X rays
Apr 25, 2026 17:07
· 5:16
· English
· Whisper Turbo
· 2 speakers
ບົດບັນທຶກນີ້ຈະໝົດອາຍຸໃນ 11 ມື້
ປັບປຸງໃຫ້ເປັນບ່ອນເກັບທີ່ບໍ່ປ່ຽນແປງ →
ສະແດງແຕ່
0:01
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Speaker 2 (X rays)
Hello, I'm Will Bain and welcome to Meet the Founders from Business Daily on the BBC World Service. This is where we speak to innovators around the world about the ideas, risks and realities of starting a business. Today we hear from someone who took a somewhat academic concept about improving the process of how we do business and turned it into a multi-million dollar reality. It's an idea which he piloted on a friendly local radio station in Munich with pleasantly surprising results.
0:30
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Speaker 1 (X rays)
It was like an aha moment for them. They were like, wow, we've never seen a look at our business like this. And so we got excited about it, but we didn't get an investor. People didn't believe that those three young guys could start a software business. So that's our guest today, Alexander Rinker, the founder of Salonis here on Business Daily.
0:52
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Speaker 2 (X rays)
Doing business can involve hundreds, if not thousands, of different processes, from paying people to shipping goods, raising invoices and customer service. The problem is, and it can be a big one, not all these systems talk to one another. So it can be difficult to fathom where inefficiencies in that process actually lie. Alexander Rinker was part of a small team that led to today's big company, Salonis. Their vision was to create a software system that would look across the different business processes.
1:21
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Speaker 2 (X rays)
and effectively perform a data x-ray to identify weaknesses and recommend ways to make them more efficient. It's called process mining and what began as an idea while he was at university has turned into a company valued at around 13 billion dollars. Our mission is that we make processes work for people, for companies and for the planet.
1:42
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Speaker 1 (X rays)
And if you've ever been stuck in a bad process, then you realize how important it is to make customer experiences better, to make businesses more efficient, and also to make everybody that works in a business happier because nobody likes to be stuck in a bad process. Take us right back to the start then, the light bulb moment, because it wasn't just you, was it? It was with friends. Me and my two co-founders, we were in Munich at the time at university. So two things happening at once. One of my co-founders heard about process mining.
2:11
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Speaker 1 (X rays)
in a university lecture. And process mining back then was purely academic field. There was maybe like 10 researchers, mostly driven out of Eindhoven in the Netherlands, that were thinking about this. And then at the same time, there was a project that we did sort of as freelancers next to college that we wanted to help a business, a local business, actually a radio station, believe it or not. And so a local radio station in Munich to optimize the IT processes. And what we learned pretty quickly is that
2:40
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Speaker 1 (X rays)
The business actually didn't have good transparency about how the processes worked, right? So you would go and ask, what's the process? What can we improve? And you'd ask three people. It's almost like if you ask three lawyers, you'd get five different answers. You know, one person thought the process was broken over here. One person thought it was broken in another part. So process mining, the idea is, well, every business generates these digital footprints when we use IT systems and technology. Could we use that to...
3:08
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Speaker 1 (X rays)
automatically discover how the processes in the company actually work. I like to call it an x-ray for businesses, right? When your doctor goes in and asks a patient what hurts with their knee, they don't just rely on what the patient tells them, they also have an x-ray to get some data on what's actually broken. And I think that's a very good analogy for our first product. It was this x-ray that you can put on top of any business process, whether it's customer service or IT or selling.
3:34
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Speaker 1 (X rays)
purchasing or manufacturing and we'll give you an accurate picture of how the process works in reality not how people imagine it works how it works in reality just strip that back a little bit further again then so the process mining idea and that example of that first product that you designed using the idea what does it do what is it looking for it looks for these digital traces and the way that works is you can think of any process let's take
3:59
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Speaker 1 (X rays)
and if you order something on amazon right there is objects and events so the objects would be the shopping cart or the item you order or the now if you have a customer service process it would be the customer and then you have events right the events are sort of what happens in the process so you put a new order in amazon confirms the order you make the payment with your credit card you get the shipment to show up at your door maybe you return it or you dispute it or there's a quality issue all those things that have my events and
4:28
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Speaker 1 (X rays)
what we do is that we find traces of these objects and events as they sort of move through the company so it doesn't matter which systems you use or even if some things are not in any system they're just sort of manual and emails and excel sheets etc but we find those objects and events in a highly automatic way and then we paint a visual map of how the process actually works it's almost like a traffic map right and you see here sort of everything's great
4:56
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Speaker 1 (X rays)
it flows through this flow. But then you see all the deviations, customers that get stuck, maybe orders that get delayed, service issues where ping pongs from one team to the other team. I don't know if you've ever done that, but you called your bank or your airline, you ping pong three different teams, nobody solves your problem. So we point out all this in a data driven way. And you can
This transcript was generated by AI (automatic speech recognition). May contain errors — verify against the original audio for critical use. AI policy
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