1 00:00:00,000 --> 00:00:02,520 The following content is provided under a Creative 2 00:00:02,520 --> 00:00:03,970 Commons license. 3 00:00:03,970 --> 00:00:06,330 Your support will help MIT OpenCourseWare 4 00:00:06,330 --> 00:00:10,660 continue to offer high quality educational resources for free. 5 00:00:10,660 --> 00:00:13,320 To make a donation or view additional materials 6 00:00:13,320 --> 00:00:17,190 from hundreds of MIT courses, visit MIT OpenCourseWare 7 00:00:17,190 --> 00:00:18,370 at ocw.mit.edu. 8 00:00:37,940 --> 00:00:40,470 ANNALISA WEIGEL: So let's start with-- 9 00:00:40,470 --> 00:00:42,420 HUGH MCMANUS: I'm Hugh McManus, the co-creator 10 00:00:42,420 --> 00:00:44,612 of the lean enterprise value simulation. 11 00:00:44,612 --> 00:00:47,070 I'm going to talk a little bit about teaching lean thinking 12 00:00:47,070 --> 00:00:49,350 principles through hands on learning 13 00:00:49,350 --> 00:00:52,770 with particular reference to what we do in the Lean Academy. 14 00:00:52,770 --> 00:00:54,840 Credited here are Eric Rebentisch Tisch, 15 00:00:54,840 --> 00:00:58,260 my co-creator in the lean enterprise value simulation. 16 00:00:58,260 --> 00:01:01,980 And Earl and Alexis, who were key in integrating 17 00:01:01,980 --> 00:01:04,080 the lean enterprise value simulation, part of it, 18 00:01:04,080 --> 00:01:06,450 into the Lean Academy. 19 00:01:06,450 --> 00:01:09,390 The reason we use simulation-based education 20 00:01:09,390 --> 00:01:15,870 for this is that teaching lean is is a difficult challenge. 21 00:01:15,870 --> 00:01:19,050 A great deal of that is because it's experience-based 22 00:01:19,050 --> 00:01:22,500 and it depends on a context, the context of existing 23 00:01:22,500 --> 00:01:24,660 industrial and engineering processes 24 00:01:24,660 --> 00:01:26,500 that are not familiar to students. 25 00:01:26,500 --> 00:01:28,560 So we really need to give them something 26 00:01:28,560 --> 00:01:32,610 to think about and work with before a lot of these ideas 27 00:01:32,610 --> 00:01:34,600 start to make real sense to them. 28 00:01:34,600 --> 00:01:37,050 So we use simulation-based education 29 00:01:37,050 --> 00:01:39,870 to increase comprehension. 30 00:01:39,870 --> 00:01:42,420 To allow them to put the ideas together 31 00:01:42,420 --> 00:01:44,310 in a more holistic, way not just bits 32 00:01:44,310 --> 00:01:45,810 and pieces of technical knowledge, 33 00:01:45,810 --> 00:01:47,730 but how does it all work together? 34 00:01:47,730 --> 00:01:50,490 And of course learning through experience, getting a tactile 35 00:01:50,490 --> 00:01:52,410 feel for the material. 36 00:01:52,410 --> 00:01:56,490 Final thing for an intensive event like the Lean Academy 37 00:01:56,490 --> 00:01:58,290 is also just to get the energy rubbed off. 38 00:01:58,290 --> 00:02:00,240 To give them something to do. 39 00:02:00,240 --> 00:02:02,470 To get their blood pressure up a little bit. 40 00:02:02,470 --> 00:02:06,150 To keep them awake and excited and involved in the class. 41 00:02:06,150 --> 00:02:10,229 The simulation is built around attempting 42 00:02:10,229 --> 00:02:14,010 to build LEGO airplanes that are actually relatively poorly 43 00:02:14,010 --> 00:02:17,040 designed LEGO airplanes, if the criteria for a LEGO airplane 44 00:02:17,040 --> 00:02:18,960 is that it's relatively easy to put together 45 00:02:18,960 --> 00:02:22,860 and it stays together once you put it there. 46 00:02:22,860 --> 00:02:24,750 This is not a very good airplane. 47 00:02:24,750 --> 00:02:26,670 And it's built in a very unlean way. 48 00:02:26,670 --> 00:02:29,580 It's built in a legacy system which 49 00:02:29,580 --> 00:02:32,280 has an unbalanced production system with bottlenecks 50 00:02:32,280 --> 00:02:33,420 and other problems. 51 00:02:33,420 --> 00:02:34,680 A long supply chain. 52 00:02:34,680 --> 00:02:36,630 A long and uncoordinated supply chain. 53 00:02:36,630 --> 00:02:40,590 The LEGOs actually come from someplace else. 54 00:02:40,590 --> 00:02:42,510 They have to be transported to the table where 55 00:02:42,510 --> 00:02:45,750 the airplanes are built. And there's a lot of paperwork 56 00:02:45,750 --> 00:02:49,020 and communications issues in both getting the plane built. 57 00:02:49,020 --> 00:02:50,520 And then at the end of each round, 58 00:02:50,520 --> 00:02:52,440 doing the accounting necessary to figure out 59 00:02:52,440 --> 00:02:55,170 whether you actually made money or not from the airplane. 60 00:02:55,170 --> 00:03:00,480 The system used in the Lean Academy is moderately simple. 61 00:03:00,480 --> 00:03:03,810 We have four manufacturing plants 62 00:03:03,810 --> 00:03:07,410 that build tails, fuselages, wings, and final assembly 63 00:03:07,410 --> 00:03:09,880 to deliver an airplane to the customer. 64 00:03:09,880 --> 00:03:12,630 We have a supplier quality representative 65 00:03:12,630 --> 00:03:15,090 who interacts with a supply chain consisting 66 00:03:15,090 --> 00:03:18,150 of a single dedicated supplier, but in a different place. 67 00:03:18,150 --> 00:03:20,640 At a table where the suppliers sit. 68 00:03:20,640 --> 00:03:24,390 So there's a flow of information between these people. 69 00:03:24,390 --> 00:03:27,690 And hopefully that creates a flow of parts, 70 00:03:27,690 --> 00:03:30,450 of subassemblies in parts, that result 71 00:03:30,450 --> 00:03:33,270 in some value being delivered in aircraft being delivered 72 00:03:33,270 --> 00:03:34,470 to the customer. 73 00:03:34,470 --> 00:03:36,870 The simulation it's not just a matter 74 00:03:36,870 --> 00:03:38,400 of building LEGO airplanes. 75 00:03:38,400 --> 00:03:42,300 It's actually a fairly rigidly defined simulation 76 00:03:42,300 --> 00:03:44,850 that has a number of features. 77 00:03:44,850 --> 00:03:47,640 For one thing, each student what they're allowed to do 78 00:03:47,640 --> 00:03:50,970 is represented visually like this. 79 00:03:50,970 --> 00:03:53,880 Each student is set is told, take these pieces 80 00:03:53,880 --> 00:03:56,850 and build that assembly. 81 00:03:56,850 --> 00:03:58,980 This both defines what they need to do visually 82 00:03:58,980 --> 00:04:01,650 so it's fairly easy to understand and it's changeable. 83 00:04:01,650 --> 00:04:02,670 Very important. 84 00:04:02,670 --> 00:04:05,790 This is a rather difficult assembly to put together. 85 00:04:05,790 --> 00:04:07,350 If the students wish to change it, 86 00:04:07,350 --> 00:04:10,780 they can in an organized way. 87 00:04:10,780 --> 00:04:13,290 The processes that they do are also 88 00:04:13,290 --> 00:04:14,820 constrained by hourglasses. 89 00:04:14,820 --> 00:04:16,779 It's not a dexterity contest. 90 00:04:16,779 --> 00:04:18,300 It's not a race. 91 00:04:18,300 --> 00:04:19,320 It's a process. 92 00:04:19,320 --> 00:04:23,130 And this process is at many steps constrained 93 00:04:23,130 --> 00:04:26,010 by the pace of some hourglasses in particular, the assembly 94 00:04:26,010 --> 00:04:27,960 operations. 95 00:04:27,960 --> 00:04:30,540 Depending on the part count, hourglasses 96 00:04:30,540 --> 00:04:34,140 with different times are used to represent the actual factory 97 00:04:34,140 --> 00:04:36,210 operations that are happening. 98 00:04:36,210 --> 00:04:39,000 That are simulated by the simulation. 99 00:04:39,000 --> 00:04:41,610 It's not just a matter of the student's dexterity. 100 00:04:41,610 --> 00:04:43,740 And so this becomes a constraint that the students 101 00:04:43,740 --> 00:04:48,390 have to work with and design solutions around. 102 00:04:48,390 --> 00:04:52,017 There's a fairly long paperwork chain and it's fairly clumsy. 103 00:04:52,017 --> 00:04:53,850 It's not that hard to learn but it turns out 104 00:04:53,850 --> 00:04:56,040 it's not that easy to use. 105 00:04:56,040 --> 00:04:57,738 Standard paper order form here. 106 00:04:57,738 --> 00:04:59,280 You could think of that even as a web 107 00:04:59,280 --> 00:05:00,810 form in the modern economy. 108 00:05:00,810 --> 00:05:04,260 But you're just saying, I want this many of this part, 109 00:05:04,260 --> 00:05:07,200 handing it off to your supplier quality representative, who 110 00:05:07,200 --> 00:05:10,080 then hands it to the supplier who has to fill it. 111 00:05:10,080 --> 00:05:14,220 And then they have to fill out essentially an invoice sheet 112 00:05:14,220 --> 00:05:16,260 that they send back to you. 113 00:05:16,260 --> 00:05:18,780 That means that every transaction with LEGOs 114 00:05:18,780 --> 00:05:23,670 involves two pieces of paper and 1, 2, 3, 4 steps just 115 00:05:23,670 --> 00:05:24,930 to get your parts to build. 116 00:05:24,930 --> 00:05:29,400 Not a very good system but not atypical of the real world. 117 00:05:29,400 --> 00:05:31,430 And finally there's an accounting system 118 00:05:31,430 --> 00:05:32,330 for Lean Academy. 119 00:05:32,330 --> 00:05:35,600 It's a cash flow system that tracks all the costs involved. 120 00:05:35,600 --> 00:05:36,402 A fixed costs. 121 00:05:36,402 --> 00:05:38,360 How much does it cost to keep your plants open? 122 00:05:38,360 --> 00:05:39,530 The variable cost. 123 00:05:39,530 --> 00:05:41,060 How much do those parts cost? 124 00:05:41,060 --> 00:05:44,450 What does it cost to do various things? 125 00:05:44,450 --> 00:05:47,390 And you can figure out whether you're making money or not. 126 00:05:47,390 --> 00:05:48,910 Often you're not. 127 00:05:48,910 --> 00:05:50,660 And if you don't get out enough airplanes, 128 00:05:50,660 --> 00:05:51,860 you don't make any money. 129 00:05:51,860 --> 00:05:54,860 Or if you do things in a wasteful way, 130 00:05:54,860 --> 00:05:58,088 if you waste parts, you won't make any money. 131 00:05:58,088 --> 00:05:59,630 ANNALISA WEIGEL: All right everybody. 132 00:05:59,630 --> 00:06:00,290 Let's check in. 133 00:06:00,290 --> 00:06:04,130 I'd like to find out how many planes each table built. 134 00:06:04,130 --> 00:06:05,450 Let's start here. 135 00:06:05,450 --> 00:06:06,307 One plane. 136 00:06:06,307 --> 00:06:06,890 AUDIENCE: One. 137 00:06:06,890 --> 00:06:09,260 ANNALISA WEIGEL: One plane? 138 00:06:09,260 --> 00:06:11,305 Two planes. 139 00:06:11,305 --> 00:06:12,650 One plane. 140 00:06:12,650 --> 00:06:13,790 All right. 141 00:06:13,790 --> 00:06:16,430 Who's making money? 142 00:06:16,430 --> 00:06:17,330 AUDIENCE: No one. 143 00:06:17,330 --> 00:06:18,955 ANNALISA WEIGEL: Let me ask a question. 144 00:06:18,955 --> 00:06:22,780 Is anybody's manufacturing operations making money yet? 145 00:06:22,780 --> 00:06:23,280 No. 146 00:06:23,280 --> 00:06:25,232 OK. 147 00:06:25,232 --> 00:06:26,690 Tell me how much money the supplier 148 00:06:26,690 --> 00:06:28,260 is making whose profitable? 149 00:06:28,260 --> 00:06:29,077 AUDIENCE: 14. 150 00:06:29,077 --> 00:06:29,910 ANNALISA WEIGEL: 14. 151 00:06:29,910 --> 00:06:30,410 OK. 152 00:06:30,410 --> 00:06:31,670 So you're barely profitable. 153 00:06:31,670 --> 00:06:33,087 That's better than being negative. 154 00:06:33,087 --> 00:06:34,460 All right. 155 00:06:34,460 --> 00:06:37,010 So the supplier might be doing well in that enterprise, 156 00:06:37,010 --> 00:06:39,740 but it might be at the expense of the manufacturing portion. 157 00:06:39,740 --> 00:06:41,323 So this is something that you're going 158 00:06:41,323 --> 00:06:43,380 to think about as you go through your simulation. 159 00:06:43,380 --> 00:06:44,880 HUGH MCMANUS: So in the Lean Academy 160 00:06:44,880 --> 00:06:49,295 we dedicate one day to the simulation, about 2/3 161 00:06:49,295 --> 00:06:50,670 of the teaching time in that day. 162 00:06:50,670 --> 00:06:53,780 There's some lectures interspersed. 163 00:06:53,780 --> 00:06:55,820 It happens in 12 minute active rounds-- 164 00:06:55,820 --> 00:06:58,760 there's 12 minutes of frenzy. 165 00:06:58,760 --> 00:07:03,650 Followed by on-- preceded by in many cases, time 166 00:07:03,650 --> 00:07:06,920 for reflection, planning, financial analysis, 167 00:07:06,920 --> 00:07:08,527 and so forth. 168 00:07:08,527 --> 00:07:10,610 And these are separated up into basically learning 169 00:07:10,610 --> 00:07:13,250 how to do the simulation, getting past the learning 170 00:07:13,250 --> 00:07:14,150 curve. 171 00:07:14,150 --> 00:07:16,370 Understanding how lean process improvements can 172 00:07:16,370 --> 00:07:20,300 be used to take a legacy state and make it lean and make it 173 00:07:20,300 --> 00:07:21,630 work better. 174 00:07:21,630 --> 00:07:27,290 And then a final round where the manufacturing suppliers 175 00:07:27,290 --> 00:07:32,450 and also a not simulated, but conceptual engineering process, 176 00:07:32,450 --> 00:07:35,690 is used to achieve enterprise lean by redesigning 177 00:07:35,690 --> 00:07:39,050 the airplane, tuning the supply chain to a really high state, 178 00:07:39,050 --> 00:07:42,440 and seeing what you can do in an almost ideal state. 179 00:07:42,440 --> 00:07:46,430 ANNALISA WEIGEL: This is a common tool around the industry 180 00:07:46,430 --> 00:07:48,200 to go and look at other facilities 181 00:07:48,200 --> 00:07:51,908 and benchmark yourselves not only with respect to companies 182 00:07:51,908 --> 00:07:54,200 that do the same thing as you do, but also to benchmark 183 00:07:54,200 --> 00:07:56,158 yourself against companies that do other things 184 00:07:56,158 --> 00:07:57,623 but have similar processes to you. 185 00:07:57,623 --> 00:07:59,540 So there's a lot to learn by going and walking 186 00:07:59,540 --> 00:08:01,100 around and seeing this. 187 00:08:01,100 --> 00:08:02,990 And from what I took away from the tables, 188 00:08:02,990 --> 00:08:08,850 I think we've got two different build-to philosophies going on. 189 00:08:08,850 --> 00:08:11,180 So you'll notice there are two kinds 190 00:08:11,180 --> 00:08:12,730 of build-to packages going on. 191 00:08:12,730 --> 00:08:14,452 Just take a look at that and see what 192 00:08:14,452 --> 00:08:16,910 cause somebody else to think differently than what you did. 193 00:08:16,910 --> 00:08:19,430 I also wanted you guys to notice this table here. 194 00:08:19,430 --> 00:08:20,660 Because I saw you guys. 195 00:08:20,660 --> 00:08:23,180 You flipped your bins upside down when 196 00:08:23,180 --> 00:08:24,590 you are ready for a new ones. 197 00:08:24,590 --> 00:08:27,245 That was your signals? 198 00:08:27,245 --> 00:08:29,120 AUDIENCE: This wasn't, we don't want anymore. 199 00:08:29,120 --> 00:08:29,750 This is, we do. 200 00:08:29,750 --> 00:08:30,920 ANNALISA WEIGEL: And that's you do want more. 201 00:08:30,920 --> 00:08:33,799 So I saw that and I thought that was an interesting practice. 202 00:08:33,799 --> 00:08:35,716 Anybody else have a practice that worked well 203 00:08:35,716 --> 00:08:37,549 for them that might not come out when you're 204 00:08:37,549 --> 00:08:41,690 doing your table tours and just looking at the static display? 205 00:08:41,690 --> 00:08:43,220 AUDIENCE: The clock [INAUDIBLE]. 206 00:08:43,220 --> 00:08:46,460 AUDIENCE: We used one timer for all four of us. 207 00:08:46,460 --> 00:08:47,720 AUDIENCE: Oh no. 208 00:08:47,720 --> 00:08:49,348 [INTERPOSING VOICES] 209 00:08:49,348 --> 00:08:49,890 AUDIENCE: No. 210 00:08:49,890 --> 00:08:50,495 Then we're all synchronized. 211 00:08:50,495 --> 00:08:50,995 We're all-- 212 00:08:50,995 --> 00:08:56,413 [INTERPOSING VOICES] 213 00:08:56,413 --> 00:08:58,580 ANNALISA WEIGEL: So there's a best practice that you 214 00:08:58,580 --> 00:09:00,470 might consider adopting. 215 00:09:00,470 --> 00:09:02,330 Did we have a comment from this team here? 216 00:09:02,330 --> 00:09:03,110 AUDIENCE: Yeah. 217 00:09:03,110 --> 00:09:05,358 We color coded our bins and then color 218 00:09:05,358 --> 00:09:07,213 coded our standard order sheets so 219 00:09:07,213 --> 00:09:09,600 that she would be able to identify more quickly. 220 00:09:09,600 --> 00:09:11,600 ANNALISA WEIGEL: OK, so did everybody hear that? 221 00:09:11,600 --> 00:09:13,670 There's color coding of bins and color 222 00:09:13,670 --> 00:09:15,380 coding of the different standard orders 223 00:09:15,380 --> 00:09:17,120 to try to match visual inspection 224 00:09:17,120 --> 00:09:19,325 and get quality good. 225 00:09:19,325 --> 00:09:21,440 AUDIENCE: We also color coded. 226 00:09:21,440 --> 00:09:23,976 So the red bin goes here. 227 00:09:23,976 --> 00:09:26,210 [INAUDIBLE] 228 00:09:26,210 --> 00:09:29,300 ANNALISA WEIGEL: So they have three marks of color 229 00:09:29,300 --> 00:09:32,240 to try to get that all coordinated. 230 00:09:32,240 --> 00:09:34,160 Other best practices that won't come out again 231 00:09:34,160 --> 00:09:36,500 if you're just looking around? 232 00:09:36,500 --> 00:09:39,020 AUDIENCE: Yes, we did a continuous delivery cycles up 233 00:09:39,020 --> 00:09:40,640 until we're done. 234 00:09:43,215 --> 00:09:45,590 Because we noticed that there was variability on how long 235 00:09:45,590 --> 00:09:47,840 it took to fill the bin. 236 00:09:47,840 --> 00:09:51,283 [INAUDIBLE] 237 00:09:51,283 --> 00:09:53,200 ALLEN HAGGERTY: The Lean Aerospace Initiative, 238 00:09:53,200 --> 00:09:55,935 which funded all this stuff years ago, 239 00:09:55,935 --> 00:09:58,660 is the consortium of all the aerospace 240 00:09:58,660 --> 00:10:00,730 companies and the government. 241 00:10:00,730 --> 00:10:05,430 And in these conferences that we have, 242 00:10:05,430 --> 00:10:07,615 the suppliers, the engineers, the manufacturers 243 00:10:07,615 --> 00:10:11,500 would get up and make presentations to basically show 244 00:10:11,500 --> 00:10:12,710 how they do things. 245 00:10:12,710 --> 00:10:14,590 And that's the benefit of this-- 246 00:10:14,590 --> 00:10:17,440 makes the benchmarking a lot easier because people basically 247 00:10:17,440 --> 00:10:20,860 put their heads together and everybody benefits. 248 00:10:20,860 --> 00:10:23,910 I mean there's an annual fee that the companies pay 249 00:10:23,910 --> 00:10:25,332 that supports all that. 250 00:10:25,332 --> 00:10:28,180 But they in fact get the advantages of-- 251 00:10:28,180 --> 00:10:30,090 gee, we took a tour through so many factory 252 00:10:30,090 --> 00:10:33,130 and they going a red light that goes on or something like that. 253 00:10:33,130 --> 00:10:38,410 So all the aerospace companies benefit from the conversation 254 00:10:38,410 --> 00:10:41,350 and the discussion and the presentations 255 00:10:41,350 --> 00:10:46,965 and the factory tours of each other's organization. 256 00:10:46,965 --> 00:10:48,340 HUGH MCMANUS: The tools that they 257 00:10:48,340 --> 00:10:53,890 use include simple organization, which 258 00:10:53,890 --> 00:10:57,280 they can use lean principles like 5S and visual control 259 00:10:57,280 --> 00:10:58,870 to clean up their workplace. 260 00:10:58,870 --> 00:11:00,670 Just get the basic process working. 261 00:11:00,670 --> 00:11:01,720 OK? 262 00:11:01,720 --> 00:11:03,970 Balancing a workload. 263 00:11:03,970 --> 00:11:06,010 Which can be planned around lean principles 264 00:11:06,010 --> 00:11:08,080 like pack time, single piece flow. 265 00:11:08,080 --> 00:11:11,320 Which essentially allows them to move work between plants 266 00:11:11,320 --> 00:11:15,880 to clear bottlenecks and get the work balanced. 267 00:11:15,880 --> 00:11:19,210 They can tear down or move facilities. 268 00:11:19,210 --> 00:11:24,340 Again, based on lean principles, not just random action. 269 00:11:24,340 --> 00:11:30,130 And they can modernize this archaic order system. 270 00:11:30,130 --> 00:11:32,350 Again, planned using lean principles. 271 00:11:32,350 --> 00:11:35,860 And there's a mechanic in the simulation to allow 272 00:11:35,860 --> 00:11:38,350 a paperless-- there's actually still a little bit of paper 273 00:11:38,350 --> 00:11:39,640 but much less-- 274 00:11:39,640 --> 00:11:43,690 ordering system that would simulate a modern web-based 275 00:11:43,690 --> 00:11:46,840 perhaps, or certainly electronics-based 276 00:11:46,840 --> 00:11:49,180 inventory management system. 277 00:11:49,180 --> 00:11:51,310 One of the key features is the simulation 278 00:11:51,310 --> 00:11:54,710 allows us is to use data. 279 00:11:54,710 --> 00:11:58,150 It's very difficult to go out to a real aircraft manufacturing 280 00:11:58,150 --> 00:11:59,990 plant and play with it. 281 00:11:59,990 --> 00:12:03,220 With the simulation, we can play with it in these 12 minute 282 00:12:03,220 --> 00:12:08,440 rounds and create and use data that we've 283 00:12:08,440 --> 00:12:12,070 collected to both plan improvements and track 284 00:12:12,070 --> 00:12:12,670 processes. 285 00:12:12,670 --> 00:12:15,148 So we can keep track of how long does it take to do things? 286 00:12:15,148 --> 00:12:16,315 How many parts are involved? 287 00:12:18,940 --> 00:12:22,117 What's the delay involved in ordering parts, et cetera? 288 00:12:22,117 --> 00:12:23,950 And we can do that quantitatively and that's 289 00:12:23,950 --> 00:12:27,130 one of the key aspects of most product improvement techniques. 290 00:12:27,130 --> 00:12:29,170 It's to use the data and let it tell you 291 00:12:29,170 --> 00:12:32,740 what to do, not just make things up as you go along. 292 00:12:32,740 --> 00:12:35,500 Be entirely dependent on common sense 293 00:12:35,500 --> 00:12:38,380 or experience to do these kinds of improvements. 294 00:12:38,380 --> 00:12:39,760 And this data can be incorporated 295 00:12:39,760 --> 00:12:42,940 into classic lean tools like value-stream mapping. 296 00:12:42,940 --> 00:12:45,880 This is the same data plotted in the classic lean value-stream 297 00:12:45,880 --> 00:12:46,930 map. 298 00:12:46,930 --> 00:12:50,440 Again it gives them the opportunity to touch a tool, 299 00:12:50,440 --> 00:12:54,700 to actually use it, to actually fill out the data with data 300 00:12:54,700 --> 00:12:58,060 that they've collected from at least a simulated reality 301 00:12:58,060 --> 00:13:02,350 and then use that to analyze it, so that they 302 00:13:02,350 --> 00:13:04,330 can find bottlenecks. 303 00:13:04,330 --> 00:13:07,900 They can find non-value added steps. 304 00:13:07,900 --> 00:13:11,920 They can find places where paperwork and lack 305 00:13:11,920 --> 00:13:15,280 of synchronization are slowing the process down 306 00:13:15,280 --> 00:13:19,560 and then focus their improvements on those areas. 307 00:13:19,560 --> 00:13:23,080 Finally at the end of the simulation, 308 00:13:23,080 --> 00:13:28,300 we essentially, as we do in the real world with lean thinking, 309 00:13:28,300 --> 00:13:31,630 ask them to expand their horizons. 310 00:13:31,630 --> 00:13:33,370 Expand the boundaries of the enterprise 311 00:13:33,370 --> 00:13:34,828 that they're considering and seeing 312 00:13:34,828 --> 00:13:37,300 if they can get bigger payoffs by doing more. 313 00:13:37,300 --> 00:13:39,760 By bringing in more functions. 314 00:13:39,760 --> 00:13:42,130 In this case, there's not an engineering function 315 00:13:42,130 --> 00:13:45,160 in the simulation, but we do allow them to redesign 316 00:13:45,160 --> 00:13:47,980 the airplane to cut part count. 317 00:13:47,980 --> 00:13:49,330 Reduce part types. 318 00:13:49,330 --> 00:13:51,580 Fix problems with the airplane. 319 00:13:51,580 --> 00:13:53,320 Make it easier to assemble. 320 00:13:53,320 --> 00:13:54,470 Do all of the things-- 321 00:13:54,470 --> 00:13:59,620 all of the engineering functions that facilitate 322 00:13:59,620 --> 00:14:01,420 lean in the real world. 323 00:14:01,420 --> 00:14:05,260 And again, touch it, understand it, understand it in context, 324 00:14:05,260 --> 00:14:08,230 and then see how it works in the final round. 325 00:14:08,230 --> 00:14:13,390 And again, by rebalancing work, by redesigning the airplane, 326 00:14:13,390 --> 00:14:17,860 by changing the facility organization and further model 327 00:14:17,860 --> 00:14:20,770 modernizing the supply chain, by getting 328 00:14:20,770 --> 00:14:25,030 into a really clean modern just-in-time supply chain. 329 00:14:25,030 --> 00:14:27,610 Using the lean principles and implementing it 330 00:14:27,610 --> 00:14:32,090 on the simulation, they can get an outstanding process out 331 00:14:32,090 --> 00:14:32,590 of it. 332 00:14:32,590 --> 00:14:35,950 And that gives them a real intuitive and tactile feel 333 00:14:35,950 --> 00:14:40,630 for how lean type product improvement principles can 334 00:14:40,630 --> 00:14:43,780 be used to not just make a process better, 335 00:14:43,780 --> 00:14:46,600 but to make it astonishingly better in a way 336 00:14:46,600 --> 00:14:49,630 that they usually do not think is possible 337 00:14:49,630 --> 00:14:51,660 when they start the simulation. 338 00:14:51,660 --> 00:14:54,810 Another thing that's done is throughout the simulation, 339 00:14:54,810 --> 00:14:58,960 we embed learning by doing mini lessons. 340 00:14:58,960 --> 00:15:00,810 And this is just a single example. 341 00:15:00,810 --> 00:15:02,310 Kanban systems. 342 00:15:02,310 --> 00:15:06,900 Kanbans are a inventory management ordering 343 00:15:06,900 --> 00:15:10,770 and transport system which is difficult to lecture 344 00:15:10,770 --> 00:15:13,627 to because it's a very simple thing that does a lot of-- that 345 00:15:13,627 --> 00:15:15,210 has a lot of different functionalities 346 00:15:15,210 --> 00:15:16,140 in the real world. 347 00:15:16,140 --> 00:15:19,170 And solves a lot of problems in ways that are sometimes 348 00:15:19,170 --> 00:15:20,190 not intuitive. 349 00:15:20,190 --> 00:15:23,910 In the simulation, they use Kanbans to basically solve 350 00:15:23,910 --> 00:15:27,720 their inventory management and supply chain problems. 351 00:15:27,720 --> 00:15:33,390 And they get both repeated reintroduction to the concept 352 00:15:33,390 --> 00:15:36,090 and what they're doing, and mentored execution 353 00:15:36,090 --> 00:15:38,290 of that concept in the simulated world, 354 00:15:38,290 --> 00:15:41,580 so that they really do get an understanding of how 355 00:15:41,580 --> 00:15:44,820 a simple system like Kanban can serve so many functions 356 00:15:44,820 --> 00:15:45,945 and solve some problems. 357 00:15:53,430 --> 00:15:55,680 The overall result-- and this is typical data 358 00:15:55,680 --> 00:15:57,390 from a real event is that they can 359 00:15:57,390 --> 00:16:00,150 go from producing no airplanes, or maybe one, 360 00:16:00,150 --> 00:16:01,770 the first time they try. 361 00:16:01,770 --> 00:16:04,770 To producing a dozen the last time, in the same time 362 00:16:04,770 --> 00:16:10,050 and using the same basic capabilities. 363 00:16:10,050 --> 00:16:12,150 They never get to throw the hourglasses away. 364 00:16:12,150 --> 00:16:14,550 It never turns into a LEGO building race. 365 00:16:14,550 --> 00:16:16,540 This isn't just a learning curve. 366 00:16:16,540 --> 00:16:19,680 What they've done is the process as it exists 367 00:16:19,680 --> 00:16:21,390 and made it much, much better. 368 00:16:21,390 --> 00:16:26,680 And tracking along with that is the financials, 369 00:16:26,680 --> 00:16:29,370 which go from losing a lot of money to making a lot. 370 00:16:29,370 --> 00:16:31,290 Not surprisingly, but again, they 371 00:16:31,290 --> 00:16:34,680 get a feel for how this kind of production efficiency 372 00:16:34,680 --> 00:16:38,550 can lead to financial performance. 373 00:16:38,550 --> 00:16:41,940 OK, so we had a successful conclusion 374 00:16:41,940 --> 00:16:44,280 of our simulation exercise. 375 00:16:44,280 --> 00:16:46,140 All of our tables managed to produce 376 00:16:46,140 --> 00:16:47,940 at least eight aircraft. 377 00:16:47,940 --> 00:16:49,770 One table got all the way up to the 12 378 00:16:49,770 --> 00:16:51,480 that the customer really wanted. 379 00:16:51,480 --> 00:16:53,640 And we had an 11 and a 10. 380 00:16:53,640 --> 00:16:57,720 Everybody got there by a somewhat different route 381 00:16:57,720 --> 00:17:00,750 and we learned some lessons along the way. 382 00:17:00,750 --> 00:17:02,940 Our group that produced eight. 383 00:17:02,940 --> 00:17:06,329 Now that was still better than the theoretical maximum 384 00:17:06,329 --> 00:17:09,190 six they were making before. 385 00:17:09,190 --> 00:17:12,420 But they didn't meet the theoretical capacity of 12 386 00:17:12,420 --> 00:17:15,329 because they still hadn't ironed out issues with their supply 387 00:17:15,329 --> 00:17:16,829 chain and with coordinating. 388 00:17:16,829 --> 00:17:19,410 It wasn't that they didn't have the theoretical capacity, 389 00:17:19,410 --> 00:17:22,890 it was that the coordination of the different components 390 00:17:22,890 --> 00:17:27,480 of their enterprise wasn't completely ironed out yet. 391 00:17:27,480 --> 00:17:31,440 So they didn't meet their production goals. 392 00:17:31,440 --> 00:17:32,340 Very interesting. 393 00:17:32,340 --> 00:17:35,340 The group that made 11 airplanes did get everything coordinated. 394 00:17:35,340 --> 00:17:36,840 They did a very good job. 395 00:17:36,840 --> 00:17:38,010 One order. 396 00:17:38,010 --> 00:17:41,400 One order was one piece short. 397 00:17:41,400 --> 00:17:44,190 And in a lean system, you're very vulnerable to that kind 398 00:17:44,190 --> 00:17:44,820 of disruption. 399 00:17:44,820 --> 00:17:45,570 That one order. 400 00:17:45,570 --> 00:17:47,490 That one piece in that one order cost them 401 00:17:47,490 --> 00:17:49,800 an airplane, because it disrupted 402 00:17:49,800 --> 00:17:51,420 their synchronization. 403 00:17:51,420 --> 00:17:53,400 It took them a minute to recover. 404 00:17:53,400 --> 00:17:55,140 That was an airplane. 405 00:17:55,140 --> 00:18:00,240 Still that is a known issue with lean production systems, not 406 00:18:00,240 --> 00:18:01,800 necessarily a bad thing. 407 00:18:01,800 --> 00:18:05,130 That the issue-- the problem that 408 00:18:05,130 --> 00:18:08,895 caused the one order to be bad was surfaced immediately. 409 00:18:08,895 --> 00:18:10,980 And in the future-- that happened actually 410 00:18:10,980 --> 00:18:13,720 early in the round and they didn't do it again. 411 00:18:13,720 --> 00:18:17,310 And of course they achieved 11, which is a lot better 412 00:18:17,310 --> 00:18:19,230 than seven aircraft. 413 00:18:19,230 --> 00:18:22,780 And we had one group that was hitting on all cylinders 414 00:18:22,780 --> 00:18:24,960 and managed to produce the aircraft a minute 415 00:18:24,960 --> 00:18:27,390 that the customers really wanted. 416 00:18:27,390 --> 00:18:29,940 Interestingly too, if we look over the course 417 00:18:29,940 --> 00:18:35,640 of the whole day, the production-- a little bit 418 00:18:35,640 --> 00:18:36,300 of variation. 419 00:18:36,300 --> 00:18:39,690 Basically everybody's improving production as they go along. 420 00:18:39,690 --> 00:18:43,890 The financial results show some interesting detail. 421 00:18:43,890 --> 00:18:46,720 It's harder to see in the production diagram. 422 00:18:46,720 --> 00:18:52,200 Which is that although everybody's profit improved, 423 00:18:52,200 --> 00:18:53,820 people took different paths. 424 00:18:53,820 --> 00:18:56,280 And this has been a great class for this 425 00:18:56,280 --> 00:19:00,270 because basically the paths that people took pretty much 426 00:19:00,270 --> 00:19:05,430 mirror the kinds of things that can happen in the real world 427 00:19:05,430 --> 00:19:09,120 when you go into improvement events. 428 00:19:09,120 --> 00:19:12,090 Group number one started out losing a lot of money. 429 00:19:12,090 --> 00:19:14,560 As soon as they stabilized their traditional process, 430 00:19:14,560 --> 00:19:16,300 they actually managed to make money. 431 00:19:16,300 --> 00:19:18,810 And when they disrupted it, trying to lean it out. 432 00:19:18,810 --> 00:19:21,900 They had what we call a worse-before-better. 433 00:19:21,900 --> 00:19:25,410 Things actually got worse until they got better again 434 00:19:25,410 --> 00:19:29,520 and stabilized at a high profit situation. 435 00:19:29,520 --> 00:19:35,160 Group number two showed a much steadier increase in profit. 436 00:19:35,160 --> 00:19:38,640 They basically showed an almost linear improvement. 437 00:19:38,640 --> 00:19:42,900 So they were not so disrupted by change. 438 00:19:42,900 --> 00:19:47,370 Didn't come to quick results, but by learning slowly 439 00:19:47,370 --> 00:19:49,800 and steadily as they went through the transformation 440 00:19:49,800 --> 00:19:52,820 process, managed to increase their profits steadily. 441 00:19:52,820 --> 00:19:56,440 That's nice because that looks good. 442 00:19:56,440 --> 00:19:58,940 It's not always what happens. 443 00:19:58,940 --> 00:20:04,550 The green te-- sorry, blue team, showed again, 444 00:20:04,550 --> 00:20:06,560 a typical reaction. 445 00:20:06,560 --> 00:20:10,550 They stabilized and then in the actual improvement round, 446 00:20:10,550 --> 00:20:13,040 the round where they changed things, 447 00:20:13,040 --> 00:20:16,220 showed at best steady financial results. 448 00:20:16,220 --> 00:20:18,320 So this was learning in a given state 449 00:20:18,320 --> 00:20:20,790 but they would have maxed out there. 450 00:20:20,790 --> 00:20:25,280 During the transformation they didn't make more money, 451 00:20:25,280 --> 00:20:29,253 but that set them up for the next round 452 00:20:29,253 --> 00:20:30,170 where they made a lot. 453 00:20:30,170 --> 00:20:32,390 And again during the next transformation 454 00:20:32,390 --> 00:20:33,600 they flattened off again. 455 00:20:33,600 --> 00:20:36,320 This is a lot nicer than that worse-before-better, 456 00:20:36,320 --> 00:20:37,820 but it's still very typical. 457 00:20:37,820 --> 00:20:39,950 While you're investing the resources. 458 00:20:39,950 --> 00:20:41,270 While you're changing things. 459 00:20:41,270 --> 00:20:43,820 You can't expect the dramatic financial results 460 00:20:43,820 --> 00:20:45,200 to happen right away. 461 00:20:45,200 --> 00:20:48,800 What you do is set yourself up for dramatic improvements 462 00:20:48,800 --> 00:20:50,510 in the next period. 463 00:20:50,510 --> 00:20:54,740 And we had a final group which also did 464 00:20:54,740 --> 00:20:56,300 the worse-before-better thing. 465 00:20:56,300 --> 00:21:00,260 It had a little bit of a unfortunate end 466 00:21:00,260 --> 00:21:02,780 result, which is the very last round they actually 467 00:21:02,780 --> 00:21:03,410 had it worse. 468 00:21:03,410 --> 00:21:06,080 And that was the group that only made the eight aircraft. 469 00:21:06,080 --> 00:21:09,110 They were quite certain if we'd done another round that they 470 00:21:09,110 --> 00:21:11,300 could have gotten the 12 and in fact 471 00:21:11,300 --> 00:21:15,860 completed their zig-zag worse-before-better journey. 472 00:21:15,860 --> 00:21:20,050 So that's a description of the simulation and how it's used. 473 00:21:20,050 --> 00:21:21,920 We're going to do a brief description 474 00:21:21,920 --> 00:21:25,820 of the pedagogical goals of the simulation 475 00:21:25,820 --> 00:21:29,690 and how we think they've been achieved in the Lean Academy 476 00:21:29,690 --> 00:21:31,580 context. 477 00:21:31,580 --> 00:21:34,040 We said that we wanted it to increase the comprehension 478 00:21:34,040 --> 00:21:37,370 of the curriculum. 479 00:21:37,370 --> 00:21:44,000 And there is some literature evidence that this works. 480 00:21:44,000 --> 00:21:47,780 In particular, in the computer world people 481 00:21:47,780 --> 00:21:50,450 have played computer games versus static computer 482 00:21:50,450 --> 00:21:51,215 websites. 483 00:21:51,215 --> 00:21:53,090 And it has been shown that the little games-- 484 00:21:53,090 --> 00:21:54,830 and these are little toy games. 485 00:21:54,830 --> 00:21:58,830 But the little games basically make people retain 486 00:21:58,830 --> 00:22:01,200 the material much better. 487 00:22:01,200 --> 00:22:04,070 And also if you look at behavior. 488 00:22:04,070 --> 00:22:07,430 There's been studies on things like healthy diet 489 00:22:07,430 --> 00:22:11,240 that people that have learned through game-based learning as 490 00:22:11,240 --> 00:22:16,147 opposed to static learning actually take-- not only learn 491 00:22:16,147 --> 00:22:18,230 and retain the information, better but it actually 492 00:22:18,230 --> 00:22:20,040 affects the outcome. 493 00:22:20,040 --> 00:22:21,140 So that's good. 494 00:22:21,140 --> 00:22:24,290 That evidence is there. 495 00:22:24,290 --> 00:22:27,710 We also hoped that there's better understanding 496 00:22:27,710 --> 00:22:30,410 of the context and the holistic nature of the material. 497 00:22:30,410 --> 00:22:32,780 And we hoped that they learn through experience. 498 00:22:32,780 --> 00:22:35,570 That it engages different learning modes and that 499 00:22:35,570 --> 00:22:36,980 it allows them to practice field, 500 00:22:36,980 --> 00:22:39,770 to actually touch and use the ideas. 501 00:22:39,770 --> 00:22:42,255 These are supported as goals. 502 00:22:42,255 --> 00:22:44,630 But there's not really a whole lot of scientific evidence 503 00:22:44,630 --> 00:22:45,590 that this works. 504 00:22:45,590 --> 00:22:48,470 Intuitively, the evidence is pretty powerful 505 00:22:48,470 --> 00:22:52,470 and the anecdotal experience from the students is powerful. 506 00:22:52,470 --> 00:22:54,380 It's not a proven outcome. 507 00:22:54,380 --> 00:22:56,090 And we can certainly say that we've 508 00:22:56,090 --> 00:22:58,730 observed greatly increased student 509 00:22:58,730 --> 00:23:01,410 involvement and excitement. 510 00:23:01,410 --> 00:23:03,920 AUDIENCE: Yeah, when we were on the same team for the LEGO 511 00:23:03,920 --> 00:23:06,870 simulation and it was a lot of fun. 512 00:23:06,870 --> 00:23:08,870 Especially since we got a little competitive 513 00:23:08,870 --> 00:23:11,690 with the other teams and trying to build the most airplanes. 514 00:23:11,690 --> 00:23:13,545 But that was really cool. 515 00:23:13,545 --> 00:23:15,170 It's something that we played with ever 516 00:23:15,170 --> 00:23:17,810 since we were little kids and to be 517 00:23:17,810 --> 00:23:20,840 able to build something but then apply the lean principles. 518 00:23:20,840 --> 00:23:23,390 And it was really amazing to see how much we 519 00:23:23,390 --> 00:23:25,160 learned through that. 520 00:23:25,160 --> 00:23:26,900 AUDIENCE: It was probably the best way 521 00:23:26,900 --> 00:23:30,140 of demonstrating how process that I 522 00:23:30,140 --> 00:23:34,100 thought it was efficient at first and after applying lean. 523 00:23:34,100 --> 00:23:37,370 We didn't think we could make 12 airplanes in 12 minutes 524 00:23:37,370 --> 00:23:39,140 but well-- we almost made it. 525 00:23:39,140 --> 00:23:40,220 We made 10. 526 00:23:40,220 --> 00:23:42,800 But it is possible to do what some 527 00:23:42,800 --> 00:23:44,750 believe is impossible at first. 528 00:23:44,750 --> 00:23:48,440 And after applying the analysis and getting all the processes 529 00:23:48,440 --> 00:23:50,760 down correctly, we were getting pretty close. 530 00:23:50,760 --> 00:23:51,830 AUDIENCE: Yeah, I mean that's pretty amazing. 531 00:23:51,830 --> 00:23:54,340 I was looking at the chart up there and I was like, wait. 532 00:23:54,340 --> 00:23:57,050 We really only made one in 12 minutes the first time? 533 00:23:57,050 --> 00:24:00,093 And then went all the way up to 10 so. 534 00:24:00,093 --> 00:24:01,520 AUDIENCE: We're impressed. 535 00:24:01,520 --> 00:24:02,930 AUDIENCE: Yeah. 536 00:24:02,930 --> 00:24:04,680 HUGH MCMANUS: So we think this is working. 537 00:24:04,680 --> 00:24:11,330 We also have had very positive experience with basically 538 00:24:11,330 --> 00:24:12,800 teaching complicated systems. 539 00:24:12,800 --> 00:24:14,630 Most of the previous literature evidence 540 00:24:14,630 --> 00:24:16,550 was on relatively simple things. 541 00:24:16,550 --> 00:24:19,550 Fact-based things. 542 00:24:19,550 --> 00:24:21,620 We're actually trying to teach a system that 543 00:24:21,620 --> 00:24:22,860 affects other systems. 544 00:24:22,860 --> 00:24:26,270 So it's a complicated body of knowledge, 545 00:24:26,270 --> 00:24:27,980 body of understanding, that the students 546 00:24:27,980 --> 00:24:30,770 are expected to absorb in a relatively short time. 547 00:24:30,770 --> 00:24:32,540 And most of these systems are not 548 00:24:32,540 --> 00:24:34,730 available for manipulation for teaching purposes. 549 00:24:34,730 --> 00:24:38,065 You can't go play with an airplane factory. 550 00:24:38,065 --> 00:24:40,190 We found that the students have a good experience-- 551 00:24:40,190 --> 00:24:41,900 and this experience is not limited 552 00:24:41,900 --> 00:24:44,150 to this particular simulation, although this 553 00:24:44,150 --> 00:24:46,190 is a good exemplar of it. 554 00:24:46,190 --> 00:24:50,210 If the simulation is complex enough to capture the key 555 00:24:50,210 --> 00:24:53,180 features, including the emergent behaviors of the system. 556 00:24:53,180 --> 00:24:56,630 If it's too simple, you're not really changing anything. 557 00:24:56,630 --> 00:24:58,820 You're not really changing a system that 558 00:24:58,820 --> 00:25:02,090 has unexpected behaviors, so you're not 559 00:25:02,090 --> 00:25:04,130 going to capture this kind of learning. 560 00:25:04,130 --> 00:25:05,450 On the other hand, it has to be simple enough 561 00:25:05,450 --> 00:25:06,992 to have an acceptable learning curve. 562 00:25:06,992 --> 00:25:09,830 If it takes three days to learn it's not 563 00:25:09,830 --> 00:25:11,930 going to be a teaching tool. 564 00:25:11,930 --> 00:25:14,960 And of course, it has to be fast enough that you 565 00:25:14,960 --> 00:25:18,860 can do multiple cycles of learning within the teaching 566 00:25:18,860 --> 00:25:20,220 period. 567 00:25:20,220 --> 00:25:23,150 It also has to be credible in the sense 568 00:25:23,150 --> 00:25:26,010 that it can't have artifacts that the students say, 569 00:25:26,010 --> 00:25:29,510 well, this is not realistic and therefore I 570 00:25:29,510 --> 00:25:33,080 will dismiss the experience because I don't believe it. 571 00:25:33,080 --> 00:25:35,840 And it has to be fun to keep people engaged. 572 00:25:35,840 --> 00:25:38,900 And basically on this set of criteria, 573 00:25:38,900 --> 00:25:43,190 we think that the simulation that we use in the Lean Academy 574 00:25:43,190 --> 00:25:45,200 is pretty good. 575 00:25:45,200 --> 00:25:47,780 Students think it's pretty good too. 576 00:25:47,780 --> 00:25:50,360 This is feedback from about 200 students, 577 00:25:50,360 --> 00:25:53,600 194 students over a couple of years of Lean Academies. 578 00:25:53,600 --> 00:25:57,140 And we consistently get the highest score 579 00:25:57,140 --> 00:26:00,050 of the types of learning, both other active learning 580 00:26:00,050 --> 00:26:02,870 and lecturing materials. 581 00:26:02,870 --> 00:26:06,913 That the Lean Academy simulation provides positive reinforcement 582 00:26:06,913 --> 00:26:07,580 of the concepts. 583 00:26:07,580 --> 00:26:09,770 That's the wording of the question 584 00:26:09,770 --> 00:26:13,020 and the students agree that that's the case. 585 00:26:13,020 --> 00:26:16,790 Just qualitatively we also get some written feedback 586 00:26:16,790 --> 00:26:18,470 and verbal feedback. 587 00:26:18,470 --> 00:26:23,540 And it appears, and again this is unprompted. 588 00:26:23,540 --> 00:26:25,910 We asked them the general question, 589 00:26:25,910 --> 00:26:27,980 what do you like about the course 590 00:26:27,980 --> 00:26:29,150 and what do you don't like? 591 00:26:29,150 --> 00:26:30,710 And what we find is what they like 592 00:26:30,710 --> 00:26:33,760 is what we're hoping, which is that it increases 593 00:26:33,760 --> 00:26:35,960 the comprehension of the curriculum. 594 00:26:35,960 --> 00:26:38,870 That the hands-on learning and practice field experiences 595 00:26:38,870 --> 00:26:40,610 are valuable to them. 596 00:26:40,610 --> 00:26:44,450 And that it increases their involvement and excitement 597 00:26:44,450 --> 00:26:46,940 with the material. 598 00:26:46,940 --> 00:26:49,220 As well as-- this was not an explicit, 599 00:26:49,220 --> 00:26:51,650 but it does show up a lot in the student responses 600 00:26:51,650 --> 00:26:54,930 as a team building and camaraderie building activity. 601 00:26:54,930 --> 00:26:56,610 It's also very effective. 602 00:26:56,610 --> 00:26:58,370 And this is just a numerical breakdown 603 00:26:58,370 --> 00:27:01,430 of those kinds of responses. 604 00:27:01,430 --> 00:27:08,600 Out of 106 written responses, we got a lot of illuminatings. 605 00:27:08,600 --> 00:27:11,060 A fair number of, we liked the hands-on aspect. 606 00:27:11,060 --> 00:27:15,540 And the excitement and bonding were somewhat secondary 607 00:27:15,540 --> 00:27:16,550 but mentioned. 608 00:27:16,550 --> 00:27:20,090 As well as a big blob is just generic, we like it. 609 00:27:20,090 --> 00:27:22,970 But that doesn't tell us a whole bunch about why they like it 610 00:27:22,970 --> 00:27:26,930 but these do and it's what we're hoping. 611 00:27:26,930 --> 00:27:27,860 Caveats. 612 00:27:27,860 --> 00:27:29,390 Always important. 613 00:27:29,390 --> 00:27:32,000 This evaluation is based on satisfaction, not really 614 00:27:32,000 --> 00:27:32,570 outcomes. 615 00:27:32,570 --> 00:27:35,630 We don't track the students in their careers 616 00:27:35,630 --> 00:27:41,660 as aerospace engineer so we don't have outcome metrics yet. 617 00:27:41,660 --> 00:27:45,320 It's cost and time intensive to do this kind of thing. 618 00:27:45,320 --> 00:27:46,970 You need trained facilitators. 619 00:27:46,970 --> 00:27:50,415 It takes money to set up a facility 620 00:27:50,415 --> 00:27:52,040 to do this, couple of thousand dollars. 621 00:27:52,040 --> 00:27:53,060 That's the startup cost. 622 00:27:53,060 --> 00:27:55,340 Not the per each, although you do 623 00:27:55,340 --> 00:27:57,650 have to pay these people somehow. 624 00:27:57,650 --> 00:27:59,630 They're vulnerable to disruption. 625 00:27:59,630 --> 00:28:03,710 Logistics, facility, failure to keep on schedule errors 626 00:28:03,710 --> 00:28:07,970 can degrade the experience badly. 627 00:28:07,970 --> 00:28:12,080 Our simulation seems to be fairly robust 628 00:28:12,080 --> 00:28:15,140 but in general simulations are vulnerable to disruption. 629 00:28:15,140 --> 00:28:17,390 And you can't satisfy every learning style. 630 00:28:17,390 --> 00:28:20,030 Amusingly, we've had written feedback 631 00:28:20,030 --> 00:28:22,670 asking for both more and last simulation. 632 00:28:22,670 --> 00:28:25,100 Because some people feel they need more time 633 00:28:25,100 --> 00:28:29,180 to internalize the information that's there. 634 00:28:29,180 --> 00:28:33,800 Others get it quickly and wish they could move on 635 00:28:33,800 --> 00:28:36,290 to other learning modes. 636 00:28:36,290 --> 00:28:39,242 And another one, and it's a unexpected psychological 637 00:28:39,242 --> 00:28:40,700 effect, is that there's real stress 638 00:28:40,700 --> 00:28:42,890 in the simulated process. 639 00:28:42,890 --> 00:28:45,650 And that this sometimes creates difficulties 640 00:28:45,650 --> 00:28:46,730 with people's learning. 641 00:28:46,730 --> 00:28:48,770 Could create competition and bad feeling 642 00:28:48,770 --> 00:28:50,210 if it's not managed carefully. 643 00:28:50,210 --> 00:28:53,870 We've learned that that's something that is an issue that 644 00:28:53,870 --> 00:28:54,860 needs to be managed. 645 00:28:54,860 --> 00:28:57,140 And these, by the way, are typical issues 646 00:28:57,140 --> 00:28:59,520 for teaching simulations. 647 00:28:59,520 --> 00:29:01,400 Conclusion to this part. 648 00:29:01,400 --> 00:29:04,280 We have a unique simulation of aerospace enterprises. 649 00:29:04,280 --> 00:29:06,920 A subset of it is used in the Lean Academy. 650 00:29:06,920 --> 00:29:11,030 We think it works and it provides 651 00:29:11,030 --> 00:29:14,990 a laboratory for experiential learning of complex systems. 652 00:29:14,990 --> 00:29:18,530 There's not a whole lot of work in this area going on. 653 00:29:18,530 --> 00:29:20,612 We've had a very good experience with it. 654 00:29:20,612 --> 00:29:22,820 Certainly the feedback that we have from our students 655 00:29:22,820 --> 00:29:24,950 indicates that it's successful. 656 00:29:24,950 --> 00:29:27,080 And the caveats that we have for our simulation 657 00:29:27,080 --> 00:29:30,140 are typical of learning simulations in general. 658 00:29:30,140 --> 00:29:32,990 ERIC REBENTISCH: There are other aspects of the simulation that 659 00:29:32,990 --> 00:29:35,090 replicate the entire enterprise and I'm 660 00:29:35,090 --> 00:29:38,090 going to talk a little bit about each of those elements. 661 00:29:38,090 --> 00:29:41,960 And the simulations are modular so you 662 00:29:41,960 --> 00:29:44,870 can go through the manufacturing part 663 00:29:44,870 --> 00:29:46,820 or you can go through the engineering part, 664 00:29:46,820 --> 00:29:52,610 depending on what the learning objectives for the course are. 665 00:29:52,610 --> 00:29:54,750 You can combine them in various ways. 666 00:29:54,750 --> 00:29:57,110 You can combine the manufacturing 667 00:29:57,110 --> 00:29:59,390 with the engineering to teach specific lessons 668 00:29:59,390 --> 00:30:03,350 about transition to production and engineering support. 669 00:30:03,350 --> 00:30:05,870 You can look at just engineering alone 670 00:30:05,870 --> 00:30:08,210 if you are interested in understanding 671 00:30:08,210 --> 00:30:11,090 how engineering processes behave in a highly 672 00:30:11,090 --> 00:30:12,657 variable environment. 673 00:30:12,657 --> 00:30:14,240 So there's a lot of flexibility that's 674 00:30:14,240 --> 00:30:17,250 built into the simulation environment. 675 00:30:17,250 --> 00:30:20,900 So this is the simulation that you all experience here 676 00:30:20,900 --> 00:30:24,410 in the Academy that has a manufacturing core 677 00:30:24,410 --> 00:30:29,120 simulation and a simplified supplier 678 00:30:29,120 --> 00:30:32,090 base with a representative. 679 00:30:32,090 --> 00:30:35,810 If you expand out to the full supplier simulation, 680 00:30:35,810 --> 00:30:38,900 you get a much richer experience of understanding 681 00:30:38,900 --> 00:30:43,190 how ordering and fulfillment processes are 682 00:30:43,190 --> 00:30:45,140 dynamic in the enterprise. 683 00:30:45,140 --> 00:30:50,240 And learning much more about network organization structures 684 00:30:50,240 --> 00:30:56,030 and the way they behave and how effective coordination is 685 00:30:56,030 --> 00:30:56,900 critical to lean. 686 00:31:00,290 --> 00:31:04,640 For the full enterprise, you can add the dynamics 687 00:31:04,640 --> 00:31:09,830 of an engineering system that is supporting the manufacturing 688 00:31:09,830 --> 00:31:11,000 and supply base. 689 00:31:11,000 --> 00:31:13,280 And this is the full [INAUDIBLE] sim, 690 00:31:13,280 --> 00:31:16,460 where the engineering changes that you 691 00:31:16,460 --> 00:31:19,940 made during the course of the redesign of the airplane 692 00:31:19,940 --> 00:31:24,170 were done for essentially free in this simulation 693 00:31:24,170 --> 00:31:26,270 that you did in the Lean Academy. 694 00:31:26,270 --> 00:31:28,813 In the real enterprise simulation, 695 00:31:28,813 --> 00:31:30,230 you have to wait for the engineers 696 00:31:30,230 --> 00:31:32,330 to process those jobs. 697 00:31:32,330 --> 00:31:35,450 And that can lead to all sorts of interesting dynamics 698 00:31:35,450 --> 00:31:38,540 amongst the players and simulated organizational 699 00:31:38,540 --> 00:31:41,050 structures. 700 00:31:41,050 --> 00:31:43,390 There's also a service and support 701 00:31:43,390 --> 00:31:47,510 module that looks at aftermarket field support for the products 702 00:31:47,510 --> 00:31:52,330 and this introduces new and interesting complexities 703 00:31:52,330 --> 00:31:53,080 to the enterprise. 704 00:31:53,080 --> 00:31:56,260 Because you now have two main value 705 00:31:56,260 --> 00:31:57,970 streams and sources of revenues. 706 00:31:57,970 --> 00:32:00,490 You have to prioritize where you make 707 00:32:00,490 --> 00:32:03,060 improvements in the enterprise. 708 00:32:03,060 --> 00:32:03,560 All right. 709 00:32:03,560 --> 00:32:06,460 So there's another variant of the simulation 710 00:32:06,460 --> 00:32:09,730 that focuses on just an engineering organization. 711 00:32:09,730 --> 00:32:12,940 Most engineering organizations have multiple projects 712 00:32:12,940 --> 00:32:14,890 going on at a given time and they're 713 00:32:14,890 --> 00:32:16,090 competing for resources. 714 00:32:16,090 --> 00:32:18,350 And those projects aren't always the same. 715 00:32:18,350 --> 00:32:22,497 So this simulation looks at how you prioritize projects, 716 00:32:22,497 --> 00:32:24,580 how you structure the organization, how you manage 717 00:32:24,580 --> 00:32:26,610 the interactions so that you get the highest 718 00:32:26,610 --> 00:32:28,360 throughput through the system and the most 719 00:32:28,360 --> 00:32:30,310 return on investment for improvements 720 00:32:30,310 --> 00:32:32,030 through lean practices. 721 00:32:32,030 --> 00:32:35,740 So some of the things that we're not covered in the Lean Academy 722 00:32:35,740 --> 00:32:39,610 simulation are a more advanced economic system 723 00:32:39,610 --> 00:32:41,980 that allows you to make trade-offs, 724 00:32:41,980 --> 00:32:45,580 to understand what the impact of lean improvements are, 725 00:32:45,580 --> 00:32:48,520 and to actually calculate financial performance 726 00:32:48,520 --> 00:32:50,020 of the kind that you would typically 727 00:32:50,020 --> 00:32:52,450 track with a real company. 728 00:32:52,450 --> 00:32:54,580 There's also a lean calculator that 729 00:32:54,580 --> 00:32:58,450 can be used to evaluate whether one proposed improvement 730 00:32:58,450 --> 00:33:00,500 effort is better than another. 731 00:33:00,500 --> 00:33:03,910 And these are levels of analysis that 732 00:33:03,910 --> 00:33:08,710 are more in-depth tools, that are more sophisticated that 733 00:33:08,710 --> 00:33:11,210 can be added on to the sim environment. 734 00:33:11,210 --> 00:33:14,830 So in all, it's a fairly sophisticated system 735 00:33:14,830 --> 00:33:18,400 for teaching the impact of lean principles and practices 736 00:33:18,400 --> 00:33:20,570 on an enterprise. 737 00:33:20,570 --> 00:33:22,330 So there are a number of organizations 738 00:33:22,330 --> 00:33:26,710 that are using the web simulation and its variants 739 00:33:26,710 --> 00:33:28,960 and they have adopted it for their own use 740 00:33:28,960 --> 00:33:32,560 and are actually using it in their own internal training. 741 00:33:32,560 --> 00:33:36,580 So we have a method for actually disseminating these materials. 742 00:33:36,580 --> 00:33:40,780 And if there are any questions about adopting the simulation, 743 00:33:40,780 --> 00:33:42,340 the best place to go would be to send 744 00:33:42,340 --> 00:33:45,550 a message to ednet@mit.edu. 745 00:33:45,550 --> 00:33:49,030 And you can get more information about how you might 746 00:33:49,030 --> 00:33:52,050 adopt these training materials.