Every Monday morning we fire five questions at a C-suite tech industry interviewee. Today we’re pleased to be joined by Tradeshift Cofounder Gert Sylvest.
Gert: What’s the Biggest Challenge for your Clients?
You would struggle to find a business right now that isn’t grappling with some kind of drive towards digitisation for their business. Specific functions like payments and procurement, both internally and in the supply chain are notorious for being heavily paper-based, highly complex and ultimately disconnected.
Many businesses that think they’re digitising by moving systems to the cloud are actually replicating the same set of problems they had before. They’re simply shifting on-premise siloes to SaaS-based siloes.
Tradeshift CTO Gert Sylvest
With more than 50 percent of IT spend moving outside the domain of the CIO, coordinating internal teams and suppliers around rapidly decreasing product life cycles has become a key strategic challenge to their digital transformation. Right now, you’re effectively asking different stakeholders to work with blinkers on.
At Tradeshift, we started with the simple vision that we already have the technologies to connect companies 100 percent digitally. We provide a kind of ‘social network’ to connect companies that do business together. In the case of companies like DHL that means connecting thousands of suppliers around the world onto a single digital platform. Once they’re connected then you can then digitise virtually any aspect of the relationship from invoicing, through to purchasing, risk assessment of suppliers.
We’re not saying we have all the answers. What we are good at is creating a starting point for businesses to become ‘digital by default.’ Once you have that foundation in place then you can start to do some really interesting things.
Technology that Excites You Most?
Definitely Artificial Intelligence/Machine Learning. The progress that ML has made since I studied information science in the late 90’s is simply staggering.
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Contrary to how it is often represented, ML is actually a fairly mature technology today. From a purely technical standpoint there’s little to stop businesses from adopting the technology. Unfortunately most organisations will struggle to get the most out of the technology because enterprise systems tend to operate in silos.
ML / AI technologies are highly adept at processing huge amounts of data at incredible speed. For spend management and classification, you should be able to cut out a whole bunch of simple and repetitive tasks, make handovers and collaboration between different departments easier and get a single real-time view of your cash flow. To get to this point however, you need to be able to draw on networked data across teams and companies so that ML / AI can access data being used in real-time and at scale.
If you look at the companies that reap the biggest benefits from their ML/AI investments, it tends to be those that have used technology to affect user behaviour in real-time. Google is using ML and AI to serve the right ads to the right people at the right time. Netflix derives 70 percent of its revenue by using ML to make the right suggestions to its users for what to watch next.
In the enterprise world, we are only just beginning to see an emergence of software that helps employees in real time, addressing challenges like making better spending decisions. In procurement for example, organisations tend only to have a few categories of spend under management. If you want to steer the organisation in the right direction, you need to influence the spend of every employee. That might not be how procurement works today, but there’s no reason why it could not work like that if you had the data insight, and if procurement was connected to the tools that every employee works with every day. For that to happen we need a supply chain that is digitised and connected, or algorithms can’t begin to do their work.
Greatest Success?
My greatest career success is being a Tradeshift co-founder along with Mikkel Hippe Brun, and Christian Lanng. It’s been quite the ride taking Tradeshift from 3 people working in a garage to over 1000 employees, and building a global network spanning 190 countries, moving close to $500 billion in transactions on a yearly basis. Yet it still feels like this is all just the beginning.
Last year I became GM of Tradeshift Frontiers, Tradeshift’s commercial incubator and innovation lab directed at exploring and transforming business networks, supply chains, and global trade through the application of technologies like artificial intelligence, enterprise distributed ledgers, and Internet of things.
Many tech companies have created R&D labs and centers with closed doors. We’ve structured ours as a hive mind that is global, distributed and open to partners across all walks of life — including customers, third-party app developers, existing players in the market, and academia.
Worst failure?
Tradeshift hasn’t always been called Tradeshift. When we first launched the company we thought we’d come up with a great name for the company. I remember the moment well when we realised that our enthusiasm may have got the better of us in those early days. It was 24 hours before our first global media story broke, and it was pointed out to us that we had accidentally named our company after a provider of portable toilets. Cue a very swift huddle and a change of name before the story went live.
In another life I’d be…
Back in my student days I studied for a Masters in music and computer science. So in another life I’d see myself finding a way to combine these passions. Who knows though, I’m not done living my first life yet!
