WEBVTT 00:00:00.000 --> 00:00:03.600 Welcome to today's deep dive. I am so incredibly 00:00:03.600 --> 00:00:05.960 thrilled to have you here with us. Today, our 00:00:05.960 --> 00:00:08.480 mission is to take a single comprehensive Wikipedia 00:00:08.480 --> 00:00:11.919 article and extract the absolute best nuggets 00:00:11.919 --> 00:00:14.400 of knowledge so you can walk away with a fresh 00:00:14.400 --> 00:00:17.039 perspective on how the world operates. Right. 00:00:17.320 --> 00:00:20.359 We're tackling something that. on the surface 00:00:20.359 --> 00:00:23.579 might sound a bit dry yeah we are decoding a 00:00:23.579 --> 00:00:26.420 concept that honestly sounds like the driest 00:00:26.420 --> 00:00:29.780 most corporate business jargon imaginable we're 00:00:29.780 --> 00:00:32.079 talking about lead time it sounds so technical 00:00:32.079 --> 00:00:35.619 it does but wait before your eyes glaze over 00:00:35.619 --> 00:00:37.560 i promise you this is actually the invisible 00:00:37.560 --> 00:00:39.719 force governing practically everything in your 00:00:39.719 --> 00:00:41.979 life absolutely everything it dictates how long 00:00:41.979 --> 00:00:44.399 it takes to get that shiny new car you just ordered 00:00:44.399 --> 00:00:46.759 it determines whether or not you survive a boss 00:00:46.759 --> 00:00:49.380 fight in your favorite video game And it is literally 00:00:49.380 --> 00:00:51.539 the underlying math of detecting life -threatening 00:00:51.539 --> 00:00:54.399 diseases. By the end of this deep dive, you're 00:00:54.399 --> 00:00:56.320 going to see the hidden mechanics of the waiting 00:00:56.320 --> 00:00:59.539 game everywhere you look. It really is the architectural 00:00:59.539 --> 00:01:03.380 framework of waiting. It's so easy for us to 00:01:03.380 --> 00:01:06.239 just assume that time is a fixed objective thing. 00:01:06.379 --> 00:01:08.239 You know, a day is a day, an hour is an hour. 00:01:09.370 --> 00:01:11.290 When you dive into the mechanics of how things 00:01:11.290 --> 00:01:13.489 are actually made and shipped and completed, 00:01:13.689 --> 00:01:16.870 you quickly realize that time is entirely relative. 00:01:16.989 --> 00:01:19.489 It depends on exactly where you are standing 00:01:19.489 --> 00:01:22.170 in a process. Understanding this completely shifts 00:01:22.170 --> 00:01:24.290 how you view almost every system around you, 00:01:24.390 --> 00:01:26.909 from the factory floor to your own daily schedule. 00:01:27.250 --> 00:01:29.709 Okay, let's unpack this. Broadly speaking, a 00:01:29.709 --> 00:01:32.670 lead time is the latency or the delay between 00:01:32.670 --> 00:01:35.810 the initiation and the completion of a process. 00:01:36.109 --> 00:01:37.890 Let's start with a really relatable example. 00:01:38.700 --> 00:01:41.519 Say you are buying a new car. The lead time between 00:01:41.519 --> 00:01:44.159 you placing that order and the manufacturer actually 00:01:44.159 --> 00:01:46.379 delivering the car into your driveway could be 00:01:46.379 --> 00:01:48.739 anywhere from two weeks to six months. Exactly. 00:01:48.859 --> 00:01:51.099 And that massive variance depends on a whole 00:01:51.099 --> 00:01:53.120 host of invisible processes happening behind 00:01:53.120 --> 00:01:56.040 the scenes. To really understand those particularities, 00:01:56.060 --> 00:01:58.000 you have to look at it from a manufacturing perspective, 00:01:58.060 --> 00:02:00.780 which operates on two distinct approaches. Okay, 00:02:00.819 --> 00:02:02.900 what's the first one? The first is make -to -order. 00:02:03.389 --> 00:02:06.030 If you are buying a highly customized car, you 00:02:06.030 --> 00:02:08.550 want a specific leather interior, a custom paint 00:02:08.550 --> 00:02:11.330 job, the upgraded sound system, that's make to 00:02:11.330 --> 00:02:13.729 order. In that scenario, the lead time is the 00:02:13.729 --> 00:02:15.889 entire duration from the moment your order is 00:02:15.889 --> 00:02:18.090 released to the actual production and shipment 00:02:18.090 --> 00:02:20.909 that fulfills your highly specific request. Got 00:02:20.909 --> 00:02:23.110 it. But let's say I don't care about custom leather. 00:02:23.229 --> 00:02:25.870 I just need a car today. That brings us to the 00:02:25.870 --> 00:02:28.569 second approach, which is make to stock. If it 00:02:28.569 --> 00:02:30.789 is a standard model that the manufacturer just 00:02:30.789 --> 00:02:33.330 wants ready on the dealership lot, the lead time 00:02:33.330 --> 00:02:35.770 is just the time taken from releasing the order 00:02:35.770 --> 00:02:38.469 to the production floor until that standard car 00:02:38.469 --> 00:02:40.550 is received into the finished goods inventory. 00:02:40.990 --> 00:02:42.969 So it's not just about how long it takes to bolt 00:02:42.969 --> 00:02:45.449 the doors onto the frame. It's about the entire 00:02:45.449 --> 00:02:48.389 lifespan of the request. The Chartered Institute 00:02:48.389 --> 00:02:50.689 of Procurement and Supply actually defines this 00:02:50.689 --> 00:02:53.830 as total lead time. And they argue it's really 00:02:53.830 --> 00:02:56.330 a combination of two completely different ticking 00:02:56.330 --> 00:02:59.770 clocks. Internal clock. And an external clock. 00:02:59.889 --> 00:03:02.949 Yeah, that internal clock is everything happening 00:03:02.949 --> 00:03:05.810 inside the buying organization. It's the time 00:03:05.810 --> 00:03:08.229 required to progress from simply identifying 00:03:08.229 --> 00:03:11.490 that a need exists to actually issuing the purchase 00:03:11.490 --> 00:03:13.930 order. Okay, so just the paperwork part, basically. 00:03:14.110 --> 00:03:16.270 Exactly. And only once that internal process 00:03:16.270 --> 00:03:18.490 is finished does the external lead time take 00:03:18.490 --> 00:03:21.530 over. That's the time required for the supplying 00:03:21.530 --> 00:03:23.789 organization to do their part. The development, 00:03:23.949 --> 00:03:26.030 the actual manufacturing, the dispatch, and the 00:03:26.030 --> 00:03:28.310 final delivery. Sweet. Think about every... time 00:03:28.310 --> 00:03:32.090 you, the listener, click buy on a website. As 00:03:32.090 --> 00:03:34.629 a consumer, does your lead time clock start the 00:03:34.629 --> 00:03:37.610 second you hit buy? Or is there a delay you aren't 00:03:37.610 --> 00:03:40.199 seeing? That is the illusion of modern convenience. 00:03:40.560 --> 00:03:42.479 You think it's just about the warehouse packing 00:03:42.479 --> 00:03:44.379 the box and handing it to a delivery driver. 00:03:44.659 --> 00:03:47.500 But there is an invisible delay running alongside 00:03:47.500 --> 00:03:49.479 all of that. What's fascinating here is that 00:03:49.479 --> 00:03:51.419 we often only think about the physical movement 00:03:51.419 --> 00:03:54.039 of goods. We picture conveyor belts and delivery 00:03:54.039 --> 00:03:56.699 trucks. But researchers who study supply chain 00:03:56.699 --> 00:03:59.479 performance, like Mason Jones and Toll, point 00:03:59.479 --> 00:04:02.080 out a massive bottleneck called information lead 00:04:02.080 --> 00:04:05.219 time. If a company wants to actually secure improvements 00:04:05.219 --> 00:04:07.680 and get things to you faster, they cannot just... 00:04:07.689 --> 00:04:10.210 shrink the material flow lead time they must 00:04:10.210 --> 00:04:12.830 equally reduce the information flow lead time 00:04:12.830 --> 00:04:15.129 I see where you're going because if the physical 00:04:15.129 --> 00:04:17.970 parts can move at lightning speed but the email 00:04:17.970 --> 00:04:20.230 telling the factory floor to actually move them 00:04:20.230 --> 00:04:22.649 takes three days to get routed to the right person 00:04:22.649 --> 00:04:25.589 you are still stuck waiting you're only as fast 00:04:25.589 --> 00:04:28.500 as your slowest piece of data Building information 00:04:28.500 --> 00:04:31.720 -enriched supply chains is critical. If the data 00:04:31.720 --> 00:04:33.560 doesn't move as fast as the delivery trucks, 00:04:33.720 --> 00:04:36.540 the whole system grinds to a halt no matter how 00:04:36.540 --> 00:04:39.220 efficient the physical manufacturing is. I never 00:04:39.220 --> 00:04:42.019 really thought about how disconnected the information 00:04:42.019 --> 00:04:44.519 and the physical items could be. And that brings 00:04:44.519 --> 00:04:46.740 us to something that completely shifted my perspective 00:04:46.740 --> 00:04:49.500 on this. Lead time is not an objective fact. 00:04:49.720 --> 00:04:52.360 It completely changes depending on who was asking 00:04:52.360 --> 00:04:54.550 the question. Let's look at how this plays out 00:04:54.550 --> 00:04:56.529 in the real world with something called the 2 00:04:56.529 --> 00:05:00.189 -5 -6 rule. Ah, yes, the company A and company 00:05:00.189 --> 00:05:03.629 B scenario. This is the perfect way to illustrate 00:05:03.629 --> 00:05:06.829 the hidden time sinks in any process. Let's walk 00:05:06.829 --> 00:05:08.930 through a hypothetical. Imagine you're running 00:05:08.930 --> 00:05:12.170 company A, and you need a very specific custom 00:05:12.170 --> 00:05:15.069 part for your assembly line. Company B, your 00:05:15.069 --> 00:05:17.250 supplier, can manufacture this part in exactly 00:05:17.250 --> 00:05:19.970 two days once they receive your order. Okay, 00:05:20.050 --> 00:05:22.680 two days to make it. Right. After that, it takes 00:05:22.680 --> 00:05:25.079 three days for company A to receive the part 00:05:25.079 --> 00:05:27.620 once it's shipped. Finally, it takes one additional 00:05:27.620 --> 00:05:30.279 day once it arrives before the part is actually 00:05:30.279 --> 00:05:32.339 ready to go into the manufacturing line at company 00:05:32.339 --> 00:05:35.620 A. Okay, so to recap the math, we have two days 00:05:35.620 --> 00:05:37.779 to make it, three days to ship it, and one day 00:05:37.779 --> 00:05:40.720 to prep it. Now, here is how that single reality 00:05:40.720 --> 00:05:44.199 generates three entirely different answers, which 00:05:44.199 --> 00:05:46.180 is where all the miscommunications happen. This 00:05:46.180 --> 00:05:48.649 is where it gets messy. Yeah. If Company A's 00:05:48.649 --> 00:05:51.329 supply chain department calls Company B and asks 00:05:51.329 --> 00:05:53.250 what the lead time for this part is, Company 00:05:53.250 --> 00:05:55.850 B will confidently court them two days. Because 00:05:55.850 --> 00:05:58.370 from the manufacturer's perspective, their job, 00:05:58.470 --> 00:06:00.870 the actual making of the thing, takes two days. 00:06:01.069 --> 00:06:04.230 But consider this. What happens when Company 00:06:04.230 --> 00:06:06.910 A's manufacturing division goes to their own 00:06:06.910 --> 00:06:10.050 supply chain division and asks for the lead time? 00:06:10.589 --> 00:06:14.009 The quote suddenly jumps to five days. The supply 00:06:14.009 --> 00:06:16.129 chain division knows they have to account for 00:06:16.129 --> 00:06:18.970 the two days of manufacturing, plus the three 00:06:18.970 --> 00:06:21.110 days it spends on a truck. And then the final 00:06:21.110 --> 00:06:24.889 twist. Imagine you are a line worker on the factory 00:06:24.889 --> 00:06:28.629 floor, and you ask your boss, When is this part 00:06:28.629 --> 00:06:30.550 actually going to be in my hands so I can do 00:06:30.550 --> 00:06:33.569 my job? The quote is now six days. Six days. 00:06:33.949 --> 00:06:35.970 Because the boss knows they have to add that 00:06:35.970 --> 00:06:37.930 final day of setup time once it comes off the 00:06:37.930 --> 00:06:40.970 truck. Two days, five days, six days. All for 00:06:40.970 --> 00:06:43.189 the exact same part from the exact same order. 00:06:43.490 --> 00:06:45.350 You can imagine the line worker pulling their 00:06:45.350 --> 00:06:47.370 hair out because someone in supply chain told 00:06:47.370 --> 00:06:50.259 them it would only take two days. It is a recipe 00:06:50.259 --> 00:06:52.360 for internal friction if you don't understand 00:06:52.360 --> 00:06:54.899 the anatomy of the wait. You can break this entire 00:06:54.899 --> 00:06:57.779 journey down into three phases. Pre -processing, 00:06:57.779 --> 00:06:59.959 processing, and post -processing. Okay, break 00:06:59.959 --> 00:07:02.279 those down for us. Pre -processing is the planning 00:07:02.279 --> 00:07:05.339 time, the paperwork, releasing the purchase order. 00:07:05.779 --> 00:07:08.120 Processing is the actual procuring or making 00:07:08.120 --> 00:07:11.160 of the item. But the silent killer of efficiency, 00:07:11.660 --> 00:07:13.860 the place where most of that friction happens, 00:07:14.120 --> 00:07:17.379 is often post -processing. The post -processing. 00:07:17.709 --> 00:07:19.589 I hadn't even considered what happens when the 00:07:19.589 --> 00:07:22.110 truck actually arrives. The wait isn't over just 00:07:22.110 --> 00:07:23.689 because it's physically in the building, is it? 00:07:23.689 --> 00:07:25.829 Not at all. There is something called put -away 00:07:25.829 --> 00:07:28.759 time, and it is far from trivial. Put -away time 00:07:28.759 --> 00:07:31.360 is the duration it takes a company to unload 00:07:31.360 --> 00:07:33.680 a product from a truck, physically inspect it 00:07:33.680 --> 00:07:36.300 for damage, log it into their inventory system, 00:07:36.459 --> 00:07:39.060 move it into storage, or perhaps hold it in quarantine 00:07:39.060 --> 00:07:42.079 for safety checks. Wow. Yeah. When a company 00:07:42.079 --> 00:07:44.300 is running on tight constraints or using just 00:07:44.300 --> 00:07:46.779 -in -time manufacturing where parts arrive exactly 00:07:46.779 --> 00:07:49.420 when they are needed, knowing exactly how long 00:07:49.420 --> 00:07:52.379 your own internal put -away process takes is 00:07:52.379 --> 00:07:54.800 just as critical as knowing the supplier's manufacturing 00:07:54.800 --> 00:07:57.009 time. Because if you don't account for the truck 00:07:57.009 --> 00:07:58.750 sitting on the dock for eight hours waiting to 00:07:58.750 --> 00:08:01.230 be unloaded and inspected, your entire assembly 00:08:01.230 --> 00:08:04.329 line might grind to a halt. It's wild how much 00:08:04.329 --> 00:08:06.790 is hidden in the margins. Here's where it gets 00:08:06.790 --> 00:08:09.490 really interesting. Because massive industries 00:08:09.490 --> 00:08:11.910 don't just guess at these numbers or rely on 00:08:11.910 --> 00:08:14.189 rough estimates. They actually model customer 00:08:14.189 --> 00:08:17.629 behavior using four distinct mathematical flavors 00:08:17.629 --> 00:08:22.899 of order lead time. Or OLT. Yes, the OLT matrix. 00:08:23.879 --> 00:08:25.660 Differentiating between these definitions is 00:08:25.660 --> 00:08:27.800 crucial for industries to model the order behavior 00:08:27.800 --> 00:08:30.139 of their customers and manage their own revenue 00:08:30.139 --> 00:08:33.299 streams. The first of these four flavors is OLT 00:08:33.299 --> 00:08:36.159 requested. The calculation here is the wish date 00:08:36.159 --> 00:08:38.450 minus the order entry date. Let's ground this 00:08:38.450 --> 00:08:40.529 in a real -world scenario. Yeah. Let's say you're 00:08:40.529 --> 00:08:42.529 listening to this and you decide to order custom 00:08:42.529 --> 00:08:45.149 sneakers for an upcoming marathon. You place 00:08:45.149 --> 00:08:47.149 the order today, so that is your order entry 00:08:47.149 --> 00:08:48.970 date. You want them in your hands by the first 00:08:48.970 --> 00:08:50.809 of next month so you can break them in. That 00:08:50.809 --> 00:08:52.590 is your wish date. Exactly. So the time between 00:08:52.590 --> 00:08:54.789 those two dates, that's your OLT request. Right. 00:08:54.950 --> 00:08:57.129 It represents the gap between when you entered 00:08:57.129 --> 00:08:59.950 the system and when you desire the outcome. Next, 00:08:59.950 --> 00:09:03.490 we have OLT quote. This is the quote date minus 00:09:03.490 --> 00:09:06.659 the order entry date. The quote date is the agreed 00:09:06.659 --> 00:09:09.419 upon time, often stipulated in a formal supply 00:09:09.419 --> 00:09:12.039 chain contract, that the supplier commits to 00:09:12.039 --> 00:09:14.159 delivering the goods. So keeping with the sneakers, 00:09:14.440 --> 00:09:16.440 the website says, based on our current queue, 00:09:16.679 --> 00:09:19.240 we guarantee delivery by the 5th of next month. 00:09:19.379 --> 00:09:22.100 That is the quote. Correct. Then you have OLT 00:09:22.100 --> 00:09:25.480 actual. This is the delivery date minus the order 00:09:25.480 --> 00:09:28.120 entry date. This is the harsh reality of when 00:09:28.120 --> 00:09:30.200 the goods actually arrived at your door. The 00:09:30.200 --> 00:09:32.909 moment of truth. Exactly. And finally, there 00:09:32.909 --> 00:09:35.509 is OLT confirmed. This is the confirmed date 00:09:35.509 --> 00:09:37.990 minus the order entry date. The confirmed date 00:09:37.990 --> 00:09:40.190 is when the provider actually sends that final 00:09:40.190 --> 00:09:42.750 notification confirming the exact day they will 00:09:42.750 --> 00:09:44.830 deliver the material, which might differ from 00:09:44.830 --> 00:09:46.990 the original quote. So you have what you wished 00:09:46.990 --> 00:09:49.970 for, what they initially quoted you in the contract, 00:09:50.250 --> 00:09:52.289 what they later confirmed when it actually shipped, 00:09:52.409 --> 00:09:54.049 and what actually happened when it hit your porch. 00:09:54.590 --> 00:09:57.029 That is a lot of data points for one pair of 00:09:57.029 --> 00:10:00.370 shoes. There is a way to average all this out 00:10:00.370 --> 00:10:02.990 for massive companies, right? The average OLT 00:10:02.990 --> 00:10:07.450 based on volume or OLTV. Yes. It sounds like 00:10:07.450 --> 00:10:09.730 dense mathematics, but the concept is straightforward. 00:10:10.649 --> 00:10:13.490 Imagine a factory receiving thousands of shipments. 00:10:13.610 --> 00:10:16.190 To understand their true lead time, they multiply 00:10:16.190 --> 00:10:18.470 the volume of the product delivered by its specific 00:10:18.470 --> 00:10:21.129 OLT, add all of those together for a specific 00:10:21.129 --> 00:10:23.830 facility, and then divide by the total quantity 00:10:23.830 --> 00:10:26.029 delivered in that period. So it's volume weighted. 00:10:26.429 --> 00:10:29.450 Meaning an order of 10 ,000 widgets taking five 00:10:29.450 --> 00:10:31.629 days to arrive matters a whole lot more to the 00:10:31.629 --> 00:10:34.049 factory's average efficiency than a tiny order 00:10:34.049 --> 00:10:36.789 of 10 widgets taking five days. Precisely. But 00:10:36.789 --> 00:10:38.250 why do companies go through all this trouble? 00:10:38.409 --> 00:10:41.070 Why track the wish dates against the actual dates 00:10:41.070 --> 00:10:44.129 so meticulously? Because this data is the foundation 00:10:44.129 --> 00:10:47.289 of revenue management. First, it gives a company 00:10:47.289 --> 00:10:50.570 a deep understanding of market behavior. If they 00:10:50.570 --> 00:10:53.330 know customers consistently have an OLT requested 00:10:53.330 --> 00:10:56.409 of two weeks, but their OLT quote is four weeks, 00:10:56.610 --> 00:10:58.970 they know they are losing business and need to 00:10:58.970 --> 00:11:01.269 redesign their schema to fit customer needs. 00:11:01.450 --> 00:11:03.690 That makes sense. Second, it creates transparency. 00:11:04.190 --> 00:11:06.570 You can improve customer relations immensely 00:11:06.570 --> 00:11:09.470 just by communicating the gap between the quote 00:11:09.470 --> 00:11:12.110 date and the confirmed date. And there's a third 00:11:12.110 --> 00:11:14.230 reason, which is really the corporate enforcer 00:11:14.230 --> 00:11:16.629 part of the equation. Tracking this increases 00:11:16.629 --> 00:11:19.149 a company's ability to detect and penalize contract 00:11:19.149 --> 00:11:22.259 breaches. If they have a massive supplier, And 00:11:22.259 --> 00:11:24.200 they can prove with data that the supplier is 00:11:24.200 --> 00:11:27.059 consistently missing the OLT, quote, they can 00:11:27.059 --> 00:11:28.799 take action. That's the power of the matrix. 00:11:28.919 --> 00:11:31.460 If OLT actual is consistently longer than OLT, 00:11:31.559 --> 00:11:34.379 quote, you have quantifiable, undeniable proof 00:11:34.379 --> 00:11:36.919 that the supplier is failing. It's the data -driven 00:11:36.919 --> 00:11:39.100 way to manage accountability, levy fines, or 00:11:39.100 --> 00:11:41.639 renegotiate contracts. So we know how to measure 00:11:41.639 --> 00:11:43.340 the waiting game down to the absolute minute. 00:11:43.460 --> 00:11:45.399 But how do companies actually shrink these times? 00:11:45.980 --> 00:11:48.460 Nobody wants a longer lead time. There are several 00:11:48.460 --> 00:11:50.799 specific methodologies for shortening lead time 00:11:50.799 --> 00:11:53.100 across manufacturing, production, and delivery. 00:11:53.460 --> 00:11:56.179 The overarching goal is improving each processing 00:11:56.179 --> 00:11:59.379 step's efficiency by minimizing waste and quickly 00:11:59.379 --> 00:12:02.139 resolving any bottlenecks. One of the primary 00:12:02.139 --> 00:12:05.139 concepts used is called hijumka. I've heard that 00:12:05.139 --> 00:12:07.639 term in lean manufacturing before. It means production 00:12:07.639 --> 00:12:09.600 leveling, right? But what does that actually 00:12:09.600 --> 00:12:12.320 look like in practice? Imagine a factory that 00:12:12.320 --> 00:12:15.620 receives orders very sporadically. On Monday, 00:12:15.720 --> 00:12:18.080 they get an order for 100 units and everyone 00:12:18.080 --> 00:12:21.559 works a frantic 14 -hour shift. On Tuesday, they 00:12:21.559 --> 00:12:23.659 get an order for 10 units and the machines sit 00:12:23.659 --> 00:12:26.480 idle half the day. That sounds exhausting. It 00:12:26.480 --> 00:12:28.860 is. And that feast or famine approach creates 00:12:28.860 --> 00:12:32.240 massive, unpredictable lead times. Hajunka is 00:12:32.240 --> 00:12:34.580 the practice of leveling out the type and quantity 00:12:34.580 --> 00:12:37.480 of production over a fixed period of time. You 00:12:37.480 --> 00:12:39.220 smooth out the schedule so you are producing 00:12:39.220 --> 00:12:42.299 at a steady, predictable pace, which ironically 00:12:42.299 --> 00:12:44.519 allows you to deliver faster overall because 00:12:44.519 --> 00:12:46.100 you aren't constantly starting and stopping. 00:12:46.299 --> 00:12:48.580 It's amazing how much time is lost just waiting 00:12:48.580 --> 00:12:51.460 around. And what's fascinating is that reducing 00:12:51.460 --> 00:12:53.740 the length of the idle or waiting process stages 00:12:54.139 --> 00:12:56.899 is often the absolute easiest place to tackle 00:12:56.899 --> 00:12:59.480 first. Don't try to make the complex assembly 00:12:59.480 --> 00:13:02.519 machine run 10 % faster if the finished part 00:13:02.519 --> 00:13:04.460 is just sitting on a forklift for two days doing 00:13:04.460 --> 00:13:07.940 nothing. Cut the idle time first. Exactly. Find 00:13:07.940 --> 00:13:10.279 the waiting and eliminate it. Now, this exact 00:13:10.279 --> 00:13:12.860 same struggle to cut out idle time isn't just 00:13:12.860 --> 00:13:15.139 a headache for factory managers. It's actually 00:13:15.139 --> 00:13:17.059 the foundational puzzle for project managers, 00:13:17.200 --> 00:13:20.179 too. Yes. In project management, lead time takes 00:13:20.179 --> 00:13:22.649 on a slightly different nuance. The Project Management 00:13:22.649 --> 00:13:26.309 Institute's PMBOK, their seventh edition, defines 00:13:26.309 --> 00:13:28.889 it as the time between a customer request and 00:13:28.889 --> 00:13:31.629 the actual delivery. It is considered a fundamental 00:13:31.629 --> 00:13:34.409 deliverable metric. Right. So if you are picturing 00:13:34.409 --> 00:13:36.070 a giant to -do list for a software development 00:13:36.070 --> 00:13:38.789 team, lead time shows the amount of elapsed time 00:13:38.789 --> 00:13:41.009 from a chunk of work, what they call a story 00:13:41.009 --> 00:13:43.610 entering the backlog, all the way to the end 00:13:43.610 --> 00:13:46.110 of the iteration or release. The clock starts 00:13:46.110 --> 00:13:48.929 the second the idea goes on the board and stops 00:13:48.929 --> 00:13:51.289 when the software is in the user's hands. And 00:13:51.289 --> 00:13:53.750 naturally, a smaller lead time in this context 00:13:53.750 --> 00:13:56.570 means the process is more effective and the project 00:13:56.570 --> 00:13:59.750 team is highly productive. But there is a secondary 00:13:59.750 --> 00:14:02.250 definition in project management that is quite 00:14:02.250 --> 00:14:05.570 clever. Lead can also refer to the saved time 00:14:05.570 --> 00:14:08.570 achieved by starting an activity before its predecessor 00:14:08.570 --> 00:14:11.870 is completely finished. I love this trick. It's 00:14:11.870 --> 00:14:14.809 called advancing a successor activity with respect 00:14:14.809 --> 00:14:17.120 to a predecessor activity. Think about it like 00:14:17.120 --> 00:14:18.779 cooking dinner. Oh, that's a perfect analogy. 00:14:19.100 --> 00:14:21.600 Let's say making the pasta takes 15 minutes and 00:14:21.600 --> 00:14:23.399 chopping and cooking the vegetables takes 10 00:14:23.399 --> 00:14:25.799 minutes. If you wait for the pasta to be completely 00:14:25.799 --> 00:14:28.519 done before you even start chopping, dinner takes 00:14:28.519 --> 00:14:31.379 25 minutes. But if you give the vegetable task 00:14:31.379 --> 00:14:33.879 a lead of 10 minutes, meaning you start chopping 00:14:33.879 --> 00:14:36.440 while the water is still boiling, both components 00:14:36.440 --> 00:14:40.379 finish at the exact same time. It is a brilliant 00:14:40.379 --> 00:14:43.039 scheduling hack to overlap work and compress 00:14:43.039 --> 00:14:45.610 the timeline. It requires meticulous planning 00:14:45.610 --> 00:14:48.570 and a deep understanding of dependencies, but 00:14:48.570 --> 00:14:50.970 it is a highly effective way to shrink the overall 00:14:50.970 --> 00:14:53.669 duration of a project's critical path. Okay, 00:14:53.730 --> 00:14:55.929 so we've covered factories, we've covered project 00:14:55.929 --> 00:14:58.789 managers trying to launch software, but the final 00:14:58.789 --> 00:15:00.889 piece of this puzzle takes the concept of lead 00:15:00.889 --> 00:15:03.769 time into some completely unexpected arenas. 00:15:03.809 --> 00:15:06.490 Let's talk about journalism first. In publishing 00:15:06.490 --> 00:15:08.690 and journalism, lead time describes the production 00:15:08.690 --> 00:15:11.399 period of a particular publication. It is the 00:15:11.399 --> 00:15:13.620 amount of time a journalist has between receiving 00:15:13.620 --> 00:15:16.080 a writing assignment and submitting the completed 00:15:16.080 --> 00:15:18.820 piece before the issue date is released to the 00:15:18.820 --> 00:15:20.779 public. Depending on the medium, this varies 00:15:20.779 --> 00:15:23.779 wildly. Right. A daily newspaper or a breaking 00:15:23.779 --> 00:15:27.220 news website have a lead time of hours, maybe 00:15:27.220 --> 00:15:30.539 even minutes. But a glossy monthly magazine might 00:15:30.539 --> 00:15:32.980 have a lead time of three to six months. They 00:15:32.980 --> 00:15:34.860 are finalizing their Christmas issue in July. 00:15:35.200 --> 00:15:38.059 But it gets even wilder than journalism. Video 00:15:38.059 --> 00:15:40.980 games. Lead time is actually a crucial mechanic 00:15:40.980 --> 00:15:43.960 in high -twitch action games. This is a fascinating 00:15:43.960 --> 00:15:46.179 application of the concept because it uses latency 00:15:46.179 --> 00:15:49.120 as a deliberate obstacle. In video games, lead 00:15:49.120 --> 00:15:51.360 time refers to the built -in delay required to 00:15:51.360 --> 00:15:53.580 successfully complete certain special or important 00:15:53.580 --> 00:15:56.120 actions, like using a health -recovering item 00:15:56.120 --> 00:15:58.299 or casting a powerful spell. Think about the 00:15:58.299 --> 00:16:00.799 last time you played an intense game. You're 00:16:00.799 --> 00:16:03.399 in a massive boss fight, the monster is charging 00:16:03.399 --> 00:16:06.039 at you, your health bar is flashing red, and 00:16:06.039 --> 00:16:08.240 you hit the button to drink a healing potion. 00:16:08.730 --> 00:16:11.409 Your character doesn't just instantly heal. They 00:16:11.409 --> 00:16:14.870 stand there for two agonizing seconds, uncorking 00:16:14.870 --> 00:16:17.029 the bottle and drinking it totally vulnerable 00:16:17.029 --> 00:16:20.480 while the boss is bearing down on you. That is 00:16:20.480 --> 00:16:23.019 intentional lead time. It is entirely intentional. 00:16:23.240 --> 00:16:25.580 Game developers build this latency in to prevent 00:16:25.580 --> 00:16:28.000 players from abusing helpful abilities or items. 00:16:28.340 --> 00:16:30.460 By making them a little more difficult to use 00:16:30.460 --> 00:16:32.799 safely, the game forces the player to employ 00:16:32.799 --> 00:16:35.679 strategy, calculate risk, and exercise caution. 00:16:35.940 --> 00:16:38.159 You have to earn the health by finding a safe 00:16:38.159 --> 00:16:40.600 window of time to endure the lead time. They're 00:16:40.600 --> 00:16:43.159 using latency as a tool to create tension. It's 00:16:43.159 --> 00:16:45.440 brilliant. But from the virtual world to the 00:16:45.440 --> 00:16:47.879 very real world, the final example we have is 00:16:47.879 --> 00:16:51.220 without a doubt the most profound. If we connect 00:16:51.220 --> 00:16:53.559 this to the bigger picture, medicine provides 00:16:53.559 --> 00:16:55.980 the most consequential definition of lead time. 00:16:56.360 --> 00:16:59.120 When referring to a disease, lead time is the 00:16:59.120 --> 00:17:01.440 length of time between the detection of a disease 00:17:01.440 --> 00:17:04.240 through screening and the moment in time where 00:17:04.240 --> 00:17:05.980 it would have normally presented with symptoms 00:17:05.980 --> 00:17:08.539 and led to a diagnosis. It's the window between 00:17:08.539 --> 00:17:10.720 catching something early because you went in 00:17:10.720 --> 00:17:12.660 for a test and when you would have naturally 00:17:12.660 --> 00:17:14.799 felt sick and gone to the doctor anyway. Yes. 00:17:14.839 --> 00:17:17.160 A common example is breast cancer population 00:17:17.160 --> 00:17:20.049 screening. Women who are completely asymptomatic 00:17:20.049 --> 00:17:22.369 might receive a positive test result through 00:17:22.369 --> 00:17:25.369 a routine mammography. That underlying disease 00:17:25.369 --> 00:17:27.730 might have taken many more years to physically 00:17:27.730 --> 00:17:31.210 manifest and show noticeable symptoms. That gap 00:17:31.210 --> 00:17:34.269 in time, that specific lead time, is the critical 00:17:34.269 --> 00:17:36.509 window where early intervention is possible. 00:17:36.809 --> 00:17:39.109 In that context, lead time isn't just a metric 00:17:39.109 --> 00:17:41.650 for factory efficiency, and it isn't a game mechanic 00:17:41.650 --> 00:17:44.029 to make a boss fight harder. It is literally 00:17:44.029 --> 00:17:46.829 the window for saving a life. The longer the 00:17:46.829 --> 00:17:48.769 lead time you can gain over the disease through 00:17:48.769 --> 00:17:51.549 early screening, the better your chances of survival. 00:17:52.029 --> 00:17:54.390 It really puts the whole concept of waiting in 00:17:54.390 --> 00:17:57.170 time into a staggering perspective. It certainly 00:17:57.170 --> 00:18:00.150 does. It transitions the concept from a measure 00:18:00.150 --> 00:18:03.250 of business latency into a measure of human survival. 00:18:03.849 --> 00:18:06.450 Time is the most valuable resource we have, and 00:18:06.450 --> 00:18:08.650 in medicine, lead time is the act of buying more 00:18:08.650 --> 00:18:11.480 of it. So what does this all mean? We started 00:18:11.480 --> 00:18:14.039 with custom cars and purchase orders, moved through 00:18:14.039 --> 00:18:16.400 the hidden days, lost unloading trucks on a dock, 00:18:16.539 --> 00:18:18.759 mapped out the equations for tracking our wishes 00:18:18.759 --> 00:18:21.460 against reality, learned how to overlap our schedules 00:18:21.460 --> 00:18:23.559 by chopping vegetables while the water boils, 00:18:23.720 --> 00:18:26.500 and finally saw how this same exact principle 00:18:26.500 --> 00:18:29.099 governs the tension in our video games and the 00:18:29.099 --> 00:18:31.099 life -saving potential of medical screenings. 00:18:31.460 --> 00:18:33.720 Whether you are waiting for a package, managing 00:18:33.720 --> 00:18:36.720 a team, or popping a health potion, lead time 00:18:36.720 --> 00:18:39.660 is the invisible framework. dictating your reality. 00:18:39.880 --> 00:18:42.299 It really is the unifying theory of latency. 00:18:42.640 --> 00:18:45.039 And there is one final concept connected to this 00:18:45.039 --> 00:18:47.079 that I think serves as a perfect concluding thought. 00:18:47.200 --> 00:18:49.200 When you look at the broader study of lead time, 00:18:49.339 --> 00:18:51.680 it inevitably links to two other fascinating 00:18:51.680 --> 00:18:54.819 disciplines. Queuing theory, which is the actual 00:18:54.819 --> 00:18:57.059 complex mathematical study of waiting lines, 00:18:57.259 --> 00:19:00.440 and the concept of safety stock. Safety stock. 00:19:01.180 --> 00:19:03.759 Is that just the extra stuff a company keeps 00:19:03.759 --> 00:19:06.259 around in a warehouse just in case? Essentially, 00:19:06.319 --> 00:19:09.579 yes. Safety stock is extra inventory kept strictly 00:19:09.579 --> 00:19:12.319 to mitigate the risks of unpredictable lead times. 00:19:12.640 --> 00:19:15.440 If you cannot trust the latency of your suppliers, 00:19:15.700 --> 00:19:17.960 you build a physical buffer to protect yourself. 00:19:18.619 --> 00:19:20.680 And this raises an important question, not just 00:19:20.680 --> 00:19:22.660 for supply chain managers, but for everyone listening 00:19:22.660 --> 00:19:24.599 right now. I like where this is going. Look around 00:19:24.599 --> 00:19:27.339 your own life, your own schedule, your own relationships. 00:19:27.779 --> 00:19:29.859 Where are you subconsciously keeping your own 00:19:29.859 --> 00:19:32.559 safety stock? Whether that is padding your schedule 00:19:32.559 --> 00:19:35.279 with extra time, hoarding extra resources, or 00:19:35.279 --> 00:19:37.380 keeping emotional buffers. You do it to protect 00:19:37.380 --> 00:19:39.339 yourself from the hidden, unpredictable lead 00:19:39.339 --> 00:19:42.359 times of others. Wow. Are you leaving 20 minutes 00:19:42.359 --> 00:19:45.279 early for every single meeting because you're 00:19:45.279 --> 00:19:47.779 buffering the lead time of traffic? Are you keeping 00:19:47.779 --> 00:19:50.430 a safe... safety stock of patients because you 00:19:50.430 --> 00:19:52.690 know the pre -processing time of your co -workers 00:19:52.690 --> 00:19:55.410 is going to drive you crazy. That is something 00:19:55.410 --> 00:19:57.990 to seriously mull over today. Thank you so much 00:19:57.990 --> 00:19:59.890 for joining us on this deep dive into the mechanics 00:19:59.890 --> 00:20:02.009 of waiting. We hope you view the systems around 00:20:02.009 --> 00:20:03.910 you just a little bit differently today. Keep 00:20:03.910 --> 00:20:05.990 questioning, keep looking for those hidden frameworks, 00:20:06.150 --> 00:20:08.329 and most importantly, stay insanely curious. 00:20:08.589 --> 00:20:10.069 We will catch you next time.