Leveraging Intelligent Automation for Enabling Responsive Business Processes

Pascal Bornet - Webinar: Leveraging Intelligent Automation for Enabling Responsive Business Processes

Pascal Bornet

Renowned Author and Pioneer in

Intelligent Automation

Anurag Shah - Webinar: Leveraging Intelligent Automation for Enabling Responsive Business Processes

Anurag Shah

AVP & Head of Digital Products


With digital acceleration becoming a priority for enterprises across industries, intelligent automation has become a critical enabler to transform content and process heavy business applications. Intelligent automation leverages robotic process automation (RPA), artificial intelligence, and machine learning to accelerate organizations’ digital transformation initiatives while helping them stay current, agile, and compliant.

Hear it from our guest speaker Pascal Bornet, renowned author and pioneer in intelligent automation, and Anurag Shah, Digital Products Head, Newgen, as they share their insights and experiences.


  • The rising need for intelligent automation 
  • How intelligent automation can help in streamlining content and processes in the post-COVID world
  • How Newgen’s Low Code Digital Automation Platform can help enterprises leverage intelligent automation
  • Real world examples 
  • Q&A 
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Gunjan Kalita:                    Good morning and good afternoon, everyone. Welcome to the webinar titled “Leveraging Intelligent Automation” for Responsive Business Processes presented by Newgen Software, a leading provider of content services, digital process automation, and customer communication management platform, with a multitude of implementations across the globe. I am Gunjan Kalita, and I shall be your host, and the moderator for this webinar. Today, we have Pascal Bornet, renowned author and pioneer in intelligent automation. And Anurag Shah, Newgen’s AVP, and head of digital products, as our speakers. At the end of the presentation, we’ll be having a queue question and answer session. We request you to type your questions, in the question window of your go-to webinar, anytime throughout the webinar, I shall take them up at the end of the session. And with that, I would like to hand it over to ask you to take a story.

Pascal Bornet:                   Thank you, thank you Gunjan. Okay, can you see my screen? Can you see my screen?

Gunjan Kalita:                    Yeah, we can.

Pascal Bornet:                   Gunjan, thank you. Thank you very much. Hello everyone, that’s really a pleasure to be with you today. I hope you are fine, and I’m sure you will enjoy this event. I’ve been following the journey of Newgen over the last four years, and I must say I’ve been impressed by the achievements. And I think today Newgen is one of the key player, which has understood how to combine technologies to automate complex end to end processes, which is basically the holy grail in innovative automation. So let me introduce myself quickly, Pascal Bornet, I’m a global expert and pioneer in the field of intelligent automation that we call also hyper automation. Out of the first reference book in this field, which is called intelligent automation, learn how to harvest AI, to boost business and make our world more human.

I have 20 plus years experience in digital transformations, and I have founded and led the AI and automation practices for McKinsey and UI over the last decade. I’m a member of the force technology council and senior advisor for many organizations like the Institute of Robotic Process Automation and Artificial Intelligence. And before all, I’m passionate about helping businesses to be more efficient and effective, and passionate about making our world more human with automation. So today I’m thrilled to share with you about this topic and the insights that I will present are coming from a book that I talked about just before. And this is the first book that is dedicated to this new fit. And this is the reason why it took 18 months to my quarters, Ian Barkin, Jochen Wirtz, and myself to write it. The book has been released six months ago and has been Amazon best seller since then. And we are very lucky for that.

So before I start going into the depths of the topic, note that I will often refer to intelligent automation as using the acronym IA. Let us start with a few thought provoking, awful pictures that I think I, and I think we don’t want to see anymore. This picture shows some realities of our world today that intelligent automation aims are changing forever. Example with this picture, I took this picture only a year ago, while supporting the finance department of a multinational company. Looking at this, it’s not surprising that according to a Gallup research, 85% of employees worldwide are not fulfilled by their work. They think it’s too manual, too repetitive and tedious. IA enables to free up employees from labor, transactional activities, and it helps to refocusing them on more value added activities, work activities that are more exciting for them. And it documents them as well, transforming them into super humans, able to generate insights from data in a few seconds.

Now let’s move to the next picture. Believe me, I took this picture only a few months ago, and this is still the customer experience that we can see today, spending hours in a queue to meet with a bank agent, or to get to train ticket. 96% of unhappy customers don’t even bother complaining, and more than 90% of them simply leave and never return. Understanding customer satisfaction and managing it through loyalty is a black box, it’s a very complex problem. And here again, intelligent automation can help us do a lot. Based on my experience, with intelligent automation, companies can increase customer satisfaction by over 50% while reducing the contact center workload by another 50%, okay.

We’ve talked a lot about intelligent automation along the last seconds, but what is intelligent automation? IA aims at automating end to end processes on computers and delivering business outcomes on behalf of the employees, working hands in hands with them, it uses a combination of methods and technologies involving people, organizations, and processes at a technology level. If this circle is artificial intelligence, you can call it also machine learning, that is mimicking human intelligence. If this circle is software robotics, which is mimicking human motor capabilities in a software base environment, think here of robotic process automation, APIs for example, and this circle is workflow and cloud platforms that enable data entry, data routing, data storage.IA simply sits at the crossroad of those fields. It is a combination of those fields. As a result, IA increases the process speeds reduces cost, enhances compliance and quality, and optimizes decision outcomes. And ultimately it significantly improves customer and employee experience. And it boosts revenues, while writing our book during our research, we took the list of the largest fortune 500 companies, and for each of them we computed their profit per employee. So think of it the profit per employee, is really the indicators that shows you how much money you will generate for each of your human resource. It really shows basically the level of automation that you have in your company.

I told you, we took this list of the largest 500 companies, and we sorted them by the highest profit per employee in order to identify the companies producing more with less people. And it’s not surprising as you can see on this slide, that’s Google, Facebook, Apple, Microsoft, are at the top of this ranking. This research proved that the most efficient companies in the world are extensively leveraging IA. IA is a business imperative about half of the S&P 500 companies are likely to be replaced over the next 10 years. So IA is not only a question of competitiveness, but also of business survivor. And I think we especially witness this in this COVID times where companies, which are not digitalized and automated, can’t resist, but the ones that are digitalized and automated resist better and even thrive in these times.

So I’m not afraid to say that companies that can’t sell their products and services online, that are not able to collect the cash online, that are not able to motivate their employees remotely, that are not able to manage their operations with minimal human intervention, those companies are on your life, thanks to government subsidies. Based on my experience, IA provides 20 to 60% productivity improvement, and this is available across function and across industries. And I think despite the devastating aspects of COVID-19, the pandemics has helped the world to understand the importance of digitalizing processes and enabling remote performance and automating them to rely less on the human workforce and to improve them. But decide those wonderful capabilities of intelligent automation. Why more than 50% of the organizations around the world have started their journey? According to Deloitte, less than 15%, 1-5, 15% of them have been able to scale it according to McKinsey. So now the Holy Grail, it’s not about implementing or starting your journey with intelligent automation. It’s about scaling it to a point that the impact that you generate is significant enough.

So the question is how to scale that, how to scale this transformation. And we’ve done some research on the topic and we’ve brought our experience and we’ve connected with more than 200 intelligent automation experts globally. And this is the outcome, five key initiatives that companies that have succeeded their IA transformation have been able to achieve. To start with, two key fundamentals, and I would say here, it’s not even related to intelligent automation, but this is really across initiatives, across projects, whatever the nature of those projects, the first point is, as you can see in the middle of this slide in reds, flashy red, always put people in the center of an IA transformation. Intelligent automation is built by people for people and I’m used to say that without people there is no IA, but without IA, there are still people. So people have key components.

And when I say people, then it means change management, education, and involving the people in the transformation so that they gain the ownership of it. As a result of this, this is also an opportunity to slowly change and shift the mindset of the company, the culture of the company, to more digitalization and more automation. People need to understand why this happens and what is their role in this transformation, so that they can really be an actor of those transformations. The second key one, and this is at the bottom of this slide, start with a strong and healthy foundation, which usually is management support and sponsorship, okay? I’ve never seen, we have never seen a project succeeding without a strong sponsorship and support from management. Those transformations have strong impacts on the organization, on the processes, and will require some investment that needs the highest support in the company.

Thirdly, combine the IA capabilities to create synergies, and be able to automate complex end to end processes, automating end to end processes instead of isolated tasks, is the most optimal way to increase impacts, and give the capacity to address the most complex use cases. So this combination is not only a technology level, but also a teams level and competencies level, the successful companies that we’ve seen have been able to merge, or at least, to create bridges between their different teams, combining talents from data science, from automation, from customer experience, from process excellence, from risk together, around the same table, to work on how can we reinvent this existing process, redefine it and optimize it, using intelligent automation.

So for example, this is a client onboarding process for a bank. It is fully automated end to end by combining different intelligent automation technologies, such as intelligent workflows, robotic process automation, computer vision, machine learning, APIs, and more. While this process used to take 20 days to onboard a client, it can now be performed in minutes, it’s 95% automated. As a result, it provides higher customer and employee experience, and has reduced cost by more than 50%.

Number four is about democratizing IA by using technologies such as local platforms that require limited skills to build IA applications. They make intelligent automation accessible to most business users in the company. And as a result, they accelerate those speeds of the transformation, they drive higher ownership and acceptance of IA, and they allow the shift of the company future, to more digitization and automation. Example of such technology, is here on the screen, local provides the opportunity for everyone to automate their work with limited coding skills. And as you can see here, it’s about leveraging user friendly screens, drag and block functionalities, business users are able to by themselves, connect APIs, build rules, connect machine learning applications with others. Based on my experience, this helps to increase the speed of a transformation by 20 to 50%, okay, increasing the speed of the transformation of course means reducing costs and reducing also the equipment of teams and increasing the time to value. That’s extremely important.

Another example is this one created by MIT. Virtual data scientists, VDS, this application runs on runs machine learning prediction through an intuitive user interface available on smartphone and tablets. So let’s take the example as we can see on this video of a medical doctor. This doctor wants to understand the correlation between the age of the patients, and the likelihood of having a blood disease. So the doctor just combines two boxes, as you can see on this video, one corresponding to data feature, blood disease, and the other one corresponding to age. And as a result, the interface automatically displays bar charts of the patient’s age distribution.

Number five, and last key initiatives that successful companies in IA have implemented. It’s about accelerating IA implementations by leveraging technology. So for example, process discovery, process mining, data discovery, automachine learning, automated maintenance, those technologies help to implement intelligence automation faster and better than when it’s done by people.

And it’s ironic to say that today, most of those IA transformations have been traditionally performed by people, they’ve been extremely manual. And this is really a revolution, those technologies coming in, is really a revolution. It really helps to, based on my experience, increase the speed of a transformation by two to five times, while increasing the scope and the capacity of identifying new use cases. For example, like two times, for example, released a few months ago, tab nine, is an autocompleter that helps to write code faster. It embeds deep learning model, which provides high quality suggestions, tab nine has been trade on more than 2 million files from GitHub.

Now I know that most of you in the audience are part of companies that have already started their journey or are able to do it. And you are all looking for advices on what is the right way to get there. What are the leading practices? I just told you about those five key critical success factors. Now let’s talk about more leading practices to make sure that those transformations reach the expected goals, affected goals. And we always talk about pictures worth more than 1000 words. And I think it’s the same for quotes. Okay and here are my favorite ones that my co-authors and I have used for decades underground, when helping our clients throughout those transformations.

The first one is, “IA is a business transformation and not a technology project.” What we mean by this is the perspective of business benefits, should get this transformation, okay, business first, business goal, is the most important part. Technology is here to help us as a tool to support the transformation. The transformation involves not only technology, but more importantly, people with change management and retraining, as well as processes with redesigns.

Second quote that I want to share with you, “IA is a journey, not a destination.” So IA is not a one off exercise. It’s a never ending transformation journey. It starts one day, but it continually brings additional benefits to organization by applying evolving concepts, evolving methods, evolving technologies, and enhance building teams with the right skills to guide the company throughout this transformation is critical.

The third quote I want to share with you is, “The tone comes from the top.” I think we’ve already discussed about it in the five key initiatives, but I think it’s really worth coming back on that. With any transformations, that bring structural changes to an organization, top management support is a prerequisite to succeed in any IA transformation. “Think Big starts more and scale fast.” What we mean here is initiate the transformation with the decision of a multilayer, companywide, vision roadmap, and business case. These plans need to be flexible and adaptable. This is for think big, okay. Then start small with the implementation of the pilots and take the time to learn from the first experiences.

Finally implement the broader scope in stages to manage the risks, okay. Gradually increase the speed and scale of the transformation. I’ll show you in a few seconds an example of such a transformation plan. It has to be in waves, okay? Step by step, and the first wave, of course, it will usually take longer than the other ones. The next one will be shorter because we’ve gained experience already. So gradually increasing the speed and the scale of the transformation, as a result to generate higher impact.

Last quote that I wanted to share with you is infusing IA into the culture of the company. So implementing IA with siloed, isolated teams, doesn’t work. Automation needs to be infused into the company, change management, education, empowerment of people, incentivization of everyone in the company is vital. Every employee should know what IA is, what are the benefits they will get from it? What are the benefits the company will get from it as well. And they have to be empowered and incentivized to identify use cases in their own work, and also to build, participate in painting the automation.

This is the end of my slides today. Oh, no, I have a bit more for you and I think we are on time. So let me share with you a bit more, a few additional leading practices that I wanted to share with you that we explain in the detail in the book. The first one is, what is the typical IA transformation roadmap? That’s a typical, what you see on the screen, is a typical transformation roadmap, where it’s composed of three main phases. The first one is the project launch. The second one is the project preparation, and the third one is the project scaling.

Okay, there are many ways call those phases, but my co-authors and I have thought those ones were the most easy to understand and easy to apply to any context. So let’s take the project launch, which is somewhere in between three to four weeks, usually, and that focuses mainly on management, vision governance setup, high level automation assessments. So we understand here, what are the overall benefits we can get from the transformation? What are the key use cases that we’ve identified, and how much they can generate as profits for the company? And this brings us to a business case, a high level business case, and when you understand what will be your business case, so basically how many use cases you want to implement. It’s quite easy to start thinking of what could be a high level roadmap. Okay so how those different use cases would be implemented in that.

The second key phase in the project in a typical project is the project preparation, valuation phase, the second phase. And it is about identifying and prioritizing IA opportunities. Remember, in the first phase, we’ve identified the high level opportunities. Now it is using those high level opportunities, getting more into detail, and understanding with more detail what would be the benefits, what would be the default, and what will be for each of those initiatives? And as you can see, very often phase one and phase two work as an iteration. In phase one, we will have the high level of value cases, the high level of the roadmap, the high level of the business case. In phase two, we go back and do two of three key components, and we detail them further, okay. So in phase two we will also have a detailed roadmap. We will anticipate the IT requirements. Don’t underestimate this, I’ve seen so many projects just being delayed by a few months because the IT components were not ready, the logins were not ready, the data was not at the right quality. It’s really so important. And finally, vendor partner selection, and start with a small pilot, okay, in this second phase.

We move now to the implementation phase, which is the project scaling phase. Okay and as you can see it isn’t an iteration, we go use case by use case, or group of use case by group of use case for each of those use cases. First of all, we redesign the processes. I forgot to include a quote that I really like it’s, “Never automate a weak process.” Automating a weak process is just increasing the weakness of a process, I would say, okay. So process redesign is really key, is critical.

After process redesign, we go into deployment sprints, okay. You use here, leverage here, agile methodologies that help to double check on a regular basis, if the expectation from the design are realized in the implementation. And finally we move to production, all of this is, for each of your end to end processes, you implement these in waves with specific teams and specific roadmap for each of those. Okay, another critical success factor that I wanted to share with you is about prioritizing use cases. You can see at the bottom of this graph, the number of processes, okay. And what we can say here, we call it processes, you can call it use cases as well. Okay, that’s the number of use cases and what it shows is that, and what you can see on the vertical, is basically the impact you can get from automating those processes. And based on our research, and this is true in every company, every industry, the top 10 to 20 processes will represent about 70% of the potential benefits to get from automation.

Okay, it’s all about then, finding those 10 to 20 processes, identifying them, and giving them specific attention, while redesigning them and implementing them. So we call it here, we call those 10 to 20 processes, the primary focus. Those are end to end, customer journey led, automation opportunities. And we strongly recommend here to apply your zero based redesign approach. When we say zero based redesign approach, what do we mean here? It’s about rethinking the whole process. Don’t try to automate the process as it is being done currently by people, but really review it from scratch. If we have to fulfill this requirement, that is fulfilled by this process today, what is the best way to achieve it, and what is the best way to achieve it with the automation? So that’s really what… Okay, start with a blank page from scratch, take the time to do that. And again, around the table, you don’t have a new automation people, you have data scientists, you have people from customer service, with natural language processing type of capabilities. For example, you have process excellence, you have risks. Okay, so you really bring the best of your capabilities around managing redesigning those 10 to 20 processes, okay.

And then you can see, there is a long tail of secondary focus processes. This long tail are smaller opportunities, they only account for, you can see here, 30% of the impact, of the total impact of what you can get from automation. So here we advise, in order to avoid spending too much time on those smaller value processes, just apply a lean approach, okay. Which is about optimizing those processes, not redesigning them from scratch, not spending too much energy on those, but being able to automate them through the automation factory, where you just get those processes and automate them by fine tuning them.

I think it’s quite difficult to read here, but there is, I mean getting the right governance in those transformation is very important. We talked about the tone coming from the top. So from C levels, in the book, we explained clearly that there is a need to have a steering committee that is composed of the key users of intelligent automation in the company. So think of the CFO or the COO, or the CIO, I mean, the CHRO, I mean, all those key function who will benefit from intelligent automation, because they need to be part of piloting, supervising the transformation, and reporting to this steering committee, which revises and pilots in pilots regularly, the progress of the implementation. Reporting to this steering committee is this center of excellence that you can see here, which is led by a center of excellence leader.

And that is really composed of different capabilities, competencies, as we said before, data science, automation, natural language processing. And with a real focus on transformation, business transformation, with education and empowerment as key components. And finally, you’ll be able to read this in more detail in the book, this is really the roadmap for successful transformation, that really summarizes all the key points that we say throughout the book and I have been able to share with you a few of these in over the last few minutes. Thank you very much for listening to me. Summary on the book, so in the book, you’ll find and solve more than 500 IA use cases. This book is the outcome of more than a hundred IA transformation successes, but also failures, okay. We’ve learned a lot from failures, and we’ve gathered into this book as well, the insight from, not only from us as practitioners, I mean, and my co-authors, but also from other industry experts. Thank you.

Gunjan Kalita:                    Thank you, Pascal that was truly insightful, and intelligent automation looks like the way to go for enterprises to accomplish their digital transformation goals, really great. And with that, I invite Anurag, to give us a glimpse into how Newgen is aiding this motion, Anurag?

Anurag Shah:                     Yeah, thank you are you able to hear me fine?

Gunjan Kalita:                    I can hear you fine.

Anurag Shah:                     And you can see my slide as well?

Gunjan Kalita:                    Yes.

Anurag Shah:                     Yeah, that was quite an insight from Pascal on the intelligent automation and a sneak peek on, on his book, thanks a lot Pascal for that, that was really insightful. Okay so [inaudible 00:36:19], yeah sure. So what I’m going to talk about is maybe continuing from what Pascal touched upon on intelligent automation, how do we leverage that for creating those responsive business processes? That’s what I’m going to primarily talk about, let me go to the next screen. Let’s see what Gartner says, it says as a survival plan and to adopt a post COVID world, businesses will be forced to bring forward their digital business transformation plans by at least five years. And that would involve higher adoption of remote work and digital touchpoints. They also say that from 27% in 2019, the share of knowledge workers working remotely will increase to 45% by next year. And this will drive permanent change in workforce structure, and by 2025, 75% of the large enterprises will employ at least four local development tools, for both their IT application development and citizen development initiatives. So with that background on Gartner, let’s look at the need for the content and process modernization in the context of the intelligent automation and the various factors that Pascal touched upon just in his presentation.

So let’s analyze what those traditional content management used to be or was existing and what is the expectation from the modern content services platform? So the market expectations have really changed from the content management system. The focus has shifted from managing the content to utilization of content. Traditionally, content was all about where it is stored, what the metadata is, but now it is all about what the content is, what is the context, how it is utilized? Am I being able to use it in the process? The human interventions have transformed into technologies like artificial intelligence and machine learning. Today, I do not have to look at the email or the documents to know the content and context I can train AI and ML services to do that for me. Content auto classification is one such example, AI and ML based service can not only identify the document tie, but also intelligently in text it for contextual present presentment.

For example, if a tax return is submitted via email or portal, and there is a loan in process, in a bank or a credit union, not only the document is identified as tax return, but it is also tagged with the respective loan transaction and presented to the underwriter or credit, or whosoever needs to work upon. The world has moved from paper documents to electronic and digital content, especially living through COVID. I mean, more and more business transactions are being conducted through audio and video channels, teams, zoom, WebEx, the proliferation of these we saw in last 12 to 15 months, and there are decisions which are being made in such meetings, and organizations are recording these audio and video meetings. So it is becoming increasingly critical to be able to search such content from the archives. The linear workforce have transitioned into more collaborated process, not only employees and internal department users, but also the external entities like agents, service providers, attorneys all of these entities are participating into the process.

The repository of content is no longer a single archive. It is scattered and federated in multiple locations, file share, share drive, email archives, databases, social archives. Today the expectation is a seamless search through these all varied repositories and presenting uniform and consistent output. The architecture has evolved from monolithic and self-contained to more modular and service based microservices, talkers, Kubernetes, all of these have transformed the way content services are managed and utilized. And adoption to cloud for new deployments, as well as migration of your existing on-prem applications. So this is how we see how the intelligent automation has transformed the traditional content management to modern content services.

So if we look at the modern content services platform expectations from last slide, we see four distinct area of investment, digital workplace with pervasive use of content through cloud and hybrid deployments across federated repositories. Content in context, irrespective of the form of content paper, electronic email, social, audio, video, in order to be able to present the content in the context of the engagement. Content intelligence, auto classification, searching through audio and video and other content types and doing this consistently each time, every time it is required. All of these doing while varying to the regulatory compliance, whether it is insurance industry, which requires SCC17A for immutable storage, or PCI DSS for payments in financial services, or if you’re buying healthcare all must be complied and in all forms of content.

So what is really slowing you down, three hurdles, the first, lack of contextual engagement. So today having only omnichannel is not going to suffice anymore, most of the processes we see are lacking the context. Second, information silos, disjointed processes, and systems leading to standalone functions, and inducing friction in the customer engagement. And third, inordinately high IT dependency. We are seeing more and more demand of app development, application development, and ultimately in the years to come, this is going to choke the IT bandwidth of the organization. So let me present you, Newgen one digital automation platform, to contextualize, to simplify and to accelerate. Enabling end to end customer journey, using its local development and deployment technologies, resulting in reduced time to market, delivering consistent and omnichannel customer experience. And all of these, again relating back to Pascal’s earlier presentation, help achieve closed loop, intelligent automation.

So if we just look at the news and digital pro product portfolio, which is recognized and featured by the likes of Gartner magic quadrant and Forester wave reports, consistently for last 13 years in different reports, different quadrants and waves. So now the digital transformation initiatives are going beyond the platform modernization, the IT transformation and modernization is certainly at the top, but just as one of the initiatives, there are other goals, rapid application development, improving customer and employee experience, making it frictionless is a big one, secure, scalable, and remotely accessible, all of these are implicit expectations. So to achieve these initiatives, what you need is a platform with modern content services and workflow, supporting low-code application development, tools and capabilities for improving customer and employee experience, portal, collaboration, sales service. And on top of it, you add content analytics and intelligence, making it more relevant, making it more hyper automation, deploy on cloud, hybrid, microservice architecture. DevSecOps, emphasizing the need to build a security foundation within your DevOps, web services, open APIs, continuous enrichment of integration catalogs, more and more standards, and out of the box integration adapters. All of these, in a single and unified digital automation platform, not just solving for your IT transformation, and rapid application development, but also your customer and employee experience needs.

So if we look at the news and platform for digital transformation initiatives, it has a layer for core content services at the bottom, you see I’m starting from the bottom of the slide, with communication services built in. You have business process automation on top of it, and then low code application development environment on top of it. And all your leading technologies and capabilities, AI ML, RPA analytics, both from process as well as content perspective. And then you have this multi experience user interface, for all different kind of user personas. All of these, allowing you to configure and develop business applications across industries, financial institutions, government, and public sector, insurance, shared service, and several others. And these business applications catering to use cases for your different personas, your employees, who are your internal stakeholders, customers, partners, your external participants, and of course with integrated ecosystem and on cloud. So this is really the stack, a unified platform that is cloud hosted, single platform, scalable, and extensible, secured, highly available, and at the same time auditable, capable of delivering deep insights and analytics, used by enterprises to rapidly develop and deploy complex and critical business applications, perform millions of transactions, handling billions of documents, and enabling remote access to hundreds and thousands of employees.

Let me quickly touch upon a case study for large us companies who have implemented their digital process services on news and platform. So if we look at the challenges that they were facing, right? They wanted to provide multiple channels to customers for initiating requests, for getting the status updates back. The content management was becoming complex for them. They wanted to serve high volumes and types of requests, more than hundred types of requests, workflows, business functions, and all of those while maintaining prescribed service level agreements for their customers, their agents, and producers, they wanted to become a market leader obviously, in terms of efficient operations. And at the same time, all of these at the same time cost of operation, not to increase linearly with each acquisition. This company is in the business of acquiring multiple blocks from different insurance companies and then making it cost efficient operations.

So the solution which they implemented on Newgen, it was an enterprise service management platform. It included all the channels on the channel capabilities, and the complex content management that was required. So, for example, let’s say if I’m a policy holder, and I’m holding, let’s say multiple policies, and I’m reaching back to the organization saying that I moved, I want to change my address for all my policies, maybe in one of the policy, I want to increase my contribution in another policy, I want to add a beneficiary so on and so forth. So as a customer, as a policy holder, I could send in these requests in different form. I can just swipe and write an email, or I can download certain forms from the company’s website, fill those forms, and submit it through portal, or I can just call their contact center.

Now, if you look at how these requests are coming in, the nature of these requests, maybe the address, proof address change request can be done straight through while it is being submitted. And it doesn’t require any back office processing, but when you are changing your contribution, maybe it requires an underwriting function to be performed. Maybe it requires somebody from finance to look into it. And if you want to add a beneficiary, maybe there is a CIP involved, there is “a know your customer kind” of check involved. So how do you not only intelligently classify all of these different request types and yet be able to provide a consolidated, summarized status back to your customer, irrespective of which different departments, users, stakeholders, or process participants are performing to complete those requests? So dashboards, alerts, integrating within the core systems to do all of these things from one standardized user interface, without having to flip through or switch through multiple screens and applications. And it also included migration of content from their legacy application about 200 million documents, 40 terabyte, which was done flat in three months. And this entire process included more than hundred types of requests and business functions, which all went live in about eight months, all cloud hosted.

It also complied with the regulatory compliance of SCC17A4 wherein you need to preserve the artifacts and the communication that you receive back from the customer, from the policy holders. This is just a snapshot of those more than a hundred business processes of functions, which were streamlined in financial, non-financial, claims, service requests, to different categories. And there could be any permutation and combination of requests coming in any shape and form of the content. So if you look at this entire digital policy servicing each and every aspect of the intelligent automation that Pascal talked about, all your leading technologies, everything it is a beautiful representation of how the process has been, not only been automated, but it has intelligently been automated.

So this platform news in one digital platform, it is being used in multiple industry, helping automate enterprise wide use cases, be it for your customers in different industries, be it for your partners who are supporting your business, or your vendors who are your suppliers, or again, participating in your business also, and your internal employees, onboarding expense reimbursement. So the platform is able to give you this enterprise wide capability for different use cases. And if I just take it to the next aspect of using the same platform for specific industries, with domain reach accelerators. So if we look at banking account opening, lending, compliances, trade, finance payment, and insurance industry, we talked about digital policy servicing as a case study. But other than that, customer acquisition, claims management, appeals and grievances, several functions of government and public sector units, shared service centers like invoice processing, extracting the data from invoice, doing those two way, three way match with purchase order, goods received notes, posting automatically and intelligently within ERP, all the functions. So I think I have come to the end of my presentation. So I will hand it back to our host for taking questions if there are any, thank you.

Gunjan Kalita:                    Thank you Anurag, that is a wonderful overview of Newgen digital automation platform. We do have some questions right here, and I’ll let you know whom they have been addressed to. So there is a question, firstly for Pascal that is here, with remote operations becoming the new normal, the need for data security has increased further. Does intelligent automation play a role in improving risk and compliance?

Pascal Bornet:                   Yes. Very good question, and I’ve seen a huge amount of use cases in those fraud management departments in those internal audits departments. For example, the capacity of a diligent automation to seamlessly investigate, analyze, quantity of logs, or quantity of entries, instead of them being done by humans, increases the speed by, I would say two to five times, and increases the scope of what is in investigable, okay, by at least two times. And when you combine this capacity of doing those repetitive, transactional reviews, that are maybe more rule based, if then type, together with pattern recognition that you can get from machine learning, you get to a point of efficiency and effectiveness that has never been achievable before.

Gunjan Kalita:                    Perfectly answered, thank you, Pascal. There is another question, and this is based on one of your success factors that you mentioned Pascal. So democratization will it not create freer of job security? How do we handle it?

Pascal Bornet:                   Excellent question. So the intent of democratization is completely the opposite. It’s really about… I like analogies because they speak more than millions of words. When I see my daughter, she’s 16, she’s about to get the driving license, but she’s scared about it, okay. And I think we all were in the same situation because of a few things, because of the unknown, and because we never tried it before, it’s like an alien element, a foreign element, so you’re scared about it because it’s not known, not controlled by you, you don’t know what it is exactly. And the democratization harps exactly on that to empower, so first of all, to inform and educate the people on what it is, okay.

They have to go through this approach of getting to know what it is, before they can even try it by themselves. So this learning phase takes, it starts with information, then goes with practice. And then what I think is really the power of democratization is that instead of those people being just passive and seeing the transformation happening around them, and I would say they would be scared, because they see everything moving around them. They are not part of it, okay? So what’s happening with me? Am I not part of it? So democratization, for example, with the local platforms, really helps everyone in a company without specific skills in coding, for example, to participate, to be empowered, to be an actor, to be part of the wave with the others. So that really prevents people from being scared of it. And on top of this, it helps to, as I said before, change the mindset of the company, because when everyone is an actor, is empowered, everyone becomes an agent of the transformation, participates in this transformation. So you really have a network effect of willingness to make this happen.

Gunjan Kalita:                    Correct. And that is actually what it is, and that is brilliant. So I think that this is a Newgen specific question, so Anurag probably we can have you on this. Do we have to involve Newgen IT team to design the processes?

Anurag Shah:                     That’s a great question. And it relates back to the local and no code kind of platform that Newgen provides. So the intent is really for the organizations to become self-sufficient and not really require news Newgen at all, if you will. The local environment and platform is expected to help you design, automate, and improve on the already implemented process, iteratively, using tools, which are part of that local environment. Be it process designing framework, or experience builder framework, wherein you design your interfaces and experiences for different personas, internal employees, processing users, external customers, exposed on the portal, or partners portal, and those kind of things, all of these dragging, dropping, creating interfaces, including utilizing rules engine for your business logic with almost near English kind of framework, or a decision table kind of framework. So really and truly, the intent is actually to be self-sufficient and be able to, as a business stakeholder, be able to manage your business process in this environment.

And of course, I mean, within any automation, there are bound to be integrations interfaces, which ideally speaking, must be available as standard web services to be plugged and played and used. But we all know how the applications, the ancillary applications, or the core applications, participating into any of the process automation, how are those managed? So you may need, from time to time, your internal IT to come in, help you, or if you want to, have Newgen come in and help you, that’s also okay. But those integration aspects may require a little bit of it. And then if you look at another aspect, which is the leading is technologies, right? We talked about artificial intelligence, we talked about machine learning, the robotic process automations, all of these leading technologies, which make the process in automation intelligent. There, again, you may need some help, and we have seen our customers having trained their internal IT organizations are able to help their business stakeholders in that endeavor. So in a nutshell, what we say as a customer organization between your business and IT arm, you should be self sufficient in using the low-code application with all these leading technologies.

Gunjan Kalita:                    That’s a great response to the question that we had, and right in the interest of time, I’ll just take up one final question and I’ll just leave it to you guys to answer, does intelligent automation mean doing away with our legacy systems?

Anurag Shah:                     Maybe I can just quickly take a first stab on this and then Pascal you can add on that. So that’s really a dilemma that we have seen most of the organizations struggle with, be it a bank, whose core banking system is running the bank, or it’s an insurance company whose policy admin system is the core of their operations, or it’s a shared service center, or a manufacturing company where there is an ERP, which is kind of their underlying system. Irrespective of the vertical or the industry that we look at, these are your core applications, which today are being termed as legacy applications. But these are the applications which have for years and years and decades are running your organization, which is fine. But today, when you are looking at digital transformation, digitalization, intelligently automating your processes, improving your processes, reducing your cost of operation, giving that “wow” experience to your customers, the omnichannel and standardized interfaces. At the same time, giving your internal employees and participants of the process that standardized, ergonomic, processing interfaces, you need this orchestrated layer, which actually leverages the strengths of your existing applications, but then it supplements and compliments what it is lacking, the automation part, the technology part, the experience part, the integration part, all of those things.

So what I would say that it is not ripping and replacing any of the existing applications, be it legacy or ancillary, it is to coexist with those and then make and then leverage the strength of those, and supplement and compliment the additional ones from the digital perspective. Pascal, you-

Pascal Bornet:                   Yes, completely aligned with you. I mean, another way to explain it very shortly is those are two different layers in the overall IT application landscape. Okay, so and when we talk about intelligent automation, this is an additional layer on top of your existing systems that is playing in the layer where the workforce, the human workforce used to play a role. Okay, and so that’s complimentary, that’s two different things that work together.

Anurag Shah:                     Couldn’t agree anymore, Pascal, on that.

Gunjan Kalita:                    Thank you. That is a very healthy discussion. And thank you, Pascal and Anurag, we really appreciate your time and valuable insights that you brought to us. Newgen will send across a copy of this recording to all the registrants. Those who are not able to share their questions today, please feel free to send them over via mail. If there are any questions for Anurag or Pascal, I’ll make sure I forward it to them and you get it answered. And thank you again and have a great rest of the day ahead.

Anurag Shah:                     Thank you. Have a great day.

Gunjan Kalita:                    Thank you.