 Big virtual welcome for Abhishek and Valmik. Over to you gentlemen. Thanks for the introduction. Myself and my colleague Valmik will be taking this session. So our today's topic is human-centric digital assistance. It very much act in the current scenario where every organization is realizing the need for automating mechanical works, and introducing digital assistance. Human life is very precious and is meant to do value act for business. It is high time that we actually introduce digital assistance in our daily work wherever applicable. So this slide, I would like to take a pause on this slide so that each of you think through that what are the pain areas in your organization where you require digital assistance and why. Can you think at least three things that you would like to change because you consider it to be bad work? Can you think that what work works you at your workplace, what causes you pain, what is biting you, what's broken and what is to be fixed? This slide highlights the inference taken from the survey conducted by an analyst last year, which is focusing whether the organization expect significant increase in the role of digital workers or will the activities remain with the human select by end of 2021. We have categorized the complexity of the overall activities in three categories, low, medium and high. As per the survey, routine technological skills such as data processing and performing complex technical activities such as IS potential for intelligent automation and basic skills as good potential for intelligent automation. These skills leave significant thinking towards which will be structural thinking, problem solving and decision making. So how do we make the shift? Let's analyze that what is the work break of a common employee? There are a lot of bad work, some amount of good work and less great work. Can we reward this one? Is this possible? Can we utilize our human brain, which is very much uniquely designed to adopt new challenges and predict various outcomes which take year and month for a machine to be trained on? Why not use our valuable gift of brain to do something which is much more worthy than spending time on bad work such as disordering data, injuries and mechanical tasks? This slide prompts us to think how we can make a shift to the quality of work, what we do. Incremental changes from redundant to value add tasks will slowly change the way organization operates today. In the next slide, so here what we have done is essentially that we have changed our approach in addressing the challenges. Additionally, we had process-centric work where we were scanning individual processes and trying to fully automate, but the impact was not much due to less adoption. However, when we change the pivot from process to the actors and make it human-centric, the impact will be more and adoption will increase. There are various avenues to introduce distal assistant in our daily work. One significant could be our buddy could be the SCDA which is human-centered distal assistant. Live along the IT industry, even if you think about the private or public sector, there are ample opportunity to replace the human-centered task written by smart distal assistant. This is like manufacturing companies, they are the first to transform the operation done by humans. For example, even in the current scenario of COVID-19, with the lack of distal assistant in banks, FFCC, and many companies, it poses the risk of human employees. In this slide, we are introducing the concept of distal assistant, which is a virtual co-worker designed to carry out certain tasks which are human tasks, human-centric tasks. If you smartly design the enterprise architecture of the organization and keep technical technology first, in fact, that's the team of the NAPCO, then it will be much easier to implement this distal assistant on the impacted segments. SCDA, which is human-centric distal assistant, that intends to automate tasks and processes for the actors. It can also interact with another virtual agent which will introduce the coordination and reduce information queries between the employees. In the next slide, in this slide, I'm talking about the technical ingredients of the distal assistant. How distal assistant can be made. At high level, the technologies can be categorized into three sections, which is RPA, robotic process automation, artificial intelligence, and analytics. Again, in RPA, there are two components, bot orchestrator and bot client. There could be two scenarios in RPA. One will be attended and unattended. Attended is something which is leveraged when someone wants to perform the front-end related tasks. Unattended is something when someone wants to perform the back-end related activities. In artificial, the main component of AI, which has been used as part of the SCDA are NLP, NLU. This is used to comprehend the meaning and intent of content to improve decision-making, to analyze the sentiment and tone of the user's employee, and then to classify the user complaints, the simulators of conversations used to identify and categorize unstructured content which allows the bot to accept decision-making data. The third piece of this section is the fuzzy logic. This is used to increase the data. And the last, but not the least, is the machine learning under AI. This has been used for improvisation. AI engine learns from the data and improvises over a period of time, and for that purpose, it has been used. And the last component, which is the analytics, this technology is used for meaningful reporting so that management can take the right decisions at the right time. This slide talks about the overall solution architecture. We can categorize this overall solution architecture into four parts. The first one, which you are seeing on the left, that's talking about the different channels. It could be through your channels like TeeM or through any portal. Then the second layer is the client component which again can be classified into two parts. One is the conversational AI platform, which has chatbot. Then the RPA client platform, using what that trigger will be sent to the server component. And the third section, which is the core engine, comprises of the orchestrator control room and the AI engine. Even the orchestrator, which you are seeing in the middle one, that's the core component. And these take care of the license management, bot scheduling, credential management, the bot prioritization. There could be some scenario that you want to prioritize the bot. Then you want to schedule some specific bot to run at some specific timing. And you want to store your credential in some kind of a secure credential vault. So all the things would be taken care by the orchestrator control room. There could be also some scenario where you need to handle the bot request during part. So that also would be taken care by the control room of the orchestrator layer. There is also integration required with the other enterprise system to exchange the right information. So this is the overall solution architecture of our human-centric distal assistant. Now I would like to hand over to Michaeli Bommi, who will explain that how to design the ACDA. And he will also take you through the interesting case story of one of the ACDA use cases. Yeah, handing over to you, Bommi. Hey, thank you Abhishek. Hope I'm audible to all. So as Abhishek has, hey, can you acknowledge, am I audible to all? Yes, Bommi, you are. Yes, you are. Thanks. Yes. So thanks Abhishek for taking through her concept and technology in a blurs. And also you've shown what are the overall solution architecture. I've been talking about the design principles of this transformation and roadmap for this journey through a case. So as the core of this transformation is human centricity. Our design principles are also built around human journeys. It could be an internal journey. It could be an external journey. It could be a journey of an employee or it could be a journey of a client. So how typical it is done should begin by deconstructing the job profile of a user's role in an organization. So largely we are for illustrating the case. We are taking an internal example. So when we deconstructing the job profile of a user's role in an organization, we understand what are his key KPIs, what are his motivations and what are the experiences that he goes through during each of his journey. And here the intention is to study the various job tasks, get his volume details by performing a time and motion study at an aggregate level. Now we conduct a design thinking approach that I will be talking in the next slide to identify the pain areas in his various journeys and then we come up with a solution spectrum on an overall level. We identify what are the key problems and define an MVP construct. It's a minimum viable product construct. There might be a case that some solution require a change in existing data strategy that we have, we may have to tweak or create a new data strategy altogether. So once we've done that, once we've defined data strategy, we build an implementation model with existing maturity of the organization. And then there is a roadmap in plan. So while that slide gives an overall approach we understand where it is coming from. We all know that when organizations processes become more and more standardized. However, it also brings a reduction in innovation level. There is a clear need to focus based on standardized tasks which are already there in place and more on standardizing the new innovative things. How can I get to next level of business? Why design thinking? Where does it fit? Well, mostly design thinking-led approach is desired to deconstruct any problem statement. Arrive at possible solution path, what is the solution spectrum of any problem adds more dimension in a solution space and helps you validate quickly whether you are going in a right direction you need a course correction. So typically we conduct when design thinking workshops with functional experts, SMEs, users. The key pasting such questions which are very fundamental to this daily journey is how do we get you to do more meaningful work? How do we get you to do, contribute more and more and make more impact in your organization? How do we get you to grow your work practice in your organization? How do we get you to make a real impact that you always desire? And how do we help you amplify the human potential in your practice or in your segment or in your workspace? So these are the fundamental questions that we keep on asking to get to arrive at a pain point of the user. Let's talk it through a case study. So this slide says a glimpse of an analysis done on a target role folder which is a QA engineer. But essentially we have done initially we reconstructed these job profiles for a segmented users and this talks about one segment user of QA engineers and we have performed a detailed analysis and after conducting various time and motion study we have understand the pain points by co-creation method which is again the design thinking approach and gather all the same the pain points of that shared segment. So on right hand side we have all of them different view pain area that is listed by all of our QA engineers. Now some areas can help him do his job more efficiently some help him work more effectively while some areas can increase experience of that individual as well as stakeholders that he interact on daily basis. So to arrive at a minimum viable product before that we identified what is the outcome that we can solve and then the solution spectrum where there is an opportunity to create a maximum impact for a whole community to find a potential solution set. Now this leaves a room for significant per-create assignment greater employee efficiency so these are the drivers that drive the solution set needs to have better employee efficiency better effectiveness in work enhance employee experience as well as stakeholder experience so with this design principle in mind we have come up with a modular approach now so this slide is while this slide talks about what is our MCDA engineer of a QA engineer what are the different skills that our current level of maturity of QA engineer has gone through in his journey I would like to emphasize on the modularity that platform has to have and it has overall three benefits first is it helps augmenting my product features very quickly and by independent teams in organization so development process can be democratized and it can be accessible to all so people are innovatively they bring their expertise building solution more quickly and more innovatively second it also gives you a flexibility to change the solution that earlier required only a basic skills but has grown in complexity over a period of time so earlier something that used to upon with certain steps now require more skills to completion and third why modular approach is because there is a positive network effect between two sides of my platform as a platform I have one side I have a developers other side I have actual customers now my developers on a platform as they will more and more solution this attracts more and more user base and when I have more and more user base it was a good opportunity for developers to develop and build innovative solutions so fundamentally there are three three large scale benefits for going through a modular design of a platform now here we have tried to arrive at an implementation model how do we go about doing it how do we give something to employ very quickly while tasks that require very simple application and data management are implemented through basic process automation or RPA technology and tasks that require more analytical and statistical modeling were involved they are all implemented through AILivers machine learning, NLP, OCR, formatter so implementation model evolves over a period of time for largely two reasons first is that certain skills are supported by basic process automation solution are no longer sufficient or they may warrant a process redesigning also there is a you need to bring a change in arriving at a decision by adding more and more variables more and more data to support and more faster and in real time so because of these two reasons you need a evolving implementation model so it's all dynamic model it's not a static model and lastly I'm going to talk about in an enterprises digital transformation you know parts to capture your maximum value first instead of aligning your people strategy to your operating model and organization change your operating model by focusing on changing the people strategy technology anyways continues to be an enabler it helps being for everyone at almost same pace somewhere early adopter somewhere you know not an early adopter but accessibility of technology remains almost same so first you have to get through you know you have to re-engineer your processes by introducing new digital assistant take some part of your job task you know help him do the certain task give 40% of task to him conduct 60% yourself and then you leverage AI capabilities and you fundamentally redesign the way of work redesign the processes and you know bring more changes and once these two steps are done you finally your platform model base capability adds more competencies in your organization it helps you evolve faster and at scale bring a change in your fundamental operating model it can help you introduce more services that never existed before it can help you create new revenue streams so all together with this insight I think I would like to conclude my presentation and have it to answer all of the questions gentlemen thank you both very much great to see these case studies and focus on the digital assistant now first question that came in was how do you deal with the employees who see the digital assistant as a threat yeah so a threat in the sense as you see that the topic is human-centric digital assistant to improve the productivity in fact it is not a threat rather it will it will inevitably focus on productive work and do the right job for which actually human being for which we are supposed to do so actually it is creating more time for us and being a threat so we are seeing from that perspective I would like to add a few points see we have actually we have brought a culture change by conducting multiple communication channels and we have not actually given them or hand over something to them but we have involved them in our transformation journey so more you involve the stakeholders they themselves see that I want to increase my learning I am not satisfied I don't want to do this repetitive task and that is an area that is an accelerator that employees don't see them as cannibalizing the model they themselves see that they want to move up the ladder quickly and I think you have to involve them in your journey yeah, let the employees see that they could focus on the higher value value add tasks rather than the more mundane ones next question what is the success with HCDA in RPA can you share some data from a successful implementation so adoption initially it was not much when we started because of a lot of challenges the first challenge was even what you said that there was some kind of first rate so we were not getting full participation initially but slowly and slowly we are seeing that option so I think over the period of time there will be a success and we are seeing that option rate is more and more but initially it was not 100% success yeah, sir Nome, you want to add anything yes, and one more dimension to this as an RPA if the question is asked in a whether an RPA is a successful technology or it's not capable so we have seen that yes, RPA is a technology that brings the agile manner of transformation certain tasks faster cycle, faster build cycle when I go and create a PI based use case and implement that it helps me take certain time to create my models create tested based models train them it takes certain time while when I do it from RPA what happens that there are certain tasks which are very fixed very mundane success ratio of my RPA based use case or RPA based what actually is not 100% all the time certain times what also gets failed because of various reasons it's all x, y coordinate based automations certain times UIS change there is a rapid upgrade upgrade was there systems got UI changed and it's all hard coded you have to bring more parameterized and more support required but and so what always RPA what doesn't you know successfully execute all the time but you have to design it where you see the variable of instance of failures of what are high and then you know see what are the learnings that you can adopt to your RPA model so it's a it's a journey for our RPA and we are seeing that solution is also promising great okay thank you which you believe one of the questions was how does a bot client how is a bot client helpful for a QA engineer so you covered that beautifully in the presentation how does HCDA help to come up with a minimum awesome product instead of a minimum viable product I certainly am not too sure with that but obviously would did you get a chance to attend yesterday's event that talk about this I think it was more it's more it's more it's it's more it's more it's more it's more it's more it's more it's more it's more it's more it's more it's more it's more I think it was more about let's try and before we actually go with with a minimum viable product, let's see if we can do something that's a little better without or something that will they talked about something that was aimed at client delight, you know, customer delight and satisfaction rather than just the minimum, minimum viable product. Yeah, so if in fact, in one of our presentation we have put so that's the kind of a shift. So even we are doing the same we are proposing the same that instead of focusing into a process. Why can't we pick specific process which is essentially and then automate or provide the kind of wow factor to the employee so that employee gets more time, more and more time for them, and that will increase the productivity of the employee. Right. But so that's the kind of it is in very much in a line with the minimum awesome product. Yeah, thanks for clarifying. In fact, we were not aware of. But yeah, it is very much in a line with minimum awesome. That's great. Great. Now is a nice twist. Gentlemen, we're we're right on time and your break. So thank you both Abyshek and Balmik for your it for your insight and and sharing your experience and we look we look forward to seeing more of these in the workplace.