Data-Driven: Data and machine learning transforming Collections – [FULL INTERVIEW]

0:01
So hi, everyone, I’m here with Paul Jozefak, who’s the CEO Receeve, and they do a lot of work in the in the digital space and got a lot expertise around digital machine learning and some of the pieces and collections. Welcome, Paul, it’s really great to chat to you. Thanks for being here.

0:15
Thanks for having me.

0:18
So I think first off, I kind of interested in terms of some of the things you’ve been seeing through through COVID. I mean, obviously, you know, it’s affected all of us across the world. And I’m quite interested in your perspective in terms of seeing in terms of what you’ve seen in the market you’ve been operating.

0:33
So it’s kind of gone up and down. So we’re, what, almost nine months kind of into the pandemic, what ultimately happened on our end at Alibaba, right at the beginning was pretty much you know, deer in headlights effect, most people didn’t know what to do. So kind of everything slowed down for quite a bit. I think a lot of companies were just extremely focused on regrouping, kind of adapting to the work from home situation, you know, we had a couple of partners where you know, they have 4000 people into a home office. That doesn’t happen overnight. So basically, you know, everyone kind of reverted to very specific core processes, things went quiet for a little bit. But then I would say kind of throughout late spring summer, things started to normalise as much as they could, with you know, a lot of countries still going in and out of lockdown. So, I would say the industry or my specific interest industry was was very quiet, almost paralysed for a little bit, then people kind of started realising Okay, we have to adapt to whatever, and I hate using the word new normal, but adapt to the new normal and, and then I would say, kind of like September timeframe, things started picking up. So again, a lot of people realise our industry specifically that, you know, there is going to be an upswing, whether you like it or not as much as the pandemic is, you know, net net very negative for society and for business. At the other end of the spectrum for collections and pretty much lenders and whatnot, there is there is quite a little bit of a civil lining, we definitely see customers of ours, you know, preparing for the future, and realising that if they don’t take a digital approach and don’t automate workflows, and don’t take a very kind of technology centric view, they feel like they’re gonna be left behind that I think that it was a wake up call. So in a sense, the industry, whatever you want to call it, you know, everyone was forced to wake up, everyone had to digitise overnight, and what would have taken 10 years, you know, we’ve all heard the cliche, saying 10 years and three months, I think it’s very much something that we’re seeing, but very positively people are starting to react, I thought they might wait until next year, but we saw kind of q3 q4, people were already being responsive.

2:37
And that made a big change in terms of people’s budgets in turn in terms of clients and like investments in digital and those kind of things. I mean, how much how much, how much is that change, because collections was always down the bottom, in terms of investments, and it feels like that’s, that’s that sort of change, really,

2:52
if you kind of think about it, I mean, Collections has always been seen something, you know, buried in the basement, within the accounting department. And once you know, a lot of these businesses started happening, having to think about, you know, their cash flows, and just basically making sure that, you know, they got the money that, you know, was basically booked as revenues collected. It’s one of the easiest ways to go about solidifying your business and your bottom line. So, you know, the focus switched to an extent to kind of looking at the cash flows and asking, how can we accelerate that, at the same time, there was so many different effects, because of COVID, when it comes to the lending inflection space. So what, what ultimately happened is that initially, a lot of people started saving heavily because they didn’t actually have expenditures. So I’m sure you’ve heard this from other people in the sense that, you know, because we were all home, people weren’t going out to eat, they weren’t buying cars, they weren’t, you know, basically purchasing luxury goods. So that actually led to a quasi upswing in terms of savings. What a lot of people also did in the collections world, or what affects the collections world is that because all of a sudden, they had this free cash flow, they were paying down their debts. So the the industry in and of itself profited short term in the sense that a lot of people were willing to step up and kind of just pay down what was outstanding, I think, you know, after a certain amount of time, obviously, reality hit and you know, people weren’t able to pay their rent, they weren’t able to kind of live their lives as they did three or six months ago, then again, they weren’t necessarily paying down any debt that they had or catching up on their collections issues or, you know, accounts that were in arrears. And I think that’s obviously just the swell that’s growing right now. Because towards the end of the year, once all these kinds of payment, holidays, mortgage holidays, you know, all these quasi postponements of due dates, when satellite catches up, which will most likely be the case by by January 1 of 2021, then you’re going to see kind of the real effects of COVID from 2020. And I fear I fear quite a bit for the economy in general that, that there’s a lot of people you know, I don’t know about Europe as much but in the US, for example, you know, there’s a tonne of people who didn’t have in three months savings on their, on their accounts. So there’s gonna be a big mess coming. And again, for the collections industry, it’s going to be it’s an opportunity, obviously, but then also the question is where they were recovery rates, will you be actually liked?

5:03
Yeah. I mean, I think all that the government, the government stimulus or the government, the government helps him to really sort of like suppress delinquencies in the short term, like over the summer. And then And then the question is just like, when does it when does it come back? I think over here in the UK, we were thinking it’s it was it was really going to be the end of the furlough period. But that’s now sort of being the CANS almost like being kicked down the road probably till certainly January if not, if not, if not sort of March. And it’s a lot, although it’s sort of starting to trickle in. It’s just when does when does that big wave come through? I think I think in the background,

5:34
I think it’s a it’s an inevitability. The question is when I mean, I’ve even heard some post, some, some predictions that it might even be the middle of next year, that could really be kicked down the road for quite a while. I mean, obviously, a lot of these governments are in a position to do so. But at some point, you’re gonna have to have some rational thinking kick in, and we’ll have to start thinking about, you know, how much of a, how much of a wave are we building up? And then ultimately, does it lead to, you know, tonnes of insolvencies, where the collections industry isn’t even able to collect on a lot of these? Loans? payments? So it’s a balance?

6:06
Yeah, and what about the the segmentation of the almost like the books, like because it’s almost like this, it feels almost like it’s cut, cut the population in a different way than it traditionally would be? Right. So normally, it’d be based on let’s say, let’s say, your your bureau score, your bureau score, and sort of like, you know, that traditional kind of indicators, and all of those things, that kind of change now, I mean, you had people who, you know, had really stable jobs, let’s say they’re in the hospitality industry, they had a really great business, and they just been decimated, it feels like and yet, you’ve got other people in, you know, you’ve got stable jobs, let’s say, for example, public sector, is a good example, seems much more stable, and it’s almost like they’ve saved money, as you say, I mean, how do you think is best to kind of react to that, in terms of that re cutting and segmentation of the, of the book, particularly factions,

6:51
perfect storm, as you mentioned, let’s say you’re in the hospitality industry, you just bought purchased a house, you know, took down a lot of, or took on a lot of debt for it, because the interest rates are so low, you might be house rich in cash for, right I mean, at the end of the day, anyone who is in that kind of a situation, is obviously going to have an issue, because they’re going to run out of run out of cash, what I think is going to have to happen is that regardless of what the governments are doing, I think there’s going to have to be a lot of almost compromised from the private sector in the sense that if you want to make sure that your customers are able to be your customers 12 to 18 months from now, you may have to kind of look at how can you potentially work together with them. Um, that’s a little bit kind of what the whole collections industry is kind of facing right now, where taking a customer centric approach to, to your customers means that, you know, you have to work together with them, and work on potentially setting up instalment plans, lending them capital, so that they can actually, you know, stay focused on what they need to do is, which is basically funded funding their funding their core lifestyle, or lifestyles, or am I just basically a life paying their rent by food and, you know, keeping the family going or whatnot. So it’s, again, it’s almost it’s almost difficult right now to say where that hit is, because you and I could almost posit, yes, of course, someone in the hospitality industry who just bought a house. But there’s going to be a bunch of kind of follow on effects, which also won’t kick in. I mean, again, travel or hospitality, whatever happens there trickles down to other industries. And you’re going to have kind of staggered effect where multiple, multiple segments which might not be hit, immediately will ultimately at the tail end, also be hit. Whereas at the front end, people might be recovering to an extent because they decided to switch industries or whatnot. And we were thinking in 12 months cycles at this point, if not longer, to an extent. Right. I mean, all the all the out of the pandemic isn’t, isn’t isn’t captured and, and wiped off off the table within within a year.

8:44
Yeah, this introduces not just the the immediate effect, you’re saying it’s also then it’s the knock on effect and the knock on effect, the knock on effect and that almost like that, that that complexity becomes complexity squared or cubed, it becomes very difficult to kind of predict what’s what’s actually going to happen.

8:59
Absolutely. And that’s, I mean, that’s the challenge, right? Because you also have to ask yourself, kind of When does one go up and the other go down? Because you have to plan over a much longer cycle. And I think that cycle of recovery is not one or two years, we’re looking 34567 years out out in terms of all of the knock on effects of what’s going to happen. Because if you just think about hospitality, restaurants, hotels and whatnot, you know, once one of those businesses is out of business, I mean, it’s it’s not coming back quickly, and then effect of just simply basically the residential or sorry, the commercial real estate, where that restaurant or hotel is, and then these are cycles that take much longer to play out.

9:36
And how do you think the collections industry should react to that? And obviously, we tend to be, I mean, front and centre in terms of talking to talk talking to these folks or dealing with these folks? I mean, obviously, we’ve got forbearance plans that are in we’ve got the various sort of treatment plans that are in but do you think there’s any sort of secret sauce anything new that we need to think about, you know, from before, firstly,

9:57
I mean, the focus has to be on on resolution via compromise of some sort, I think you have to be pretty creative in terms of what you offer anyone who’s in arrears as a solution, because again, if someone doesn’t have the cash, what are you gonna do? At the end of the day, you gonna have to figure something out. So I think there’s gonna have to be a lot more of quazi versus kicking the can down the road and finding a solution that allows for a midterm, to mid to long term resolution. Because you simply can’t, you know, basically write everything off or take everything to court. I mean, at the end of the day, you’re also going to have to make a decision of do you take someone, for example, in a collections process into a legal process, with the respective costs that are attached to that, knowing well, that you won’t be successful? And who even knows what kind of happens regulatory wise. Next year, I’d be I’d be quazi pretty foolish right now to try to predict, you know, what are the government’s doing 12 months from now, when you know, everyone is hit by this, a lot of us kind of in the situation where you and I are interacting, you know, we we’re not maybe blowing up around this right now. But there sure is a lot of people that we’re not, that we’re not interacting with, that are already kind of in the midst of it. And so, you know, you might you might just have this wave that is also in via some regulatory changes, you know, being held up. And my thought is that the industry, and I think the question you asked what needs to be done, I mean, I’m always a big proponent of digitalization, I mean, everything that you can digitise, which allows kind of significantly more to be done, obviously, should be done. But that’s something new. I mean, everyone, the whole industry knows that it has to digitalized and automate workflows. I mean, that’s just a no brainer right now. But I think you have to become creative about how you interact with anyone in arrears. And I think that’s where, you know, certain products might might even show up on the market that we don’t, that we don’t foresee right now, there might be a whole new kind of wave of lending, which is targeting a very different approach to lending, right? Who knows, you know, what the government’s do next year or the year after? So I think there might be there might just be opportunities in industry in terms of thinking outside of the box. What that is, specifically, I think it’s very difficult right now to say what it’s going to be.

12:01
What about, what about so digital, you’d mentioned around digital and sort of, you know, putting digital processes in place? You’ve got a we’ve got a lot of experience around that. I mean, how have you seen it seems like take up from from a consumer point of view? I mean, do you think that’s really sort of helped the adoption, you know, in terms of like, I suppose adoption from, you know, end end clients and end customers really using it and getting more used to it. So I’m using different levels of ticket rates and you were before?

12:27
Well, I mean, we, it’s almost it’s almost chicken or egg, right. I mean, at the end of the day, there was a huge shift that was going on in the collections world anyway, because of a shift in demographics, and the fact that almost everyone has gone to mobile or the online devices. And let’s put it this way, over the last couple of years, I mean, obviously, making sure that the end customer is given the opportunity to pay using the modalities that they like to use, and that they’re comfortable using, the industry simply hasn’t caught up to that you’re still in a situation where people have to sit down, go to their PC, put in a 14 digit iBank code, which is the most ridiculous way of paying anything. So we are seeing, for example, with our technology, where we give multiple modalities and give the end customer a very simple way of paying. And depending on country, it could be something completely different, right. So for example, the Czech Republic is a QR code, which moves the needle significantly in a very short amount of time. In other countries, that might be a different type of payment via credit card or via PayPal or something. So you see the immediate effect of that, when you give it to a customer like ours, who hasn’t had it. I mean, the uptake is enormous, because you see kind of things being paid within 24 hours, that normally would have taken a couple of weeks. And the cycles of you know, up to 120 days can be reduced down to seven or 14 days. And that’s just by giving the end customer kind of what they want. And also making it as easy as possible, ie they can open something up on their on their mobile phone and click a button and pay. I mean, it’s as simple as that. But a lot of the industry hasn’t caught up to that yet.

13:54
And do you see other different behaviours and different markets? So you mentioned the Czech Republic there? I mean, is it is it? Do you think? Do you think there’s different ones that are different that are popular in different countries? And do you think it will sort of combine into like the same kind of approach? I mean, will we reach will have a common kind of approach? Do you think?

14:09
I think down the road, yes. You know, we’ll all be paying with Bitcoin. I mean, that’s, I kid, I definitely don’t think that we’re all gonna be paying with Bitcoin. But you see, you see a lot of differentiation based upon, I guess, also the sophistication of specific countries, or just kind of the historical growth. So in the Czech Republic as an example, half of the population is completely modern in the sense that they live their lives on a mobile device, they skip the PC and went by mobile because of the penetration of mobile networks versus landline. So that’s something that happened in the last 20 years. But you also kind of see in the Czech Republic, for example, that there’s a way of paying where you basically go to your local post office bring cash and then the post office wires, the money. It’s a very rural urban rural population and I actually come from Slovakia originally. So if you look at Slovakia, the Czech Republic or a lot of Eastern European countries, in the main in the main cities, the capitals, Prague Bratislava, Budapest in Hungary different sophisticated everyone has a mobile device, everyone is used to using apps for payments and whatnot. Once you get, you know, an hour outside of town into very rural farm country, let’s call it that people are still forced to go to the post office. And because they don’t have a computer at home, or they’re not used to using a mobile device for things, so you’re gonna have certain countries that are going to be adapting things slower other faster if you’re Scandinavia, everything is so digital. And it feels like it’s miles ahead. I think it’ll take a while for everything took was equalised throughout Europe, for example.

15:28
What about what about digital and data? I mean, digital gives us the opportunity to get a lot more data, and then really use that to sort of drive experience, I think, I mean, what are you seeing with that? And what are the benefits? The because that can allow us to do new new things?

15:44
What about if you started interrupt? If you kind of think about it? I think I understood your question, probably I mean, once you have these massive amounts of data that you can harvest, because the data has been there, but it’s just, you know, I would say in the last 10 years, they could have been or the industry in general, it could have been taken advantage of the state. And it has been stated that all this data that’s basically there in terms of the transactions, once you start harvesting it, you can just basically take the amount of transactions which generate that data. And already start optimising with very simple pieces of the process. Right. So a lot of people talk about AI, in general. And when you think about AI, it’s basically you know, the machine thinking for itself, we all have kind of from from movies and films and whatnot, this this vision of what AI is, but you know, there’s a very, there’s a very long term immediate intermediate step called machine learning, that’s the dirty secret secret of AI, that anyone who knows what they’re talking about knows that it’s just machine learning. If this, then that is pretty much the the dirty secret. But once you start doing that, I mean, we see that alone with our technology, if you see a specific behaviour, and then you can have the software adapt automatically to it. Some you know demographic pays at a certain time, well, hence, then the software should obviously trigger that messages are being sent at that time to that demographic. It’s not rocket science, right. But it’s that it’s just not being done. If you think about that, in the typical collections process, that process is kicked off with a physical letter. And even in that situation, you’re you’re just not getting as much data as you could, if you were to send an email and in comparison, physical letter, you don’t have any confirmation of being delivered with an email, you can still see if that email was delivered, and it was opened, right there, just that piece of data allows you to start kind of testing different approaches as part of your collection strategy.

17:22
And so last last year, at least over here, there was a lot of noise around or a lot of discussion, I would say around AI as almost like as a banner that was used. And you sort of explained a little bit about machine learning. But do you think there’s there’s special almost like use cases that are best in collections that to look at? I think I think, you know, we’d looked a little bit around sort almost like contact strategies and decisioning strategies or segmentation to do that. What’s your view around? Where is it best Where’s where’s best to focus versus got the biggest, almost like, bang for the buck.

17:53
I think the segmentation probably plays the biggest, the biggest role in the sense of that you can actually speak to your end customer based upon their behaviour, I always like to use the example of you know, the 45 year old executive or the 21 year old student, there’s, you know, there’s worlds in between there and how those two individuals will ultimately behave, and being able to segment around those details and then adapt automatically the content as well as the communication channels. Because again, it’s what we’re doing, for example, a lot of other people are trying to do is that they’re they’re trying to adapt the content at point of, since the injection into the process, ie, right now, a lot of times the content is pre configured, there’ll be multiple templates used. But ultimately, you can have 1000s of if not hundreds of 1000s of templates that can also be dynamically served, you know, sent out as needed to and to a respective segment. And then also the the timing around that, again, just based upon time of day, when you send the communications out, followed by look and feel, again, certain people are going to react more to certain channels via WhatsApp message versus an email. There’s also kind of a look and feel aspect to that right now. It seems kind of very touchy feely is the term I like to use, but it ultimately can all be analysed, and you can see if certain things work better,

19:09
and it’s time to to test and learn. And so like test and learn has been around for quite a long time as you try different strategies and they’re sort of they usually play out then you learn from the new you adopt one, I think was quite interesting, what you’re saying is almost like, how do you do that and you look at the FinTech world, or do a B testing on a much more massive scale, with do with much small changes, smaller changes, like you know, types, types of, you know, types of presentation of a document or slight wording changes those kind of things and do that almost like in a much more sort of almost like industrial type of scale, which is machine learning. It’s

19:38
quite I mean, yeah, let me think about it even a step further. I mean, I don’t I don’t look at building my own company. Based upon the processes of a large DCA in Europe. I actually look at Facebook, and say, How’s Facebook learning, basically serve the messages on your Facebook screen. I look at it more from even almost like a marketing perspective. All the marketing technology that’s been out there for 10 years. doing exactly that. It’s basically testing and then delivering basically what works. One thing that I would add to the to the testing aspect, though, is that don’t forget that right now, if you look at the testing that could possibly be done with the current processes, you could throw 345 variables into the equation. Once you do it completely digitally and your processes are automated, you could be throwing 1000s of variables and algorithm. And that’s where the difference comes in. I mean, if you think I was like using the Facebook, bottle, Facebook and test everything, because they have billions of transactions, or not even transactions, what kind of interactions happening on your screen, and think, Well, you will a Facebook, I’m not the biggest fan. But at the end of the day, they become so sophisticated in terms of targeting everything that happens. And this is basically QA testing, right? I mean, it’s it’s, it’s basically going back and forth, and seeing what works and sticks and what doesn’t, you still have enough transactions in a collection process? Well, to learn quickly,

20:57
and how do you think about it, so a lot of a lot of a lot of, you know, clients, or a lot of creditors will have quite low volumes. And so how do you think of that in terms of like creating the volumes to be able to do that. So the more data, the more meaningful, it’s going to be? If you’ve got if you’ve got a relatively small number of accounts, or soapstone number of people, a small number of people in collections, how do you sort of adjust that do you think you’ll be able to share some of the principles across different creditors?

21:22
I was about to say it’s the only chance is network effects. And again, network effects have been around for 30 years, but the collections industry has actually had zero benefit from it. Because everyone’s in a silo, have their own business and be at the enterprise or the DCA lab, basically, some kind of technology on the back end, it’s completely siloed siloed. In their organisation, once you have providers like ourselves, who are creating a platform where multiple parties are using that platform, there’s obviously a network effect, based upon the data that everyone is collecting. And I’m not talking about like specific data to individuals, but behaviour and segmentation and whatnot, can flow across the platform and create that network effect what you right now don’t have, you have too many incumbents who are basically completely siloed, around the few customers they have. Or conversely, your your use case where you say someone small, and they might have a couple 100 claims per month, they’re not gonna get the benefit benefit of implementing a technology to then harvest the data, they need to tap into a network to get the network effect.

22:19
So one of the big questions that was around machine learning or AI, as being termed was was around explainability. So that’s, that’s been a quite a big, that’s been quite a big topic of discussion. Certainly over here, I think everywhere. I mean, what’s what’s your view on that in terms of like, how best to approach that? And I think one of the concerns is really around it, right? If you if you’re doing making machines to make decisions, you’re using the the algorithms to make decisions. You know, at some point, you have to get through to humans as well. So I mean, I think that’s the fear that’s really going on. How do you how do you feel about explainability? And sort of transparency? And those kind of things? What’s what’s, what’s the best approach?

22:53
Do you mean to the users or to the end customers, because yeah, the end customer should never see it right, ultimately. So to the actual purchasers of such technology, let’s put it that way. My clients, I think the explainability is, is still a hurdle. So there’s definitely a there’s definitely a fear, I think fear is the right word in the sense that, you know, if I, if I let the machine take over, it might ultimately start doing something that I don’t want, that I can also have, or the legal repercussions for, what I think you have to do is you have to do an interim strategy, which is what we pursue, we want to basically make it as transparent as possible, the way the strategies are set up. And then peace for peace, allowing the AI to take over more and more of the process, I think if you learn your way into it and become comfortable with kind of the performance, and at the same time, you also have to track it, and make sure that you understand exactly what’s happening. And not from a technical perspective, but simply from making sure that you’re not, for example, in a country where not allowed to send WhatsApp and all of a sudden, the algorithm decides to start sending WhatsApp in that country, you have a major issue as as a user of that technology, you have to make sure that you’re comfortable with the decisions that the that the software makes, and the algorithms ultimately make so that you’re comfortable letting more and more of those processes be be steered by the AI.

24:05
And I think I think I think it’s interesting, but there’s also and there’s also a little bit to the end consumer as well, which is almost like the transparency and explainability piece feels like it’s holding back some of the mathematical techniques. For example, neural network seems quite held back by that because it’s kind of like, when it’s gone into a black box, do I already know how it’s how it’s coming out? And it’s gonna give me a decision, particularly around lending decisions, or particularly around light. So like, where the hard where the hard decisions in terms of mathematically, it probably does better describe it, because that’s what the the math and the stats will say. However, I think there’s a fear around that. And so people seem to have almost like it’s held back neural networks as almost like as the algorithm and sort of gone into things like random forest and those little things that are a little bit just a little bit easier to explain. You’ve got decision trees as an example. And I just wonder if we’ll ever if we’ll ever be able to use that or do you think it’s going to hold it back longer term, or does it limit where it needs to go?

24:59
Yeah, I think we get there eventually. The question is, what’s the timeline to get there? I think there’s going to be a lot of fits and starts kind of until then. And I also think there’s also certain things where you have to simply kind of determine at what level do you let the machine take over, if it’s a low value claim, let the machine kind of make the decisions, if it’s a high value claim, steer kind of far early into the process into a human around interaction, for example, especially if it comes to some kind of instalment plan that’s being offered or whatnot, which ultimately, indirectly is lending, right. So what you want to do is you want to actually put kind of stops and starts into the into the system that allow kind of at a very early stage right now for things to kind of diverge into a path where there might be a human interaction, if it’s a low value, claim or interaction, and you can let it completely run, so to speak, autonomously, I think that’s going to be kind of the interim step where you’re just going to kind of also segment by value, and everything that’s very low value will completely be steered into a self service path without any kind of opportunity to get anyone on the phone. Conversely, if it’s something that’s more value, or even, maybe not necessarily financial value, but customer value, where you throw that I mean, I think down the road, I mean, let’s let’s take a little step back from collections, one of my theories about customer service in general, is that we’re now also evolving into into a era where customer service might be the differentiator, in terms of human customer service, right. I mean, there was all these examples of the last 10 or 20 years where some retailer did something in a customer service type of a situation of, you know, whatever the clothing store that took back winter tires, just because they were so trained about customer service, that they that they let someone return winter tires, although they didn’t sell winter tires, I think there’s going to be a differentiator going forward where certain businesses by actually letting you get someone on the phone and talking to you will be a differentiator versus your competition, where you’re just forced to go through some kind of automated processes. And hence, I think that you’re gonna have the segmentation based on on the actual customer value, and relationship or whatever you want to call it lifetime value. That will also keep a lot of these processes at bay. Because the customers say the customer will reject it, if if they if they feel improperly treated by the machine,

27:10
as almost like you have the value, the value end, which will be much more automated, but then people pay a premium for really good for really good service

27:18
that you do now in certain in certain instances, right? I mean, you’re already right now, if you buy a car, or in certain industries, where you get the VIP or on a premium type of service, where you’re basically having everything taken care of, I think that ultimately is going to happen around, you know, banking, lending and whatnot, people are just gonna say I’m a VIP customer. So I want VIP service.

27:36
I think I think it’s really interesting. Even just looking at like these video calls, I’ve got so much more used to video calls over the last like nine months or so. And I think about you think about the kids today, who are who are doing this natively. Right. So I mean, this is this is this is what they all grew up doing in terms of these things. And then what’s going to happen, and it’s becomes almost like a bit of a generational divide in terms of before and after. I mean, we’ve adopted it, but the new kids coming through, I mean, they just do this naturally. And it’s and it’s not just about replicating what went before, as much as now there’s new opportunity. And you can do things very different. You can talk to people, you know, across Europe, across the world very easily. I mean, it’s just this new opportunity really,

28:14
it also creates all kinds of different ways of interacting. And then I mean, back to the questions world, if you think about the fact that you can almost get someone into a video call versus just a regular unfriendly, normal call, there is a certain customer service aspect to it, where if you actually get a physical person talking to you, there’s there’s a certain amount of I mean, especially if you see that they’re trying to help you. Right, yeah, very kind of, let’s call it charged situation, if you feel that the person on the other side really actually cares about helping you that can move the needle quite a bit. And it might then be a very high value interaction with the customer. And because that customer is used to it, I mean, think about even two years ago, someone actually video called you most people be like, what’s this all about? They didn’t know? Yeah, don’t kid the kids were doing it. I mean, we’re, we’re all kind of age wise, we’ve already aged out of that. The kids now you know, this is a 1012 1418 years old, they were all talking via video before the pandemic anyway, we’re now just being forced as quasi the old guys to adapt to what’s already been the situation in the younger demographics anyway.

29:15
So I’ve heard that quite a bit in terms of like, you know, not being out on the road, not visiting people face to face not being in the office and sort of like, you know, has that damaged relationships, from a business point of view? Has it has it meant that, you know, we’re basically relying on relationships that were built pre COVID, right, in terms of like, you know, getting getting on with people. And then I’ve had a contrary opinion, which is really around saying, Well, look, these video calls actually really help. And actually, it’s short video calls that help as much as trying to replicate what we did before. So you need you can do it, but you have to do it in a different way. I mean, you got to you got to view on whether the face to face helps, or can we replicate it with video?

29:52
So my you know, my background over the last 25 years of my career has been extremely network driven, right. I came out of the investment side so I was ready capitalist for years now I’m back to quazi. running a startup, which still in and of itself is all about networking, right? ultimately finding customers, partners, employees, and it’s all about the network. I feel extremely, so to speak. How do I put it privileged to have an extensive network that I’ve built up over 20 years. So the fact that everything is now switch to video, I already have that existing network, which I can always fall back on. I do ask myself, if someone is right now kicking off their career, which like, for example, out of my employees are doing right now, who don’t bring that network with them? It’s extremely difficult. So exactly what you said that building out that network, just using video, attending virtual events and whatnot, you don’t have any of that serendipity effect, right? I mean, over the years of the conferences that I’ve gone to in the lunches and dinners that I’ve gone to, and people that I’ve met that kind of just random introductions that you don’t get in a one to one call, right? How many times I’ve been sending an event with someone I know, someone else walks by that person grabs them, it says, Hey, you got to be Paul. I think that right now, you and I might not even be seeing what’s happening in terms of the way people are building networks using the available technology. So just again, another example there’s a there’s a software or service called Lunch Club, I believe, where you can just do random meetups, you put in your interests, and you get kind of introduced to people and you do a quick half hour call with them. I do two a week, using that technology just for people in the industry trying to just keep my network kind of kind of stable or growing. It’s one of the kind of things that showed up in the last, let’s say, six to 12 months where where networks are being are being juiced in the sense of trying to make things grow.

31:31
I think I think that serendipity is quite interesting. If you go back to the modelling piece as well, which is like it’s kind of what you build in as well. Otherwise, you get like local, local, local minimums, and also all of those kinds of things as well. So it’s like, it’s almost like we’re having to replicate some of that, actually, in real life, right?

31:46
Yeah, I think I find that super exciting. And when I actually think about, is there a way to replicate serendipity that happened in the physical world into an online environment or a virtual environment?

31:56
Well, pull. It’s been fascinating chat to you. I could chat with you for enough for another hour, I think so. I really, really enjoyed it. Thanks very much. I really appreciate you taking the time. So and hopefully we’ll chat and chat again soon.

32:10
Definitely. Thanks.