I’m a fan of agile practices in programming, and encourage my team to work along agile principles as much as possible. One thing that has always been tricky about that for us, however, is that we don’t really match the usual profile of a software team.

Most agile teams (at least in the literature) are focused on a single project, and have multiple people working together to get that project done. We, on the other hand, do all the development work for Texas State University’s Learning Management System (about 32,000 users), Content Management System (287 sites at current count), an Event Calendar system, the University iPhone app, a reservation system for training classes, a custom web content caching system, various custom-built content management systems for accreditation and regulatory compliance, and a bevy of internal tools — all with 6 people.

Needless to say, I’m very proud of my team.

Prioritizing the time of six people when we have ongoing responsibility for more than twice that many projects is, however, a daunting challenge. Our approach for a number of years had been to set release milestones for each project, to do release planning meetings to determine what should go into a given release based on our Planning Poker estimates, and then to try our best to get the work done in time.

This approach had a few problems:

1. Release planning meetings were long and boring. We would walk through the list of unresolved tasks for a given project one by one to see if anyone wanted to prioritize that task. 90% of our time was spent saying “Ticket #666: add a green widget to the defrobulator. Anyone interested? Anyone? Class? Bueller?” (Only to have Bueller pipe up three tickets later: “Can we go back to ticket #666 for a minute?”)
2. It was easy for people who had an interest in one project to commit 100% of the development team’s time to that project, while folks who were keen on another project would commit all of our time to that project as well. Our planning process didn’t reflect the fact that all the projects were competing for the same resources.
3. If we finished all of the tickets for a release early and had extra time (a pretty rare problem, admittedly), we didn’t know what to work on next.

So a few months back, I decided to try an experiment. I got the stakeholders for all of our projects in a room together, gave them each 10 pennies, and explained to them the rules of the game:

“Today you are going to help the development team set our priorities. You each have 10 pennies, which represent tasks you can vote for. In order to vote for a particular task, write it on an index card, put that card in the middle of the table, and plunk down as many of your pennies as you’d like on that card. You can use all of your pennies on one task, or spread them among as many tasks as you like. Also, I encourage respectful argument. Try your hardest to persuade the people around you that they should put their pennies on the tasks you like as well. When we’re done, the number of pennies on a task will help determine its priority for our team.”

Good natured chaos ensued for the next 30 minutes as we wrote cards, passed them around, combined them, discussed the relative merits of the tasks ahead, bumped into each other as we moved around the table, tried to figure out what the heck some of the cards meant, and generally made a mess of the conference room we were working in. When we were done, we had a big, unruly pile of index cards with big, unruly piles of pennies on each:

After the meeting’s conclusion, the dev team took another 15 minutes to count the pennies on each card and put that count into a special “Bounty” field in our ticketing system, creating new tickets as needed. (We use “bounty” and “pennies” interchangeably.) When I was done, I told the system to sort our tickets by bounty, and suddenly had a prioritized list, across all of our projects, of what tasks had the most business value. Beautiful!

Task List Sorted by Bounty

Of course, the number of pennies on a given ticket doesn’t directly determine the order in which we work on things. We also factor in the estimates for a given task we’ve come up with individually or during our Planning Poker sessions. One can divide the pennies by the estimated hours to get a “bang for the buck” rating for each of the tickets — a much more useful way to prioritize one’s work.

I don’t like to assign tasks to people on my team directly more than necessary. I find people to generally enjoy work much more when they are able to make their own decisions about what to spend their time on. On the other hand, I do want us as a team to provide the most real value we possibly can to our various customers. Since the penny game provided us a “here are tasks with business value” list, I decided to provide a couple of incentives for folks who were completing those tasks:

1. I took a bizarre southwestern style pot that I had sitting around, labeled it the “Pot of Honor”, and told the team that it would be filled with candy and awarded to the team member each week who managed to complete tasks worth the most pennies during that span. Battling for the dubious honor of having this homely artifact rest on one’s desk for the week provides some silly, low-level competition and recognition for individuals.
2. I set the team a collective, cumulative goal and told them I’d take them to lunch when they reached it. When we tally pennies for the awarding of the Pot of Honor, we also add up the number of pennies the whole team has completed and add them to a running total. Progress is noted on our work-area whiteboard, so we can all see how close we are to getting to have free food.

The Pot of Honor

I’ve also made space on the whiteboard in our team area where we have our daily stand up meetings to put up the “Top 10” list of tasks that have accumulated the most pennies to help maintain focus on those high-value items.

The next time we played the penny game, a month later, it went much more quickly: we already had cards on the table from the last meeting, everyone had a better idea of what we were doing, and some folks had looked through the tickets in advance to see which tasks they wanted to support. I was surprised to see that, as we got more practiced, we were able to finish the entire exercise in about 20 minutes. We simply added the new pennies to the existing bounties in the ticketing system, making them increasingly juicy as they got older and people still had interest in them.

We’ve been playing the game for a number of months now, and I count our experiment a solid success. Advantages it has provided for us:

1. Prioritization is way more fun and engaging. It also goes considerably faster than all of our individual release planning sessions did.
2. The development team always has a clear idea of what our business needs are, and which of our tasks will provide the most value.
3. Stakeholders cannot say “everything is top priority”, but are forced to choose where to allocate their pennies. The finite scarcity of pennies reflects the limits on developer time.
4. Individual developers can exercise a good deal of autonomy and choose their own tasks while we still, as a team, deliver on the things we need to.
5. There are a number of tasks that, while people say they are important, apparently do not merit the expenditure of a penny. As these persist for a sufficient period of time without accumulating any pennies, we can close them as not really being a high priority. (We can always reopen them later if someone decides to spend a penny to raise them from the dead.)

We’ve introduced a few refinements as we’ve gone along: Because some of our systems have tens of thousands of users, it’s ill-advised to get all of the stakeholders in a room at once. To account for this, we give the support staff extra pennies to distribute as proxies for the absent users. We’ve started writing project names and ticket numbers on the index cards to make it easier to correlate them to our ticket system. We’ve begun bringing as many laptops and iPads as possible to the meetings so that people can see the details on the various tickets in question. We now add a penny to each task whenever a user request comes into our support team.

I should note that during the time I was designing this process, I was also reading through Total Engagement, and consciously built in many of their 10 Ingredients for Games: Feedback across a range of time scales (completion of individual tickets, weekly discussion of bounties cleared, longer-term goal of team lunch), Reputation (the awarding of the Pot of Honor), Marketplaces and Economies (the game itself is a market to “buy” the development team’s time), Competition Under Rules that are Explicit and Enforced (there’s no ambiguity about how many pennies are on a ticket or how they’re assigned), Teams (working toward the common lunch goal), and Time Pressure (weekly tallies of points, implicit time pressure of not wanting to be the last person with pennies left to spend while everyone else sits around). I think these elements have been critical in making this a more engaging way for us to do things.

So, if you’re facing a similar challenge with more projects than you have people, feel free to swipe any of these ideas that look helpful. I hope they’re of some use to you. If you do give the penny game a try, please post here and let me know how it goes. Good luck!

All of you folks who are as interested in location-based gaming as I am have been checking in on Gowalla, Foursquare, SCVNGR, Facebook, Rally Up, or Yelp for a while now. But the lame thing about those services is that you actually have to go somewhere and do something to earn points! Enter Mojo, the web-location based game for folks who are shackled to their desks all through the day but still want the spurious sense of accomplishment that these games bring!

Teasing aside, it’s an interesting concept: allowing people to check-in on various websites and engage with the content there in various ways to earn credit. I’ve added it to the site here; feel free to play around with it if you’d like to see how it works. Just click that little “Earn Mojo” tab on the right to get started. (Though given how infrequently I get around to posting, if any of you earn the “365 Days in a Row” achievement, I’ll be forced to come over there and cut off your internet privileges. Don’t think I won’t.)

I wrote a piece about a year ago called Workplace Motivation and Game Mechanics which summed up some of my ideas for bringing some of the compelling character of video games to the office. Since then, some much smarter people have been doing some thinking and experimenting with similar ideas.

Jane McGonigal gave a terrific talk at TED called “Gaming Can Make a Better World”. It’s well worth the 20 minutes it takes to watch:

Additionally, I’ve started reading Total Engagement: Using Games and Virtual Worlds to Change the Way People Work and Businesses Compete. It covers the authors’ experiences in this area, starting with poolside conversations and ending up with forming a company around these ideas. It’s a good read so far.

Based on these, it looks like the invasion of games into the workplace has the potential to create some important productivity gains and is already underway. It should be fun to see what the next decade brings.

One of the things about writing software for a living is that customers are rarely happy when you tell them “It will be done when it’s done.” Even though development is fraught with uncertainty, it’s still incumbent upon us who practice this craft to be able to give people some idea of what kind of effort will be involved to implement a particular feature.

One way to do this is to have a project manager or senior programmer sit down, think really hard about it, and come up with numbers. This has the advantage of being  expedient, but the disadvantage of being almost certainly wrong. The reasons for this are many: it’s hard to estimate a job accurately when you’re not the person doing the work. All of us as individuals possess blind spots. And programmers are notoriously optimistic about how hard it will be to do something. (Not as optimistic as marketing people are when faced with a programming task, but still…)

One of the approaches I’ve seen that seems to promise the best results over time is Evidence-Based Scheduling. By having programmers estimate the tickets they’ll be working on, then record how much time they actually spend on it, comparing one to the other, factoring in how much productive time they have during the day once meetings, email, and the ilk are all done, and doing a lot of math, one can come up with good quality estimations — especially as one accumulates data on which programmers tend to exaggerate and which think they can finish nearly anything before lunch today. This approach has the advantage of producing really good estimates, but requires detailed tracking both of estimates and actual work time to produce good results.

Somewhere in the middle is Planning Poker, an approach that allows teams to collaboratively create estimates with a minimum of fuss. The basic idea is that you get all your developers together, give each of them a deck of cards with a time estimates written on each card, and have everyone choose how long they think a given task will take by throwing the corresponding card on the table. If there’s not agreement, everyone discusses it, explains their reasoning, and then you do it again until there’s a consensus. (You can read more details here if you’re interested.)

When we’re planning what to do for the next phase of a project, we have to consider two things: how important an issue is, and how much work it will be to do the fix. The latter has, up to now, been done off the cuff by whomever of the developers happened to be in the room. But in the past week, we’ve added a field to our ticketing system for estimates and started doing Planning Poker sessions to capture estimates for the tasks ahead. These seem to be going well, and I’ve noticed some interesting things about them:

• These sessions are actually pretty fun. Nobody has come away hating the process, and several of the devs involved have said they’ve really enjoyed them.
• Because the rules of the game call for the people with the highest and lowest guesses to explain their reasoning, we hear from people who are sometimes a bit more reluctant to speak. Having their opinions respectfully listened to can be a very affirming, especially for new folks who may not have a history with the team yet.
• We’ve actually been doing on-the-fly technical design as we discuss the issues, and have come up with some really good ideas and insights that we’ve then recorded in the ticket since we already had it open there. This was a pleasant surprise to me; I’d only been hoping to get estimates, but have also benefited from some terrific collaborative technical brainstorming.
• It provides natural cross-training, since even programmers who aren’t involved in a particular project get to listen, ask questions, and vote on its tickets.

So after two sessions, I’m counting Planning Poker as a success, and have scheduled regular sessions to finish estimating our backlog of tickets and to handle new ones as they show up.  Many thanks to Mike Cohn for the great writeup that got me excited about it!