The Future of SaaS - Part 2: Input is Error
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What is the vision for automation and why is “input is error” important for SaaS?
Today, both the CPU power available and also the algorithms available means that you can optimise functions that was not easy to optimise in the past. For your particular type of software, find the areas that you really can automate with machine learning and build up a little team that are able to work with that.
So this is another in a series of conversations that I'm having with Oyson Moen, who is the long term chief executive and chairman of Visma. And fortunately for me, maybe not fortunately for him, a good friend of mine. We've known each other for a long period of time, over sixteen sixteen or so years. More relevant is that Oysten has got forty years plus experience in the technology and particularly the software industry. in Europe and we're using that experience to really give some views on both the kind of past, things that have happened in the kind of last four or five years, and in this case in the kind of future. We're trying to look to the future and ask a couple of questions about what might be happening kind of five and ten years from now and what the important trends are.
So Oyston, welcome again. So turning to the future this time, could you comment about some of the technology and how you think they might influence what is happening to software or even cloud software, you know, maybe over the next few years, maybe things that we won't see really impact consumer lives or small business lives for a while, but things that you're working on and that people you know are working on at the moment within Vismo or elsewhere.
I think what we will see more morrow is all kind of automation. Elon Musk says that input is error. That's a little harder maybe but but consumers and users do not want to input things twice or over and over again. Yeah. They expect the system to understand what they mean. So they like to do as little input as possible. Yeah. So we will see that in in various forms and maybe the first stage is to have systems with very good APIs. That is programming interface so it's easy for other software to to interface. We see that on quite a few of our n uh own ERP systems know that eighty percent of input is coming from other software through APIs. And it's just now in twenty-one. I I think this will just develop so that in a few years a high ninety percent of input is actually coming from other software automatically.
Yeah. So if data or information exists somewhere, I think customers and user expect the system to retrieve that data automatically so they don't have to input it.
Yeah. Which presumably as well reduces errors, yeah, reduces kind of frustration on behalf of both the inputter and and the user as well.
Yeah, absolutely. Yeah. So so much data exists already and with good APIs and any software you want to
How will APIs become the primary way software communicates and why does that matter?
survive in the future will have good APIs. For software vendors, it has impact on how they charge for the software.
Yeah.
Their per user or perceit model is going to be meaningless in the future. As most of the data and most of the uh consumption of the software is is done by other software.
Yeah.
So so you'll be much more even revenue sharing from the other software vendors and it's all transactional volume based pricing.
Yeah.
So that is one thing. Having very good APIs, making sure that data that exists somewhere are taken in automatically. But then we see a lot of happening of course in the space that is widely known as AI, artificial intelligence, which are a lot of different things. And in business software I I think we see particularly three areas that uh are interesting. One is machine learning, the other is optimization, and the third is natural uh language processing. Yeah. So if you start with machine learning, machine learning is to use to categorize and to understand patterns and to to see what's uh what's hap understand what's happening. So one example where uh at least in financial software where you typically use machine learning is that you have invoices coming in.
Yeah.
Still quite some on paper or PDFs. And you want the software who a machine learning algorithm can read those invoices and understand what is what.
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Chapters
8 chapters
1
What is the vision for automation and why is “input is error” important for SaaS?
0:03–3:00
2
How will APIs become the primary way software communicates and why does that matter?
3:00–5:20
3
How can machine‑learning be used to automatically read and book invoices with near‑perfect accuracy?
5:20–7:44
4
What role does optimization play in logistics, healthcare and resource scheduling?
7:44–9:41
5
How is natural‑language processing transforming support with chat‑bots and self‑service?
9:41–11:59
6
What practical roadmap should a SaaS company follow to adopt continuous delivery, APIs and AI?
11:59–13:47
7
How should SaaS firms invest in machine‑learning talent, university partnerships and off‑the‑shelf tools?
13:47–14:51
8
What are the key take‑aways on building a future‑proof SaaS business from this conversation?
14:51–14:56
Speakers
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