (velocity) as a useful measure of progress and also as a leading indicator towards when we should be done. However focussing too much on velocity is dangerous; it leads to myopic mindsets and even moronic behaviour.
velocity is good, but not at the expense of quality, good-will, or noticing subtle
changes in direction. At the Agile 2012 Conference Jim Highsmith and Pat Reed hosted
a session called “Velocity
is Killing Agility” which examined how velocity (which should be as much a
measure of team capacity as it is a measure of their output) is being misused.
When organizations overly publicize and analyze velocity, misguided attempts to
“Go Faster” lead to gaming velocity scores and not project team improvements.
A Measurement Parallel
For the last 6 months I have been using Strava.com to track my running and biking exercise. It is a social web site for tracking and sharing workout performance data that creates maps, leader boards of hills climbed, point-to-point fastest times, etc. Using your phone or GPS device while out running or riding your performance is automatically recorded and then uploaded and compared to everyone else that has ever covered the same route. Individual rides and runs become virtual races against people you have never met. After posting the fastest time for a segment Strava will send you emails such as “Uh Oh, <fast guy’s name> just beat your record on Heartbreak Hill, go out there and get it back!” It can all get pretty competitive and silly if taken too far.
I have found Strava to be a fun, addictive work-out analysis tool that has led to a few special outings just to retake some records back and generally push harder to beat my own previous times. I have also met a few new people who run and bike locally and found some new trails by looking at the maps of where people train. The trouble with obsessing on getting the fastest times for segments is that it can drive stupid, myopic behaviour. Stories of people barrelling down trails on mountain bikes at crazy speeds yelling “Strava, get out the way!” at people are getting more common.” Similarly, if you can’t ride the last technical descent on “Coal Chutes Drop” – then just throw your phone over the finish line and you should get a better time!”
Strava.com focuses on times and velocity which, when used appropriately, are a great metric for running and cycling performance. However, people being people have a way of misinterpreting, taking things too far, and gaming systems. The site DigitalEPO.com lets you “enhance” your GPS tracks for faster times. Some of the Strava metrics are interesting but questionable, if you believe you get what you measure. For instance the “Suffer Score” metric which attempts to measure cumulative effort based on your heart rate is interesting. While in small does pushing hard is good, undoubtedly some people will take it too far with negative side effects.
A Balancing Force
Strava recently announced integration with Instagram the photo sharing site. If you enrol, photographs you take using Instagram while out are associated with your performance stats and maps. So, not only do you get elevation profiles and leader boards of your course, but also photo streams to remember it by.
I am still in awe of the beauty of Western Canada where I now live and like to take photo’s when I’m out. However I soon discovered pushing for fast times and stopping to take photographs are not very compatible. Stopping, getting off you bike, taking off gloves, fishing out an iPhone and taking a picture with Instagram before setting off again all takes time that messes with your Strava segment times.
Instagram is the perfect antidote for the temptation of being too velocity
focussed with Strava. It encourages me
to lift my head from the immediate velocity goal, look around for nice things
to photograph, and appreciate where I am more often. This better aligns with why I want to be
running and biking anyway. Yes the exercise portion is a big part of it, (and
the competitive side has been an unexpected draw), but mostly it is to be outside,
moving through nature in a positive way.
Saving Agile Velocity
Bringing the comparison back to agile methods, if, as Jim Highsmith and Pat Reed assert, we have an unhealthy obsession with velocity; what is the Instagram equivalent that will help us stop and smell the roses, recognize the other good things happening, and generally restore a more balanced perspective?
I think Appreciative Inquiry is a good place to start. Appreciative Inquiry (AI) is a practice for recognizing what people are doing well, or what is good, and drawing attention to it so we can build on it. Traditional problem solving looks to find issues, identify the root cause, and plan solutions. AI however, takes an alternative view point of appreciating the best of what is, envisioning what might be, encouraging dialog about what should be, and innovating ways to get there.
From a mountain biking perspective, if you focus too much on the rock you want to avoid you will likely hit it. Instead looking further down the trail at where you want to be, is generally a better place to focus. If that is too Zen or trite for a commercial environment then consider this quote from the AI conference: “Organizations grow in the direction of what they study” If we spend all our time studying defects, problems, down time, and low velocity then guess what? We will grow towards those things. Yes, it is important that we are aware of those items, but also create a balancing force by examining what is working, the accomplishments, synergies and appreciation.
The following table contrasts Problem Solving and Appreciative Inquiry:
Felt need, identification of problem(s)
Appreciating, valuing the Best of What Is
Analysis of Causes
Envisioning what might be
Analysis of possible solutions
Engaging in dialogue about what should be
Action Planning (treatment)
Innovating, what will be
AI exercises are often undertaken as part of retrospective workshops. We can start by asking “What’s working well?”, “What’s good about what you are currently doing?” Then ask participants to imagine the next iteration is already over and we can talk to our future selves and ask what the most productive, most satisfying elements of it were?
This exercise of imagining we are in the future is a deliberate step to help produce better responses. People are often poor at generating lists of ideas or activities. As Luke Hohmann explains in his book Innovation Games when describing a similar exercise called “Remember the future”: “The act of asking people to imagine the date is some point in the future and then “remember” all the things that occurred to be successful yields significantly different results. Now because the event is “in the past” we must mentally generate a sequence of events that caused this result to have occurred and this gives rise to better quality definitions and more detailed interim-step descriptions.“
If this still sounds too touchy-feely, I can associate with you. As a reserved Brit’, I felt a little uncomfortable suggesting group-hugs for stuff we have not done yet. However, I was OK with asking people “What is going to have to go right for us to be successful?” and building from there.
There is also nothing wrong or touchy-feely about recognizing what is working well and bringing greater visibility to it. For one of my client’s, I produce a weekly project status report for the extended stakeholder group. It summarizes work done that week, work planned for next week, and any issues or risks arising –like a weekly stand-up review. I started adding the occasional recognition and thank you statements too. The first week it was for some user acceptance testing done by a business group. The changes have been positive and even for the most cynical, results focussed people, if something so quick boosts performance, then as long as it is legal, we should do it. The fact that it is also ethical and positive is just an added bonus.
These are small, but significant steps in raising the focus from velocity and problem solving to appreciation and the upward spirals of high performance they bring. Since “Organizations grow in the direction of what they study” focusing on the strengths is not premature self-congratulation, but instead smart working practice.
So how do we perform Appreciative Inquiry? Well, the AI 4D Cycle shown below illustrated the process.
1) It starts at the top with the “Discovery” phase. This is all about finding out what is working well right now, what have been the best achievements, etc. The Discovery phase focuses on appreciating what is good and best. We demand and expect a lot from our teams on challenging projects and that is fair, but it is also important that we stop to recognize all the good things they are doing.
2) The next step is “Dream”, it challenges the group to imagine how good we could be. What we really should be doing and where the greatest benefits are. The Dream step asks “What could be?” with no confinement and promotes envisioning a better project environment.
3) Next we “Design” how to get to that better state. Some steps may be obvious, others requiring changes outside the project team. The Design step is where our envisioned future is planned out, tasks defined and responsibilities decided. “Co-Constructing” is the term used to describe the whole-team approach to planning that gains consensus and support.
4) Finally the “Destiny” step is the empowering and exercising of these Design plans. Doing the things we said we would, walking-the-talk, executing, it does not matter what we call it; benefits will only come through action not dreams or plans.
Once the theory of AI is understood the facilitated exercises from retrospectives such as “What went well?” and “Remember the Future” make more sense. They are portions of the AI 4D cycle covering Discovery and Dream. We just need to make sure that we follow through with creating concrete action plans with the team and executing these in the subsequent iterations. I like getting the team to create story cards for the agreed improvement tasks, gaining consensus on estimates, and talking to the product owner about prioritizing them in the backlog.
A subtle but important shift
AI is important in retrospectives, but is most effective when used in everyday conversations and reporting. To make it work consistently we have to learn the Art of a Good Question. Remember that projects are basically problem solving endeavors, so people see issues and impediments wherever they look; we want to focus on the positive, solution based side of things to bring a balancing element to the project view.
So, look out for and avoid Bad Questions that focus only on the problem and don’t help people shift to a more positive view of the future where the solutions are. Examples of Bad Questions include:
- What’s the biggest problem here?
- Why do we still get these issues?
- Why don’t the users understand?
Instead, we want to ask questions that promote thought towards improvements and a better tomorrow. Examples of Good Questions to ask would be:
- What possibilities exist that we have not thought about yet?
- What’s the smallest change that could make the biggest impact?
- What solutions would have us both win?
Usually when I see a problem then my first reaction is forming bad questions about the situation, yet since learning to reframe them as good questions I have seen consistently better outcomes so it is definitely worth the translation effort.
Managing agile projects is the new science of dealing with Knowledge Workers. Peter Drucker in his book Managing in The Next Society explains that “The task of leadership is to create an alignment of strengths, making our weaknesses irrelevant”. This quote summarized the concept nicely. Take time to recognize the good and the project environment will improve bringing rates of progress with it.
I encourage project managers to consider the balance of metrics and reporting on projects. Obviously velocity is important, but by also highlighting achievements and gratitude through approaches such as AI we will get better results through an improved project environment.
So, just as Instagram encourages appreciation of your surroundings beyond point A to point B speed, AI encourages appreciation beyond velocity and problem solving. Both create a bigger picture balance that, ironically, increase velocity - time for that run!
A great resource for learning more about Appreciative Inquiry is the AI Commons.