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Incredible Data: How to Become More Profitable and Have Fun Whilst You Do It35:01 with Dave Kelly
Does drinking coffee make you more efficient? Or is the time spent coding on your coffee high mitigated by the extra time spent in the loo? Dave answers this and many other questions in a talk aimed at showing you how to make your business more successful by collecting and analysing data about everything you do. If you're fascinated with stats and info-graphics then head to this session and Dave will tell you how to find the one key metric you can use to run your business successfully. You'll leave this session in a position to assess your business in a new way, making you and your team more profitable, efficient and effective.
[MUSIC] 0:00 >> Thank you all very much for coming along to this rising star track. 0:09 My definition of rising star I think is scared person 0:15 who once upon a time somebody heard say something interesting. 0:18 So stick them on a stage. 0:20 So bear with me, this is my my first talk at a conference. 0:22 I hope you'll enjoy it. 0:25 Incredible data. 0:28 [COUGH] as thanks for the wonderful introduction. 0:29 I,I have been lucky enough to be in a position in my life 0:33 where I started a web dev firm when I came out of university. 0:37 And through the opportunities and the people I've met from, from that 0:40 web dev firm I have, had the opportunity to buy other businesses, basically. 0:45 So clients of ours who have then gone and 0:50 taken shareholdings, and some of them, up to 100%. 0:53 In industries that I know absolutely nothing about. 0:57 But all of them have involved data. 1:00 Either the selling of data or the fact that we've been using data to 1:02 go and change the industries So, today, I'm gonna talk to you about three things. 1:05 First a little bit about incredible data and what on earth I'm 1:11 talking about, the second is how we use data, two methods to use 1:14 data to become more profitable in your business and the third and probably 1:18 the most interesting is that we decided to do this internally at storm. 1:22 We spent an entire month a couple of months back where we 1:27 literally tracked everything from the people 1:30 were wearing pedometers, the number of 1:33 stairs they climbed, the number of coffees they drank, the number of 1:34 times they went to the toilet, 1:37 the temperature, the light, the heating everything. 1:37 Everything, everything. 1:40 Their perceived mood, their perceived productivity. 1:41 And I'm gonna tell you about what we did with that data. 1:43 And to be honest with you, the main reason I wanted to give 1:46 this talk is cuz I found quite a lot of it quite funny. 1:49 And there are a few people who are actually in 1:53 the audience that, who, whose names would have been obscured 1:55 for obvious reasons, but I'll point to them when the 1:58 facts about them, so you know who I'm talking about. 1:59 Some funny stuff up there. 2:02 So, I'm, I'm gonna crack on and talk about incredible data. 2:04 A few little stats to start with, which you've got nothing to do 2:07 with very much but 4.1 million hectares of forest have been lost this year. 2:12 Which I'm sure as you all really wanted to know is 2:18 an about an area the size, twice the size of Wales. 2:20 But at least we're doing our bit to be green. 2:23 We've produced nearly 112 million bicycles this year. 2:28 And I know what you're all thinking, how big is that 2:32 if you lay them all down flat in terms of Wales. 2:34 Well, it's 1 86th the size of Wales. 2:36 This is actually quite a nasty statistic when you think 2:39 about it. 2:44 Nearly 900 million undernourished people in the world. 2:45 Which when you put it in the context of the 2:48 fact that there are 1.5 billion overweight people in the world. 2:49 Which is when laid flat about 112 the size of Wales. 2:54 >> [LAUGH]. 2:58 >> But that's not very nice to think about. 2:59 By the way, if you took all of those people, 2:59 you could actually fill the Seven Estuary, rejoin them in 3:01 negating the six pound 20 toll charge, which is a 3:03 net saving of 84 and a half million pounds a year. 3:05 But, that's the world spending on illegal drugs this year so far. 3:08 Gonna go down now Breaking Bad's finished. 3:13 But still, ten people a year. 3:15 Are killed by vending machines. 3:17 I found the bugger. 3:19 Its him. 3:20 I would be watching out if that was the vending machine I was using. 3:20 Now I'm, I say data. 3:23 You're probably looking at this saying that's that's not actually data. 3:25 That's that there's a fact. 3:28 They're stats. 3:30 They're jokes. 3:30 And you'd be right. 3:31 And here comes the first management program of the day. 3:32 [LAUGH] Don't run. 3:34 data. 3:37 Is, is nothing at all on its own, it means bugger all to anybody. 3:38 When you contextualize it in the form of those, kind of, stats, jokes, etcetera. 3:43 It starts to gain meaning. 3:48 But in terms of business it can't help you until you feed into some sort of process. 3:50 That might be a learned behavior. 3:55 That might be a model. 3:56 That might be some business theory. 3:57 And that is really what I'm gonna be telling you about today. 4:00 Two pound fifty is some data. 4:03 It means nothing. 4:04 When we can textualize it, a pint costs two pound fifty. 4:06 We're thinking learned behavior that might be a 4:08 really budgie pint especially if it's in London. 4:10 But maybe I'll get my wallet out and maybe that's actually a really good thing. 4:13 And the end result might be 11 pints, great! 4:17 But it is useless and so the context and the application is where. 4:20 The becoming more profitable comes in. 4:25 And what I'm gonna show you is two different methods, the 4:28 first of which is going to tell you about how you put 4:30 data in context of your business, why that data is important, actually 4:34 add some logic to the fact that they, it should be important. 4:37 And the second example to making more 4:40 profitable is gonna focus around the application. 4:41 I'm gonna give you a real life example of how 4:44 you can find uh,one number that probably runs your business. 4:45 Whether you're freelancer or a multi-million 4:49 pound business, the chances are, there's going 4:51 to be one number in there somewhere which is the application of data. 4:52 And then at the end, I'm gonna show you how Storm actually. 4:56 Took this found loads of data and found some funny things. 5:00 So let's talk about becoming more profitable, and again a little caveat. 5:03 I say more profitable I don't mean more profitable. 5:09 I mean more successful because for some 5:13 people success is this rolling around in money. 5:15 But it is perfectly reasonable if for you success is having the time to do a hobby. 5:19 Just enjoying yourself at work, you know, having 5:24 time to chill out with your, your colleagues. 5:27 For some people they'll accept nothing less than world domination. 5:29 It doesn't really matter. 5:31 The point is that, just because I'm talking about money in terms of success, 5:32 that doesn't necessarily mean it's the thing, that you have to be focused on. 5:37 So on to the first of these methods. 5:41 I call it, using data to create your own luck. 5:44 and, those of you who were paying attention of 5:48 course and not asleep would have heard me at 5:52 the very beginning of the talk say that I feel I've been lucky in my life so far. 5:54 That I've been in the right place at the right time. 5:59 There was Here we're gonna go back in time a bit. 6:03 A Roman philosopherum, who [LAUGH] yeah, I know, 6:06 tech talks and all um,let's get the Romans involved. 6:08 Luck is what happens when preparation meets opportunity. 6:12 And I really believe this. 6:15 The, the, luck isn't something that kind of 6:17 just, stumbles on you, it's, if you're prepared by 6:19 whatever means, and an opportunity presents, and you grab 6:23 that opportunity, other people will see you as lucky. 6:26 How come he got to do that? 6:28 How come he won that? 6:29 Well probably. 6:30 Lots of preparation and in the right place. 6:31 And bringing that up to, slightly up to date. 6:32 This chap here who actually if you Google 6:37 for the Roman guy it looks remarkably similar. 6:39 This guy a chap called John Boyd, was a military strategist 6:43 who came up with a stratagem for basically beating his opponents. 6:46 It's called the Boyd Loop. 6:52 It's actually a very well known piece of 6:54 management theory, but very rarely gets talked about. 6:55 Quite simply, observe orientate, decide, and act. 6:59 And putting that in the luck kind of bid world. 7:03 That's the opportunity bit, the observation. 7:06 This is the preparation bit. 7:09 And I'm gonna give you an example of how that works using two two corporations. 7:12 So have a massive corporation which we'll call Massive Inc. 7:16 And we're gonna have a, a small company which we're gonna call Brian's Cheese. 7:19 And the idea is if Massive Inc. 7:24 See, for example, that someone brilliant is about to come onto the market 7:26 as, as a really good hire, they're just leaving their, their current job. 7:31 Massive Inc might be looking and thinking that guy, that's the one we want. 7:35 So, they'll have a meeting. 7:39 They have to decide whose cost base it's gonna come out of. 7:40 They'll have a chat about who he's gonna 7:43 be reporting to, and what his objectives will be. 7:44 At some point a decision will be made. 7:47 We should offer that guy a job, really we should and then there'll be an action. 7:48 Shall we send him a letter and see if we can get him in. 7:51 Unfortunately, Brian's Cheese in in the middle dancing 7:53 around in circles going, I wanna hire that guy. 7:55 Do you wanna job? 7:57 Very simplistic example, but it makes the point that 7:59 small teams can almost always out maneuver, large opponents. 8:02 Simply because they can get decisions made more quickly, they can be more agile. 8:06 There are some brilliant examples of this. 8:10 Fitbit and Nike with the fuel band. 8:14 Both of these companies started talking about this tech in 2007. 8:17 Which one of the two had a product in 2008? 8:23 Which one didn't have a product till 2011? 8:26 By 2011, there were two more of these out, and by 2012 another one. 8:29 The fact is that [UNKNOWN] may well have had a little team, 8:33 but those decisions about this had to go right to the top. 8:37 There were strategists involved. 8:40 There were all sorts of people involved. 8:42 They didn't take an opportunity and go. 8:43 Can we get something out there really nice and quickly 8:46 and I mean there are a, a, another example which I 8:49 really like is actually the fact that everyone forgets that once 8:51 upon a time Apple was being run out of a garage. 8:54 And there were people like IBM and 8:56 Microsoft who are these massive, massive companies and. 8:58 The, the, the biggest for me is when, Apple had a,a period just 9:03 before the, the Northeast where they, where 9:07 they were actually in decline, where they 9:09 weren't doing so well and it was only when they released the new unified 9:10 one body Mac in the early 2000s they started to pick back up, but. 9:14 This is, I think, now keep in mind at that time they were way 9:19 smaller than Microsoft cuz this is kind 9:22 of, slightly, just before pre, pre-iPods and pre-iTunes. 9:23 And there's a couple of quotes from Steve Jobs, Steve Jobs, I'm 9:26 sorry, about Steve Jobs from Bill Gates specifically about iTunes, which I think. 9:30 Demonstrate that this can happen even in the biggest business. 9:35 And that is that Bill Gates said, Steve Jobs has 9:38 an ability to focus in on a few things that can't. 9:41 And this time somehow he's applied this talent to 9:44 getting a better license deal than anyone else's got. 9:47 I think we need some plan to prove that even 9:52 though Jobs has left us a little bit flat footed. 9:55 Again, we move quickly and both match and do stuff better. 9:57 Basically, this was Bill Gates going,how did they manage to do that so quickly? 10:03 How did they manage to get that problem solved and out the door? 10:08 What the hell has happened here? 10:11 We've missed something. 10:12 And you can see that literally across the board in business. 10:14 So what on earth has that got to do with data? 10:18 Well, it's this bit. 10:20 Opportunity, as we called it earlier on, kind of 10:22 presents an idea of something coming on to find us. 10:25 I'm sitting down in my deck chair and an opportunity comes along. 10:28 The way Boyd puts it, is that it's observation. 10:31 You're there looking for the opportunity. 10:33 You don't sit back and wait for it to come to you. 10:35 You're actually actively looking, and that is data. 10:37 In your business, there is so much data 10:40 flowing around your business in terms of the market, 10:42 in terms of your competitors, in terms of your 10:44 friends, in terms of legislation, the list goes on. 10:46 And you're probably not looking for it. 10:49 You're probably not looking at it. 10:54 You probably find out about it when 10:55 your competitors do something really amazing with it. 10:57 And, usually the reasons small more businesses aren't looking is quite simple. 11:00 Haven't got any time to look. 11:05 I'm too busy. 11:06 I'm too busy to do that. 11:07 You're too busy to succeed? 11:09 If you don't leave some time in your business to actually go and look 11:10 at the things that could make you 11:13 more profitable, that could give you opportunities. 11:14 How are you ever going to? 11:17 Now it doesn't matter if you're a freelancer, who 11:18 should probably be keeping an hour a, an hour 11:20 a week to just generally keep an eye on 11:22 what's going on, or whether you're a multi-million pound company. 11:24 Who probably has got the resource to do the looking, but when 11:26 they see something it takes them bloody ages to do anything with it. 11:30 [COUGH] So to put that idea of, if you're not 11:34 looking you are never going to find it, into context. 11:36 Let me show you how you can find one, one number in your business. 11:39 That will help you run your business, and it 11:42 should put that into context a little bit for you. 11:45 So. 11:47 This is something that we run with a lot of the 11:49 companies who, who we work for as a, as a software [UNKNOWN]. 11:50 If I didn't say, make it clear in the beginning, my role within 11:53 the store is, is mainly sitting with new business in a strategy sense. 11:56 So I basically sit with them and I will 12:00 work out what their idea is cuz it's probably in 12:02 the industry I'd understand how you can apply tech 12:04 to it and actually make some money out of it. 12:06 So we, we run through this with a lot of our clients. 12:08 And the answer to the question either. 12:11 Why am I making money, or why should I be about to 12:13 be making money, or quite often, why am I not making any money? 12:15 Which is not such a nice conversation. 12:19 And it revolves around this very scary thing of a critical resource limitation. 12:22 Quite simply it is the thing that when you run out of it. 12:29 You can't make any more money. 12:33 Now bear with me on this it's not necessarily the thing you sell. 12:34 It might be the thing you sell but 12:40 it might be something that comes slightly earlier on. 12:42 So, very obviously if you've got a certain number of bedrooms in 12:43 your hotel or seats in your restaurant or whatever that might be. 12:46 And you've run out of that thing. 12:50 You can no longer sell it. 12:51 But the example I'm gonna give you is actually sales hours. 12:52 So if you imagine that you've got ten devs who've sat around doing sod all and 12:55 the thing that's actually limiting you is, you 13:00 don't have enough sales time to feed them. 13:02 So you could be doing the work but you're not. 13:05 The thing that is your resource that is limiting you is your salespeople. 13:06 You haven't got enough of them making enough phone calls. 13:10 So it's not the thing we're selling. 13:12 So we're not selling sales time. 13:13 And you've got to be really honest with yourself and 13:15 ask how much of that thing have you actually got? 13:17 Cuz, I mean, no offense to some of the guys who 13:19 work for me, but they're supposed to be on 36-hour weeks. 13:21 But they don't do 36 hours a week of work. 13:24 You know, productive week might be somewhere close to, say, 20 hours. 13:27 So let's say we've got two sales people in the business. 13:30 They're producing 20 productive hours a week, so we've got 40 sales hours. 13:34 And as I said. 13:37 We're assuming, for the sake of this, that there is unlimited 13:38 resource down here, we're feeding, we're feeding them, it's not a problem. 13:41 The second thing we need to do to find this 13:44 one number is a couple of fairly simple bits of, data, 13:46 this can be projections if you aren't yet a business, 13:50 but your projected income, your projected expenditure, or your income expenditure. 13:53 Looking at this, we can tell one thing hm, profits. 13:57 There is 250 thousand pounds in there somewhere because of 13:59 the fact that we are spending less than we are making. 14:02 Great. 14:04 And what we want to know, is, what's the value add for our critical resource limit. 14:04 So for every hour we're spending on the phone, trying to make 14:09 the sales calls, how much value is that adding to the business. 14:11 And the way you work it out is, quite simply, you've got 52 weeks in the year. 14:15 We divided that by the number of productive sales hours in 14:19 the week, and that gives us 120 pounds per sales hour. 14:21 Bare in mind here, that that assumes no one has any holidays, [LAUGH] 14:24 and you work 52 weeks a year, so I'm just keeping it simple. 14:29 I'm just going to recap on that, because it does get slightly complex. 14:30 The only deal here is, that in our business, 14:34 we are not just making money from selling dev time, 14:37 cuz we've got as much of it, if we could sell a million hours of dev time we could. 14:40 The thing that's stopping us making more money. 14:43 As we cannot get enough sales calls through to feed that dev time. 14:45 So, we've divided our business profits by that 14:49 limitation which has given us 120 pounds an hour. 14:52 Okay. 14:54 Okay, now let's bring it all back to some sanity here. 14:55 How does that fit with what I've been talking about so far? 14:58 Well, quite simply. 15:03 [COUGH] What we can observe are three opportunities. 15:04 If we want to increase that 120 pounds we can do one of 15:09 three things, we can increase the number of sales hours available, lets hire 15:12 someone, more sales people, four more sales people go on lets go get 15:15 them, but obviously we don't know is that a good thing for the business. 15:19 How much is that gonna cost? 15:22 Can we get them? 15:23 Will they be here in a years time? 15:23 Not really sure. 15:24 Increase the costs to the client of thing ultimately being sold, 15:27 the app, the room, the hotel room, the cost of the dinner. 15:30 Whatever it is. 15:33 We can stick that up, and that will mean the effort the sales people are 15:34 putting in are ultimately resulting in more 15:37 money, but is the client gonna like that? 15:38 Are we still gonna be positioned the same in 15:41 the marketplace if we go and stick our costs up? 15:43 Number three is the opportunity that most people like, 15:46 because it essentially preserves the status quo of your business. 15:49 You're not putting your price up, you're 15:53 not introducing any more people into the mix. 15:54 You're just going, you lot, work harder. 15:55 Please, cuz I, I don't want you to be doing 40 productive hours if 15:58 you can do 50 productive hours, I can make some more money in my business. 16:01 I can become more profitable. 16:04 But even when you've observed in, in your business, 16:07 that you've, you've, you've identified a critical point in your 16:11 business, where if you can shift this number, if you 16:13 can make that more efficient, you can make more money. 16:15 You know what to do. 16:17 The chances are, you're actually gonna need more data. 16:18 To inform, which of these is correct. 16:21 You're gonna need data to tell you whether you can afford more sales people. 16:23 You're gonna need data to tell you whether or 16:26 not the client's gonna accept an increase in cost. 16:28 You're gonna need data to tell you whether or not 16:30 the people who are [UNKNOWN] there are already doing it. 16:31 Even remotely have the capacity, the mental capacity, 16:34 the physical capacity to go and do that. 16:37 Essentially, to make themselves more productive. 16:39 And so, if you haven't got that data, you're stuck. 16:44 You've found an amazing business problem. 16:49 You know that it fits from a business point of view, 16:52 and that you should be, as a small business, acting upon it. 16:54 You've observed it and you think my advantage here is that 16:57 I can do the Boyd loop quickly, I found this thing. 17:00 I need to do something about it. 17:02 And you haven't any data to base your decision. 17:04 So, that's kind of where the experiment at storm came in. 17:06 But we realized that, thi-, this was us. 17:09 We, we could do the, the maths and work out what our one number was. 17:11 For us it happens to be the value out per developer hour sold. 17:15 So we are actually adding value onto the actual thing we're selling. 17:18 And what we realized is that if we 17:22 could make our productive developer week slightly more productive 17:24 we don't have to change anything else but 17:28 we make more money which makes me happy obviously. 17:29 I am one of the people with the rolling 17:32 in the money I'm not the gardener, so just, we,we 17:35 embarked upon this experiment with some of the lovely 17:38 people at Storm and basically as I have already identified. 17:41 We wanted to increase our productivity. 17:46 And the way we did that was to, [LAUGH] this 17:48 is very scattergun, and I don't suggest that every business 17:52 does this, but this is the kind of having fun 17:54 while you do it, like, I thought this might be interesting. 17:56 We actually tracked everything. 17:59 Everything. 18:03 So. 18:03 People's steps, they were wearing pedometers, their actions and 18:05 activities around the office, the number of times they went 18:08 to the loo, the number of cups of cups of 18:10 coffee they drank, the number of soft drinks they drank. 18:12 How high were the noise levels at any particular of time of 18:14 day, the light levels, the humidity, we looked at people's perceived mood. 18:16 We looked at their perceived. 18:21 Productivity so we're actually asking how productive they felt. 18:23 We were looking at the loads of our 18:25 other KPIs that the businesswas already looking at. 18:27 Weather conditions, one that got added right at the end by 18:30 I think it was Scott who sat right at the back. 18:34 We are rather unfortunately we, we work in 18:36 the beautiful city of Bath and it is amazing. 18:39 The one thing that's not nice about where we are is the fact that. 18:42 About six feet from our office is one of the most popular busking spots in Bath. 18:45 Now some of the buskers are very talented. 18:51 They can play some great stuff. 18:53 Unfortunately they've only got three songs, and when 18:54 they busk over the course of a year. 18:58 That's a lot of repetition for the people who are working six feet away. 19:02 So, we even actually monitored what people thought of the buskers outside. 19:05 Crazy, I know. 19:10 And [LAUGH] here's what we found out. 19:11 And I'm hoping that by the end of this 19:13 you'll be able to see, I'm gonna, once I've 19:15 shown you what we found out, there's some graphs 19:17 and stuff in here which are a bit amusing. 19:19 I will tie it back into what we actually did in our 19:21 business, to solve the problem of, can we actually make people more productive. 19:24 So, 19:30 the lower the morning light, the more quickly productivity picked up. 19:32 I don't know why that is. 19:37 But when it was kept quite dim in the 19:38 mornings people got in to their groove more quickly. 19:40 And they were telling us they perceived they 19:43 were more productive and indeed we were, we timed 19:44 tracked which I'll show you a bit later on 19:47 and people's productivity did indeed seem to go up. 19:48 When it got darker earlier in the evenings people went to the bugger off earlier. 19:52 Hm, colder days, in general, were accompanied 19:58 by extended periods of above average productivity. 20:00 Whereas very hot days actually had much higher levels of 20:05 productivity, productivity but in a much more condensed period of time. 20:09 And obviously the kind of average temperature days 20:12 seemed to average productivity, which kind of makes sense. 20:14 But again, interesting. 20:18 This was a little bit more scary. 20:20 When you are interrupted by a colleague who 20:21 did need you you felt you were giving value 20:23 back to them, you were 24% more likely to have a cup of tea in the following hour. 20:25 [LAUGH] Even more worrying, if you, if they didn't need 20:29 you, you were 40% more likely to have a pee. 20:33 [BLANK_AUDIO] 20:37 Which obviously is kind of annoying for, for a majority of people. 20:41 This is one that I've taken to heart. 20:46 When it was raining, people were buying more stuff. 20:48 So this is a side note and there are any devs in here who want to make me, help 20:52 me make this which is a weather powered safety deposit 20:55 box I'm very up for talking to you later on. 20:57 Cuz I'm going to be locking that credit card away on days that it is raining. 21:00 We found the people's tolerance was about one 21:04 phone call before they felt they are being interrupted. 21:07 One phone call in the space of a 21:10 couple hours they didn't mind answering that was okay. 21:11 But as soon as it was over that people started registering. 21:14 They felt disrupted and their productivity did indeed drop. 21:17 And we found out we were losing, on average, around 21:19 an hour of productivity for the second and ongoing phone calls. 21:21 On to the interesting stuff. 21:26 This here is a graph of a a particular day 21:27 where [COUGH] I'm going to tell you about productivity and coffee. 21:29 You might be thinking that kind of makes sense. 21:34 We've got a. 21:35 People pick up their productivity and kind of peak in the morning 21:36 then there is lunch so clearly not so productive, then in the afternoon 21:38 you kind of ramp up a bit again, not quite as high as 21:41 you were before, before tailing off because hell it is nearly home time. 21:44 I'm, I'm gonna kind of throw this open now but, we split, we split the class into the 21:47 greens and the yellows and both of these drank 21:53 different their drinking habits were different in terms of coffee. 21:56 So the the yellows drank more than two cups of 22:01 coffee two or more, sorry, cups of coffee before 9 a.m. 22:06 On average. 22:09 And the greens were one or none. 22:10 Can anybody, would anybody like to speculate 22:14 why those who drank more coffee earlier on. 22:16 Ended up losing productivity by kind of mid-morning. 22:20 They were peeing, you're right [LAUGH]. 22:24 This is the toilet break, the first recorded toilet break 22:26 on average for the yellows, whereas the greens were up here. 22:29 Now you'll notice that, that the climb in 22:31 productivity for both is actually very similar, but. 22:32 The, the because of the fact the yellow started 22:36 early essentially, gave themselves, they were getting out of sync. 22:38 Here we go, Buskers versus Mood. 22:43 Now, the first half of this graph so, 22:44 we've, we've got good buskers and good mood. 22:45 So, that's kind of, it ki-, th-, this has by the way 22:48 been smoothed slightly and it is over the course of a month. 22:50 But, this is in general, quite nice. 22:53 You know, the better the busker, the better the 22:55 mood, the worse the busker the worse the mood. 22:56 Only once, we get down to the pretty awful buskers. 22:58 All of a sudden, people are happy again. 23:01 Again, I'm, I'm very happy to throw open to any suggestions. 23:05 Dan. 23:08 >> Headphones. 23:08 >> Headphones. 23:09 You are correct. 23:10 That is exactly what it was. 23:10 This is the point in which people go, sort of that, 23:12 and stick their headphones on, and so they are happy again. 23:14 I like this one. 23:19 This is actually one person on one day 23:19 but again it just illustrates the amusement I had. 23:22 This is their contentment, how contented they felt over 23:25 the period of the day massive dip around, around 12,12:30. 23:28 This is a, a graph [LAUGH] of another member of staff and its 23:34 actually the frequency of time they got up and went away from their desk. 23:38 And there were a couple of events that happened very close to each other. 23:43 Event one was by the person who got up, saying, I had to break to chat to 23:46 John, feeling content, calm, funny, and jokey, whereas 23:50 John won't stop interrupting me, feeling annoyed, frustrated, interrupted. 23:52 I like this one. 23:59 This one is two weeks worth of productivity across the 24:01 company, and you'll notice there are some spikes in there. 24:03 And there's actually something, there's actually I have a theory 24:05 about this which I'm going to tell you in a moment. 24:07 This was the day that was Scott's birthday so cake was brought in. 24:10 Hm. 24:14 On this day, Andrew brought his dog into work and everyone was very amused. 24:14 Liam won some. 24:18 Quality streaks on this day. 24:20 I will genuinely give a prize to anyone who knows 24:22 or can think of what happened on this particular day. 24:25 Borrowing people who may well have been in the office. 24:28 That might of caused some mirth on that day. 24:31 It was the day that a Bath bus came around the corner and 24:34 took out nine bollards in a row because it completely missed the corner. 24:38 So why are we more productive on these days? 24:42 And you know, you kind of have to hypothesize. 24:44 My, my personal opinion is that that's to do with productivity sync. 24:46 If you have events that happen at a particular time, they kind 24:50 of chop everybody's day but then get them back into sync thereafter. 24:53 Because our guys don't actually start the day at the same time. 24:57 We, we, we kind of do the tech company 24:59 flexible thing of yeah, you know, as long as 25:00 you're in by ten and you work the right 25:02 number of hours, and we're measuring output, not input. 25:04 That's all lovely, but genuinely, getting people's attention synced up seems 25:06 to be a repeating factor in the data we were looking at. 25:12 So I'm gonna actually tell you a few of the results now, because 25:15 I could go on with funny data for,for for a very long time. 25:17 But here are some things we've actually genuinely done. 25:21 We've started stand-up meetings at a very set time 25:23 in order to bring people's productivity back into sync. 25:26 So every, we've got one at 11 o'clock, we're 25:30 gonna start doing one in the afternoons as well. 25:32 The idea being that it kind of syncs people up 25:34 into relatively nice chunks, so that you kind of just. 25:36 Stop. 25:39 Hello, everybody good. 25:39 Back to work. 25:41 But it gives you a short mental break. 25:41 And we are going to encourage teams to start working at the same time. 25:44 That's not everybody in the company has to be in there in a particular time. 25:46 But, if you work in a particular group. 25:49 As we've got our designers that often work closely 25:51 with the front end devs and the back end devs. 25:53 We're trying to get people to kind of look at 25:56 their colleagues and go, I shouldn't come in at seven 25:58 if you're going to come in at ten because our 26:00 working day is going to be completely off the clock. 26:02 We've changed the way our phone systems ring in hunt groups. 26:05 So we're actually making sure that people who are, who, who 26:08 are more susceptible to being interrupted already, get interrupted again, basically. 26:10 And also, we're gonna try and do something very clever where if 26:14 somebody's phone's been rung once It won't ring again quite so soon afterwards. 26:16 We're turning off the lights in the morning. 26:22 We're only turning on a couple. 26:23 Where as it used to be, first one in, all 26:24 the lights on, you know, literally fire the place up. 26:26 We're, we're not doing that anymore. 26:29 We're leaving it dim. 26:30 Just because of the fact that it appears that people get more into their 26:31 productive zone when the lights can get turned on as and when people want them. 26:34 We're even we were, by the way, just a tiny thing. 26:38 We moved office a couple of months ago, which means we've been 26:40 very lucky that we actually have been able to do something about this. 26:43 So when we have our new heating system put 26:46 into the, the new office, we had some wires and 26:48 stuff so that they all hook up and we 26:51 can set them and start to do some clever things. 26:52 Which wasn't in the old office. 26:54 So But we are, we're trying a 26:56 bunch of different heating settings, including having. 26:58 Different settings at the office which are warmer and cooler. 27:00 Depending on whether you think alright, I need to get a bunch of work done. 27:02 I'm gonna go to a quiet space that's nice and warm. 27:04 Or we're giving it a go. 27:07 We don't know. 27:08 It might turn out that it's complete and utter rubbish 27:09 and it means nothing, but we're gonna give a go. 27:11 We're gonna collect the data. 27:13 Oh, that's a good idea. 27:15 We've created no interruption zones around the office so 27:16 you basically,again the new office has got enough rooms that 27:18 we were able to kind of go, we'll have 27:21 those two or three rooms where we'll just stick her. 27:23 On the door, and hopefully won't get up and get too distracted. 27:25 We've put, I've called them, busker-neutralizing stereos, 27:29 this isn't a thing you can buy. 27:31 You can't kind of go into Curry's and go, One busker-neutralizing stereo please. 27:33 This is a, this is a standard stereo, you know, a normal one which happens 27:36 to be turned up to the volume at which you can no longer hear the buskers. 27:40 So they're now in the offices say that when we get down to the really annoying. 27:43 You can kind of turn them up a bit. 27:47 We've started recording emotions, cuz this is not something we'd ever done before. 27:49 We, we'd never recorded what people were feeling in the company before. 27:53 And you know, I, I didn't even think people 27:56 were gonna be very forthcoming with how they're feeling. 27:58 But oh no, people love to tell you how they're feeling. 28:00 I'm gonna show you some of the funny things. 28:04 This is gonna be, this is the bit where there might 28:05 be a small live demo, and our first potential gawk up. 28:07 Bear with me. 28:10 We use a system called Minim, which is something we wrote. 28:11 Contrast is awful here, but basically it is a standard time tracker, so 28:16 I'm doing a forward talk, but you know what I'm finding it annoying. 28:20 So, I am, I'm just, I am not tagging it, if there was a hash tag there. 28:22 Okay. 28:29 Have I got annoying in there? 28:30 I think 28:32 I 28:34 should have got annoying. 28:38 [SOUND] On any particular project, so we can just call this FOWA. 28:39 And how long have I been doing it for? 28:45 Thirteen minutes, its not billable, I'm gonna log it. 28:47 The point being that we're encouraging people to put meta data into their 28:50 time tracking so annoyed interrupted phone call, 28:53 toilet break, whatever the hell they want. 28:58 with, with the results being that we can actually go and look at that data by tag. 29:00 So if I go into the you see annoyed, that's what it should be. 29:03 This is dummy I did ask the guys to go back 29:07 and edit some of their previous time entries to be annoyed. 29:10 So our company isn't actually as annoyed as you're about to think it might be. 29:14 But I've asked them to do this. 29:17 So we are able to go and actually have a look and say well 29:18 I can see when people are being most annoyed over a particular period of time. 29:20 I can see that the most recent activity for when 29:24 people have been annoyed, the projects on which they've been. 29:26 Most annoyed, the top contributors to the tag annoyed. 29:29 Whether or not that annoying time was billable or not. 29:32 And I can even go into actually explore data, so if I go back a week. 29:35 This weeks' probably not the best. 29:40 I can go, well, show me for example. 29:42 I wanna find out of that where Liam was annoyed particularly. 29:44 And it was showing me, well, Liam was mainly 29:47 annoyed just on the 17th of October, and I can 29:49 go back and find out what Liam was doing on 29:51 the 17th of October, and why he was particularly annoyed. 29:52 Now, we had already been using this system for our own general 29:54 tracking of what we're doing, what we're up to, and exploring the data. 29:57 Cuz we like data. 30:00 We hadn't been asking people to genuinely go for it. 30:01 And tell us when they were annoyed. 30:04 When they're pissed off. 30:05 When they were cold. 30:06 When they were tired. 30:07 When they had, you know, been kept up late by the baby. 30:08 Whatever. 30:10 And so we've actually started to ask people to 30:10 record their genuine emotions within the within the time tracking. 30:12 Because of the fact that, that it, it, it gives a 30:17 whole nother layer to To what people have been up to. 30:19 Now, you're about to see why it's important 30:23 to actually record the words alongside the data. 30:25 And we, we are kind of coming to a close now. 30:29 And I'm, there, there's gonna be a a few funny bits in here. 30:31 But first I'm gonna tell you the net result, which is the. 30:36 We haven't calculated this exactly. 30:39 But, and, and keep in mind that 30:42 we were looking at people's perceived productivity. 30:43 But combining the perceived productivity with some of 30:45 the data we got off our time tracker. 30:47 We're nearly up 10% productivity. 30:49 Nearly. 30:52 Which is pretty phenomenal, given. 30:53 All we've done is things like turn the lights off slightly later, 30:55 have an extra meeting where we stand up for a few minutes. 30:57 We've done very, very simple, micro things with our 31:00 business that have ended up making us way more profitable. 31:03 So, this is the, this is the any comment field, which I think was. 31:06 Respectively the best thing we added to our, our data collection and let's just 31:10 say the guys and girls at Storm have been abusing it quite, quite rampantly. 31:14 And I have not put all of them in, cuz of some them are a bit amusing 31:19 but anyway, this is why it's important to 31:22 record the words as well as the actual data. 31:23 This was a general comment, 11:30, fucking cold. 31:26 But later on don't worry, at 12:15, less 31:30 cold, have jumper, not sure who it belongs to. 31:32 Emotions, annoyed, frustrated. 31:37 Now if I were to ask you in a, in a web dev environment 31:39 reasons why you thought that this might 31:41 be recorded, you might be thinking, annoying client. 31:43 Bug which I couldn't fix. 31:47 Oh no. 31:48 Walked into Gladdy's bike and now my shin hurts. 31:49 Hm. 31:53 A general comment and this baffles me. 31:54 And frankly scares me slightly. 31:56 It's raining which means I'll get soaked on the way home and I like that. 31:58 Also get a shower when walking from the gym. 32:00 I like that too. 32:02 Multitasking. 32:03 >> [LAUGH] >> Who are we employing? 32:04 [LAUGH] Productivity basically unproductive. 32:06 Now this is probably a little bit more like the kind of 32:11 actual thing that people would be doing in a, in a dev shop. 32:13 Which was a, you know, it was great until 32:15 it ended on both feed backs and then whoops. 32:17 But nevertheless, [LAUGH] that, that shows that it 32:19 wasn't someone being unproductive because they were interrupted. 32:21 We actually know why. 32:23 A general comment at three o'clock. 32:25 Liam won't shut up. 32:26 General comment at 4:30, one hour 30 minutes later, Liam still chatting balls. 32:28 >> [LAUGH]. 32:34 >> Hm, Liam. 32:36 Emotions, excited, sense of achievement. 32:39 Now this is actually my favorite and genuinely makes 32:40 me think, what the hell is going on here. 32:43 But again,applying your brain. 32:45 Maybe we've had a, a particular win. 32:48 We, we've you know, won a new client, we've 32:49 delivered a little bit work ,something amazing's happened you know. 32:51 I'm feeling excited and I have a sense of achievement. 32:53 Because I'm back from home base baby, yeah. 32:56 [LAUGH] So that, that kind of is I'm gonna round up, like I 33:03 said I could go on with more stats, but I wanna leave some time 33:07 for questions and so I'm going to give you a few take away 33:10 tips uh,and hopefully you can remember back to the start of the, the talk. 33:12 Make sure that you've got the time, as well 33:17 as the ability to be observant with your new business. 33:19 Just, just tracking the data means nothing if you 33:22 haven't got the time to, to do anything with it. 33:24 You've got to leave yourself some time in business to do that. 33:26 And make sure that you're in a position 33:29 to quickly react when the opportunity has been observed. 33:30 Which kind of comes back to the time thing, but it also is, is one of process. 33:33 Not something that we have internally, but I know a company that has levels. 33:38 So an issue comes in, and they will. 33:41 Whoever gets it is, is told to make their best judgement on what level issue it is. 33:43 So on level 1 issue needs to go to management a level 2 issue can be dealt 33:48 with your general staff a level 3 issue is 33:51 something that can be handled by an admin staff. 33:54 It's quite simple they've got a simple process that means that when something 33:58 comes in it gets dealt with, there's a bit of a process there. 34:01 For quick wins you can focus on something very specific. 34:04 You don't have to go looking for 34:07 opportunities and hoping you stumble across them. 34:08 You can do things as simple as trying 34:10 to find the weakness points within your business i.e. 34:13 That point that when you run out of 34:16 something you no longer make any extra money. 34:17 So, you can find those and that's a quick win because you can go and 34:19 focus on it, collect some data around that and try and say I'm trying to improve. 34:23 Productivity of this type of person within my business, how can I do that? 34:27 And finally, you, you can have a bit of 34:31 fun while you're doing it, like we did and it, 34:32 it generally will give you sometimes a quite disturbing, 34:35 but nevertheless insight into the people who work for you. 34:37 So I hope you've enjoyed hearing a little bit about what we've been doing. 34:41 I'd be delighted to answer some of your questions about just our 34:43 general tracking experience, what we did, how we did it, or anything else. 34:46 Alternatively you are, of course, more than welcome to 34:51 find me and,and catch up with me during the breaks. 34:53 But for now thank you very much indeed. 34:56 [SOUND] 34:58
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