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Podcast Episode 4

Automating Human-led Operations to Drive Business Growth

with Pethachi Pichappan, VP of Information Technology at Concentrix

Automation, AI, ML and related technologies should be all about enhancing what humans can do – and how that can improve the customer experience. In our latest podcast, Pethachi Pichappan, VP of Information Technology at Concentrix, joins host Dayle Hall to discuss how automation should be laser-focused on enhancing business performance – which means improving the effectiveness of employees.

Full Transcript

Dayle Hall:

Hi, and welcome to our podcast, Automating the Enterprise. I’m your host Dayle Hall.

This podcast is designed to give organizations insights and best practices on how to integrate, automate, and transform the enterprise.

Our guest today is an automation veteran with over 35 years of experience in the tech industry. He was awarded the Verizon Individual Excellence Award in 2001 for establishing Verizon India. And in 2022, he was awarded the Trailblazer Award by the CEO of Concentrix in 2022, and for successfully establishing the automation center of excellence at Concentrix. And by the way, he also has a few patents to his name. 

He has an amazing proven track record of successful automation initiatives done for IBM, Verizon, and now as VP of Information Technology at Concentrix. Amazing powerhouse of automation in our industry.

Please welcome to the show, Pethachi Pichappan, on our podcast. Welcome to the show.

Pethachi Pichappan:

Thank you, Dayle. Yep, it’s my pleasure.

Dayle Hall:

That is some strong history there. I feel like I’m talking to a guru of the automation industry.

Pethachi Pichappan:

I’m still learning.

Dayle Hall:

I love that. I love that. I love that you can always be learning something, right? That’s excellent.

So look, before we jump in, and I know you have a very broad industry knowledge, and we appreciate your time here.

I’d love to just kick off with, how did you get to where you are today ending up at Concentrix? What about this area of automation? And as we go into AI, and ML, and NLP, all these latest buzzwords, how did you end up where you are today? How has this journey progressed for you?

Pethachi Pichappan:

Yep. It really started in Verizon. The CIO and the CEO at that time were encouraging innovation and bringing in a lot of internal capabilities for Verizon operations. So it all started in the year 1999, 2000, when there was an internet boom, and that’s when we were establishing websites. Mobile apps did not start at that time, but natural language processing was really coming into the business world from the research labs. IBM had a research lab, and Verizon had a research lab, and a few companies, startups at that time, had their own engine. For example, Nuance, which is well established, was SpeechWorks at that time.

Natural language processing was initially coming up. And so as Verizon was engaged in innovation, we were trying out, and most of our interactions were voice at that time. Chat wasn’t very big. Email were just kicking up. 90% of the transactions in contact centers was voice. Being Verizon, it’s a huge operation. Since the CIO was encouraging innovation, so I was asked to look into the automation of voice calls. So that’s where it started.

And in fact, we deployed one of the largest voice portals at the time. It took us a few years. We tried it out initially within our operations, and then we launched it in 2003, natural language processing, not the IVR, not the touchstone IVR. You know, press one for that, press two for this.

And we were putting our customers in a very confined manner in the IVR, and not letting them speak to an agent. But we wanted to improve the customer experience. So the CIO wanted to try out the natural language processing. That’s when we launched it.

We were successful to a certain extent in the sense that we did automate pretty simple transactions. When is my balance due? What are my last three payments? Where do I go and pay? Store locations and all that. Literally, about 15% of the transactions were automated. And since we were the first ones, we learned a lot on how to tune, recognize different accents. In fact, most of the testers were Indians and Chinese testing those apps, speaking English. We call it a success. And then my journey with automation started from there on.

Dayle Hall:

Siri can understand me, but my car cannot understand me when I talk on the voice recognition. So I understand.

You move from this, you know, the IVR world and contact centers. You start to look at NLP. What was the genesis of that for the organization? Was it, “Hey, we feel like we want to provide a better service.” Was it a cost measure? Was it competitive pressures? As you started to move into trying this technology, is it the same principles today with technology like AI? Is it due for a better experience? What is the genesis of these technology innovations that you’re bringing into organizations today? Where does it start?

Pethachi Pichappan:

It really started with customer experience because in the IVR, you can’t have a long menu or an IVR tree structure, that we used to call. But if you go back to the year 2000, that’s where mobile wireless started booming. And then there was the Apple iPhone coming in more or less at the same time.

There were various offers. The pricing structures were different. The telecommunication company was offering so many range of plans for customers, and there were so many issues. So you can’t grow the IVR structure and say, press one for that, and then take them deep down into different menu levels. If you have that, if you have this, keep going down. It was frustrating for the customers. They were all pressing zero and going to the agent. And the old touchstone IVR was useless. No one was using that structure because of the long menu structure.

So that’s where the natural language processing, we felt the customer comes onboard, welcome to so and so. How can I help you? Whereas if you have to go down the touchstone IVR, you have to go down three or four levels to explain what he wants. And then also the deregulation happened in the telecom world in 1996. There was a lot of competition to gain customers from each other. So whoever was providing better pricing structure, better pricing plan, better customer experience, was winning customers. So that was the motivation to bring in the natural language processing.

Dayle Hall:

Right. Do you think that’s the driver today? Because obviously with a lot of the AI and machine learning, and we’ll get into more details on this.

But do you see, within your organization, or you’re seeing around the industry, is customer experience still the key driver? Because as I look across the industry and as I talk to various people on these podcasts and through events and other means, we sometimes see that they feel pressured to implement these technologies. It feels like everyone’s doing it. And then they have a big digital transformation budget, and they’re trying to identify, but what does that mean? But I like what you said, which is, they started from the customer experience in the past. Is that still the same today?

Pethachi Pichappan:

For cost-cutting, I can go into depths in this. With the natural language processing and with the machine learning, I can cut costs in various ways, just not in the IVR alone or self-service. Because self-service is only a portion of the application of machine learning or automation. When the call comes to an agent, he can be completely assisted by a robo doing all the work that he used to do himself.

For example, with a lot of acquisitions and mergers, a single company might have five screens for him to go and get information. If you are an X of this company, I should go to this screen and get information. Or I have to go and check the compliance statement. After the call is over, I have to write notes. So all that I can automate and save the cost, and to let the agent focus on the customer.

So customer experience is still a huge piece, and automation is not only applied in the IVR or the upfront self-serve, it is also in assisting the agent in the work that he needs to do. In our operations, we have brought in automation, every piece, every function is automated one way or the other.

Dayle Hall:

And that’s good, I think, as we talk to more customers, we have something called Iris AI, which helps suggest connections, pull their technologies, their data’s applications together on behalf of them. But it’s still one of the best conversations we can have with a prospect or a customer upfront is, okay, but what problem are you trying to solve? And not just I’m trying to cut costs. Well, yes, you would hope by having these kind of technologies that, that will happen. But the customer experience, making it easier and more seamless to serve customers, to figure out the right products at the right time, because you’ve got that data, I think that is really the power of AI and ML and these new technologies, whether it’s the call center, or around anywhere else. 

You talked earlier about, or I mentioned, the best practice center, center of excellence at Concentrix. How did that come about? And how are you using that to think about those initiatives and really drive that better customer experience?

Pethachi Pichappan:

How it came about is, in fact, it both started out a couple of years ago, even five years ago. Mainly because the technology was new. There were a lot of options. There were a lot of solutions available. There were a lot of vendors available. And you can’t have different departments doing different things. You needed a central center which can evaluate all these technologies in a very structured manner, buy versus build versus partner, and apply it in a very structured way, and develop partnerships with the key capable service providers or even software developers or even startups.

And then in niche areas where things were not available, we wanted to develop ourselves internally, have internal talent, as well as have vendor partnerships. And in some cases, even invest in companies which we think might do well. Apply all these strategies by a central group. And then also in identifying opportunities for automation, you need to have a very structured process. Having a very well-established process in how to identify opportunities for automation was very helpful to have a center of excellence determine these opportunities and criteria for automation.

And then you can apply it to our own internal operations, our HR function, our F&A function, our IT function. We had evangelists from this automation center of excellence, going and talking about educating different functions on what all can be automated. At the same time, not only for our internal operations, but even for our clients, saying, this is a way to go about automation because a lot of them were struggling with how to make this happen within their own organization. So we shared our best practices with our clients also.

Dayle Hall:

Right. I think that’s a really good opportunity, particularly for larger enterprises. But I’d like the principle of some central place that allows you to identify opportunities, but also have that criteria of assessment of how you’re going to make it work.

Where do you see the request coming from? Is it still driven through IT? Do you see it more from other lines of business? Where are people approaching this center of excellence? What kind of requests are coming in and where are they coming from?

Pethachi Pichappan:

It’s a thought leadership that comes from this center of excellence. Then you go and sow the seed, these are repetitive processes, which can be automated. So give a set of criteria, [inaudible 00:14:26] if you have these processes, bring it to us and we will help you to confirm that it is a good function to be automated. And then go and help them to make that happen, the automation, go and implement those automation. It’s thought leadership. It is helping people to identify areas of automation. It’s helping people on what technology should be deployed.

And also signing up for business benefits. Before we go and deploy, we even develop the return on investment. We check, A, is the volume pretty high and if this is a cost for me to deploy it. And what will be the benefit? What will be the savings? So for each of these opportunities, we develop the ROIs, and get approval from the business owner, saying, yes, I want to deploy this. And then finance reviews the ROI business case, and then we go and deploy it. So it’s a very structured way in which we went about deploying it.

Imagine if you did not have this automation center of excellence. Each team, or each function, some vendor would’ve knocked them and said, hey, I have this capability, and each function would’ve partnered with different vendors. They wouldn’t have a structured process, everything would’ve been one off. At the end of the day, if you look at it, it’ll be hotspots deployment of automation in your organization. So by establishing automation center of excellence, you bring in structure, and it’s really benefited the organization here.

Dayle Hall:

I have to tell you, we see that, your second example, a lot more than we see your first example, which is what you’re doing around the center of excellence and the thought leadership, and showing the business what’s possible. What I like on these podcasts, as well as getting your experience, I like to try and give people who are listening, something tangible to take away.

So let’s say someone out there is listening to this, and they may have had some experience of different parts of the business is saying, oh, I want to do this. Or maybe they’re off doing it already or they’re worried that it’s going to get out of control. And you have kind of the other side of the coin, which says, we try and drive the inspiration and thought leadership. 

What advice would you give to them, or to other people who think they’re going to go down that path? Like, where do you start? Or maybe they don’t have to build their own full center of excellence, but what should they be thinking about before they get too far down the path?

Pethachi Pichappan:

The way we went about the sponsorship at the CEO level is, or at the board, even sometimes at the board is very important. And getting that sponsorship, getting that funding, really it’s all about people, isn’t it? So hiring the right people with the skillset to run this automation center of excellence, who have done this before, or who have a similar program management or a governance process of- in my career, I’ve run year 2000 governance process. I’ve run off-shoring or outsourcing governance process. When I came to the automation center of excellence, some of the lessons which I learned from running those governance process, I adopted here. So that is important.

Hiring the right skills is important, and then showing value. So what we used to do is as soon as we deploy a successful automation, we turn it into a one-page case study, and share it among our clients, among our functions. And then having regular cadence with the senior leadership on how this automation center of excellence is doing, and wider communication and exposure to everyone within the organization, or even to our clients, what is happening with the automation center of excellence. That is very important.

Getting the right sponsorship, filling with the right people, establishing a very strong process on the buy, build versus partner, having initial successful deployments and turning them into case studies. Then you start the communication training and getting more and more projects in. These are the key vital steps, yeah.

Dayle Hall:

I have two questions that came specifically out of what you’ve just said. I think that’s great. I think that’s good advice around thinking it’s board level, or at least CEO-level sponsorship. And I liked what you said around driving ROI.

Two things that came out of it. One is skillset, and that goes into the hiring. How do you identify the right people to bring into the organization? You mentioned around governance and that kind of thinking, but who are those people? Where do you find them to actually help run this?

Pethachi Pichappan:

There are three layers of people that we need. One is this whole program management set of people. And they would’ve run large programs of IT deployments or IT initiatives. Those are key people. The second set is the solution people, who understand BPO space quite well, the operational side. So anyone in any industry, people who understand the business process or the process side, and who can solution it. Just not understanding, they can even solution it. Process plays a big role in automation. Unless you understand the process, you cannot automate it. You’ll be a complete failure. If you look at it only from a technology standpoint, without understanding process side, it’ll be a disaster. So you need process people.

The third layer is the technology layer. You need data scientists. You need developers. A lot of people oversee that because this is all about customer experience. Don’t write a workflow or a call flow without understanding the user experience. So we have layers of people. Data scientists, java.net, Python, UI/UX skills, and then business analyst, all these. And then the whole testing group, and then the cloud services group, all that come in.

Now, if you look at the skillset, most of our skill is based out of India. And since we were very early in the process, well now we expanded to different other countries also over a period of time. But since we started off much earlier, before everyone started adopting this, we were able to hire good talent five years ago. And some of the leadership is still with us. We were able to retain, encourage them, give them space to grow and all that. So we were able to retain that talent. Attrition will happen, you know, but that’s part of it. As long as you keep your leadership intact, then you have the knowledge and the skillset, and then the lower level keep changing.

Dayle Hall:

That’s some good descriptions of the type of people, too. And if you can’t even get to a center of excellence, but those are the right type of people to help them, show them the art of the possible, do the ROI of these kinds of technologies, because we’re all being inundated with so many opportunities around the new technologies.

And then the second thing you touched on there, which is around the people. On a couple of these podcasts in the past, and in my previous roles and this role, as we start talking about AI and ML, there is this old perception. And I say old perception, it’s been around for a while, and I’m sure you’ve faced this, which is, these kind of technologies are going to take jobs away.

In my experience, and what I’ve said in the past is, it gives the opportunity for the skilled workers that you have to be focused on more business value activities and different levels of engagement and strategy, and the more thoughtful things that you want to pay them for. And automate some of the tasks that is the mundane, that people hate most of the time about their jobs.

As you think about these technologies, and there is usually a people impact. How do you build that into your process, which is not removing people’s jobs. It’s not replacing people. It enables different opportunities. How have you worked that in your positions, so people are not afraid of this kind of technology?

Pethachi Pichappan:

There are a number of data points around this topic. The first thing is, if you don’t do it, someone else is going to do it, okay? So you better be in the leading edge stuff and do it yourself, or you offer it to your clients. So that is the first thing. From a competitive edge standpoint, you got to do this.

Second is, I really think it’s a myth that jobs are gone, or as you’ve pointed out and what I’ve seen, I’ve been doing this for 25 years. I’ve not seen jobs go off. I’ve seen, in fact, jobs increase, and the type of jobs you do is improving, or it’s much more leading edge. In fact, I’m working on the next generation of contact centers, not even natural language processing. We are talking about metaverse and avatar, and augmented reality. So we already started thinking about where is the next phase?

So you continue to evolve yourself from a technology standpoint. And none of these technologies are about removing people. It’s more about enhancing customer experience. We are making the lives of everyone else much better, and not about taking away someone’s job.

As you rightly said, the third key point is the mundane stuff. You yourself, when you do this, you’ll be wondering, why am I doing this? Why can’t some bot do this for me? Pulling information from one spreadsheet and putting it into a PowerPoint or into some of the database file. Why am I pulling this information? It’s a very repetitive standard work. Human brain is meant for doing more advanced stuff, rather than pulling information from one to the other. So I think people have already started thinking about, hey, this can be done by a bot, not me. That’s a kind of request we start seeing these days, people saying, I really think I’m doing this kind of a work that’s not meant for me. Can you get a bot to do this for me?

Dayle Hall:

Yeah. I was talking with someone else recently where we were talking about recruiting. It was interesting. I wonder if we’re ever going to get to the point where when people go through interviews, that they’re going to start asking a question. Okay, well this is my role. What do I have to do, and what do you already have automated? Will it get to the point where they’ll take or decline roles, based on the kind of technology support they’ll have in that role?

Pethachi Pichappan:

Absolutely. I think we are seeing that kind of [requirement? 00:26:40] more and more. Even our agents, their life is made better by the bots, rather than feeling I’m losing my job. In fact, interacting with our end customer is so important, because our end customers at the end of the day, if they are elated that the problem is solved, and even the advisor gets a sense of feeling and accomplishment that I solved this problem. I would rather focus on the end customer, empathize with them, solve this problem, the rest of the work can be done by bots and given to me.

Dayle Hall:

Yeah, no, absolutely.

So I know you do a lot of advising for other startups around Silicon Valley, common to the kind of advice that you give or what you would give outside of what we’ve already talked about. But how do you even stay current? How do you stay up to date? Technology moves so fast, and I get this question all the time around there’s now 10,000 MarTech tools. And clearly, I don’t know half of them because most of them are in crossover categories. And there’s so many things. And we hire teams to figure those things out, demand gen versus customer experience, versus many other things. What’s the best way to stay updated with technology, with advancements outside of what you’re doing within your own company?

Pethachi Pichappan:

There are two best parts of my job. One is interacting with our clients, with our own internal functions. From those interactions, I get to learn what issues they have, what problems they have, and your mind start ticking, how you should resolve those problems. The second part of my job is on a regular basis, even on an everyday basis, we have partnerships with a few of the leading edge companies in this field. And I get to also meet a lot of startups and vendors who are working in this field. I get to know what they are working on from a technology standpoint, and get to know from them what problems they’re working on, even things which are not generally available, which is in the pre-lab stage or in the lab stage. They are bouncing ideas on what’s going on.

So the second part is where I get to know what’s happening in the industry, either with the startups or with the middle-tier vendors, or with the large companies. And with them, it’s a very bi-directional discussion going on. This is a problem I have. How are you solving it? And they come about with the creative ideas on solving, or some of the leading edge solutions that they’re working on. The other thing is basically reading Wall Street and all that, the regular stuff on what’s going on in the market.

And since we are a global company, I also have the fortune of spending time with vendors in China, vendors in Korea, vendors in Brazil, vendors in India. So I have a global exposure to vendors across the board, across different geographies. And they’re solving problems in different ways. So get to know how they’re solving them. That’s how I keep myself abreast on what’s going. 

The third area that I especially focus on is, where is the industry going towards? Sometimes you discuss with the Gartners, and the Forresters, and the HfS, the analyst also, they’re also now picking your brains. They also share what they learn from others.

So there are different sources of information that you can process. I think my special trait has been always, get to know what the business problem is and how do you resolve it in a leading edge manner? 

Dayle Hall:

Right. I think you and I could talk for hours and hours at this, but obviously, we try and keep these in little bite-sized chunks. We could potentially have a podcast version too, for some of these things that we’re talking about. I think probably what would be a good summary, a good wrap up, and we’ve covered a bunch of things, right? We talked about focusing on customer experience, talked about a structured process for looking at these automations, integrations, these technologies, at how to look at ROI, how to recruit.

As we wrap up the podcast, and we’ve talked about advice for the people, but what do you think is one of the biggest myths around implementing these technologies? What do you think people have a misconception around when they’re looking at these kind of ML/AI, automation, integration technologies? What’s out there that you still hear, that you’re like, I can’t believe people still think that.

Pethachi Pichappan:

Losing jobs is a wrong way of thinking. I don’t think it’s about automation taking jobs away. Automation enhances the business. That is one.

The second one is identifying opportunities to apply these technologies. Don’t go and try big things. Always do a proof of concept, have a set of criteria on where you want to deploy it. Do the ROI. Do the POCs, proof of concept, see the results. Look at the data. Don’t go by each person’s perception. Just believe in the data. Look at the data and make your decisions. Whether identifying opportunities or looking at ROI, it’s all data-oriented. And when you partner, partner with someone who has done this before.

Choose your partner with a good evaluation criteria, and based on their experiences of having done this. And hire the right skillset. And in companies like Concentrix that really support you with following the process, doing the right stuff, believing on the data, not believing on who said what? So these are very critical things. And once you have a few successes, that’s where you should really blow your own trumpet, because that’s where people get to know these successes and how it is done. And the good thing I like about this podcast is also about I’m sharing my experience so that people who are listening to this are successful in their attempts to automation.

Dayle Hall:

Yeah, I hope so. I hope some people listen to this and say, I want to get on that, because I have things that I want to say too. Because I think part of this journey, getting rid of some of those myths, sharing these experiences, I think will help us all. I know there’s some competitors that we’re all trying to do something similar, but it feels like there’s so much opportunity out there, that sharing the experiences I think will help all of us.

Okay, a last question. What is the one technology or opportunity around this field that you are most excited about? It doesn’t have to be the next 2 years, 5 years, 10 years. But if you could put your finger on something that you’re really excited about, what would that be?

Pethachi Pichappan:

My excitement changes every day, what I come across. But what I’m really working on is the next generation BPO, where you have a combination of natural language processing, 3D technology, you have edge-based computing, low-code/zero-code, or the computing part is improving. The AI/ML capability is increasing. Now you combine all this, and bring it into my industry, it can do wonders. I’ll still tell you, people are talking about replacing humans. The sixth sense of human is very difficult to replace, the empathy, the split-second decision making, that is so difficult.

The split second with the emotions, making decisions in an emergency, with all so many variables, it’s very difficult to replace. So I don’t think people should focus on replacing humans. It’s about, how do you enhance humans and take the human to the next level? So what I’m working on is the next generation BPO, bringing all this together. I’m working on patenting this idea too, so I can’t talk too much about it. But that’s what I’m excited about. So you think about AI/ML today, but I think I’m beyond that. I’ve done that. I’m thinking to the next stage. That’s what is exciting to me.

Dayle Hall:

That’s great, I love that end. Talking about keeping the human aspect, keeping them as part, but obviously helping them be more successful. Pethachi, brilliant podcast. Thank you so much for your time. I couldn’t be happier with the things that you’ve discussed. And hopefully, people took a lot of interesting tidbits away from this podcast. And thank you very much for your time.

Pethachi Pichappan:

Thank you, Dayle. Great questions. Very insightful questions. I hope I was able to bring my experience and share my experience. Thank you for this opportunity.

Dayle Hall:

Absolutely. To everyone else, thank you for listening to this podcast, Automating the Enterprise, and we’ll see you on the next version.

Pethachi Pichappan:

Thank you.