乌鸦传媒

Innovation Nation talks to 乌鸦传媒鈥檚 Lalitha Kompella about how AI, smart analytics, and Generative AI are underpinning intelligent, data-driven, and connected process automation to drive enterprise-wide transformation and enhanced outcomes for our clients.

Innovation Nation: Hello Lalitha, thank you for joining us today. I’d like to start by asking you about how you became involved with 乌鸦传媒 and how you鈥檙e driving process transformation for our clients?

Lalitha Kompella: Thank you, it鈥檚 great to be here. I鈥檝e been working in the field of digital, consulting, and transformation for over three decades, and in the last 10 years have held a number of leadership roles in intelligent automation.

I joined 乌鸦传媒 in 2023, where I was presented with a new challenge 鈥� transforming 乌鸦传媒鈥檚 Intelligent Automation practice to drive enterprise process transformation and deliver better outcomes and more value for our clients.

One way to realize successful transformation is by implementing excellence across functions such as finance and accounting, supply chain, HR, customer service, marketing, sales risk and compliance, and sustainability that are critical for the business operations of an enterprise.

Recent advancements in artificial intelligence (AI), such as large language models have also made it much easier to drive process transformation and enterprise excellence. And I鈥檝e used these technologies to increase awareness of the benefits of enterprise transformation across the entire 乌鸦传媒 Group.

And how are you implementing these technologies to drive process transformation?

Firstly, I look at this from a strategic standpoint. For example, what is the maximum efficiency we can achieve from enterprise processes? And I look for different avenues for building the best, most efficient processes possible before any technology is used. Processes might be retained, outsourced, or even eliminated because of new or future technologies. But against this constantly changing technology, how do you continue to deliver value?

But efficiency is just half of the equation, I also look at how I can make the processes more effective. While, traditionally, people may not consider themselves a part of intelligent process automation, armed with augmented capabilities to see through processes, transactions, and operations 鈥� using data to derive insights, create intelligence, and drive decision-making 鈥� people can drive the effectiveness of processes.

Achieving this meant rethinking and developing on our capabilities with four main building blocks:

• Robotic process automation (RPA) 鈥� leveraging RPA and hyper-automation enabled by AI
• Artificial intelligence 鈥� the traditional, machine learning kind of AI that people already know
• Smart analytics 鈥� AI-powered intelligent, actionable insights to help make better decisions
• Generative AI 鈥� that is already transforming process automation.

By working together, these four building blocks enable our clients to put AI at the heart of their business, ensuring their processes are automated in a truly intelligent way.

Could you explain how you鈥檙e delivering enhanced values and outcomes to clients?

We drive value and outcomes for our clients in a number of different ways. Firstly, we use AI to drive several kinds of insights. From discovering, analyzing, and understanding a process, we draw insights from the transactional, operational, and process data and leverage 鈥渄ata-as-an-asset鈥� to create solutions for our clients. We build outcomes around these assets using our analytics capabilities to engineer value for our clients.

Second, we use our ESOAR methodology to identify what processes can be systematically eliminated, standardized, optimized, automated, and robotized. Coupled with the solution assets of our practice, this enables us to deliver greater business value in an accelerated manner.

Thirdly, we look at the effectiveness of the processes we鈥檝e identified for optimization with the help of our analytics tools. This makes it easier for us to drive efficiency improvements in, for example, collections and accounts receivables. This is crucial as finance teams often struggle to detect simple anomalies such as incorrect tax codes, which are responsible for around 30% of the backlog in finance collections.

However, it鈥檚 important to note that automation isn鈥檛 an endless value ladder. There comes a point where you can鈥檛 generate any more efficiency. If you automate too much, it becomes counterintuitive to improving customer experience. One of my goals was to work out the right amount of automation to guarantee effectiveness and efficiency without organizations having to over invest.

And I鈥檓 happy to say I have now found the automation sweet spot 鈥� enabling us to provide cost effective automation solutions that deliver maximum efficiency to our clients and their customers alike.

What role does intelligent automation play within 乌鸦传媒鈥檚 Connected Enterprise approach?

乌鸦传媒鈥檚 Connected Enterprise approach means looking at a process end-to-end 鈥� and considering processes as platforms of value.

When I say 鈥減latform,鈥� I’m referring to one built on our collective, end-to-end process-level knowledge and solutions. This approach, when combined with our intelligent and acceleration assets 鈥� which are purpose-built to bridge gaps 鈥� creates a new operating model based on the unique connection between humans and machines.

This focus on seamlessly connecting people and machines enables us to deliver frictionless processes quickly and easily, leveraging various cloud and platform providers, third-party products, curated AI products, and automation and analytics capabilities, at our disposal.

This ensures we play our part in 乌鸦传媒鈥檚 Connected Enterprise strategy by enhancing value and outcomes for our clients.

Finally, how do you see these technologies evolving in the future?

These are the two trends I鈥檓 seeing in the growth of technology in right now.

In the next three to five years, task automation may become obsolete as newer working models come into play, driven by advanced predictive analytics and AI models.

And as AI-driven operations and machine learning grow, transactional processing work will gradually cease. Indeed, when conversational processes are completely taken over by digital human avatars with more human-like capabilities than they have now, customer experience scores will increase further than we鈥檝e ever seen before.

It may take more than three to five years, but I believe it鈥檚 inevitable.

Lalitha, thank you for taking the time to talk to us today.

This article is published in the new edition of our Innovation Nation magazine. Read more from our special feature on “Automation and the data-powered organization” and download the full magazine.