1 00:00:08,850 --> 00:00:11,970 Welcome to the APM podcast. APM is the chartered body for 2 00:00:11,980 --> 00:00:14,800 the project profession. My name is Emma De Vita and I'm 3 00:00:14,810 --> 00:00:17,180 the editor of Project at OPM's Quarterly Journal. 4 00:00:17,190 --> 00:00:20,760 And your Host and this podcast. I'm speaking to three project 5 00:00:20,770 --> 00:00:22,810 professionals with a deep interest in artificial 6 00:00:22,820 --> 00:00:25,900 intelligence to consider what impact this technology is having 7 00:00:25,910 --> 00:00:28,600 right now on projects, what it might hold for the future, and 8 00:00:28,610 --> 00:00:31,360 what project managers should be doing to adapt to this brave new 9 00:00:31,370 --> 00:00:33,180 world. I'm delighted to have with me 10 00:00:33,190 --> 00:00:36,180 today Professor Antonio Nieto Rodriguez, Founder of the 11 00:00:36,190 --> 00:00:38,960 Strategy Implementation Institute and author of the 12 00:00:38,970 --> 00:00:42,130 Harvard Business Review Project Management Handbook, James 13 00:00:42,140 --> 00:00:45,430 Garner, Global Head of Data and Intelligence at Gleed and Chair 14 00:00:45,440 --> 00:00:49,330 of the Project Data Analytics Task Force and Martin Paver, CEO 15 00:00:49,340 --> 00:00:51,330 of Consultancy Projecting Success. 16 00:00:52,150 --> 00:00:55,720 The Autumn 2023 issue of APM's Project Journal also covers this 17 00:00:55,730 --> 00:00:58,720 topic, so please do make sure you grab a copy. 18 00:01:02,540 --> 00:01:05,069 Welcome everyone. I just wanted to thank you for 19 00:01:05,080 --> 00:01:06,710 joining me today. I'm really looking forward to 20 00:01:06,720 --> 00:01:10,490 our discussion on AI and its impacts on the world of 21 00:01:10,500 --> 00:01:12,830 projects. I think a good place to start 22 00:01:12,840 --> 00:01:16,490 would be for each of you to just tell us a little bit about 23 00:01:16,500 --> 00:01:22,610 yourself and what fuels your interest in AI, or even better, 24 00:01:22,620 --> 00:01:26,380 what gets you excited about it. So, Sherrie, begin with you, 25 00:01:26,390 --> 00:01:31,250 Antonio. Well, myself, I'm, I'm, I'm 26 00:01:31,260 --> 00:01:34,950 coming more from the PMI world. I was the chairman of PMI a few 27 00:01:34,960 --> 00:01:37,860 years ago I launched the Brightline initiative. 28 00:01:37,940 --> 00:01:40,850 My my goal is always to close the gap between the senior 29 00:01:40,860 --> 00:01:43,650 leaders, the business, the strategies and projects and 30 00:01:43,660 --> 00:01:46,650 project management. So I'm a practitioner as well. 31 00:01:46,660 --> 00:01:50,520 I'm I'm part of a big sustainability transformation in 32 00:01:50,530 --> 00:01:54,530 a corporate in the pharma sector, but also an academic. 33 00:01:54,540 --> 00:01:56,210 I like to research. I publish. 34 00:01:56,220 --> 00:01:59,410 I published several books, one of them with Harvard Business 35 00:01:59,420 --> 00:02:03,530 Review, which has been my my goal because that's the way to 36 00:02:03,540 --> 00:02:08,070 switch the people mindset around projects and project management 37 00:02:08,080 --> 00:02:11,090 to appreciate it. And what drives me on a I what 38 00:02:11,100 --> 00:02:15,400 makes me excited is something that is in my mind, it's around 39 00:02:15,410 --> 00:02:17,730 delivering more value. I think there's very few 40 00:02:17,740 --> 00:02:22,850 professions that are challenged about their success rates. 41 00:02:23,440 --> 00:02:27,500 If you look any research around project management, 60 to 70% of 42 00:02:27,510 --> 00:02:32,070 the project fails and and you can challenge that but that's 43 00:02:32,080 --> 00:02:36,190 not acceptable. So we're we're wasting value 44 00:02:36,240 --> 00:02:42,110 money impact and I think AI is a unique opportunity to close that 45 00:02:42,120 --> 00:02:45,270 gap to say OK, out of 10 projects we deliver 8 46 00:02:45,280 --> 00:02:48,310 successfully and we are here like a. 47 00:02:48,470 --> 00:02:52,560 Some some that we we can bring value fast for, for 48 00:02:52,570 --> 00:02:54,980 organisation. So that's for me the biggest, 49 00:02:54,990 --> 00:02:58,740 biggest driver on ICE, increased success rate of this profession 50 00:02:58,750 --> 00:03:01,160 that we love so much. OK. 51 00:03:01,170 --> 00:03:04,990 Thank you and Martin. So in terms of me personally, 52 00:03:05,000 --> 00:03:08,910 I've been a project professional for about 30 years, so I'm a 53 00:03:08,920 --> 00:03:13,380 fellow of the APM and back in about 2014, fifteen I started to 54 00:03:13,390 --> 00:03:15,430 look into things like lessons learned. 55 00:03:15,440 --> 00:03:18,930 I pulled together about 20,000 lessons learned and from that I 56 00:03:18,940 --> 00:03:21,390 realised that we're not learning from those lessons, we're just 57 00:03:21,400 --> 00:03:23,270 repeating the same things time and time again. 58 00:03:23,520 --> 00:03:27,810 So what I try to do is to apply advanced data analytics to that 59 00:03:27,880 --> 00:03:30,170 and I realised that it's the wrong journey. 60 00:03:30,360 --> 00:03:32,930 So we're not collecting the right evidence at the moment. 61 00:03:33,840 --> 00:03:36,710 So we can start to use those techniques and really start to 62 00:03:36,720 --> 00:03:39,930 drive it. So back in 2017 and then set up 63 00:03:39,940 --> 00:03:42,410 the project data analytics community that's grown to over 64 00:03:42,420 --> 00:03:45,190 10,000 people and I start to run hackathons, et cetera. 65 00:03:45,300 --> 00:03:49,150 So for me personally, I see this is the way of leveraging that 66 00:03:49,160 --> 00:03:52,230 vast experience that we've got as professionals that it's all 67 00:03:52,240 --> 00:03:55,730 codified in data. So back to Antonio's part about, 68 00:03:55,740 --> 00:03:58,330 you know, we're not doing good enough at the moment as a 69 00:03:58,380 --> 00:04:00,230 profession. We could do a lot better. 70 00:04:00,300 --> 00:04:02,600 It's for me, data is right at the heart of that. 71 00:04:02,830 --> 00:04:06,470 So I don't see this as a tweak. I see it as a transformation. 72 00:04:06,540 --> 00:04:08,130 It's a completely different way of thinking. 73 00:04:09,420 --> 00:04:12,280 How about you, James? Where does your interest in AI 74 00:04:12,290 --> 00:04:15,530 stem from? Eastern I've been interested in 75 00:04:15,680 --> 00:04:18,850 from the very beginning of my my journey Even back at university 76 00:04:18,860 --> 00:04:22,210 I was looking at sort of digitization in the construction 77 00:04:22,220 --> 00:04:26,850 industry back in sort of 2000 or even before then with this 78 00:04:26,920 --> 00:04:31,100 overwhelming kind of needs to to understand that there must be a 79 00:04:31,110 --> 00:04:33,150 better way of doing things. That's really where it comes 80 00:04:33,160 --> 00:04:34,930 from. Comparing ourselves to other 81 00:04:34,940 --> 00:04:38,130 industries and thinking, you know, the way we do these things 82 00:04:38,140 --> 00:04:42,410 just inherently seems so inefficient and a lot of that 83 00:04:42,420 --> 00:04:44,630 was because of the very nature of the industry. 84 00:04:44,640 --> 00:04:48,120 But the as Antonio races, we have this unique opportunity 85 00:04:48,130 --> 00:04:51,390 right now in that the the technology has kind of finally 86 00:04:51,400 --> 00:04:54,790 caught up with our aspirations in terms of what we can do. 87 00:04:54,940 --> 00:04:58,600 And we we need to grasp it So we'll talk about it I'm sure 88 00:04:58,610 --> 00:05:00,860 later in the podcast this kind of balance between the 89 00:05:00,870 --> 00:05:04,310 opportunities and the risks and and we've got this very very 90 00:05:04,320 --> 00:05:09,010 small window of opportunity to make this a I work for the 91 00:05:09,020 --> 00:05:12,880 profession rather than for for other interested parties. 92 00:05:13,140 --> 00:05:16,490 I guess my other kind of inspiration is other people have 93 00:05:16,500 --> 00:05:19,510 inspired me and you know Martin was one of the people who really 94 00:05:19,520 --> 00:05:22,350 put me on this journey and really inspired me to to follow 95 00:05:22,360 --> 00:05:25,510 this follow my passion. I I I come from a QS background. 96 00:05:25,580 --> 00:05:29,350 You know, there's so many people in this field who are really 97 00:05:29,400 --> 00:05:32,290 passionate about this that there's there's great hope for 98 00:05:32,300 --> 00:05:33,670 the future. We can all sort of come. 99 00:05:33,740 --> 00:05:36,960 Given to to make it work for the better of the profession, 100 00:05:38,770 --> 00:05:42,320 there's been a lot of hype around AI should really be 101 00:05:42,330 --> 00:05:44,620 listening to the people are saying this is the end of 102 00:05:44,630 --> 00:05:48,180 humanity and no one's gonna have a job or should we be feeling 103 00:05:48,190 --> 00:05:51,180 excited about it. Probably like to put that to you 104 00:05:51,230 --> 00:05:55,420 too, Antonio first. The question of whether it's a 105 00:05:55,430 --> 00:05:59,180 hype or not, I don't think so. It's a reality and people like 106 00:05:59,250 --> 00:06:02,820 Martin has been working on this space way before many people 107 00:06:02,830 --> 00:06:07,220 started to even think about it. So I think it's not a hype, it's 108 00:06:07,230 --> 00:06:09,060 a reality. It's happening. 109 00:06:09,210 --> 00:06:12,860 And I think in the profession we have not embraced very quickly 110 00:06:12,870 --> 00:06:16,160 new disruptions. We kind of always very cautious. 111 00:06:16,170 --> 00:06:19,080 We we talk about change, but we're not quick at adapting to 112 00:06:19,090 --> 00:06:21,940 change. And this is an opportunity where 113 00:06:21,950 --> 00:06:25,140 we can drive, we can embrace these changes. 114 00:06:25,150 --> 00:06:28,460 The fact that there will be parts of our work that are 115 00:06:28,470 --> 00:06:33,080 automated, it's a blessing for I think for anyone that wants to 116 00:06:33,090 --> 00:06:36,700 develop. More executive kind of career. 117 00:06:36,910 --> 00:06:40,360 If you want to stick to your spreadsheets and your dashboards 118 00:06:40,370 --> 00:06:44,260 and and just chasing people. Yeah, your job is at stake for 119 00:06:44,270 --> 00:06:47,260 sure because you are not adding very much value. 120 00:06:47,410 --> 00:06:49,240 I don't know. I've been working in PMO's 121 00:06:49,250 --> 00:06:53,060 project management for 25 years. I can't wait to automate all the 122 00:06:53,170 --> 00:06:57,700 the the 50% of our work that we do and PMO it's 80%. 123 00:06:57,710 --> 00:07:01,400 So bring it tomorrow and and let's embrace it, right and and 124 00:07:01,410 --> 00:07:04,920 let's start focusing on on where we can bring more value, which 125 00:07:04,930 --> 00:07:09,160 is that alignment, stakeholder engagement, team kind of 126 00:07:09,170 --> 00:07:12,640 engagement and commitment where I think that's what in the end 127 00:07:12,650 --> 00:07:15,500 what Martin? Was saying we know why projects 128 00:07:15,510 --> 00:07:18,060 fail. I hate when people ask me what 129 00:07:18,070 --> 00:07:20,340 you need to do for a project to be successful. 130 00:07:20,350 --> 00:07:23,050 We know that it's everybody knows that people even that 131 00:07:23,060 --> 00:07:25,140 don't know projects know why projects fail. 132 00:07:25,150 --> 00:07:30,660 So we have an opportunity to use technology and AI to get those 133 00:07:30,670 --> 00:07:35,180 things out of the way and focus on those important matters which 134 00:07:35,190 --> 00:07:38,330 I cannot solve, which is the cultural aspect, the 135 00:07:38,340 --> 00:07:41,360 organisational aspects, the leadership aspects. 136 00:07:41,450 --> 00:07:44,580 So there will be change definitely in the skills that we 137 00:07:44,590 --> 00:07:49,140 need to build up, but I see it as a huge opportunity, exciting 138 00:07:49,230 --> 00:07:53,740 time for for our profession. Is there anything that concerns 139 00:07:53,750 --> 00:07:57,080 you that needs to be thought about and dealt with and planned 140 00:07:57,090 --> 00:08:00,490 for right now? I think there's concerns of 141 00:08:00,500 --> 00:08:02,510 course, but they're really far off. 142 00:08:02,560 --> 00:08:05,840 I think the project management profession, these are there's 143 00:08:05,850 --> 00:08:09,310 something bad around, yeah, we cannot influence this. 144 00:08:09,380 --> 00:08:12,790 I think what concerns me is that we don't take action. 145 00:08:12,880 --> 00:08:18,290 And when I see chaps, GDP and some other of these AI early 146 00:08:18,300 --> 00:08:21,530 developments, I questioned the role of the project manager. 147 00:08:21,700 --> 00:08:25,850 I could see self-driving projects if we don't step up. 148 00:08:26,040 --> 00:08:29,250 So I think it's more the concerns is more that the 149 00:08:29,260 --> 00:08:32,510 profession and the can be extremely disrupted that 150 00:08:32,520 --> 00:08:36,100 somebody else can start doing our job because they've embraced 151 00:08:36,110 --> 00:08:38,370 AI. So that is the immediate. 152 00:08:38,570 --> 00:08:42,370 Is that how can we move fast so that we take that spot, which is 153 00:08:42,380 --> 00:08:45,620 the integration of product managers, agile project 154 00:08:45,630 --> 00:08:49,120 management, change management, which if we don't step up, 155 00:08:49,130 --> 00:08:51,280 somebody else will do very quickly. 156 00:08:51,340 --> 00:08:54,560 And that's what worries me. The bigger picture of course, 157 00:08:54,570 --> 00:08:56,960 but I just don't know these fears. 158 00:08:56,970 --> 00:08:59,780 I'm very far off. Entirely agree. 159 00:08:59,790 --> 00:09:02,160 I mean, and the question about hype, I mean the Garden, the 160 00:09:02,170 --> 00:09:05,200 height cycle refers to where we are, this peak of inflated 161 00:09:05,210 --> 00:09:08,500 expectations right now, thinking it's going to, you know, change 162 00:09:08,510 --> 00:09:11,040 everything. And then you go through what's 163 00:09:11,050 --> 00:09:13,050 called the through of disillusionment and that there 164 00:09:13,060 --> 00:09:15,620 will be this kind of period coming up where ohh OK, it 165 00:09:15,630 --> 00:09:18,400 didn't totally change the world, but that doesn't mean the hype 166 00:09:18,410 --> 00:09:20,200 is not there. And actually we will go on this 167 00:09:20,210 --> 00:09:21,910 journey towards what's called a jive. 168 00:09:21,920 --> 00:09:25,220 It's artificial general intelligence and some people 169 00:09:25,230 --> 00:09:27,540 think it's 30 years away, some people think it's 100 years 170 00:09:27,550 --> 00:09:28,980 away, but we will get there eventually. 171 00:09:28,990 --> 00:09:31,930 So we're on the journey. Towards that reality. 172 00:09:31,990 --> 00:09:34,650 So it's not hyper in that sense, but sometimes I think maybe 173 00:09:34,660 --> 00:09:37,410 people think where the technology is right now and they 174 00:09:37,420 --> 00:09:40,370 get disappointed when it can't do these incredible things at 175 00:09:40,380 --> 00:09:44,590 this moment in time that some people predicting that there 176 00:09:44,600 --> 00:09:46,630 shouldn't lose faith. You know that it's only a matter 177 00:09:46,640 --> 00:09:49,670 of time it keeps improving the the improvement is huge. 178 00:09:49,720 --> 00:09:52,750 But I agree with what Antonio says in terms of and this goes 179 00:09:52,760 --> 00:09:55,000 back to what we said at the introduction, You know, we have 180 00:09:55,010 --> 00:09:59,530 this opportunity and if we don't carve this technology for 181 00:09:59,540 --> 00:10:02,880 ourselves and make it work. Of ourselves and control the 182 00:10:02,890 --> 00:10:06,540 data, then we risk giving it away or given away control of 183 00:10:06,550 --> 00:10:09,660 our industry to other people and other third parties who may not 184 00:10:09,670 --> 00:10:12,360 have the best interests of the industry at heart. 185 00:10:12,450 --> 00:10:15,580 And that's why we're, I think three of us are pushing so hard 186 00:10:15,590 --> 00:10:18,040 to say, look, this isn't something to be afraid of. 187 00:10:18,210 --> 00:10:20,680 Yes, the hype is something that is going to change your 188 00:10:20,690 --> 00:10:22,130 workflows. It's going to change the way you 189 00:10:22,140 --> 00:10:24,120 do think. But embrace it, because the 190 00:10:24,130 --> 00:10:27,280 other option is we start giving away control slowly but surely 191 00:10:27,290 --> 00:10:29,920 to third parties. Which third parties are you 192 00:10:29,930 --> 00:10:32,780 talking about? It effectively third party 193 00:10:32,830 --> 00:10:36,680 vendors or software companies. So it it it could be small 194 00:10:36,690 --> 00:10:39,020 startups, it could be the big giants, you know the Googles, 195 00:10:39,030 --> 00:10:42,140 the Amazons, the Autodesk. In this world, you know you can 196 00:10:42,150 --> 00:10:46,480 see a future very clearly if we don't intervene and and protect 197 00:10:46,490 --> 00:10:49,760 our industry where we we slowly but surely have that kind of 198 00:10:49,830 --> 00:10:51,680 Netflix moment. I suppose is the best way of 199 00:10:51,690 --> 00:10:54,390 describing it where, you know before we know it clients are 200 00:10:54,400 --> 00:10:56,440 paying subscription something and not using project 201 00:10:56,450 --> 00:10:59,270 professionals. OK, Thanks Martin. 202 00:10:59,280 --> 00:11:01,570 What are your thoughts? Love to hear what you think 203 00:11:01,580 --> 00:11:04,390 about all of this. So it's back to that point 204 00:11:04,400 --> 00:11:08,070 really about, you know, is this an an apocalypse, You know is it 205 00:11:08,080 --> 00:11:09,010 going to be the end of the world? 206 00:11:09,020 --> 00:11:11,530 And I think we've got separate out, you know, what's the impact 207 00:11:11,540 --> 00:11:14,110 of this on future wars and all that sort of stuff. 208 00:11:14,120 --> 00:11:15,790 Like that's an issue for the state. 209 00:11:15,800 --> 00:11:18,330 It's not something I can control as a project professional. 210 00:11:18,340 --> 00:11:20,270 So I bring it back to project delivery. 211 00:11:20,340 --> 00:11:23,380 Is this an existential threat to our profession? 212 00:11:23,420 --> 00:11:26,110 And personally I think it is. If we don't respond to this, 213 00:11:26,220 --> 00:11:28,270 others will. And these data people start to 214 00:11:28,280 --> 00:11:30,330 come into our jobs and start to automate a lot of it. 215 00:11:30,380 --> 00:11:32,970 So it's a case of moving ourselves up the value chain, 216 00:11:33,040 --> 00:11:35,350 and it's not just. Artificial intelligence. 217 00:11:35,460 --> 00:11:38,750 So something I like to say is if you can describe something in 218 00:11:38,760 --> 00:11:41,450 logic, you can probably code it. So if you can code it using 219 00:11:41,460 --> 00:11:44,350 Python And various other tools, then you can do that fairly 220 00:11:44,360 --> 00:11:46,350 simplistically and fairly cheaply. 221 00:11:46,400 --> 00:11:49,410 A lot of that is available today that just put it into Microsoft 222 00:11:49,420 --> 00:11:51,430 XLS well. So you can now code in Python as 223 00:11:51,440 --> 00:11:54,330 part of Excel. If it's more intuition based 224 00:11:54,340 --> 00:11:57,270 than what you need to do is to grow the data set so you can 225 00:11:57,280 --> 00:12:00,070 look at the patterns in the data so you can extract some of that 226 00:12:00,080 --> 00:12:01,970 intuition. And that's when it starts to get 227 00:12:01,980 --> 00:12:03,710 a bit magical, right? And that's when we start to get 228 00:12:03,720 --> 00:12:05,400 some really cool insights coming out of it. 229 00:12:05,520 --> 00:12:07,860 If we layer on top of that, things like the large language 230 00:12:07,870 --> 00:12:10,610 models, so it's not just ChatGPT, there's larger and 231 00:12:10,620 --> 00:12:13,490 various other ones out there. So what we can do now we can 232 00:12:13,500 --> 00:12:16,580 take a model that's being, say, trained on English and then 233 00:12:16,590 --> 00:12:18,500 teach it to speak with a Yorkshire accent. 234 00:12:18,510 --> 00:12:21,580 But it's that sort of approach. So what we're doing at the 235 00:12:21,590 --> 00:12:23,980 moment. So I've got a call tomorrow with 236 00:12:23,990 --> 00:12:26,300 Adrian Dooley who created the practise framework. 237 00:12:26,310 --> 00:12:29,410 So instead of having a body of knowledge or a book, it's now 238 00:12:29,420 --> 00:12:30,880 online. So Adrian's taking it all 239 00:12:30,890 --> 00:12:33,220 online, There's templates and there's various collateral on 240 00:12:33,230 --> 00:12:35,880 there if we can now train a model on all of that. 241 00:12:36,200 --> 00:12:40,230 And then train it on all of the National Audit Office reports, 242 00:12:40,600 --> 00:12:43,670 the GAO reports in the US etcetera, We start to get a 243 00:12:43,680 --> 00:12:46,850 large language model that is trained on project delivery. 244 00:12:46,900 --> 00:12:48,810 So it becomes very project delivery. 245 00:12:48,820 --> 00:12:52,570 Nuance, we're going to have that in about two or three weeks 246 00:12:52,580 --> 00:12:54,890 time. So that's going to be available 247 00:12:54,940 --> 00:12:56,190 and it's all going to be open source. 248 00:12:56,200 --> 00:12:57,350 We can open source it for people. 249 00:12:57,420 --> 00:13:00,090 So just imagine if we push that further and further and further, 250 00:13:00,100 --> 00:13:03,650 if you can now start to train it on data, on schedules of risks, 251 00:13:03,660 --> 00:13:06,250 on compensation events, on technical queries. 252 00:13:06,730 --> 00:13:08,850 That's when it becomes even better. 253 00:13:08,860 --> 00:13:11,490 It's starting to predict where we're going to end up, right? 254 00:13:11,500 --> 00:13:14,530 So it's not just about forecasting envelopes. 255 00:13:14,540 --> 00:13:17,330 It's now starting to say to me, what is my call to action? 256 00:13:17,540 --> 00:13:21,030 And people who don't understand this stuff will get replaced by 257 00:13:21,040 --> 00:13:22,870 the people who do understand this stuff. 258 00:13:22,920 --> 00:13:25,410 So if you've got a choice of two project professionals, one 259 00:13:25,420 --> 00:13:28,090 person who really understands this and can leverage it and can 260 00:13:28,100 --> 00:13:31,270 make the most out of it and get better at making decisions and 261 00:13:31,280 --> 00:13:33,870 somebody who doesn't, which person would you choose? 262 00:13:34,000 --> 00:13:35,370 Which? Which person's going to get 263 00:13:35,380 --> 00:13:37,250 promoted? I think that's the issue for the 264 00:13:37,260 --> 00:13:42,020 profession. How do we share knowledge? 265 00:13:42,030 --> 00:13:45,260 How do we share this experience? How do how do we learn from the 266 00:13:45,270 --> 00:13:47,620 first movers if we're not one ourselves? 267 00:13:47,770 --> 00:13:52,490 And also, I'll be really pleased if any of you want to just talk 268 00:13:52,500 --> 00:13:56,720 about a couple of practical examples of how AI is being used 269 00:13:56,730 --> 00:14:00,210 in the world of projects today so that we can move away from 270 00:14:00,220 --> 00:14:03,470 the kind of theory and the hype. So, Antonio. 271 00:14:04,220 --> 00:14:09,070 Yeah, I think the sharing is great, but somehow we say I to 272 00:14:09,080 --> 00:14:12,850 me it feels that there's a bit more strategic advantage. 273 00:14:13,160 --> 00:14:18,770 So why should I share something where I'm using an AI tool with 274 00:14:18,780 --> 00:14:22,410 my competitions, they can adapt it and do better. 275 00:14:22,420 --> 00:14:26,920 So yeah, I was talking earlier with the podcast in Australia 276 00:14:26,930 --> 00:14:29,950 and we were talking about the PPM market as well. 277 00:14:29,960 --> 00:14:33,150 We which we know and we collaborate with some of these 278 00:14:33,160 --> 00:14:37,400 big players that have been there for. 20 years, But discussing 279 00:14:37,410 --> 00:14:41,550 that, you can see that they're they're struggling to adopt AI 280 00:14:41,560 --> 00:14:46,080 and there's one big big player which is Microsoft whose open AI 281 00:14:46,090 --> 00:14:50,000 and has charged BT who might just take everything away in 282 00:14:50,010 --> 00:14:55,240 some niche players around. But for me the the sharing of 283 00:14:55,250 --> 00:14:58,650 AI, there's still the issue of IP and whether they can use all 284 00:14:58,660 --> 00:15:01,620 the information for free or not, but that's a bigger kind of 285 00:15:01,630 --> 00:15:03,580 discussion. We don't know where it's going, 286 00:15:03,650 --> 00:15:08,130 but for me using AI. Can be a strategic tool. 287 00:15:08,140 --> 00:15:10,930 It's not like we're using Excel or we're using Microsoft 288 00:15:10,940 --> 00:15:13,710 Project. No, no, there's much more 289 00:15:13,720 --> 00:15:17,570 intelligence that you can use it to to do your projects better, 290 00:15:17,580 --> 00:15:21,420 faster more successfully. So I don't have an answer it's 291 00:15:21,430 --> 00:15:26,450 just thinking in my head of can you share or should keep it bit 292 00:15:26,460 --> 00:15:32,190 more confidential to make it a competitive edge right. 293 00:15:32,200 --> 00:15:36,930 So that is in the the point I wanted to to share in terms of. 294 00:15:37,020 --> 00:15:40,100 Some parts, I think in my article with Ricardo Vargas, we 295 00:15:40,110 --> 00:15:46,380 talk about Walmart using AI for managing their supply chains and 296 00:15:46,390 --> 00:15:50,360 data analytics to manage the demand and the streamlining. 297 00:15:50,430 --> 00:15:53,980 Another example, I think we talk about Siemens that they've 298 00:15:53,990 --> 00:15:57,300 implemented system to streamline manufacturing process. 299 00:15:57,310 --> 00:16:02,740 This is already well known general electrics applications 300 00:16:02,750 --> 00:16:05,600 on AI and project management in the energy sector. 301 00:16:05,610 --> 00:16:10,910 So there are already. Companies that are using pieces 302 00:16:10,920 --> 00:16:14,890 of Asia to some extent. So I I would not replicate what 303 00:16:14,900 --> 00:16:19,860 is in the in the article which you published in the APM 304 00:16:19,870 --> 00:16:22,350 magazine. So, but yeah, I think there is 305 00:16:22,360 --> 00:16:25,400 more and more and I recommend people to just follow some of 306 00:16:25,410 --> 00:16:29,070 these newsletters around and I because it's just amazing how 307 00:16:29,080 --> 00:16:34,070 quickly it changes. Martin, any practical examples 308 00:16:34,080 --> 00:16:37,090 you want to talk about or how we can learn from each other? 309 00:16:38,200 --> 00:16:40,650 I personally see we've got choices to make here. 310 00:16:40,700 --> 00:16:43,810 So we can either compete around this artificial intelligence or 311 00:16:43,820 --> 00:16:46,190 can work together and to accelerate. 312 00:16:46,480 --> 00:16:48,510 If we work together, we started to pool our data. 313 00:16:48,520 --> 00:16:51,550 We start to sort of open source some of these solutions. 314 00:16:51,560 --> 00:16:55,390 Now in terms of the solutions, a lot of them aren't actually 315 00:16:55,400 --> 00:16:58,970 intellectual property. It's more about configuration of 316 00:16:59,040 --> 00:17:02,890 Python libraries or it's a configuration of Microsoft tool 317 00:17:02,900 --> 00:17:04,880 or a low code app or something like that. 318 00:17:05,819 --> 00:17:08,930 So what we've been doing, so this is for the past five years 319 00:17:08,940 --> 00:17:10,750 or so. So we've been running these 320 00:17:10,760 --> 00:17:14,980 hackathons, so the last one in Manchester City Football Stadium 321 00:17:14,990 --> 00:17:18,680 and we had about 230 people come along to it. 322 00:17:19,150 --> 00:17:22,079 So we Co create solutions to shared problems. 323 00:17:22,170 --> 00:17:24,609 So we're then open source and James can tell you about some of 324 00:17:24,619 --> 00:17:27,900 the solutions because he's been pulling them through into gleeds 325 00:17:27,910 --> 00:17:29,280 as well. It's now part of his product 326 00:17:29,290 --> 00:17:31,800 portfolio. So those are all the scenes of 327 00:17:31,810 --> 00:17:34,560 ideas that people can now fork and take in a different 328 00:17:34,570 --> 00:17:36,700 direction. So if we do that, we're learning 329 00:17:36,710 --> 00:17:38,620 on the fly, we're learning from each other. 330 00:17:38,670 --> 00:17:41,210 We're starting to accelerate. So I'll give you an example. 331 00:17:41,220 --> 00:17:43,930 Instead of 100 people all working on a health and safety 332 00:17:43,940 --> 00:17:46,970 app, because every company wants a health and safety app, if we 333 00:17:46,980 --> 00:17:50,150 just develop one or two of these health and safety apps and then 334 00:17:50,160 --> 00:17:54,910 share them, it means we can do the other 98 things individually 335 00:17:54,920 --> 00:17:56,760 as well. So we go 100 times quicker. 336 00:17:57,360 --> 00:17:59,460 And I think that's the difference is that we shouldn't 337 00:17:59,470 --> 00:18:03,390 be competing. On some of these low value sort 338 00:18:03,400 --> 00:18:06,730 of aspects of data-driven project delivery, which should 339 00:18:06,740 --> 00:18:10,670 be worth together, get us to the data volumes, get us the data 340 00:18:10,680 --> 00:18:12,490 quality as well. And that's one of the biggest 341 00:18:12,500 --> 00:18:14,810 issues at the moment. So artificial intelligence needs 342 00:18:14,820 --> 00:18:16,890 lots of data, needs good quality data. 343 00:18:17,220 --> 00:18:20,850 We'll never get to that point unless we work together on 344 00:18:20,860 --> 00:18:23,790 things like the data model, the ontology about how this data all 345 00:18:23,800 --> 00:18:26,170 fits together and it's not flat data. 346 00:18:26,180 --> 00:18:30,250 You can't just look at things like cost data by itself, the 347 00:18:30,260 --> 00:18:32,290 cost data and the work package and the. 348 00:18:32,480 --> 00:18:34,570 Now is it a Greenfield or brownfield site? 349 00:18:34,580 --> 00:18:37,510 All these other things, they become the features in this 350 00:18:37,520 --> 00:18:40,450 artificial intelligence model and then we can look at the 351 00:18:40,460 --> 00:18:42,790 correlation between those features and that drives the 352 00:18:42,800 --> 00:18:44,660 artificial intelligence engine basically. 353 00:18:45,970 --> 00:18:49,760 We're APM, the only chartered membership organisation for the 354 00:18:49,770 --> 00:18:53,030 project profession. When you become an APM member, 355 00:18:53,040 --> 00:18:55,590 you'll receive the resources and support you need to make an 356 00:18:55,600 --> 00:18:59,130 impact, delivering better projects with better outcomes. 357 00:18:59,400 --> 00:19:02,550 Plus, you'll access exclusive training and benefits to support 358 00:19:02,560 --> 00:19:05,890 your ongoing career development. Find out how we can help you 359 00:19:05,900 --> 00:19:11,030 reach your potential by visiting apm.org.uk, because when 360 00:19:11,040 --> 00:19:16,380 projects succeed, society benefits James. 361 00:19:16,390 --> 00:19:20,740 Any practical examples of AI that you've that have inspired 362 00:19:20,750 --> 00:19:23,540 you or you would like to share with listeners? 363 00:19:24,980 --> 00:19:27,700 Before I talk about some examples, I think Antonio picked 364 00:19:27,710 --> 00:19:29,250 a really important point around this. 365 00:19:29,360 --> 00:19:33,290 Some people think that AI or data more generally some kind of 366 00:19:33,300 --> 00:19:36,280 competitive advantage. And I think what I'm trying to 367 00:19:36,290 --> 00:19:38,990 do is challenge that to say that actually we're not in 368 00:19:39,000 --> 00:19:43,090 competition with each other as consultants or or contractors or 369 00:19:43,100 --> 00:19:44,670 whatever we are. We're actually in competition, 370 00:19:44,680 --> 00:19:47,050 like I said with the big tech company. 371 00:19:47,060 --> 00:19:50,650 So we we got to change our thinking and innovate ourselves 372 00:19:50,660 --> 00:19:52,770 above that. There's enough to go around, 373 00:19:52,810 --> 00:19:55,550 there's enough projects to go around and if we can use AI. 374 00:19:55,660 --> 00:19:58,840 As a way of improving project delivery, it will clients 375 00:19:58,850 --> 00:20:03,840 effectively less reason to start looking for moving, moving to 376 00:20:03,890 --> 00:20:06,490 vendors. The other bit before I go into 377 00:20:06,500 --> 00:20:11,000 some practical examples is is around the messaging and how we 378 00:20:11,010 --> 00:20:13,280 get this out there. Now I think all three of us 379 00:20:13,290 --> 00:20:17,550 probably say that's probably the hardest bit, because you can, 380 00:20:17,560 --> 00:20:20,120 you could, you could have every single project professional in a 381 00:20:20,130 --> 00:20:23,120 room and you could tell them about this, but it would still 382 00:20:23,130 --> 00:20:25,660 sometimes not necessarily go over people's heads because 383 00:20:25,670 --> 00:20:28,260 people are people intelligent. To understand it, I think 384 00:20:28,270 --> 00:20:31,520 there's a there's a fear people have different motivations for 385 00:20:31,580 --> 00:20:35,960 not wanting to pick up AI. Some of it is fear, some of it 386 00:20:35,970 --> 00:20:39,170 is ohh, it's, you know, it's not gonna affect my profession, it's 387 00:20:39,180 --> 00:20:42,840 not gonna affect what I'm doing. My bit is somehow unique from 388 00:20:42,850 --> 00:20:44,900 everything else, so it's not going to affect that. 389 00:20:45,010 --> 00:20:48,620 That's where I think the skills need to come in and sort of 390 00:20:48,630 --> 00:20:50,940 upskilling people. And Martin does a lot of that 391 00:20:50,950 --> 00:20:55,340 with his various data academies. We also do training to upskill 392 00:20:55,350 --> 00:20:58,300 people and we've been working with the APM on the positive 393 00:20:58,310 --> 00:21:02,850 dramatics deals guide document. So you know some of the examples 394 00:21:02,860 --> 00:21:05,600 of things we've done is like training our own large language 395 00:21:05,610 --> 00:21:07,500 models. So for years, one of the things 396 00:21:07,510 --> 00:21:10,510 that we do in Leeds is published market reports about what's 397 00:21:10,520 --> 00:21:15,310 happening in the project world and those have been issued as 398 00:21:15,380 --> 00:21:18,950 traditional reports. We've actually trained a large 399 00:21:18,960 --> 00:21:22,750 language model, ChatGPT basically of our market report 400 00:21:22,760 --> 00:21:27,450 so that clients don't have to interact and read reports, they 401 00:21:27,460 --> 00:21:29,510 can literally just talk to these reports. 402 00:21:29,640 --> 00:21:34,310 That's a very simple example. We've been also using it to sort 403 00:21:34,320 --> 00:21:37,660 of track material prices and what's happening in the market, 404 00:21:37,670 --> 00:21:41,580 how kind of micro level almost in a daily so we can see what 405 00:21:41,590 --> 00:21:45,420 trends are happening, you know even within a week or so prices, 406 00:21:45,430 --> 00:21:47,920 steel or prices of labour in a certain region. 407 00:21:48,130 --> 00:21:52,060 And that all of that is just giving people the tools so they 408 00:21:52,070 --> 00:21:56,380 can become more efficient. Antonio, in the article you 409 00:21:56,390 --> 00:21:59,120 wrote for us you you covered off some of the challenges and how 410 00:21:59,130 --> 00:22:01,700 to overcome them when it comes to AI and and projects. 411 00:22:02,010 --> 00:22:05,780 One might want to pick up on is the lack of skilled personnel. 412 00:22:06,230 --> 00:22:11,420 So if you're speaking to individuals right now, what 413 00:22:11,430 --> 00:22:16,060 advice would you give to them about adapting themselves to 414 00:22:16,370 --> 00:22:20,550 this new reality? Yeah, that's something. 415 00:22:20,560 --> 00:22:23,970 Again, one of these topics where there's no black or white 416 00:22:23,980 --> 00:22:27,510 answer, I say things are moving really fast. 417 00:22:27,760 --> 00:22:31,170 It's more like a mindset of continuous learning and trying. 418 00:22:31,180 --> 00:22:34,690 I think you learn technology by trying, not by just listening. 419 00:22:34,700 --> 00:22:38,870 And I think this is something that maybe we don't dedicate 420 00:22:38,880 --> 00:22:42,530 enough time. But for me, it's about getting 421 00:22:42,540 --> 00:22:46,180 involved in some of the work that both James and Martin are 422 00:22:46,190 --> 00:22:50,370 doing, and and others and and and get connected with the 423 00:22:50,380 --> 00:22:54,600 people who are in that. Breach of of this AI and and and 424 00:22:54,610 --> 00:22:56,600 project management but also trying. 425 00:22:56,610 --> 00:23:00,740 I think first of all everybody should have used already ChatGPT 426 00:23:00,750 --> 00:23:06,280 or or bar to see what we have. What are the risks in in 427 00:23:06,290 --> 00:23:09,480 projects like mine any like knowledge management you go to 428 00:23:09,490 --> 00:23:13,240 chat and you can ask what kind of projects that in this sector 429 00:23:13,250 --> 00:23:16,300 we've seen in the past and what are the key learnings you get 430 00:23:16,310 --> 00:23:19,720 that immediately So that curiosity to experiment with the 431 00:23:19,730 --> 00:23:23,710 tools I think it's. Is more important than saying 432 00:23:23,720 --> 00:23:27,360 you need to develop the kind of design thinking or critical 433 00:23:27,370 --> 00:23:29,320 thinking which is a bit more abstract. 434 00:23:29,380 --> 00:23:33,070 We are not going to be developers for sure, but I think 435 00:23:33,080 --> 00:23:37,790 that kind of constant checking and trying and new tools and see 436 00:23:37,800 --> 00:23:40,730 how can make me better. How can I see that this 437 00:23:40,740 --> 00:23:45,030 technology will help me to get to deliver value better. 438 00:23:45,040 --> 00:23:47,750 I think that's where I I would put my focus. 439 00:23:47,760 --> 00:23:51,570 That's what I'm doing. Of course, going through AI 440 00:23:51,580 --> 00:23:53,780 courses. And and learning. 441 00:23:53,790 --> 00:23:56,570 And I think one point. I did a survey with Ricardo 442 00:23:56,580 --> 00:23:59,750 about this. Area is great, but don't forget 443 00:23:59,760 --> 00:24:03,870 that AI is an enabler. So don't forget about if you're 444 00:24:03,880 --> 00:24:08,250 working on sustainability, diversity, growth that should be 445 00:24:08,260 --> 00:24:11,890 connected to. So don't just one thing, but see 446 00:24:11,900 --> 00:24:15,700 how this connects to other bigger topics that are priority 447 00:24:15,710 --> 00:24:19,050 in organisations that will make you even more special and 448 00:24:19,060 --> 00:24:21,420 unique. So connecting AI with all these 449 00:24:21,500 --> 00:24:25,470 other topics, I think something that I would recommend to do as 450 00:24:25,480 --> 00:24:28,510 well, but the most important is try. 451 00:24:28,700 --> 00:24:32,130 Don't be afraid just you said turn you'll get mistakes, you'd 452 00:24:32,140 --> 00:24:33,920 struggle. But this is the best way to 453 00:24:33,930 --> 00:24:38,170 embrace new technologies and and most of the softwares you have 454 00:24:38,180 --> 00:24:42,220 the most uh that you can just watch and think about how do 455 00:24:42,230 --> 00:24:45,240 they could benefit your your projects. 456 00:24:45,450 --> 00:24:49,180 But I cannot give you one specific skill. 457 00:24:49,230 --> 00:24:51,920 I think there's so many skills that we need to develop. 458 00:24:53,650 --> 00:24:57,360 Thinking more strategically about one's career, should you 459 00:24:57,370 --> 00:25:00,720 be thinking about the very human side of work? 460 00:25:00,770 --> 00:25:03,750 So when it comes to decision making, So if all the AI 461 00:25:03,760 --> 00:25:07,120 eventually is going to give you all the information you need and 462 00:25:07,130 --> 00:25:11,000 flag up the risk areas of a project or suggest ways that 463 00:25:11,010 --> 00:25:14,120 seems to be become better, what does that leave the project 464 00:25:14,130 --> 00:25:17,550 manager needing to do? So if you're thinking five years 465 00:25:17,560 --> 00:25:21,120 ahead of or 10 years ahead, what is it about the project 466 00:25:21,130 --> 00:25:24,360 manager's role that will change from now until? 467 00:25:24,480 --> 00:25:27,860 Kind of short term future, what should you be cultivating or 468 00:25:27,870 --> 00:25:31,150 developing in within yourself to ensure that you? 469 00:25:31,860 --> 00:25:35,430 Still going to be necessary and needed in a five years time. 470 00:25:36,460 --> 00:25:40,810 In the skills, for me it's it's what we talk about is soft 471 00:25:40,860 --> 00:25:44,930 skills, but in on a higher level is that alignment between 472 00:25:44,940 --> 00:25:49,070 different groups of priorities and projects and critical 473 00:25:49,080 --> 00:25:54,030 thinking of strategic thinking. These are things that a I will 474 00:25:54,040 --> 00:25:58,530 for sure not do very soon. So engaging on stakeholders, 475 00:25:58,540 --> 00:26:03,250 talking about the value of your projects, learning to speak the 476 00:26:03,260 --> 00:26:06,530 language of the organisation, connecting with the right 477 00:26:06,540 --> 00:26:10,050 people. I think this is where we should 478 00:26:10,060 --> 00:26:12,750 have done that before anyway, because these are essential 479 00:26:12,760 --> 00:26:15,230 skills. But now AI is going to make that 480 00:26:15,240 --> 00:26:19,190 more obvious that if you want to have a job in this space in five 481 00:26:19,280 --> 00:26:23,460 years, you need to develop that really acceleration there. 482 00:26:23,470 --> 00:26:27,210 Because it's about also following empower, feeling the 483 00:26:27,220 --> 00:26:30,990 confident, feeling confident to talk to our CEO of your company. 484 00:26:31,040 --> 00:26:35,390 This kind of mindset we've never heard and it's the moment to 485 00:26:35,460 --> 00:26:37,590 step up. And I always say it's more of a 486 00:26:37,600 --> 00:26:40,230 mindset. Issue then the skills and the 487 00:26:40,240 --> 00:26:44,530 mindset says you're in power to do these things to deliver your 488 00:26:44,540 --> 00:26:48,650 project benefits and this is something that is built based on 489 00:26:48,660 --> 00:26:53,310 confidence on on looking another examples and and trying this 490 00:26:53,320 --> 00:26:57,970 kind of new new approaches to to delivering projects. 491 00:26:57,980 --> 00:27:00,230 I think if there's something I would recommend it's the 492 00:27:00,240 --> 00:27:03,070 mindset. Feel empowered to drive your 493 00:27:03,080 --> 00:27:04,150 project. You're the owner. 494 00:27:04,160 --> 00:27:05,870 You should be able to say let's stop it. 495 00:27:05,920 --> 00:27:08,620 You should be able to go to the CEO, say I need. 496 00:27:08,720 --> 00:27:12,540 Resources or this is not going to happen unless that in that. 497 00:27:12,550 --> 00:27:16,100 So that's something that I always push in in conferences 498 00:27:16,110 --> 00:27:20,120 and workshops. Martin, what are your thoughts 499 00:27:20,130 --> 00:27:21,940 around this? So how project professionals 500 00:27:21,950 --> 00:27:24,870 should be thinking about upskilling themselves or any 501 00:27:24,880 --> 00:27:30,210 advice you'd pass on? So basically we saw this back in 502 00:27:30,220 --> 00:27:34,130 2017 and the first point was about just awareness. 503 00:27:34,140 --> 00:27:37,190 So that's why we set up the project data into its community 504 00:27:37,200 --> 00:27:38,670 and that's why we start the meet ups. 505 00:27:38,680 --> 00:27:41,550 We ran monthly meet ups and then pre COVID we were going to 506 00:27:41,620 --> 00:27:45,270 Birmingham and we're going to Bristol and Manchester up to 507 00:27:45,280 --> 00:27:48,650 Aberdeen as well and start to spread the word and share these 508 00:27:48,660 --> 00:27:50,830 experiences as well. So we get guest speakers in. 509 00:27:50,840 --> 00:27:53,770 So a chat came and talked about the Tour de France and he played 510 00:27:53,780 --> 00:27:56,470 it back through a lens, which was brilliant, right, Really, 511 00:27:56,480 --> 00:27:58,470 really brilliant. So what we then start to do is 512 00:27:58,480 --> 00:28:00,500 to run these hackathons. Because it gave people some 513 00:28:00,510 --> 00:28:03,160 practical experience and it took away some of the barriers. 514 00:28:03,170 --> 00:28:06,810 It's not as scary if someone sat next to you and showing you what 515 00:28:06,820 --> 00:28:09,420 to do and showing in two days what can be done. 516 00:28:09,430 --> 00:28:12,760 So we run that and then people said to us that's not enough. 517 00:28:12,770 --> 00:28:14,000 We need some practical experience. 518 00:28:14,010 --> 00:28:15,920 You know, we need to be shown how to do it. 519 00:28:15,990 --> 00:28:18,860 So we then started training, so we run the Project Data 520 00:28:18,870 --> 00:28:22,130 Analytics Academy, So that's funded through the government's 521 00:28:22,140 --> 00:28:25,360 Apprenticeship training levy. So it's basically free for most 522 00:28:25,370 --> 00:28:30,080 organisations and that enables people to get up skills in data. 523 00:28:30,180 --> 00:28:33,400 Even project delivery for nothing and a byproduct of that 524 00:28:33,410 --> 00:28:36,220 process is each person has to do three or four projects as part 525 00:28:36,230 --> 00:28:37,760 of the course. So there's no exams anymore. 526 00:28:37,770 --> 00:28:40,560 It's all about your portfolio that that you develop. 527 00:28:40,950 --> 00:28:44,640 If we do that, we start to develop this collateral then. 528 00:28:45,390 --> 00:28:48,580 So we start to develop these little modules of capability, 529 00:28:48,590 --> 00:28:51,180 these Lego bricks that we can all start to piece together. 530 00:28:51,890 --> 00:28:55,220 And just imagine if you had 1000 people with three or four 531 00:28:55,230 --> 00:28:59,000 projects seats, that's 4000 Lego pieces of capability. 532 00:28:59,770 --> 00:29:02,800 If we start to pull along that like won't put it on cause some 533 00:29:02,810 --> 00:29:04,740 of it will be commercially sensitive and et cetera. 534 00:29:04,750 --> 00:29:08,300 But if we could pull half of it, we will transform the industry. 535 00:29:09,060 --> 00:29:11,670 So that training is available now, so finders on 536 00:29:11,680 --> 00:29:15,930 projectingsuccess.co.uk and look at the training page as well. 537 00:29:15,940 --> 00:29:18,250 So it's all in there and it's funded by government. 538 00:29:18,260 --> 00:29:21,290 So government is trying to help you to get these skills so you 539 00:29:21,300 --> 00:29:24,250 can remain. At competitive and we start to 540 00:29:24,260 --> 00:29:30,150 drive up UK PLC productivity. So back to one children's point, 541 00:29:30,390 --> 00:29:32,920 you know what will project managers do in the future. 542 00:29:33,270 --> 00:29:36,980 And for me there is a phase shift that's coming, a massive 543 00:29:36,990 --> 00:29:41,280 phase shift as in spite of as spending loads of time, you know 544 00:29:41,290 --> 00:29:43,600 looking backwards through reporting, doing assurance 545 00:29:43,610 --> 00:29:46,220 etcetera, a load of that it's just going to be automated. 546 00:29:46,670 --> 00:29:49,120 That doesn't need artificial intelligence, it just need needs 547 00:29:49,130 --> 00:29:53,020 code and some of these sort of modules of capability that we 548 00:29:53,030 --> 00:29:56,170 can develop through things like Power Automate and and Power BI 549 00:29:56,180 --> 00:29:58,550 and that sort of stuff, right. So that's fairly easy to do, and 550 00:29:58,560 --> 00:30:02,390 it's all accessible today. Well, this is 10 years away. 551 00:30:02,400 --> 00:30:05,690 It's all available today. So what we then start to do as 552 00:30:05,700 --> 00:30:09,170 project managers or project professionals, we start to say 553 00:30:09,740 --> 00:30:13,270 where do I need to focus my laser beam so I can deliver 554 00:30:13,280 --> 00:30:16,470 these projects more cost effectively and with greater 555 00:30:16,480 --> 00:30:18,660 delivery confidence. So if you look at HS2 at the 556 00:30:18,670 --> 00:30:22,270 moment, is it the politicians fault that it may get turned off 557 00:30:22,280 --> 00:30:23,840 from Birmingham up to Manchester? 558 00:30:23,880 --> 00:30:27,410 So is that a political decision or is it a case that IT cost 559 00:30:27,420 --> 00:30:30,510 growth is so extreme is it's no longer investable? 560 00:30:30,650 --> 00:30:32,760 So is that a project delivery issue? 561 00:30:32,990 --> 00:30:34,460 Right. I think the jury is out on that 562 00:30:34,470 --> 00:30:36,900 argument. But if projects are becoming an 563 00:30:36,910 --> 00:30:40,220 investable once they get to a certain size, then that's a 564 00:30:40,230 --> 00:30:44,150 massive issue for society and we can help to solve that through 565 00:30:44,160 --> 00:30:47,300 advanced data analytics. So we start to understand which 566 00:30:47,310 --> 00:30:50,040 parts of a project are predictable and which ones 567 00:30:50,050 --> 00:30:53,560 aren't and why and what we need to do to sense that and and to 568 00:30:53,570 --> 00:30:56,150 understand it. So the role of a project 569 00:30:56,160 --> 00:30:59,860 delivery professional is going to evolve at pace. 570 00:30:59,910 --> 00:31:01,660 So it's all about the superpowers. 571 00:31:01,730 --> 00:31:04,350 Of individuals. So if you can see what's in the 572 00:31:04,360 --> 00:31:06,970 future, you can predict where something's going to go wrong, 573 00:31:07,020 --> 00:31:09,950 you will outperform your peers. And if you really, really good 574 00:31:09,960 --> 00:31:12,410 at it and you're going to get paid a lot of money because you 575 00:31:12,420 --> 00:31:14,740 can save the country and absolute fortune, you can save 576 00:31:14,750 --> 00:31:17,490 your employees of fortune. The problem with this is, so 577 00:31:17,500 --> 00:31:20,210 I've been posting a lot of things on LinkedIn at the moment 578 00:31:20,300 --> 00:31:22,670 and people have said we need to take everybody on this journey 579 00:31:22,680 --> 00:31:25,100 with us. So let's not scare the horses. 580 00:31:25,830 --> 00:31:28,280 And let's not put out there that you know there's going to be 581 00:31:28,290 --> 00:31:32,680 various people losing their jobs and plugged into this as I see a 582 00:31:32,690 --> 00:31:35,600 lot of the time about all of this sort of efficiency 583 00:31:35,610 --> 00:31:38,520 improvement and productivity improvement through project 584 00:31:38,530 --> 00:31:42,360 delivery and some organisations will just cash that productivity 585 00:31:42,370 --> 00:31:45,020 improvement in. So it will be heads, it'll be 586 00:31:45,030 --> 00:31:47,860 headcount loss. It's the more visionary 587 00:31:47,870 --> 00:31:51,810 organisations will transfer those people and start to move 588 00:31:51,820 --> 00:31:55,400 them up the value chain. So they've got these superpowers 589 00:31:55,810 --> 00:31:58,480 and they can deliver projects a lot more cost effectively. 590 00:31:59,290 --> 00:32:02,240 So for me it's not necessarily about taking everyone with us 591 00:32:02,250 --> 00:32:05,020 because they'll always be sceptics, It's about taking the 592 00:32:05,030 --> 00:32:08,900 five or 10% who's really going to start to accelerate this, 593 00:32:08,960 --> 00:32:11,340 this journey. We're going to pull a load of 594 00:32:11,350 --> 00:32:14,400 other people along with them in their wake because we'll start 595 00:32:14,410 --> 00:32:17,420 to develop the evidence and we'll start to demonstrate this. 596 00:32:17,490 --> 00:32:22,060 That pace. Any last thoughts before we 597 00:32:22,070 --> 00:32:24,380 finish? We run out of time already and I 598 00:32:24,390 --> 00:32:26,120 could talk to you for another two hours. 599 00:32:26,930 --> 00:32:31,170 Yeah, I think we cover a great questions and I think nothing to 600 00:32:31,180 --> 00:32:34,220 what I think it's a great opportunity for the profession. 601 00:32:34,320 --> 00:32:40,190 Let's step up, let's take this opportunity, follow Martin James 602 00:32:40,200 --> 00:32:44,030 all the work that you are doing in PMG to focus on on a I and 603 00:32:44,220 --> 00:32:48,070 and I think the future it's very right for for us in this 604 00:32:48,080 --> 00:32:51,930 profession finally. So now I'm very excited and 605 00:32:51,940 --> 00:32:55,410 looking forward to connecting with with everyone who's 606 00:32:55,420 --> 00:32:58,940 listening. I think the big point for me, 607 00:32:58,950 --> 00:33:00,570 it's about vision and leadership. 608 00:33:01,570 --> 00:33:04,130 So with project professionals, we're all busy people. 609 00:33:04,140 --> 00:33:06,240 We're stuck in the knife fight over the here and now we're 610 00:33:06,250 --> 00:33:09,070 trying to deliver a project. It's probably going pear shaped, 611 00:33:09,080 --> 00:33:11,640 you know, in most cases. Ohh, that's what the start 612 00:33:11,650 --> 00:33:13,920 filling us. So we don't have the headspace 613 00:33:13,930 --> 00:33:15,520 for this, we just don't have the head space. 614 00:33:16,260 --> 00:33:19,830 And that's what I'm finding from speaking to organisations is 615 00:33:19,840 --> 00:33:23,290 this is a job for tomorrow, it's not for a job for today and I've 616 00:33:23,300 --> 00:33:26,230 been facing that for the past six years, so it's always a job 617 00:33:26,240 --> 00:33:28,950 for tomorrow. So it needs client leadership, 618 00:33:29,000 --> 00:33:31,650 it needs professional leadership, it needs all of us 619 00:33:31,660 --> 00:33:33,450 to pull together to start to drive that. 620 00:33:34,250 --> 00:33:35,750 I don't think that's where we need to be. 621 00:33:35,760 --> 00:33:37,760 We need to be showing people the path. 622 00:33:38,720 --> 00:33:40,950 And showing them the way to take this forward. 623 00:33:42,280 --> 00:33:45,480 So some of the work we've done work with James as well and and 624 00:33:45,490 --> 00:33:47,290 the project data on it, it's task force. 625 00:33:47,300 --> 00:33:49,390 So James is the chair of the project date on it. 626 00:33:49,400 --> 00:33:51,190 It's task force. So it's worth reaching out to 627 00:33:51,200 --> 00:33:54,870 James if you're interested in some of this is the visions for 628 00:33:54,880 --> 00:33:57,120 2025. So we said let's start to 629 00:33:57,130 --> 00:34:00,150 reimagine things like risk management, let's start to 630 00:34:00,160 --> 00:34:06,770 reimagine benefits management. Could that look like in about 18 631 00:34:06,780 --> 00:34:08,130 months from now? All right. 632 00:34:09,210 --> 00:34:12,380 If we can start to imagine it and break it down into some sort 633 00:34:12,389 --> 00:34:15,719 of modules of capability to get us there, it becomes deliverable 634 00:34:16,239 --> 00:34:19,080 and we can all do that if we unite around it. 635 00:34:20,460 --> 00:34:23,080 And and James will probably share with you some of the pain 636 00:34:23,090 --> 00:34:26,400 to try and motivate the community to line up around 637 00:34:26,409 --> 00:34:29,969 those visions. And it's normally because it's 638 00:34:29,980 --> 00:34:32,480 getting access to those thought leaders and those visionaries 639 00:34:32,489 --> 00:34:35,120 and the people who's got the ambition to make this happen. 640 00:34:36,010 --> 00:34:38,400 And I think that is changing in places now. 641 00:34:38,409 --> 00:34:41,340 I think we are starting to see it in ChatGPT has brought this 642 00:34:41,350 --> 00:34:43,460 into the imagination, right? It's made it a lot more 643 00:34:43,469 --> 00:34:47,420 accessible for people. So I do sense that changing. 644 00:34:48,429 --> 00:34:50,540 And I think people like Adam Bonnesen and we've got Andy 645 00:34:50,550 --> 00:34:53,070 Murray as well from the major projects association. 646 00:34:53,350 --> 00:34:55,940 Then I really started to understand this and get all over 647 00:34:55,949 --> 00:34:59,460 it and start as well. So I do think we'll see a major 648 00:34:59,470 --> 00:35:04,190 change probably this year. And James, any any last thoughts 649 00:35:04,200 --> 00:35:07,280 from you? Yeah, so Martin mentioned the 650 00:35:07,290 --> 00:35:08,610 Project Data Analytics Task Force. 651 00:35:08,620 --> 00:35:13,000 So Martin set that up how to how many years ago probably four or 652 00:35:13,010 --> 00:35:15,860 five years ago and he's passed the championship on to me. 653 00:35:15,870 --> 00:35:19,600 We've got our first meeting this week actually. 654 00:35:19,650 --> 00:35:23,660 And you know, I I think what out of the objectives, if I could 655 00:35:23,670 --> 00:35:28,220 think of 1 objective that would move the goalpost most rapidly 656 00:35:28,290 --> 00:35:30,650 is all the institutions started to work together. 657 00:35:30,660 --> 00:35:34,560 And if I see that as my role as helping create this kind of 658 00:35:34,570 --> 00:35:36,500 overlay. So you've got you know what you 659 00:35:36,510 --> 00:35:39,710 guys do which is brilliant. You know these podcasts and 660 00:35:39,850 --> 00:35:42,220 stuff and in in the journals is brilliant. 661 00:35:42,310 --> 00:35:45,060 PMI is doing some of the things. Ohh ICS are doing things. 662 00:35:45,410 --> 00:35:49,080 But you know if we rather than all we're doing little bits 663 00:35:49,090 --> 00:35:51,190 ourselves if we can bring it under one umbrella. 664 00:35:51,200 --> 00:35:53,530 And that's what I hope the project they genetics task force 665 00:35:53,650 --> 00:35:57,780 can become a kind of a way of putting all of this information 666 00:35:57,850 --> 00:36:01,200 like an overlay on top of it all so that people can see there's a 667 00:36:01,210 --> 00:36:05,420 very clear direction that the profession is, is moving in and 668 00:36:05,430 --> 00:36:08,220 then all the institutions and government these are doing their 669 00:36:08,230 --> 00:36:10,400 bit to drive towards that vision. 670 00:36:10,650 --> 00:36:14,030 So I am optimistic there is that there is with all these kind of 671 00:36:14,040 --> 00:36:17,030 things, there's dangers and there's, there's risks and we 672 00:36:17,040 --> 00:36:19,800 have to control that and who's better than to do that, than 673 00:36:19,810 --> 00:36:22,140 project professionals, you know that's part of our part of our 674 00:36:22,150 --> 00:36:23,610 role. All right. 675 00:36:23,840 --> 00:36:26,670 Just leaves me to say thank you to everyone. 676 00:36:26,680 --> 00:36:28,710 Thank you for your time and your thoughts. 677 00:36:28,720 --> 00:36:31,550 Could talk another two hours about this, but we just can't do 678 00:36:31,560 --> 00:36:34,090 that, I'm afraid. But thank you so much. 679 00:36:34,100 --> 00:36:39,750 It's brilliant. Thanks again to Antonio, Martin 680 00:36:39,760 --> 00:36:42,390 and James for joining us, and to you for listening to the APM 681 00:36:42,400 --> 00:36:44,570 podcast. Don't forget to look out for 682 00:36:44,580 --> 00:36:47,150 more episodes or to rate and review us wherever you get your 683 00:36:47,160 --> 00:36:49,350 podcasts. We'd welcome you to get in touch 684 00:36:49,360 --> 00:36:52,690 with your comments, feedback and suggestions by emailing us at 685 00:36:52,740 --> 00:36:58,450 apmpodcast@thinkpublishing.co.uk. This podcast has been brought to 686 00:36:58,460 --> 00:37:01,430 you by APM, The Chartered Body for the project profession. 687 00:37:02,070 --> 00:37:05,910 For more information on APM, visit apm.org.uk.