• " >

Symphony Labs Looks to Help Companies Embed RPA into Larger Digital Transformation

Late last year, Symphony Ventures launched a new initiative: Symphony Labs. Headed up by Chris Gayner in London, the goal of the endeavor was to establish a small agile shop that could think about the big-picture challenges facing the automation sector and determine how to better help clients implement the right solutions.

To learn more about the focus and plans for Symphony Labs, we recently sat down to chat with Gayner. He explains how the company is navigating a world in which new technologies like automation and artificial intelligence need to integrated into the overall digital transformation journey that so many enterprises are now embarking on.

Photo: Chris Gayner, head of Symphony Labs, a new innovation center for RPA provider Symphony Ventures. (Credit: Symphony Ventures)

Jared Wade: So you just got started last year. What is the nature of Symphony Labs and your role there?

Chris Gayner: What I began looking after was: “How do we look at the world?” It is a critical thing. There’s so much happening in the AI/cognitive/RPA/automation space — let alone the wider technology landscape. So the key thing for me has been to come up with a way to look at world in such a manner that it gives us an objective view on all the things that are happening.

As a business, we have a great handle on RPA. But when you start to move outside into other things — like workload management, intelligent OCR, and other “spot technologies,” let alone full-scale technologies — the question is: “How do we look at all that in an objective way and help clients cut through the mess?” “Do we start with RPA or do we start at the other end with the bleeding-edge of AI and cogni-technology?” “How do we get from A to B?”

So my role is everything from helping clients understand what their journey looks like as well as mentoring a small team here and continuing to talk to a lot of technology providers. Engaging with clients, engaging with other partners. So there’s very much a bit of strategy, a bit of evangelism, and a bit of structure and building — and then a whole bunch of everything in between.

Jared Wade: Very interesting. But when I hear “labs,” I think a little more about creating new products, creating new innovations. Is that the goal long-term as well?

Chris Gayner: Yeah. I think “labs,” as a concept, it’s an odd thing to have in a services business. But the idea is that I’ll give you a challenge and then the lab comes up with a solution to that challenge.

As I mentioned before, the world of technology and the world of AI and automation — on top of normal technology — is massive and very hard to handle. So a lot of clients we talk to, as of today, are struggling to get that scale. And “that scale” doesn’t mean 10 robots running a process over and over again. “That scale” means they’ve got an end-to-end automation solution, or even they’ve got a solution that uses people and robots but is actually more on the autonomous side. That’s what we’re actually seeing.

“We want to be able to show that these labs have an impact on the real world. We’re not seeking to be a gadget house. We don’t want to be seen as this gimmicky experiential lab.” – Chris Gayner

So, the labs concept, in my view, is about figuring out how you run up those big challenges. How do we cut through that mass of technology? How do you start to bring those propositions from all those different providers and solution providers to the table? How do you bring multiple technologies together?

In essence, the labs are to help us and our clients identify and incubate new ideas, new technologies, and new concepts. It also has a capability-build exercise on the side as well, which determines how you actually put things into play once you’ve identified them. How do you move them into the real world?

I think that is the key challenge. As the technology staff grows and grows and changes, I think managing that — especially when things are starting to run all by themselves — is critical. How do you start to move through that landscape? And I think that the labs are definitely helping in those conversations with clients. Give us a challenge, and we’ll either help you or we’ll do it with you jointly to configure a solution to that problem.

Jared Wade: So, it sounds to me that, maybe two years ago, there would have been a lot of companies that you could approach with an single RPA solution. You could say, “Hey, we’ve got this solution” and then implement it in a one-off way by itself. Whereas, now, most companies are at some point of a digital transformation that is more sweeping than just adding some robots to the mix.

So you’re kind of trying to figure out how your RPA solutions, and various automation and cognitive technologies, can become a part of the larger whole? You’re figuring out how they can be implemented in a way that is helpful — and not disruptive — to the overall, larger digital transformation companies are going through?

Chris Gayner: I think you’ve got the right word there: “digital transformation.” I think that’s bang on. A lot, if not the majority, of companies are on some journey towards digital transformation. They’ve got crucial concepts happening — not just in automation, but other organization-wide solutions. They’ve got impressive concepts all over the business, and they’re starting to get concerned about how to start to bring those together. Well, Some are concerned. Some are interested — and some are opportunistic.

But they’re looking at how to move these technologies from proof of concept (POC) to scale. And they’re asking what happens when they move them into that production-scale environment.

There have been a couple of papers written recently on that: bringing together multiple technologies and scaling them in such a way that everything still works within their legacy environment and doesn’t disrupt the core principles in their business. That’s a critical challenge for most businesses.

Jared Wade: So you’re in London and you said you’ve started with a few people there. So it’s not going to be too large of an operation at the beginning?

Chris Gayner: Yeah, it’s quite small and scrappy at the moment — or, rather, “nimble and agile,” I should say. It’s about first focusing on the right priorities, and then we can focus on everything.

A lot of the conversations that we have with folk are around what we doing in the AI space, and that is all about prioritization. While everyone gets very excited about AI and cognitive tools, there are a lot of conversations out there about the adoption of AI. And the way I look at it is that a lot companies are still coming to grips with what AI looks like at scale within the enterprise environment.

“A lot companies are still coming to grips with what AI looks like at scale within the enterprise environment. Until then, we want to work our way to that point practically.” – Chris Gayner

Until then, we want to work our way to that point practically. So we have started with a very small, agile team to look just outside of the realms of robotic process automation. We’re looking at things like intelligent OCR, workflows, and basic machine learning. And then we’re going to work our way towards those more-cognitive tools — hopefully in line with where the market’s moving and the markets’ appetite for those tools.

Jared Wade: It’s an interesting point. I’ve wondered — after seeing some statistics and just from talking to people — whether it’s a little of a chicken-or-the-egg thing. What I mean is whether the companies aren’t ready or if the technology isn’t ready. From your end, does it seem more that the companies are a little scared to jump right into that AI ring without going through the first step of automation and some of the lower-level opportunities?

Chris Gayner: Yeah, I thoroughly agree, and there’s a couple of key facts here. One is that a lot of our customers work in a shared-services environment or they work in the outsourcing environment. And these guys sign really strict service-level agreement when they engage clients to do work for them. These agreements suggest that work must be done in a certain way, by a certain time, in a certain format — each and every time. If they break that format, they are basically penalized.

Imagine putting in a piece of technology that self-learns or learns probablistically and delivers outcomes differently every single time. It simply can’t work in that environment because of the changes that are littering the outcome.

However, if you bring it into the front office, or you use it data center, and it brings back a higher level of confidence about fraud, then that is probably more likely where the adoption will happen. And we’re already seeing that. Facebook, Netflix, all those guys have built it into the front end of their toolsets.

Jared Wade: How will you view success? What are you trying to accomplish in your role over the next year or so? What is the future of Symphony Labs?

Chris Gayner: We’re really touching on some pretty exciting projects at the moment. The idea is we want to be able to show that these labs have an impact on the real world. We’re not seeking to be a gadget house. We don’t want to be seen as this gimmicky experiential lab to a degree.

The idea for success for us will be to actually walk a line through some of the projects and areas we’re actually working on and let those lead the lab’s thinking. That’s really interesting. We need to help clients in real areas and actually get them thinking bigger about automation and the wider transformation journey. I think that’s success.

This conversation has been edited for clarity and space.

  • " >

Related Posts

After Acquiring Symphony Ventures, Sykes Names Ian Barkin as Chief Strategy & Marketing Officer
(Photo credit: rawpixel / Pixabay)
Sykes to Acquire RPA Consulting Firm Symphony Ventures for $69 Million
crowdsource artificial intelligence machine learning (Image credit: geralt / Pixabay)
The Benefits of Crowdsourcing Innovation with Artificial Intelligence and Machine Learning

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Do NOT follow this link or you will be banned from the site!
%d bloggers like this: