What is Product Mining? With Maximilian Kissel, Co-Founder and Managing Director at Soley

Mining your business podcast is back with yet another episode about product mining, data science, and advanced analytics. Yes, you heard that right. Product mining. Jakob, what do you know about product mining? Well, about Drake, I'll be honest. Not much. Yeah, same here. I'm in the same boat. But thankfully, we have Maximilian Kissel, co-founder and managing director at Soleil here to tell us all about what product mining is, what challenges in the manufacturing industry you can tackle and what in the world of bill of materials is, let's get into it. We are here with yet another episode of Mining Your Business Podcast and we are super happy that you are tuning in and listening to our talk with yet another guest in Maximilian Kissel. Max, welcome to Mining Your Business Podcast. Yeah, thanks for having me in the show. Hi. Max, you actually studied complexity management at the WEM, which is University in Munich. In process mining, we like to reduce the complexity. What was the studies actually about? Did you also try to do the same thing? Yeah, I mean, actually, my background as I started mechanical engineering with my PhD at Munich and that's where I was really in the topic of complexity management. This was kind of my nerd topic, but also a big passion of mine for the last 15 years. There was also always my motivation to provide intuitive guidance for people in the industry to navigate and decide in complex industry situations. Also, of course, I mean, it's also the aim of Soleil and also the aim of product mining to reduce complexity. So this is, I would think, something that we have in common here. Can you real quick just kind of elaborate what complexity management actually means? Like, how am I supposed to imagine what complexity management entails and what it doesn't include and include? Oh, yeah, good question of our definition. So to make it maybe simple, I would say, in complexity management, you're co-with huge systems with a lot of, let's say, many and many different kind of elements and dependencies and connections and they change over time and maybe sometimes you cannot foresee or anticipate how it changed and that makes the system complex and I would say this fits very well with what we have in industry as an industrial company. So you have also a lot of, let's say, business objects, if you take it quite abstract and they are dependent on each other and they change over time and as a business leader you have to take your decisions on that and you have to get a big transparency about what is happening, what could happen, what is the impact and so on. That's, I would say, how complexity management gets applied in business. I mean there are many other applications but I'll skip that for now. That sounds very much like when we are doing process mining where we have very complex systems and we are trying to reduce the complexity by looking into them. However, we actually won't be talking about process mining today but rather about product mining and before we get into that, Max, I would actually be interested how did you even came up to doing and working in this field and when we were actually preparing for this interview and we had this short talk at the beginning, you said that there was a very interesting story when you actually met with the co-founder of the company that you started, right? Please, please, please share. Yeah, true. So yeah, as I said, I did my PhD at TU Munich and I was in this, that doing my research and the field of complexity management and manufacturing industries and I was working with a lot of bill of materials had to compare them, find similarities, try to get, come up with some, let's say, KPIs for engineers how to work with it and the only tool I had that time was actually Excel and some other tools and that was really, really hard to work with them and really to come up with results and I was searching, let's say, the whole globe and all scientific conferences and so on, search the web for better tools. That was all back in 2000, let's say, 2011, 2012, something like this. And I was searching for a tool and then I found it right next door to my office. There was the bagging, bagging, hamps, my co-founder, the other co-founders are Alex and Peter. But he said, yeah, I have a cool tool, I can model a lot of complex dependencies and I can do a lot of automatic expert knowledge automation and apply it to that but he was really searching for a real problem and that's how we got together. He had a tool and no problem and I had tons of problems and no tool and we talked and out of that, Solay was created together with our two other co-founders and then we found it in 2015, we found it, the company and started with several, yeah, try to find use cases in the industry and as engineers we were of course quite driven by the development of products, our products are created, they consist of many parts and things and this was the field where we applied this technology and it came out that this is quite nice to cope with complexity here and yeah, Solay has 40 international people in the team, we're located in Germany and in the Ukraine we have quite a big part of the team there as well and yeah, we serve our customers in the manufacturing industry today so from smaller companies around 100 million of Euros of revenue up to larger companies with several billion revenues in Germany and Europe and we also have first customers in the US and what we chip today is a SaaS product, a product mining platform that helps the customers to really fundamentally transform their business towards more performance and by eliminating the bad complexity in the product portfolio and the value chain and keeping the good complexity to perform the business better because there's also always complexity has two sides, there's the bad complexity and the good complexity and complexity you need to be successful in your competition, Mark and Julian. So I imagine that Solay, like you said, is all about complexity management, displaying complex relationships within the manufacturing process, so going a little bit further away from the abstract, I mean in process mining we do a lot of purchase to pay, that's like the basic standard process for pretty much all businesses, can you tell us what Solay's standard implementation is or what the most common use case for Solay is? Yeah, so I mean, I know that in process mining you work on the variances of processes, how to work for example, as you said, procurement to pay, order to pay and so all these processes that are covered there and you want to mitigate the number of process variances or process goes to, let's say, into timely and inefficient ways and you want to eliminate that. And I think this is quite comparable but product mining is more working on business objects, so it's not of how the business runs but more rather what do we do in the business? So what do we put through all these processes? And that's why I mean the biggest focus here is check out the products a company has. So if they decide which products make most of sense, you can then also have better processes at the end. I mean if you do the wrong products through very lean and optimized processes, you're still doing the wrong products and you still waste resources. So you ask for the typically use cases there and what we created as a methodology around product mining is we had this five step approach of C cut, shape, scale and shield. So you always start with C and cut and C means you get an overview of your product portfolio, what's the actual status, how do you think's perform and so on. And then you can take the first decision is something bad in my product portfolio and then you cut. So this is the phase out process, you can decide, okay, my product portfolio, those products are not valid for the market anymore, so let's face them out. And this is the first really complex decision to do. Of course there are these typical consultancy companies who do this long tail cut projects, but these are getting quite complex because we have to keep in mind a lot of dependencies that you have to check first, otherwise you're cut into your flesh and you cannot sell anymore to maybe core customers and so on. The next step for us then is, so if you have a cleaned up portfolio and you have a only core product, only relevant side products in your product portfolio, then you can think about, okay, how can we further optimize and structure the portfolio in a way that we can smoothly produce it, that we can harmonize with the production strategy we have, for example, an engineer to order to make to stock and something in between, you will choose wisely how you can reduce the delivery times and reduce the stocks on the other hand, so this is what you do in shape. And then after that, you have a brilliant, nice product portfolio which is shaped and structured, optimally, you can then go into scale and scale means, do we have strange pricing? Do we have strange discounts or are there typical shopping baskets of customer that they buy typical collection of products together, so can we support sales here with indicators or what other products to sell to a customer, things like that. So really scale the business, increase the revenues and that's what you do in scale. And last but not least, there's shield and shield is the step where when everything works quite smoothly, there's still risk that things change over time and might have an impact on your product portfolio and here you can really search for bottlenecks in your product portfolio, in your value chain, just to give an example, a typical pattern that we are searching for is this monosupplied parts that go into products which end up in the big share of revenue of the company. So it's quite common that there are small material numbers which are maybe not very pricey, not very important and then you check out okay in which bill of materials do they go into, which products are created with that and which core customers buy these products and then you can sum it up and you end up in a decent amount, share of your total revenue and then you can say okay this is a big revenue at risk and we should do something to mitigate this problem. I think there is a lot of ideas to come back and to really go deeper into what I wanted to also say so you already know we are a process mining podcast and just listening to I almost feel like this product mining is filling the gap between when we look at the process at like two activities when we basically let's say we're looking at order to cash a customer buy something from us and we know when the customer orders something and we then know when we have a finished product and we ship it to them, what we don't know is actually what happens in between unless we do some kind of a task mining unless we do collect some other information from other unstructured data and it almost feel like product mining could basically fill in this gap and at least uncover or get deeper into the root causes that might be behind business implications such as light deliveries or something. Would you agree on that? Yeah I mean if you take this order to cash process I mean this can be done very smoothly you can eliminate process variants that cause time delays and so on everything that's totally fine and totally complementary with what we do because we what product mining supports the customer with is that they can take a decision on which products we offer to the market and which are maybe preferred variants which are special variants and which are standards and then they can combine it and say we have a promise of delivery so can we ship it from stock can we ship it within four days within four weeks within four months I mean this should also be decided at some point on and maybe there's also some I mean in the last few months and years we saw a lot of supply chain interruptions so since change I'm also with the big and reliable suppliers since change there and they have an impact on my product portfolio and on my offering and you should be like online and aware of the problems that arise from there and then change your offering and what can be ordered and then I mean this will have a positive impact on the whole order to cash process afterwards if you first decide what to offer to the market and what should maybe be put on pause I don't know what I also wanted to ask is so we have this product mining you are looking into data you already mentioned a bill of material probably first question would be what even is a bill of material so for listeners who never heard of it I think they might be up for a surprise and then you have these these recursions you have these data that like that linking to one another how does product mining actually go into picture and place a role in solving this yeah so first of all maybe take the first question what is a bill of material here and so let's say the bill of material describes a list of material numbers let's say keep it easy a list of material numbers and there is like a parent note and some child notes and the child notes so for example let's say an electrical pump has some turning wheels some shafts some screw some housings and so on so and all these items are listed in the bill of material and they should end up at the end in this electrical pump and there are different way ways and applications of a bill of material for example there's an engineering bomb a bill of material and manufacturing bill of material and there are several assembly things that can be used and so on so we are using here most of the time the the manufacturing bill of material so how are things then combined to a physical product and and there are some additional layers of complexity if you consider some configuration logic that is maybe in the in the process that for example if you buy a car you can configure that online and there are some rules described in the in the K-Mart so configured material and so there are some rules how to configure that and that you have at the end the idea of your final physical product and you can order it and in the best case the the producer can even produce it and can ship it and sometimes they call you and say we cannot do this and that because we don't get the parts maybe but this is first of all this bill of material and this is let's say the the focal point in the network we are creating with a product mining platform so what we do is we create an enterprise digital twin so this is represented with craft technology and so we get the data from different sources in the company mainly from ERP systems for example SAP where an SAP partner here and get bill of material information we get some transactional data we get orders from customer and supply purchase orders to suppliers and so on we collect all these data and create a big graph of knots and edges so we really focus on the dependencies here and based on this graph we then in the next steps we enrich the graph with automatically created segmentations categorizations KPIs that we can calculate and so on and this is the so the graph generation process and this gets done every time we get new data into the system and of course then you have like a all your products segmented in core site and ballast products for example all you have low medium and high risk products that are maybe affected by some changes things like that so this gets all pre-calculated and based on that we can then apply our value pattern technology so this value patterns it means it finds the needle in the haystack so what kinds of business patterns are critical to the business and should be should be tackled should we prioritize and set as prioritize task for for the user then so this is what the system doesn't helps the user with to prioritize patterns that then have an impact on the business and if you tackle them you can then reduce costs we use delivery times and so on so this is this is the way it goes and then if this value patterns found several of these critical things to tackle the next step is then to go into the decision making so what action should we apply to this element and so on and there we have an orchestrated organized decision making process in the tool so you don't have to just stay there with your insights and then okay we have a problem but what to do next the whole system orchestrates then a decision making process and yeah operationalizes the results you got and you can then take the next steps so so one of the typical things that we get asked is when we look at for example material shortages like when you have a specific amount of a screw or something in in stock and you realize okay on average you're using I don't know x amount per month and you're starting to get low and there's no no replenishment in sight you you can display that but then the obvious follow-up would be okay which one of my finished materials or end products is affected by the shortage right I'm assuming that through this graph technology that you mentioned and you can figure this out with that be one of those risk flags that you can display with this technology or am I am I closer far from it you're pretty close I mean you have this this full network from the supplier who maybe is short in in quantities or cannot deliver in time and then you have like the whole chain through the graph to which shopping basket of which critical or non-critical customer what is affected by that so what's what's the impact you can directly get that from the system and then from there you can also yeah check what how how high is the risk of losing business here or should we maybe first serve a full shopping basket of a course sub for a core customer or of maybe strategic customer and should be informed the others that we have to yeah deliver later or maybe there's no promise for a certain delivery and so on so where can I maybe also reduce the penalties that maybe are within contract things like that so we can check this out and then take decisions here so I'm a very fairly provocative question from my part if if this is somehow extractable into axle can I not just do look at these complexities of these levels in axle or some other BI tool like why would I need solace to show me this in the in this graph form that I mean it really depends how much time do you have here right so so let's say if you if you check it out in axle I mean we also do have customers who that that was the way they did it before they they have like the work with SAP they had some data dumps they worked with with excellence on and what they reported was is that before they worked with Solane product mining they had like it took them like about four weeks to come up with all the dependencies to check out what's the impact and so on and this time got reduced by factor 10,000 to four minutes around that's what they said so that they before and they had like four weeks and now they they have the answer in four minutes and I mean this gives them yeah hats up and I'll put a competitive advantage let's say to to act faster than others and and also to come up with a faster solution for the customer then maybe if a customer's directly affected by that and I think this is an advantage that you can easily work with the platform and get transparency and CD impact and so on have this collection yeah definitely don't take it the bad way we just spent two weeks ago we spend almost an hour me and Patrick discussing on on our podcast what is the difference between BI tool and process mining tool and I was making an argument that our biggest competitor will forever be Excel and seeing sometimes people you know for making a fall back to Excel hurts my eyes but it is what it is so you know we are all facing the same competition and you actually mentioned that the users and the interaction so how does this actually look like for and from an analyst perspective when I you know in in process mining we have this happy path we see these processes and increase the complexity with like click of the button what would be the first thing I saw if I opened your tool and how would it look like and I know that picture problem makes would make more explainatory than than talking about it but what can a listener who's just driving his car or her car imagine if they went into your tool right now yeah and so when the typical user opens soleil they see an overview that should hopefully if we did a good job that should indicate where are your most urgent and most obvious problems in your product portfolio and where do you have huge potential to forecast reduction risk reduction and so on so what should you take tackle first so this is like the recommendation page and just imagine a collection of KPIs maybe what is the progress in certain fields where I'm on what we wanted to target and what is maybe and a heat map that shows for example the core site ballast products over the margins and so you can tackle then maybe you start with the first collection of products where you have core products with bad or low margins and you should really work on that to improve the cost factor there or you have some ballast products which have a negative margin that it's pretty clear to eliminate them directly and not no hesitation so this is the starting point you get like the results of the value patterns that we found and we display it in a way that you can then choose okay with which thing do I want to start today in order to yeah to fulfill my goals to work on a strategy we have today in the business and yeah for example some of them want to grow some of them want to be more resilient more innovative more profitable profitability should be higher or things like that yeah I did hear a story from from one of our customers where we found out that they were actually producing for higher cost that they were actually selling the end product just because that they had such a mess in this inventory that they didn't know how much these material costed them and therefore then they just produced an end product that was more expensive than you know sorry the end product was the produce the product was just more expensive than what they charge their customers for and I guess with with product mining you could probably also find this inefficiency and you also mentioned that there are some core KPIs what other KPIs could you think of that there would be and what do you base them on especially looking just on the materials so do you like look at how often these are produced what are their prices and so on yeah I mean in the material looking at the materials first of all it's interesting what kind of use case are you working on for example if you want to face out products it's really interesting to check if the materials used in a product are they used somewhere else so in other products so typically there's this reuse factor which is an important KPI to think about okay yeah these material numbers are they exclusively in this product so if I face out the product I will also face out these exclusive materials this will have a direct impact on a value chain because you don't have to put them on stock anymore and so on and but if they are still reused in other products you will not have a such a big effect maybe you will even have negative effects because there are suppliers who ship this component and if the quantities go below some threshold maybe other prices then apply things like that yeah I mean these are these side effects that were often not quite transparent and visible but now you have at least a platform to to check out if there are side effects if this decision will have some negative impacts on other on other ends of the of your whole company so yeah so the KPI here for example is the reuse of component is interesting but also then some ratios of how many core side or ballast customers let's say I'm really buying a product here doing the revenues or is the revenue based on products that you maybe sold once you had to let's say refit the whole production line just because of this one product which yielded to some revenues and maybe some margin but the cost for all this was quite big and you could really think about is this really necessary or should I focus more on my core business on my core and my A, B and C customers but maybe not so much on the D and F customers because of transactual cost they're higher than what I gain right and I mean to make this clear and then take let's say educated decisions here to to really think okay is they really serve the whole market or should they serve a focused market and be more profitable there so can I so when we do process mining there's always there's a point where we say this this company or this enterprise is ready for process mining or they this is a perfect example of when process mining is efficient will get value there are some instances where they're not mature enough either through data quality or things like that where this isn't applicable yet can you tell me some of the requirements that you would think that a company should have for product mining to be starting to become effective and where it's most effective yeah always a very good question and I would say if they're using an EAP system to support their processes and their production processes and shipping processes in the company they can also use product mining then then they have the most critical data available and it's not so super critical if all your master data is maintained and updated fully and completely or if there are some maybe some misbelling or something else in your system that's not so super critical and important but if you do your whole purchase orders and selling process and so on via the EAP system you have a quite good basis to start I would also say but this is more in terms of price and cost for the platform because it doesn't come for free let's say it like this and then of course we have some some minimal amount of revenues that companies typically should have in order to be able to yeah set up an IT project like this I mean if you have an IT budget of a few thousand years a year you shouldn't I mean then it's also not necessary also the the findings and the arrow eyes then not that attractive and but if you up to one hundred million euros or higher also some around 50 million euros could work with but then we can show our quite nice and quite nice arrow eyes return on investment and it makes most of sense to introduce something right I'm assuming because of most it has a lot of cases or quote unquote objects that we can write or save value in and thereby justifying the cost of the IT set up software and all these things yeah right is there some sort of key indicator for you where a potential customer something mentions a problem and you think that is exactly what this is for like is there some sort of when they list a bunch of problems do you know exactly like product money will be perfect for this specific one though I would say there are several sentences that indicate okay we should we should talk but one of them is so of course I like the number of stockkeeping units so the number of SKUs is growing every year by 10,000 and we have like 150 160,000 SKUs and things like that so if if a company reports something like this they have exploding complexity they have a huge increase of variance and so on and they are not able anymore to maybe some of them might be but I would say if they are not able anymore to control this complexity and manage it to to keep the good complexity and get rid of the bad complexity and I think we should talk. I'm here actually a question what do you mean by good and bad complexity? Yeah I mean the good complexity is something the way you can differentiate from competitors in the market so if you have maybe this this smartphone and it only has one yeah one chip for performance or this does this play and so on you have only this one and then maybe you have two to few complexity to few variants offered in the market but if you have a product for example you sell a pump or electrical engine and you have like more variants than stars in the Milky Way then maybe you have too many and something in between should be feasible and good and if it takes if it costs more to have all these variants and also the cost of choice gets too big because the customer cannot decide anymore what product makes most of sense because there are so many options and I want to have the right one and then maybe it's getting too complex but there's no no defined line I would say maybe some companies can come up with a definition here but now I'm one of the most pressure pressure to think currently in the world of process mining where everybody is pushing in the direction is a value creation you know it's one thing to see the problems it's it's one thing to have this insight into your process see what's going wrong even do the root cost analysis and put a number on the problem and it's a whole another thing to actually say okay let's fix it and this is how much we saved by fixing it when I was you know sir or looking through your website you also had these slides and materials where you were saying okay this is how much we save so maybe two questions here how do you calculate the saving and the second how do you also motivate the the users the company that you work with to actually do something about it and how does the action even look like yeah so I mean we also put the value for the customer in the in the center of our projects with the customer when we ramping up and introducing product mining as a platform um the the savings I mean there are um many things that you can that you can then save or speed up or um or set free let's say so I would say we first start always with um can I reduce the number of materials um because you and if you have a lot of legacy products and material numbers there are many people occupied with these legacy products to maintain them to keep them on the market and so on and if you can reduce that you can reduce a lot of effort here so this is one thing to reduce effort for example in R&D or in the in the sales department and so on also the the cost of training and sales if you have a very complex product portfolio it really is hard to get well really efficient salespeople and if you can reduce the product portfolio can more efficiently train salespeople can or even give them recommendations then you can increase the revenues that's another thing but what our customers always report is that um based on the results of the product mining methodology applied they can reduce the inventories the the cost of inventories um they have the right things on stock they have better delivery performance after that um and they have faster reaction times which also ended up sometimes in some um let's say uh um avoided costs um but then there's also this connection to the um to the value chain and if you for example can set free some resources in production because um you can remove some products that we're still occupying one of these production lines and you can set this free or you can create some space and so on so it's entrepreneurial freedom to take new decisions on the options you create and then I think this is what the what the platform can bring in and of course direct cost reductions of less material numbers and so on that can be reduced um what are some of the let's say problems when you are what are you facing when you're trying to convince the customers that it actually makes sense for them to to go uh with your solution um because again when we are doing these process mining projects what we do is we do some kind of a proof of value or proof of concept when we just show some numbers um and they're usually that's what we already mentioned in the beginning we have some of these um core processes that we are focusing on be it purchasing be it sales and so on now looking from a product mining perspective um would there be also one maybe two use cases that you usually like to start with and what would those be yeah I mean I just um introduce this model of C cut shape scale and shield and it makes most of sense to first clean up before you move somewhere I mean this is also if you move your flat you should first clean up otherwise you need two tracks to to transfer all the things um so for a good business transformation makes sense to to clean up first and this is also uh the first use case uh I would say makes most of sense I mean sometimes there are special customer situations where it makes sense to do other things as well in the in the beginning but um to start with a with a solid phase out process makes most of sense and then you should not stop after uh one iteration you should take this as an ongoing project in the company to keep the portfolio clean yeah because uh it really has good impact on on on your cost structures and so on and on your uh business performance and delivery times and everything so it makes most of sense to keep this running but then of course as said um then other things like in in shape you you think about um the structuring of the product portfolio and your production strategy so um to to harmonize that in scale you look at uh prices cool shopping basket gives recommendations to sales and then cheat you try to mitigate the revenue at risk this is of course also a nice impact that you'll be what and um another question and that actually comes from your your own experience and from applying the technology at your customers um was there ever something that first of all uh like surprised you when looking into the data that uh in terms of oh my god we really made a huge difference a huge splash and you don't really have to name anyone but uh some interesting findings that you uh generated through uh product finding because i'll be always love these examples yeah i mean the first thing is um that is um this Pareto principle more um often the end applies so you have like 20% of the products make 80% of the revenue margin and so on so and there are some who have more than 10% which yields to 90% or or something else but i mean this is the first uh thing that was at the beginning for me quite surprising is this Pareto principle really applies and and the other thing which um that was maybe surprising for our customers that they had a complete new view on their materials and and so on so they they when they had uh first had to look at it's um at the in the results of solides are okay these all these data sets don't make sense at all it's not your fault but maybe it's the raw data we provided you and they found then this this huge list of of materials numbers that were already more than that and not eliminated from the system and so on so they found like um yeah a bite catch yeah it's a like um you have like a data quality project on the site but you didn't meant to do have it and um that this was sometimes a little bit fun here um can i ask so what is in future for solide like what are your goals of trying to implement or where where do you see solide going in in the near future yeah i mean this um this technology we created um it's also good not only for product but also for looking at customers at suppliers at um um operations um um uh business objects and so on so it's a it's a platform that can um help to take good decisions around business objects and i think we can extend um from the methodology side in this direction um for us uh this year is also um quite um let's say focused on value delivery so we really um try to create additional patterns that deal to additional value um that can help our customers to increase the value of the platform itself of itself and um also bring in people who have the customer to to really get the value out of the platform and so on so this is the um this is the big mission for this year okay so it's um expanding on the existing platforms and existing implementations you already have and delving deeper and deeper generating more value for the customers but also then expanding into parts of businesses that you haven't yet touched yet yeah yeah and then of course i mean this um this technology can also be applied in other verticals but i mean step-by-step i mean we also see some potential here in in the retail industry or in the chemistry industry and so on so we see some um additional verticals coming up but step-by-step yeah and what about long-term vision well what do you see in in future there i mean you know you know we made some fun about this b-hack this big area dishes goal and uh when uh when a manager gets arrested because he didn't use the lay uh in 10 years from now and so it just looks like so you should have used the platform you know you took a very bad decision and yeah it didn't use the system but of course this is more uh kind of a joke and uh but should illustrate of course we want to um get into the decision making processes and industry want to become a standard there that you take better decision if you have all this complexity uh handled and managed there max where would people go if they wanted to know more about product mining about your company or about yourself of course uh with it our website it's uh www.solay.io um you can of course also directly contact me you can contact me we are linked in and sent me a message there and i'm more than happy to to find news bearing partners new contacts uh also of course customers very welcome this interesting maybe has some uh challenges then they want to discuss i'm very open to do that as well and um yeah i have to say i would definitely use product mining because one of my biggest nightmares uh in my five years of experience of working on process mining was actually working on use cases from um exactly below materials where i had to do these um joins uh over and over again when i was looking on a material and i had to find this node go to a uh a level lower and then actually find uh the the correct um the the correct part where it actually should have gone right so um that's the graphic work for you yeah yeah yeah yeah that was a fun time you could write Jakub BOM and he would start to cry as eko and sdb it's just uh brings bad memories um that's why we automated it but then because we couldn't see that anymore yeah make some of that i remember then you just get into the face where you just um pointed to the same node over and over again and you never know when to stop right just you know as crew goes into screw and it goes into screw um but um max uh thank you very very much for coming to our show and introducing uh product mining and also salay azir company um i hope that everybody actually enjoyed it because to me it opens up even more questions and even more uh realms new realms that i've never even knew before about and it's exciting to see how um slightly different technologies can actually complement in one another in this whole um and to end holistic view on your process um so max once again thank you very much and uh good luck with the building uh um the the platform and the kind of big fun talking to you thanks for the notation and thanks you too awesome with your show so uh to you dear listeners we thank you for listening and tuning in on our episode uh as usual you can reach out to us on LinkedIn we are very active there um either through directly through our page uh mining your business or just reach out to me or potry directly uh we also have an email uh miningyourbusiness podcast at gmail.com so drop us an email um that's it for today and we are looking forward to talking to you in uh two weeks time with the next episode of mining our business both cast thank you very much thank you mox thank you potry