Session Information:

How Automation Brings Value to Supply Chain Management

Here from a leading expert on how automation brings value to supply chain management. 

Session Transcript:

Our next speaker, because he brings the real intelligent automation perspective to our supply chain development, and I'm talking about ..., Who is here with us? Not far from me here, I'm in San Antonio, Texas. He's based in Houston, Texas, and Shivaji is the senior director for Global Industry Solutions at UI path, where he leads supply chain, management, legal, and contract solutions, bridging business needs to emerging technologies of the robotics process, automation plus, artificial intelligence, shivaji. What? A pleasure. What a gift to have you with us. Thank you so much for sharing your wisdom and expertise of our global audience today.

Because A, it's a pleasure. So my goal is to match 50% of your energy with my content. I love the passion and energy you bring into it. So if I could match 50% of what you bring in, I would consider it as a success. And you do it. Thank you.

So, folks, thank you for the opportunity to present in front of you.

It's a beautiful day today. And in Houston, Texas, it was quite cold. But now, the warm sun is out, so, I'm really excited.

The next few slides, we will talk about intelligent automation and supply chain management.

Now, in the past 24 months, 18 months, 12 months, and six months.

Increasingly, all of us, if not all of us, most of us, have started to feel the pain in supply chain management. In fact, if you look into the goods inflation, we haven't seen something like that since 19 80 though.

In fact, it sometimes goes even further back in 19 70, 476, so we are touching 11, 12% of goods inflation.

Now, the idea here is not to sound jittery or negative about it, I think, along with the realities of the world.

There lies an opportunity.

And that's where my message will be in the next few slides. And I believe this opportunity lies with the evolving technologies, which are specifically in robotic process automation, and Artificial Intelligence.

As you may know, UI path is a leader in robotic process automation, and I lead the supply chain competent offered along with legal contracts.

So, it's my pleasure to dive straight into it.

Without further ado, I would love to share some data points that I gathered from AP QC. So, we have a partnership with a big QC. And if you know that AP QC does publish baseline map.

So these are some of the numbers, if you look into it.

Oh, the impact of garbage 19 has been bad. And I will be preaching to the choir, stating how things went in the past two years, almost. ...

states at about one in five supply chains barely survived, but some of them did have a modest to complete success.

I will not focus too much on to the specifics of it, but from to set the stage, where we are at, and where we can go from here, will be my objective.

The next slide is around the trends in supply chain management, which APIC uses states, companies, organizations will focus on, in the next 2 to 3 years. From an RPA AI perspective, we totally understand that we will not be able to influence all of it.

But when it comes to some of the key elements, for example, artificial intelligence and cognitive computing, robotics process automation is right up there, the at number four.

We believe UI path can play an important role in this sphere.

Now, another metric around AI and RPA supply chain has been a law adopter of this technology. And I have the privilege to work with multiple company companies across the globe.

While this whole industry is warming up to RPA and AI, I still believe there's a tremendous opportunity, own the table up for grabs, along with AI and RPA.

There are other emerging technologies like blockchain, where, which will play an important role pretty soon.

Now, working from home has changed the dynamics. I am, I have been working from home for the past two years now. I miss traveling. I'm missing out on all my miles and hotel nights. But hopefully United keeps my status this year and I'll try to get back to it and hope to see you folks in person sometime very soon.

So let's let's get a little deeper from a macro to try to get to a slightly micro-level that.

What are some of the focus areas?

Where, organizations plan to align the resources, coming up in this year, and, the following years, You will see, planning, remains at the top of the chart, and, I believe everything revolves around planning, if you have a good plan.

The downstream impact is significant and also, if you don't have a good Blatt, and, also, the downstream impact is significant.

Sourcing logistics innovation, they are at a close, they are, they are at a time, right?

So sourcing and procurement, traditionally, very manual labor intensive, could be error prone, boring, if I hit put logistics inventory management, again, multiple systems, ton of paperwork.

And, you know, it's not very fun to just look at paper and do data raghav.

Yeah, challenges that exist in these processes.

Innovation.

So this is, uh, this is what I was alluding to in my previous slides, that innovation around AI, around robotics process automation, is playing in the minds of all the leaders in supply chain management, right. As we start to address, the again, the man will mundane tasks off, let's say, our management, for product development, etcetera.

Manufacturing, by itself, and the correlation of supply chain, and manufacturing, goes on, since, since the beginning of everything, my focus, I would not focus too much on the manufacturing component here, But I'll try, in my mind, manufacturing.

Supply chain enables manufacturing. So, as long as the upstream and the downstream. So, we'd get the right product to the amount to the production facility, and we make sure we distributed properly.

Then supply chain is a successful one, all right, so, this slide, I wanted to give a perspective as what some of these different companies and leaders across the globe are planning to this year and the coming years.

So, the next slide.

I believe supply chain will always be about the right job at the right place, at the right time, at the right price.

Those are the most are, I mean, in one sentence, that is the key message: any supply chain leader would love to focus on.

Other than that, the three other areas that I come across quite often, around how do we enhance the agility of our supply chain? How do we reduce risk?

How do we have our people positioned to do the right work in innovation?

And I like to take a moment here that I'll start from the people compliment.

I think the job satisfaction as a metric, is rising up rapidly.

And of course, we're all seeing the great, resignation as our Chief people Officer says, she says, It's great migration, Not great resignation, and I agree to it, and this migration is happening.

Because people are realizing that they can do much more value added tasks rather than getting stuck in reading paper and just doing the data entry kind of thing.

We, as human beings, we are much smarter than a lot of these jobs that exist today.

Now, reducing risk will always be one of the key metrics. Of course, we, we want to minimize risk.

And minimizing risk if mathematically if I call it, is introducing the variables.

Human input is a variable.

So, how do we address human input?

If we can automate it through intelligent automation, that's where, as one of the key metrics we can influence and, of course, enhancing the agility of supply chain. What does that mean?

You are getting bombarded by multiple changes, which quite which happens quite often. You know, planners need to change the planning. Sourcing managers need to update their plans on the buyers, the expedited, or even the accounts payable processes.

The carriers, Every department, every function, every process, gets continuously bombarded by multiple changes from other sources.

Now, if it is, again, people dependent, You become, when I say you, the processes become more rigid because it's depending upon chabad you to do a certain data entry to make sure things move from A to B Now, intelligent automation couldn't be leveraged to enhance that agility, A robot can work for you 24, 7 without taking any coffee breaks, and any other breaks you may think of.

So those are the three main areas That I come across quite often and from here, and we'll try to get slightly deeper into each second, and of course it's a 30 minute presentation, So I have some couple of demos for you as well to showcase how the robots work.

In reality, some of you may have implemented Robotics Process automation along AI, but I love to share about 2, 3 minute videos, just to give you a perspective how our robots work, Before I get there, it's, I think it's important for us, too.

Look into some of the other key metrics. What intelligent automation maye.

drive, improving planning accuracy, spend visibility, and overall efficiency. when it comes to logistics, you know, how can we improve the warehouse operations efficiency, or the shipping efficiency last, not the least around, you know, improve customer satisfaction. In fact, I should update this slide. It's not only customer satisfaction, it's employee satisfaction, customer satisfaction, even vendor satisfaction plays an important role, because, you know, you, there is a shortage of the right vendor to sub to supply the right material that you may be. So you have to be very careful about how you're managing your vendor relationships.

So, and if you notice here, you know, accuracy, efficiency, satisfaction. These are some of the key themes which emerge. And again, going back to the intelligent automation team, robots don't make any mistakes. So hopefully not hopefully they will drive higher accuracy, higher efficiency.

So, what is intelligent automation?

I think it's important for us to define intelligent automation, and I sometimes feel the, the word intelligent is thrown around quite a bit, and we just accept it. Oh. It must be intelligent. It must be super cool. I want to simplify it, and hope it makes sense.

In my mind, intelligent automation in supply chain means something which is connected, it's predictable.

It can work on its own, and it can give you insights about your operations.

So, when it, when I say it's connected, can our robots connect to multiple systems? Of course, that care.

Internal, external legacy systems, ERP systems, Anything.

If there's a key keyboard that's being used, or a mouse click, we can connect. But that's a use, that's a user interface.

We can also connected on API level, but we'll get into that later on.

Predictive is the application of artificial intelligence. And, one of the examples, I will show the videos, I would show, in, that you will see, how our robots, along with AI, could consume the data of materials, which are being used and then recommend to a buyer a far part ABC. You need to order this quantity because we take the demand will go up by experts that age within three months.

This is pretty cool stuff ...

is the Robots in Action, auto numbers.

RPA means you command a robot to do certain tasks, it will work on its own, therefore significantly reducing all the keystrokes and mouse clicks.

Last, not the least, is the insight.

Are the insights, are the analytics competent of it. So you, you, unless you know what's happening in your process, it's very difficult for you to control the process. So if you can measure it, you can manage it. So, that's the analytics competent of it, that's, I believe, is the overall, entirely in supply chain.

Now, what makes UI path Platform suitable for intelligent automation? I'd like to take, action, focus on this area.

So, people who are new to RPA, or who have been in RPA, one of the most common misconceptions, which I see here, is, OK, RPA, whatever I can click and do, a robot can take it.

I believe that's a smaller view of overall UI, that platform.

How I would recommend you, to look at the UI Path Platform is like, if you were to hire somebody today, you would want that person to see what they're doing.

You want them to think what they're doing. Then they actually do the work.

Then they connect with other people. And then you measure.

You're path platform is exactly, this, is like hiring a very smart individual who can do all this.

So, when I say see, folks who have been in Lean six Sigma or process improvement been drawn, they know that to see or understand the process, it could take weeks or even months, but through our process, mining, task, capture, et cetera. We can map out your process without being intrusive with your SME. So you're not rubbing elbows with an SME trying to find out, hey, what are you doing there? Can I copy this? Can I take a screenshot?

Now, our platform can do it for you. Not only that, it can visualize the flow of data. It can tell you where the bottlenecks are. Who touched it? How long did they touch it for? What was the reason behind it? So imagine, just imagine the power, you get, by having that visibility about your processes. We haven't even gone into RPA yet. This is just the first part.

Now, once you start visualizing this processes now, give them the power of artificial intelligence.

Now, now the AI comes in and say, OK, by the way, if you have build ML models in some other platform, you can bring them in, or you can build ML models on our AI fabric.

Now we're giving mind, or we've given intelligence, to this data, or this information that we captured, that's the AI competent and act, is the RP. So it's a robotics process automation, which is you just go ahead and do the manual key in Ogden Mouse Clicks.

Connect is, how can we make ourselves nimble? And one of the key metrics, which we talked about previously is supply chain agility.

So, connect to apps, two, bringing in human and robots, working together.

All that comes under the Connect. And Measured, as I stated earlier, is the analytics competent, so we have something called Insights through which you can see how your processes outperforming.

By the way, let's not confuse insights with Orchestrator. Orchestrator focuses only on the performance of the robots, but you want to know how your sourcing process is working, how you're planning processes work, how your payables process is working.

That comes under measure.

The next one, this is my anchor slide when I speak about supply chain.

We have divided it into four areas: planning, sourcing, logistics, and off the market, by design. I did not, but manufacturing in it, and I completely understand, manufacturing and supply chain go hand in hand.

We do have a manufacturing practice, so, that goes much more details into it, But, as I stated earlier, the objective here is, How can we make sure that the goods and services reaches the manufacturing plant on time and in full.
19:02
And then how do we distribute it?

We talk about After Market, it's primarily the reverse logistics component of it.

So that 10 20 percent of, hopefully, not 20 percent of the goods, which goes back, how can robotics process automation plus AI enable that business?

No.

The green boxes under the hexagons are some of the key metrics that we're looking at, which is the planning accuracy for planning now for let's let's take one at a time. Let's take planning.

As for my understanding and working with top consulting firms globally, we, the data that we have collected, it looks like, what do you do 45% of the time spent by planners are on data collection, they go to multiple systems, They have the corner to excel sheets, et cetera. And if you look at the characteristics of those processes, then they are just manual collection of data.

Our robots can do it.

I'll give you a practical example.

When I am, when I'm getting ready to talk to a senior executive of a company and I want to understand the financials for the past three years, five years, I have a robot on my desktop and I run that robot NNSA company ABC, I think their peer groups is X, Y, and Z Could you run the report of the financial comparisons and tell me how it has been doing against this peer group.

And while my robot is running, I chillout, grab a coffee and say, hi to my daughter. When I come back.

It's ready.

It is ready in a three page PowerPoint, which I can beautifully present two to a CXO.

And, by the way, I could, that's my choice, whether to take a coffee break or not, I could continue to work somewhere else, as well.

So that's the beauty in planning. And sourcing is, again, A: the entire appeal. management, PR, fuel management, and in fact, if you bring in AP into it, sometimes you know, AB sits in the finance. Some organization does surrender supply chain. So the entire procure to pay process we have, you could have visibility around that drive efficiency and accuracy.

Logistics, as I mentioned, shipment tracking now, when it comes to B to C, if you ordered some something on Amazon, it's relatively easy. When something gets picked up. You get a notification track on UPS, or FedEx, you know, where it is, From B to B, gets a little challenging. Folks who have worked in the logistics industry, understand that, you know, we have the expert, either to the buyer assistance, sometimes the buyers, tracking hundreds, sometimes thousands of lines of Excel sheet, Weekly. When I started my career at GE, I was an expert data for GE Power. And my job was to send e-mail notifications out to the suppliers every every week.

So all that could be automated. And let's not forget the paperwork, all and every kind of paper that comes in.

And if you have to read it, our robots had the ability to read it, extract information, and even enter it to any, any system, to be ERP system, to an ER, to SharePoint. Sending an e-mail out, all of that.

And the after market, again, the reverse logistics bottle fed parameter focus being, customer satisfaction.

How quickly can we create visibility around the returns and making sure, you know, the customer is refunded, et cetera?

Do I did a quick time check? I think I'm doing well on the time.

Let's I'll take some questions in the end. I hope we started to get some questions.

You're doing great, have five minutes to go, and the questions are coming in.

Fantastic, fantastic.

Moving on, I think it's important to look into automation slightly broader. I know my focus area here is only on supply chain.

But as I interact with multiple leaders globally, this diagram or this honeycomb, if you notice in the planning is connected to listed the contract before the sourcing happens, or the logistics happens, And that may be connected to your customer service. Now, that customer service may be connected to the reverse logistics spot, and again, all of that may be connected to your finance department, where you're looking into your auditor, can actually, Treasury is looking into how much money they can release this week.

All the recording, that ricotta report process, that goes around it. All the analytics that goes behind it.

So, if you are a leader in supply chain, or any other function, my humble recommendation is to look at the linkages amongst these different processes and then start thinking about an enterprise wide automation.

That's the key message here, and, of course, don't forget about the IT cybersecurity, the cloud infrastructure, management, application management, et

That's the key message here that look for linkages across functions and processes.

I have a, I have a video, and I hope this works, because we tried it during the demo.

So this is an, this is an inventory planning and purchasing demo, this should be a 2, 3 N, three minute video. Let's draw.

Yeah.

Hello, everyone. My name is Jeremy Leven today. We'll be going over the Use Case Inventory Management.

In this use case, we are a retailer who is looking to protect unnecessary inventory for each product in order to maximize sales and revenue for the next time period.

There are four main steps in this use case. First, extract inventory data from the CRM.

Second, the robot will obtain a sales position for the next time period using the modeling fabric.

Sure.

The robot will form the necessary inventory increase, and received the purchase request from a user, Additionally. The robot them capture this data scientists data back, to act, to, retrain, and improve the model and forth.

The robot will complete the purchase and its inventory.

Let's try to add fabric to deploy the inventory matched up.

First, we will create a project, and we'll title this project in inventory management and provide a brief description.

Next, we will navigate to ML packages, click, upload a zip file, because we are uploading a custom model.
26:25
We will provide a package description and an example input to the model in our model.

This will bridge the gap between data scientists and RPA developers, as ... will understand how to interact.

Additionally, we will select enable training as this model is retrievable.

Now that we uploaded the zip file containing the model, we need to deploy this model as an ML skill, so the successful in your studio.

We have deployed, the model isn't scale.

Now, we'll take a look at the workflow in UI Path Studio.

Here, you can see a high level view of the workflow.

If we dive into that predict sales sequence, you can see the ... activity we used to get the prediction from the model. You can see that we have selected the inventory management model that we deployed.

If we take a look at the complete purchase workflow, you can see the upload file activity that we're using to send data points back to act fabrics that we can be retraining and improve the model.

Now, let's watch the robot. Run the automation.

First, the robot will open a browser, navigate to the CRM, and log in.

Next, robot will navigate to the Inventory product page, and capture pass sales data for each of the five products.

This data will be sent to add fabric in order to predict the optimal inventory for each of these products.

The robot will take these predictions and create a task, an action center, or an employee to review and validate the purchase request.

Now, we aren't action center, and we can see the task that the robot created.

I'm going to assign this to myself, and open the task.

You can see on the left side.

Yeah, the products and the middle we have an explanation for the purchase, and on the right we have the purchase number For this TV, the explanation is: So, I'll take a pause here and explain a, finish it, because I realize it: half past, What this model just did, is, based on the ..., it gave an explanation, gave an explanation that you need to order additional 10 or 5, whatever the number is. And that purchase, nobody's. It's not a punch purchase numbers or purchase quantity. So, the model is predicting what purchase quantity needs to be ordered, and then it is giving data recommendation to the buyer.

And if I may, forward there.

So what happens is, as a buyer, you have the ability to change this number, and once you approve it, the robot picks it up, goes into your purchasing system, creates a PR RFP, or directly sends it to multiple suppliers. And it can even follow up with the suppliers and then your entire ordering process is complete.

So, if you look into it, the thinking part of it, the actual doing bottle fed, descending part of it, even following up part of it, it's all automated. The only thing now, your buyers, or even the planners are doing, is making a decision.

That's what we're designed to do, make intelligent decisions.

And that's how I would conclude my presentation for intelligent automation, is our team members, you'd be using their mind, their intelligence, to run a process, and not their fingers to do data entry, and collect data from multiple sources.

So, let's make our Workforce intelligent through Intelligent Automation, Josey, that's fantastic shivaji, and we have some good questions here. Kimberly is saying that Thanks for the fantastic presentation on the, on the, on the how we can make this concepts of intelligent automation a reality for what we do. So, thank you for bringing those perspectives. So, let me bring my camera back on here with you, and I will, I encourage our audience to continue to ask questions.

And the On this, the first question and the kind of a theme that I want to convey to you is about getting started, You know, organizations are all different levels of maturity. So for an organization that is Doesn't have, you know, enterprise architects and are well developed, you know Center of excellence or things of that kind.

And then they hear things like, Well, Let's start small and scale. It sounds really good, but they don't know what that means.

What does it look like when you're starting small and scaling in a way that you'll find that.

It's, it's both effective and efficient for a, let's say, smaller to mid-size organization to start developing this capabilities?

Kimberly, that's a fantastic question, and I, I answer that, with my foresees, or any kind of transformation, irrespective, if it's a digital transformation or not there are four C's. The first C is about culture. Your capability, your capacity, and your control. What I have seen is, if the culture is not there, if organizationally your senior leaders have not bought into this concept of whether our PA plus AI will work, you will struggle by you.

I mean, the organizations struggle, and from there on, How do you build your capability as a Do you have to treat people who can do it, and then capacity? Now? Do you have 20 people who can do it, or, do you go to a partner to do it? And, last not, the least is the control.

You don't want multiple people just creating random automations on their own.

These foresees fundamentally play an important role for scaling now, if your answer is very specific, that, You know, how do we train our own people, so there are few avenues, the first avenue is I've seen, by the way, our platform is drag and drop. It's relatively easy to learn, and we offer all the free courses on our website. So, that's one way you could have a training session internally, when you start building it.

You could leverage our partner network from, from an investment point of view, and the time it takes, I can assure you, it's, it's not gonna break the bank. And, of course, you could go through UI path to directly where we can help automate, let's say, your first five process, your First 10 Processes, and also train your team members on how, how to automate and provide the certification sector, by the way, all the certifications are free.

So, those are some of, some of the some options you could look into.

Those are, those are great insights. And just so that I make sure that everybody understands how to get to some of these references that you having, you're mentioning Shimbashi. Is this under a UI path dot com? Is that way you go and you can see, you know, the training and things that are available for free, I think, for people who can take this, right.

Correct. So UI Path Academy, if you Google UI Path Academy, you should find it, or you could go from UI path dot com as well.

Terrific, terrific. And what another question or theme that has emerged here is that about the intelligence of robots. Because one of the, the perception anyway that a lot of the, our participants have about robotic process automation.

The current stage, it's, it's possibly quite useful for processes. There are well defined and repeatable. And then maybe there are standardized processes in which we do things.

So there is that bit of understanding. But also there is a saying about smart robots and adaptable robots.

I mean, how, how adaptable are robots nowadays, choo may be changes in the process? Or maybe you're looking at documents. But the documents have different structures. Talk a little bit about intelligence. They're really the reality of the current level of adaptability, and the intelligence that this robot software robot may have.

That's a fantastic question. So I'll give you two words.

Structured and unstructured, that's fundamentally defines Robotics process automation now.

ideally you want structured data, structured processes.

That makes things easier, right?

So if you have a structured way, a template, things come in, you can automate 99% of that challenge comes with when it is unstructured.

But when the unstructured data comes in, and I'll give you specific examples, let us say an invoice, when invoice processing started, through optical character recognition, and the AI started coming in. The initial challenges were, oh, we had 5000 different templates of invoices. So do we have to create 5000 different templates for RPA.

Initially, that was the challenge.

But now, through AI arm. This is the learning model. Robots will pick up.

So, if you So what we asked, if you'd give us one thousand invoices, we train our robots read one thousand invoices. There's a very high probability. The thousand and first invoice you send us doesn't matter what template it is on. Our robot will be Peck. Peck will be able to pick up all the 10 15 fields you need.

That's taming the unstructured data through machine learning.

Right, now, when it comes to process, I recommendation still is, it helps if the processes are structured, are standardized, if not 100%, 70%, 80% at always helps, even if it is not. There are instances where robots could still learn, especially with task captured and task mining, where it can observe how specifically, I'm doing my doors, Just, say, how specifically you're doing your task.

And then two and digitally.

Now, it will tell us, OK, what is the optimal way to do a specific task, hope I answered.

Very good. And because you mentioned the task mining, and this, and the related subjects there is, I was going to ask that later, but I'll bring in Albert for continuity. Another question that came up has to do with process to mind. At least was referred to as process mining, So, talk, a little bit about that, how that works. How process mining, and text mining work with RPA. And if you can do to kind of, a more basic level, for some of us, don't, really, are our RPA experts. And how does that look like when it's done well?

Just say, here's my question.

Today. If you, let's say, manage a team of 10, and you want to find out how your process works.

Let's say you're a new manager coming in and you have no idea, you would traditionally go and do what is called the SOP standard operating procedure, where you got screenshot by screenshot, and there's some definitions within. Typically, that's how most organizations are still working.

Now, I imagine, imagine this: let's say there are 10 systems which are being touched upon by European Team members to do a certain process.

I say, just say, Here's process mining. We will tag the flow of information across these 10 different systems. And at the end of three weeks, four weeks, I will visualize the process.

Why example, purchase requisition to goods receipt, purchase acquisition?

Who are requesting purchase requisitions? How many, what's the volume? How long is it taking for purchase requisition to get converted into purchase orders? Who is convert, who is approving those peers, and how many of those peers are getting rejected?

From there on it it goes to how long is it taking us to send that POs to the suppliers?

How long is it taking us to do the goods receipt?

How many times before the goods receipts there are changes in purchase orders? How long is the wait period?

Just say, I can give all that information to you without talking to your SMEs because that's what process mining does. It works in the backend.

It tracks the flow of data across multiple systems and visualizes the process for you. So, all that effort of manually tracking that information could be automated through process mining.

Now, to ask, captured and tasked mining is a micro level. So, here's an example. Let's say you have 10 people who are doing accounts payable invoice processing. Now, ideally, you want all 10 of them to do the same or a standardized approach.

Now, if you have task capture on each one of these computers, our system can find out how exactly are differently. All these 10 people are working. Now to task binding. What our system can tell you is that, hey, 60% of your process is standardize. What the person is not this, by the way, this there's a ABC guys, is completely out of whack. I don't know what he's doing. So you could get that detail. So again, to summarize, process, mining is at a higher process level. Gifts, process, visibility, Task capturing data mining is at an individual level, how they're working.

And then, if I may add RPA, then we'll, coming in after that. And you identify the opportunities where you can automate those part of that process, Ryan, correct, Absolutely. Thank you for finishing my thought. Yes. So once you identify those bottlenecks, you can start automating. it starts giving the ideas of automation as well.

Perfect, perfect. Karen Kirby says here. Great presentation, she buys you, thank you.

Her question is about industries where you, where you see the industries that are the leading use cases for adoption of RPA, and a follow up to that, Is that whereas RPA creating the most value? I mean, if you, where do you see the use cases in terms of industries, but also maybe specific use cases that you think are very high value creation?

If it's a broad question around industry, then banking, insurance, life, sciences, healthcare, tremendous amount.

If it comes to supply chain specific, most manufacturing companies, we are seeing high adoption there and the, and this one question, which, as I think I've felt, is part of it around the value.

I think there's a shift when it comes to what value mean the definition of value. Traditionally, value has always been associated with efficiency, OK, how many dollars can be saved?

But that's not the game. Now, it is not the game, efficiency will come. It's by default. It's like Maslow's hierarchy. You will get food, clothing, shelter that will come with automation. What's next is it gonna impact your Risk mitigation? is going to impact your revenue? Is it going to increase your customer satisfaction, employee satisfaction?

Those are the areas leaders are focusing on. Leveraging AI plus RPA.

Very good, Very good. Yeah, we, we had a conference on RPA and intelligent automation, just prior to this one that wasn't fully focused on RPA intelligent automation. And to your point, you know, financial services and healthcare and the broader, broader level are really accelerating quite a bit.

But you mentioned this it's it's cross industry.

Now I think every organization that that has a process that has and which is like all organizations has have potential applications for RP. Let me get in a very big tactical here with you.

On these use cases, if I look at my organization, regardless of industry, it is, what kind of process looks like, right, For RPA, that feel like you know what kind of characteristics you look at, in a process, in our organization, that says, hey, let's start here. Because this is a good way of building momentum, and showing kind of value for the organization. What kind of characteristics those processes have?

Yeah. Great question. High volume, rapid that they've rule based low exceptions. Low decision making. Those are some of the key areas and I'll digress lightly 20, 25 years ago.

Just say there is a big movement around OK, let's centralize. Let's create this ...

where you can outsource and get this process is automated upstarting, not automated, but worked upon.

If you look into those processes which were centralized and put into one location, they have the exact same characteristics what I just mentioned.

So what I'm also referring to is that if you were to look for Automation Lookup for those processes in your organization, those processes, you could get up to 70, 80% of automation. So, not only there's obviously much more cost saving, whatever you're getting right now. Plus the control component of the risk mitigation competent of it, but that's how it summarize it.

She bought here, I can't believe it's already time. It's been a masterclass on intelligent automation and RPA. I mean you are, you have such great knowledge on the subject and you communicate it so effectively, thank you so much on behalf of our global audience, We want to thank you for sharing your wisdom and expertise with all of us.

Thank you very much, Josie, Iwas pleasure to host it with you. Thank you, everybody.

Thank you, Ladies and gentlemen, that was shivaji, thus, senior director of Intelligent Automation RPA, Industrial Solutions for UI Path, who is transforming organizations to create value for all. And that, as he mentioned, this see the four C's of Great Transformations. We're gonna be looking at next supply chain transformations and culture.

None of this things happen. If you don't have a culture that's aligned with this purpose. So we are going to tackle that subject in the next and final segment.

I am going to share with you directly, the benchmark of thousands of organizations, and that is much smaller fraction of those organizations that have achieved great and during performance.

Because achieving excellence is one thing, maintaining that excellence is, is very different. So maintaining greatness is a challenge. And you can't do that if you do not have an aligned culture. So we're going to talk about the successes, the failures, the good, the bad, and the ugly, off supply chain and transformations. So, taking a break now, I'll see you back at the top of the hour, with supply chain and transformation.