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De-Risk Your Innovation Project

The Driving Eureka! Podcast - Find, Filter and Fast Track Big Ideas to Innovate

Release Date: 04/18/2019

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More Episodes

Driving Eureka! Newsletter #26 

Your Innovation Podcast. This is the 26th episode of the Driving Eureka! Podcast. Segment 1:Confront Reality & Build a Plan to DE-RISK your Innovation Project!; Segment 2: Reducing Risk by Understanding Variation 3: Brain Brew Whisk(e)y Academy.

Subscribe to learn how to Find Filter and Fast Track Big Ideas.

Show Notes

[00:00:01]
The Driving Eureka! Podcast

[00:00:33]
Episode 26 - Risk and Innovation

[00:01:09]
Eureka! Ranch Project to De-risk Innovation

[00:03:18]
Depending on Project - High and Low Risk

[00:04:14]
Trailblazer to Help You with Existing Projects

[00:04:30]
Ranch Can Help and Train You

[00:05:07]
New Product with New Capabilities

[00:06:34]
Must Understand Variation and the Causes of It to Reduce

[00:08:25]
Eureka! Ranch Will Help with the Numbers

[00:09:31]
Driving Eureka! Book Segment

[00:09:44]
You Must Understand Variation in Management and Innovation

[00:11:59]
Common Cause the Responsibility of Management; Special Cause Usually Felt by the Worker

[00:13:16]
Run Experiments to Reduce Variation

[00:14:04]
The Innovation Engineering System Helps Bring Data to Life Through Modeling

[00:18:28]
Using the Weather as an Example

[00:21:04]
Inherent Uncertainty Makes Life Exciting

[00:23:30]
Brain Brew Whisk(e)y Academy

[00:23:54]
Scalability and Risk

[00:24:17]
Scaling in the Spirits Industry is a Problem

[00:25:30]
Reduce Variation to Scale

[00:27:45]
Quality Mindset has to Be Addressed at the Start

[00:29:32]
Brain Brew Sweats Over the Wood

[00:29:45]
Craft Cocktail Recipe - Strawberry Mint Julep

[00:30:13]
Step 1

[00:30:15]
Step 2

[00:30:17]
Step 3

[00:30:21]
Step 4

[00:30:22]
Step 5

 

 

Transcript

Tripp: [00:00:01] Welcome to the Driving Eureka! podcast. We share ideas and advice for helping you find filter and. fast track. big ideas.

 

Tripp: [00:00:14] Hi I'm Tripp Babbitt advisor to global organizations on the Deming philosophy and host of the Deming Institute podcast.

 

Doug: [00:00:22] And I'm Doug Hall inventor speaker teacher in whisk(e)y maker. I'm also the founder of the Eureka ranch and author of the Driving Eureka! book.

 

Tripp: [00:00:33] This is Episode 26 of the Driving Eureka! podcast and our subject or theme this week is risk and you're talking here Doug. Basically all three three sections with the Book segment and Brain Brew Whisk(e)y Academy two about reducing the risk and it looks like you've got a new way to do that. Tell us about how your de-risk if that's a word it is a word de-risking your innovation project.

 

Doug: [00:01:09] So this has been a lot of thinking this has been a lot of thinking by the Eureka ranch team. So I'm sharing what they're thinking about I didn't come up with this the thinking went along these lines. Okay. So people buy into the idea of innovation. But the idea of doing it is scary. So theoretically it's a good idea as a way to grow sales and profits. But I'm kind of scared that we might lose. And I don't want to fail the ranch team thought about this for a bit and they said OK. So we approach it as a system of interconnected parts. What if to D risk projects. We need to have a place to focus our energy because the problem with a system of interconnected parts is if you're not careful you play whack a mole. You grab one part and then another part another part another part and they never come together. And the team came to the conclusion that the project piano the profit and loss statement of what's going to be our revenue what are going to be the expenses what's the profits. And related to that what's the return on investment. That is the one document. Where the entire innovation system comes onto one piece of paper.

 

Doug: [00:02:23] Mm hmm. And we said Huh. And and in that document if we do the math in the way that we teach at the Eureka! Ranch with innovation engineering if we.

 

Doug: [00:02:38] Model the variance or risk. OK so risk is because a number could be higher could be low. There's this variance in that input. So the number of potential customers the trial rate awareness distribution repeat rates how much they're going to buy when they buy. They're gonna make a small purchase or a large purchase all of the different things that go into a forecast of sales.

 

Doug: [00:03:02] All the things go into cost raw materials packaging overhead manufacturing cost energy etc. etc. Each one of those numbers has a degree of risk associated with it some of them have small risk or small variance.

 

Doug: [00:03:18] Some of them have high risk high variance because we're really not sure what those are. And so by using the trailblazer software that the team has created which allows you to do basically a virtual introduction of your innovation basically a marketplace simulation where you can introduce that some 10000 times in in the marketplace you know virtually. It can predict five years of trial repeat and diffusion of innovation to the marketplace and it gives you the uncertainty so that now you can identify which of the three areas whether it's in revenue or in cost. That could cause the greatest impact greatest potential for you to not hit your targets or where's the areas where you could fail. So now you know where to focus some energy.

 

Doug: [00:04:14] And. Kind of cool kind of cool. You don't even do it and you do it with existing projects. So you start with a project that already exists. So you've been working on this project for a while. The team can come in and quickly teach you how to do it.

 

Doug: [00:04:30] Doug with the Ranch team would do it to begin with but then in time what happens is you take it over and your people get trained to be able to do it yourself. And suddenly we're bringing data. We talked a little while ago about the data was a great way to start to confront some of these risk things. We're dealing with this on a on a very factual type basis.

 

Tripp: [00:04:53] Is this an addition then to the software that you're already had or is it kind of a culmination of some of the things that were already in Trailblazer and then adding this component to it.

 

Doug: [00:05:07] It's really a combination. It's like we've been working on different parts of this from Delphi to rapid testing to a whole lot of different components and they've all now come together into this whole tapestry where you can you now have the ability do it we didn't have this a couple of years ago you couldn't do this. We didn't have the capability to do it. We couldn't do all the cost modeling we couldn't do those things. It's only in the last really two and really even last year that we finally got all of the components to make this possible do it. It's quite a bit of work but it's easy once you've got it automated with the software.

 

Tripp: [00:05:43] Ok. And this is going to help people then know OK here's kind of the range I guess of what your your sales forecast is going to be. This is what costs are associated with it because these are some of the inputs that you're putting into this. This P&L project P&L software and then it's can also tell you based on and this is the part I'm trying to understand a little bit better is going to tell me the amount of risk associated with those inputs.

 

Doug: [00:06:17] That's right. That's right. And what we're doing is basically looking at the standard deviation of each divided by the mean it's a general sense to see what's the relative impact that each one of those have. So we're looking at the standard deviation so we're going to model those.

 

Doug: [00:06:34] So when we do a consumer test you know you know you do a consumer test and you get a number. Well the truth is that no actually it's a number with a plus or minus with it. And sometimes there's wide agreement on your on your offering and sometimes it's not. We use that variance in the model. So best set. The crazy thing about this is sometimes the companies already have all this data but they're not looking at it in this way. Now there's usually some missing you know this is usually third to half that they don't have in this way which we have to get them but we show them how to do that but they've got a lot of this information to make it smarter but they've just not been taught you know statistics was not exactly a class that many people took for fun. You know it's just so the.

 

Tripp: [00:07:18] So if I have a product out there and we're we're working on it or doing different things but we we're still not sure what my piano is going to look like for this particular product. But basically you're going to come in with with the software say OK we're going to need the data for this this this do you have these things and if they have them you're going to input it and then if they don't you're gonna help them find the other things on the checklist of other.

 

Doug: [00:07:48] Do the P&L the assumptions and the P&L. We're gonna we're gonna help them get it. We're gonna show them some new ways that they've never done before and oftentimes on critical numbers what we'll do is we'll you know measure three times cut once to use the thing where we will will measure like the persuasion ability of the idea with three different methods. So to increase our confidence in the number that we got.

 

Tripp: [00:08:11] Ok. So you're going to take their existing numbers refine those even before it goes in based off of some of the things that you already know by some of the questions that you're going to ask them assessing with the numbers that they have and then help them get the ones that they don't.

 

Doug: [00:08:25] Yeah I mean we've literally as a team we've got the staff that we've got now we've got new lady Vicky who's with us now in between her Greg me and the others. I mean we've literally got hundreds and hundreds of thousands of sales forecasts that we've done probably. Our teams probably done more sales forecasts than any other innovation firm out there.

 

Doug: [00:08:46] And so we've got a lot of not only we have tools but but we've also got miles underneath us of of traveling through these things and then seeing what happened and then you know learning from that.

 

Tripp: [00:08:57] Ok. And with this tool is there some way if somebody is interested in it how is there a place we can send them for.

 

Doug: [00:09:08] Yeah I mean you can call if you're in the U.S. or Canada you can call 800 invents. INVENTS to reach the Ranch team or just visit Eurekaranch.com and connect with the folks there and they can help you with it.

 

Tripp: [00:09:31] It's time now for the Driving Eureka! book segment with author and inventor Doug Hall.

 

Tripp: [00:09:43] All right.

 

Tripp: [00:09:44] Well let's go to your book segment and reducing risk by understanding variation you know every time I see something on understand various. I get really excited and mere fact someone posted on LinkedIn last week. I a media firm. I can't remember which paper it was actually posted a control chart in an article. And I can't even remember what the subject was so excited to see that somebody had actually used it in a publication because it's one of the tools that that's so needed by every organization.

 

Tripp: [00:10:22] And unfortunately very few people really understand what variation is about and what it does. So when you're talking about reducing risk by understanding variation I got excited already. So tell me Tell me how you're using an understanding variation here.

 

Doug: [00:10:38] Ok. So. So people need to understand and this is a small excerpt from the book and there's this much more. We're going to get through here in a few minutes. But basically every measurement has this basic Deming has variation to it that's a plus or minus with it. However and this can be charted and systems have a regular variance that has some you know there's a certain level of raw material variance that causes variance in your product. I mean there's certain things that happen and there's two types of variance. There's common cause and special cause common cause are built into the system. So if you have a ruler that only measures two inches then you're going to have a pretty big variance when you're trying to estimate how many you know an eight or sixteenth or a 30 second to this. If you have a ruler that goes to 130 second you're gonna be much closer. You're gonna have less variance and you still can have variance because you're going to be looking at it and you're not going to quite see it the same if three people did it. And may see a little bit different but it can be smaller variance.

 

Tripp: [00:11:41] You know Doug there's just to interject here real quick here. Dr. Don Wheeler he calls that chunky data when you have large measures like that when when he can't go down to you know a 16th of an inch or a 32nd of an inch or even more versus you know measuring in one inch.

 

Doug: [00:11:59] I just thought it and it depends and it depends on the system in some cases that's fine. That's good enough on human systems because the variance is so high that may be enough. But so that's built into the system and only we have to change the system to change that the worker can't do anything about that. And then we have special cause which is an error by the employee. They didn't follow the procedures. They fell asleep. You know they just made a mistake they made a mistake and we need to first separate common costs from special costs because special cause you retrain the employee you do this need to learn how to do it or you have to fire them because there is some that disobeying men are following the process whatever it is. But usually you educate them and they find the common causes where we need to reduce the variance. And when it comes to the risk associated with innovations what we find is when we go back to the project piano and we're looking at that stuff is there will be variance in it. And so for example we'll find variance when we do modeling of how much what. What percentage of stores are going to take the offering. What percentage of consumers will be aware of you that you're doing it. What what amount of repeat purchase are you gonna get. We'll find these numbers sometimes have huge variance associated them because they're built into the systems that we do it.

 

Tripp: [00:13:16] And so you have to then start to break this down and break this down to reduce this variance in it by running experiments and by changing your offering so so to reduce the variance in it. And but understanding it the whole process starts with understanding there is variance in systems and and that the system can reduce the variance and for those of you say well you can't do this with innovation you're no different than the guy in makeup and you Pennsylvania told me a paper machine can't be done.

 

Doug: [00:13:43] They were wrong then and you're wrong now. I mean it's just reality. OK. And so we've got to reduce the variance in the in the process and do it but we've got to make sure that we're dealing with common cause not special cause because if you take a special cause and you're putting rules to prevent it you create a hopeless bureaucracy.

 

Tripp: [00:14:04] Before I met you I mean. I struggled with trying to understand how from an innovation standpoint I would be like everybody else I think. And I think it's probably something I spend a couple of minutes talking about. Is that it is mystifying when you're talking about innovation because it just seems like there's so many unknowns when you're working on something that's innovation. And it was the first time where you know when I attended your classes that I started to understand how to go about it. Everything from measuring whether a product is meaningfully unique which we've talked about in previous episodes to Generally in the forecast to some of the forecasting methodologies those types of things you take a couple of minutes and just talk about those things well.

 

Doug: [00:14:56] So we take the variance that we're dealing with and rather than ignore it. We model it and in fact I went at the National Institute of Standards and Technology with the Department of Commerce I went through a big review with a guy named Jim Philbin on forecasting and they had never really approved a forecasting system before for innovations. And he sat down and he said Doug. So they tell me you can tell me how much I'm going to sell. I said That's ridiculous.

 

Doug: [00:15:23] Of course I can't do that. He said What do you mean. I said because this variance in the inputs and if this variance in the inputs has to be variance in the output. He said So what you're saying is that variance is the fundamental key to being able to model it. I go yes. He looked to me says you're the first person who's ever understood that. Tell me more. Long story short after six months he ended up doing a two hour presentation on what we were doing because we were modeling that uncertainty as opposed to ignoring the uncertainty. And so all of our test systems are sales forecasting systems all of our methodologies take that information that is in that variance and use them to make the forecasts by running Monte Carlo simulations with it. So you start to see the dynamic range and this is truth. This is true. That variance is true.

 

Doug: [00:16:17] You know when we've got this in sometimes you get mad they say Doug but you're saying we can have results all over the place. I go and that's the truth. They go Well I don't like that. I said then we have to reduce the variation. It's the same as manufacturing it's no different. This is no different than reducing the variance of raw materials to make a factory run better and reducing the variance to make sure our innovations hit their numbers. It's the same thing folks. It's not any different. It's exactly the same. You just didn't have the tools and techniques and frankly in damage time you couldn't do them. I mean because you couldn't you couldn't do the modelling today with the computers. We can do 10000 simulations in a microsecond and we can run permutations and we can run simulations that literally five years ago you couldn't do. I mean what we were doing five years ago was horrifically compared to what we can do now. There are new tools that you're just not even aware of.

 

Tripp: [00:17:12] You know it's interesting when I was taking your class there. I was also reading a book that a friend had given me and I called the Signal and the Noise. It's a book by Nate Silver who's the statistician that does 538. Sure I know. Yeah. So. So he had when I was reading that I was also reading the chapter about how they forecast weather. And I made so many comparisons associated with some of the things that you were talking about that hey this this you know even in weather what's take the weather first. This one input if it changes just a little bit it could change a lot of things. But knowing that is part of the knowledge that you guys bring to the table from my standpoint is you know which ones are kind of. OK we got to watch this one or we need to dig in deeper to this one because we know that it's really going to affect that particular project or product that someone is working on and I thought I said and I was it just now sometimes you were set up with things that are very similar. But I I was fascinating to me how you guys had gone about it and how really well it followed.

 

Doug: [00:18:28] Yeah. And when we sit with finance department folks who generally get this pretty quickly one of the things becomes do you want to air on the side of false positives or false negatives. And so it becomes more sophisticated. So let's take the weather example. You know when the weatherman says 70 percent chance of rain. People read that and go it's going to rain. OK. The fact of the matter is is three out of 10 times it shouldn't rain for the forecast to be right.

 

Doug: [00:18:57] That's just the way it works now as it turns out the weather stations the TV stations have learned this and the newscasts. And so what they do is they increase the odds. So if you look at the government forecast which you can get a stream for in this Apps for it will tell you the true odds. But what the weather people do for snow and for rain and storms is they increase the odds of bad things happening early because when it doesn't happen you feel good.

 

Doug: [00:19:34] So if you're a weather man just take the odds and had 10 points and you've got a better chance of people liking your forecast because their memory. They will remember when you said it wouldn't rain. Did they get mad. But when it's the other way around they're happy. So there's a bias. If you read about it it's hilarious. There is a bias in the weather forecast you're given and you can look it up yourself. It's it's it's pretty funny. It's pretty funny.

 

Tripp: [00:20:05] I got it. I got to tell the story Doug I can't remember it's probably it's probably going over 10 years ago but you know big event here in Indianapolis is obviously the Indianapolis 500 which happens in the end of May every year and one year. There was a there was a weather person that was on there and saying it's going to rain 100 percent. It's definitely going to rain tomorrow. You know just be prepared you know I wouldn't even go out there. It didn't rain at all that day. I never saw that that weather caster again. Now I haven't seen that person on that channel. I haven't seen it on that person on any other channel but it was just it was so funny that this person was so and it looked bleak. I mean it was it had been raining and everything but the next day came out it was a little cloudy in the morning and the sun came out and everything went on time and everything. Never saw that person again.

 

Doug: [00:21:04] I'll tell you that this this idea of variance is part of what makes life exciting. Is this an inherent uncertainty. The inherent uncertainty of these things and when you become comfortable. With uncertainty and you understand that this variance in things and you learn how to confront this manage it reduce it. Then it suddenly becomes a lot easier to do things because you don't get. You don't get as frustrated and I mean I don't know. It's just it's just so much better to know this. And because otherwise you're like I can't believe this happened. How could this happen. Well of course it could have happened. You know I have never found a team when an innovation has failed and they have me do a forensic.

 

Doug: [00:22:02] So we do these forensics which I am beginning to hate doing them because you know where they say well this has failed it should have succeeded I don't know what happened something's wrong. And so you start to go in to look at it and then it's like a search for the guilty and it just becomes these nasty things. But every time you do it. Every single time and I've been doing these for over 30 years every time I do one of these we find that there are some fundamental systemic flaws in the companies systems that are the root cause of it and has nothing to do with this project. This project just happened to hit at the low end of the control chart on two or three variables this time versus if they did it again it might hit on the higher end of the control chart. There's just so much variance in the system. I did it once for a guy I took the same product that had been introduced in like 12 different countries and we did the forecasts for them and we modelled the variance and the senior executive in charge the president. He looked at the results he said. So what you're telling me is when they come in and tell me a number I'd be just as good just throwing a dart as the number they're giving me I said Sir Yes you're absolutely right. I said your system is so far out of control. It is a random walk each time. If the idea is not what matters here it's the different elements of the system when they kick in the sales and distribution system. You've got huge variance in that very good.

 

Tripp: [00:23:22] Well a lot of fun unless you're a weather caster it may not be so much fun.

 

Tripp: [00:23:30] This is the Brain Brew Whisk(e)y Academy podcasts where we will take you behind the scenes so you can see what it takes to build a whisk(e)y distillery business.

 

Tripp: [00:23:41] Eureka ranch team led by Doug Hall are creating a craft whisk(e)y company with patented technology like has never been done before.

 

Tripp: [00:23:54] Ok well let's move to the Brain Brew Whisk(e)y Academy Doug you went to Orlando. My you went to Disney World my favorite place in the world. I did when I read this section have little bit trouble understanding how the scalability of things relates the risk or maybe it doesn't. And you just like talking about scalability.

 

Doug: [00:24:17] Well so so the issue was as I was at the Wine and Spirits Wholesalers Association conference and they had a brand battle seven entrepreneurs camera to pitch their product. And when I went through my notes from the event I was I was surprised that every single person was ask a variation of Do you have capacity can you scale. Interesting. It's been the same question I've got with rainbows. I've met with potential customers. Can you scale. Do you have volume and this constraint on capacity is one of the greatest various craft spirits success. And if we're not careful what happens is this. We spend so much time getting started. We don't take the time to put in place systems to reduce variation in our process. And so as a result when we start to scale the system quality just becomes a disaster. I mean it's typical if you're doing hundreds of cases and then thousands of cases and then tens of thousands of cases which every step change what happens is is that you know when you're small you can do work arounds. Oh that's a little off here I'll just add here. This is a law for justice here. But as you get bigger and bigger you can't do that.

 

Doug: [00:25:30] I mean the system is just cranking and running and so on so that whereas we're getting more scale to the thing. And so in order for you to get scalability you've got to reduce variance and end and all of that variance is the risk that you're not going to be able to scale. I mean it's just all connected. And so those small variances that don't matter when you small matter a lot when you're big. And so it's easier to build this discipline in when you're small than when you're large. I mean we went twenty eighteen 10 times what we're supposed to do 20 19 is 10 times what we originally supposed to do. That's right we're a thousand hundred times greater today than we were thought to be in 20 19 thankfully thankfully we worked on variants early on we didn't have to bring it in today. And so we've been able to scale still having to deal with challenges but we've been able to scale because we've reduced that variance. We're much tighter on our wood were tighter on our spirit. I mean our equipment runs that you know tenth of a piece I mean very tight tolerances on everything that we're doing so that we can scale.

 

Tripp: [00:26:48] You know this is true for almost every industry I can think of there's stress tests in software where you you've tested the software at working fine and then all of a sudden instead of you know 200 claims are coming through the system let's say in a health care environment now you've got a million claims coming through in a day and it just breaks the breaks the code basically.

 

Doug: [00:27:15] That's right.

 

Tripp: [00:27:15] And the same thing with equipment. You know I've seen it in contact centers where they have equipment set up and they've tested it. And then all of a sudden the real call and real volume starts to come in it just just explode.

 

Tripp: [00:27:28] So you're so you have the same issues then in a distillery in that you have these in essence bottlenecks that have to be cleared out as you go and I guess your point here Doug is that you need to do it as as your moving forward is that kind of your message here.

 

Doug: [00:27:45] That's right. You got to get the mindset in at the start. You got it because it's very hard when people have been winging it. It's very hard to suddenly turn around and say OK now we need to put some discipline into the decisions that we're making and we need to reduce the variance as we're going along. It's very hard to add that later. And so you need to get that in at the start. You need to get that in at the start because otherwise you're just going to be frustrated. You're gonna be frustrated with it.

 

Tripp: [00:28:14] So what you just. Just out of curiosity when you read these. Why why were they asking. They were asking about capacity at this conference and scale because it's such a big problem in the industry then.

 

Doug: [00:28:27] It's a total disaster. It's a it's a disaster. It's an absolute disaster everywhere. People can't you can't scale you can't get larger and so it just because it causes massive problems. And when they do scale the quality goes all over the place or they just literally don't have capacity. They just don't have the capacity to do it.

 

Tripp: [00:28:50] This also brings up and I know we talked about this before but every time I see Joe Girgash's name I think of it which is your you try these different words that you're you're putting in and I always kind of blows my mind from a standpoint of wood and variation being so great and how you guys are able to control that.

 

Doug: [00:29:15] I mean that is our focus. I mean that that is literally our focus is to reduce that variation in that because the wood is where all the magic happens. And that's where all the magic happens.

 

Tripp: [00:29:28] Is that where you get most of your variation from then.

 

Doug: [00:29:32] When it actually happens all the way through the process. But but the but the one that we are at. We sweat more than anything else is. I mean that's where the biggest value add happens is is in the wood.

 

Tripp: [00:29:45] Ok. All right well let's go to your craft cocktail recipe. The straw Berry mint julep. Kind of on a julep roll. This is our third Julep up recipe that we've had in Brain Brew Whisk(e)y Academy.

 

Tripp: [00:29:59] We had the jalepeno and then we had your basic in your face mint julep that you talked about last week. So what's the strawberry mint julep. Is this something you made up.

 

Doug: [00:30:09] Yeah. Just this still a bit of fun. So a basic julep you know.

 

Doug: [00:30:13] Five leaves a mint.

 

Doug: [00:30:15] A teaspoon of simple syrup.

 

Doug: [00:30:17] Three sliced strawberries muddle it really firmly.

 

Doug: [00:30:21] Add some ice crushed if you got it.

 

Doug: [00:30:22] Two ounces a noble oak stir and enjoy maybe with a strawberry is a garnish and it's just it's kind of a fun way to open it up tones down the mint a little bit strawberry and mint play well together very well together and so it's just a perfect summer kind of spring summer refresher at a little bit of spring champagne sparkling wine to it and it becomes even more magnificent.

 

Tripp: [00:30:48] Ok so are you doing something with the sliced strawberries or are you just adding them.

 

Tripp: [00:30:53] I'm muddling them. OK. I was I wasn't sure because I knew you didn't have the medal simple syrup but. So when I saw that on there I want to make sure that that that was being muddled also comes like a another interesting drink to try and you've got your noble bourbon in there again. All right. Very good. Any final comments for our Brain Brew Whisk(e)y Academy.

 

Doug: [00:31:15] No it's just it's just folks when you get into this kind of stuff you've got to look at the variation.

 

Doug: [00:31:23] Look at the variation associated with things. I mean that's the whole key to this whole process and the more you get to understand that variation and make it your friend instead of your enemy sort of being a victim to it the more successful and the more fun you're going to have.

 

Tripp: [00:31:38] Well that concludes this week's Brain Brew Whisk(e)y Academy. Thanks Doug.

 

Doug: [00:31:43] Thanks.

 

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