AiThority Interview with Spencer Lentz, Principal, AI and Digital Process Automation, Digital Customer Experience at Capgemini North America

Please tell us about your current role and the team / technology you handle in the company.

As a Principal within the Digital Customer Experience (DCX) group, I work with leaders of major industries to grow the portfolio of Capgemini’s solutions in artificial intelligence, digital process automation, and digital customer experience. Solving key business challenges with leading edge innovation is incredibly challenging, engaging, and fulfilling. The technology landscape is changing so rapidly that it’s hard for our clients to separate what is real versus hype. A lot of my time is spent helping clients understand emerging technologies and platforms to achieve their business goals.

What is Capgemini’s greatest achievement during the pandemic phase? How did you associate yourself with this movement?

Capgemini has made a lot of smart decisions as part of our own internal transformation. In fact, cloud and digital technologies together represent over half of our business. Our clients need our help even more in times of crisis and business disruption. For example, we deployed a pandemic response management solution to one of our aerospace and defense clients in just five business days. Today, many of our clients are making additional investments to be more agile and better equipped to compete in an all-digital world.

What is the most contemporary definition of Cloud computing platform that you use to differentiate solutions and services at Capgemini?

When my clients are taking on a cloud migration project, I always try to emphasize the importance of also embracing the process and practices that will make that cloud platform or technology more efficient. After all, it is essential to the success of the cloud project. For example, many DevOps practices could be considered optional for traditional on-premise environments. But in the cloud, our clients need to have fully automated their deployments and ideally are also doing automated regression testing. The types of improvements translate to faster time-to-market and higher quality products.

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Could you tell us more about Capgemini’s BPM solutions and how it could accelerate digital transformation?

Capgemini has a full wheelhouse of BPM capabilities across a multitude of platforms. The digitization of those processes is the driving force behind most any transformation project. BPM is most typically deployed in back-office type operational scenarios where there are a specific set of tasks and apps. One successful transformation strategy includes building a layer of orchestration across legacy systems rather than just replacing them. This reduces the implementation costs while still delivering business value. It also gives the clients improved agility for future changes.

The BPM landscape is constantly evolving, and the no/low code platforms are becoming increasingly powerful. Things that used to take days, like building new integrations, can literally take minutes. The platforms are now able to control one another and can stitch together a seamless customer experience.  All while riding on top of legacy systems much like an overpass.

How do you measure the performance of your customer’s platform adoption?

We have a formula that is roughly based on the number of platform transactions divided by total transactions. But the important question here is how do we increase adoption? To me, this is the central goal of design. If we build a system that is intuitive, fast, and helpful, it will invariably see higher adoption. In that sense, adoption metrics are a pretty good report card for how well we’ve done.

Tell us about your ambitions for the AI ML market in 2021.

I’m not sure if there’s going to be a massive shift, but there will be an increase in expectations when it comes to business outcomes. What I’m seeing now is that other industries are gaining ground on early adopter industries like Financial Services and Telecommunications. The latter has long been using AI to build stronger relationships by leveraging a comprehensive view of the customer. Manufacturers, drug-makers, auto-makers – they’re all focused on direct-to-consumer. The technology and approach to the same successful AI use cases follow in suit.

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Your take on Low-code software development technologies?

No/low code platforms are becoming the default answer, and rightfully so. Unless it provides them a unique competitive advantage, I advise our clients not to build, and instead buy and tailor a platform solution. If a company is a software company and has a lot of those skills internally – it might make sense to build. But too often I see companies tending to build their own tools when they don’t consider the total cost of ownership.

Your prediction on the future of customer experience transformation using Cloud / SaaS platforms?

Cloud is the future. It’s a standard for most of our clients at this point. Just make sure you put the right people and resources in the right place to support the roll-out.

Any advice to CIOs looking to improve digital transformation models for their company?

It’s more than just buying technology and deploying it. A huge piece of the success is getting your senior leadership team bought into the vision and understanding their unique roles within it. Having multiple points of view on critical transformation decisions is so important.

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Thank you, Spencer! That was fun and we hope to see you back on AiThority.com soon.