How a small change to customer engagement can make a huge impact on software delivery. Impact Newsletter by Gojko Adzic.
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The most important lesson to improve software delivery

Richard Tattersall of the parish of St. George-in-the-Fields, liberty of Westminster, gentleman, as he liked to be described, had a lot of interesting claims to his name. In his youth, in mid-18th century Lancashire, he wanted to join the jacobite rebels. After a family intervention, he ran away from home, and ended up becoming a stud-groom in the service of the Duke of Kingston-upon-Hull. A unique business sense led Tattersall to start his own race-horse farm, then establish an auctioning house. Tattersalls Auctioneers’ ended up at Hyde Park Corner, and their clients included the key British nobility and even the King of France. Two and a half centuries later,  France is no longer a kingdom, the dukedom of Kingston is extinct, but Tattersalls auctioneers still runs. It is the oldest such institution currently operating in the world, and Europe’s largest. Tattersall was not just a good businessman, he also knew how to entertain. Even the future king George IV was known to frequently visit Tattersall at Highflyer Hall, to enjoy ‘the best port in the land’. In his late years, Tattersall was so universally known and respected throughout the realm, that Charles Dickens wrote about Tattersall ‘no highwayman would molest him, and even a pickpocket returned his handkerchief, with compliments’. It would, then, come to great surprise to the gentleman how often software developers curse his name today.

In an epic twist of irony, people often don’t even know that Tattersall, the person, had no influence on the cause of all that pain. Tattersall had just the right mix of business sense and social skills. At his Hyde Park Corner venue, he reserved two ‘subscription rooms’ for the members of the Jockey Club. The two rooms quickly became the centre of all horse betting in the UK. The Tattersalls Committee, an successor organisation to the informal clubs from the two subscription rooms, had the legal ability to exclude people from the sport or access to racecourses in Britain all the way up to 2008. The rules and regulations they used to settle disputes still more or less govern British horse racing today. And among those rules, there is the famed 4(c), the destroyer of software models. For all the pain it caused me over the years, it’s also responsible for one of the most important lessons in improving software delivery I’ve ever come across.  

For teams working on horse racing software, ‘Rule 4’ is the one thing you can always mention to disrupt a meeting, cause everyone to tell you to go to hell, and then spend the rest of the afternoon playing Desktop Tower Defence. It’s the edge case a tester can easily invoke to break almost anything. It’s the reason why people phone in the next day and insist to stay home because of some unforeseen illness. That’s because Rule 4 messes with the one thing developers hate to touch — time. 

Horse racing bets are priced either at the time when a bet is placed, or at the time when the race starts. Punters generally prefer the first, called ‘fixed odds’ because they know what they’re expecting. The price and the potential winnings are fixed, hence the name, and that’s the rock solid agreement between a punter and a bookie. Such a premise allows developers to design some nice and elegant settlement models, and then deal with the difficult stuff they like to solve, such as latency, throughput, and performance optimisations. But then Tattersall’s Rule 4 kicks in. It controls what happens in a case when one of the horses doesn’t show up for a race. If, for example, the favourite ends up in a ditch somewhere ten minutes before the race, all the people betting on the second favourite now stand to win a lot more than the bookies expected. Rule 4 allows a bookie to pay out the bets on the other horses as if the favourite never existed. This means going back in time, recalculating the odds for all the other runners, and applying the new price. With weird math, that isn’t exactly completely logical. For each single bet, at the time when that bet was placed. This is where the stomach problems start. Developers realise they need to start saving a lot more information at a time when the bet is placed, mess up with the nice elegant settlement models, break system performance, and a ton of other things. That’s why, generally, once Rule 4 is finally implemented correctly, that piece of code is off-limits. Nobody gets to even view it on a screen, to prevent an accidental Heisenbug. 

Rule 4 makes a lot of sense when one of the favourites misses the race, but it’s also applied to Limpy Joe, the horse that almost died in the previous race of old age and boredom. It can lead to weird and pointless complaints about why someone got 5 pence less than expected, and it can cost more in wasted customer support than it protects against fraud. I once worked with a company that tried to save a bit of money on customer servicing, and do something nice for its punters at the same time, by not taking advantage of Rule 4 below a certain threshold. Switching rules on and off wasn’t such a big deal, it turned out that they could actually do it themselves, and everyone was happy. No need for anyone to stay home playing Desktop Tower Defence. 

But then, one day, they asked us to change the monthly customer statements, and print out the bet results as if Rule 4 was still applied, then add the deduction back. Not only did this mess with time, but it messed with it twice. It required us to record something that didn’t happen as if it happened, combine it with a ton of other rules that did actually happen, and then flip back the whole thing again. And they asked us to do that not at the point when the bets were recorded or settled, but when the monthly statements were produced. This required keeping a lot more information so we could settle all the other rules backwards and forwards in time, break system performance, and change the one part of the system that nobody wanted to touch. Some of the additional rules were implemented by third parties, so we’d have to chase them to change their code as well. Of course, the whole thing needed to be done as quickly as possible, ideally yesterday. Lots of towers were successfully defended that day. 

The next week, on a visit to the call centre, I sat next to an operator who was one of the people insisting we ‘fix the statements’, and watched him deal with a disgruntled punter. The person on the other end of the line heard about the Rule 4 promotion, and called in to complain that he was short-changed. In fact, some other rules produced an odd value for the final payout. The operator was stuck explaining that the amount on the statement is OK, and he had to take the punter through the whole weird math required to settle a bet according to all the other on-going promotions. A few minutes after that call, another one came in. Instead of saving money on customer support, the Rule 4 voiding idea made it worse. It was clear that the interaction of rules was causing the confusion, not Rule 4 itself. I asked about why they singled out that one, and the operator said that they were going to ask for all the other promotions to be pulled out into separate line items as well, just later. They didn’t want to overload us with work, so that Rule 4 could get done quickly. 

Observing the problem first-hand, I could see the whole mess, and why they wanted something done about it. But just thinking about the implications on our nice, clean, elegant software models made my stomach turn. Luckily, being next to the one person who suffered the most, and finally understanding what’s going on, I could propose an alternative. What if, instead of actually redoing the numbers to list individual calculation components, we just listed the names of the special promotions applied to a bet? So punters would immediately see that there was more than one thing going on, and that their Rule 4 promotion still applied. That information was already available in the database. The fact that the solution could be deployed in a few days sold it easily. The trick with labels reduced the confusion, and not just for Rule 4, but for all the other promotions they were going to ask about later as well. 

That day, I learnt that how important it is to spend time observing people actually using the software that we were building. Sitting next to a user allowed us to together flush out all sorts of weird and wonderful assumptions, and work together on ideas that solve real problems, not just plaster over a huge crack. Together, we discovered insights that nobody could predict. That’s just common sense, so surely everyone is doing it by now, right? Not so much.

With the previous post, I asked people to fill in a quick questionnaire about how frequently they observe people using their software. With slightly less than 800 responses, I can’t really claim any kind of universal statistical relevance for the whole industry. On the other hand, given that you’ve self-selected into a group by reading this, the data should be relevant for teams similar to yours.

Roughly fifty percent of the survey participants said that had no direct interaction with end-users, ever. They’ve never seen an actual user work with their software. Only about 10% teams, across the whole group, actually engage with their users every week. 

I asked separately about observing end-users testing future software ideas, pretty much the key aspect of getting any sort of user experience research executed. The numbers are even worse. Only about 6.4% of the respondents said that they do that on a weekly basis. In a fast moving industry such as software today, where bad assumptions and communication problems can cause serious damage, that’s just depressive. 

This is both good and bad news. For most people reading this, the bad news is that you’re not benefitting from all the insight that you could easily collect.  The good news is that the bar is so low at the moment, that you can easily change your delivery process a bit and be far better than the competition.

If you’re a developer or a tester, figure out an excuse to sit with the actual users for a few hours every week. If you’re managing a team, think about sending the group to observe actual users periodically. I guarantee this will significantly improve the software you deliver. It doesn’t matter if your company already uses a UX specialist agency to deliver the decisions, or if you have someone else already tracking the usage patterns and results. Go and see things for yourself, you will learn stuff you could have never predicted before. 

For example, we recently added text notes to MindMup 2.0. This was one of the most requested features on the user forums, so we had a ton of data to start with. Instead of just charging ahead with the ideas collected through initial requests, we spent a week building a rough version, and then invited actual users to try things out. The results were surprising. We got a bunch of assumptions about ordering and exporting wrong, and our users wanted something significantly simpler than what we planned to develop. As a result, we were able to launch that probably a month ahead of the schedule, and make it a lot more intuitive. 

Of course, there will be plenty of excuses why spending time with users isn’t possible. Especially if they are not easily available. The survey results broken by type of software delivery clearly show that. Reduced only to software delivered internally, roughly 27% of the participants said that they observe users working with their software at least once a month. This is significantly better than just 16.5% of those working on consumer software. Enterprise B2B, of course, ends up in the last spot with roughly 14%. 

Don’t let the fact that your users are remote, or numerous, stop you from talking to them. Even for consumer-oriented products, getting this kind of feedback is easier than it seems. I go to lots of software conferences, and I always try to get a few people to try out MindMup between conference sessions. It doesn’t cost us anything, and most of the people I approach are willing to spend a few minutes helping us out, especially during long boring lunch breaks. If such direct contact isn’t possible for your team, think about remote screen-sharing sessions. It’s not the best way to do user research, and I’d love to have one of those hi-tech rigs that tracks eye movement and blood pressure that ad agencies use, but that’s far beyond my budget. However, even a simple screen share session opens up an incredible amount of insight. The text notes research we did for MindMup 2.0 was done 100% over remote screen sharing, and we had people participating from all over the world. Just get people to think out loud while they are clicking around the screen, and be ready to get surprised.


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