What is our primary use case?
I have worked on a number of use cases, and one of them that I can discuss was used in a contact center environment. This is a project that we had done for an automotive insurance company, and it had to do with incident management. Our contact center received the first notice of loss (FNOL) from incidents, such as an accident.
When an accident occurs, they raise a ticket to our customer service representative. This can either be done using a chatbot, which is integrated with our ServiceNow platform, or they can call the customer service representative. In the latter case, the customer service representative will pick up the call and get the details. This includes adding their insurance ID and a couple of other fields, and that is integrated into our system.
Our system was acting as an intermediate between their existing platform and ServiceNow. Part of the system included a database, where they were checking to see if the insurance amount the claimant is asking for is above the limit. There were other similar business rules, as well, which the bot was responsible for checking. Based on the result of these checks, the claim was automatically approved, and then a corresponding ticket was raised in ServiceNow.
There was also a manual process, where there was a person who would go to the site where the actual accident took place. They do their analysis, and then they create a review report, and that report would automatically be handled by an attended robot. The robot would take the detail from the agent and based on the review, fetch certain details like the approved amount.
The bot is responsible for sending other information to ServiceNow, including, for example, details about damage to the vehicle. If there are scratches on the front or scratches on the back, then these details are all posted to ServiceNow. At that point, ServiceNow has a workflow that is initiated.
The workflow uses the information taken by the representative and moves from the review stage to agent verification, and then to a mainframe. The system running on the mainframe is responsible for generating checks, according to the amount that is approved, and then mailing them to the claimant at the address they have on file.
How has it helped my organization?
In our FNOL process for the insurance company, we use unattended robots quite extensively for both chatbots and IVR. We use the AI capabilities for language understanding and based on the user sentiment, it will trigger the unattended bot. If instead, they want to speak with a representative then it will trigger the IVR process.
In terms of the robots prioritizing and correctly routing a transfer to agents when necessary, it is a work in progress. From a priority perspective, if you talk about chatbots, let's suppose a customer sale is highly urgent, the AI model can use language understanding to determine an urgent message and in turn, create an urgent ticket. It is something that we can do but it is not 100% accurate. I would say it's 80% of the way there, because of the different types of sentiment that people express during interactions. As an example, when a customer says "I need to have this resolved as soon as possible", there are a number of different things that can happen. According to our business rules, when somebody says ASAP, it should be treated as a high priority, but 20% of the time, this does not work. Overall, at this point, the AI models and machine learning models are not very accurate.
The robot-enabled self-service channels have definitely increased the resolution of issues through self-service. Prior to using the robots, 90% of the calls would need to be addressed by a representative. Since implementing the bot strategy, only 10% have to be handled by a human. We have used UiPath Apps for this and also created some web pages, but those are just to help the bots. Definitely, self-service is one use case that has really benefited because of UiPath.
What is most valuable?
The Studio is where the development takes place and the interface is very user-friendly. You have the ability to drag and drop components, and this is part of why I think that Studio is the best feature in UiPath. The next best feature is Orchestrator.
The Orchestrator is quite good because it is a one-stop shop where you can run robots after creating them using Studio. You can create queues, monitor the bots, and if there are any issues then you can debug them at the Orchestrator level.
UiPath has a low-code feature called Studio X, which is specifically for business users. They can just drag and drop activities like reading emails, retrieving email attachments, reading data from Excel, and posting data from different sources into different platforms. It is a very good platform for business users who don't know much about coding. It is customizable in the sense that business users can have the system follow a set of simple steps, although it won't do complex things.
UiPath Insights is a feature that has everything from a tracking perspective, which tells you how the bots are working at the production level. It provides statistics about the live environment including how many processes are being run, how much time the bots are being used, and the productivity in general. There is more analytics available from data services, tests, and the AI center. All of these features really help when it comes to analyzing the data, not only from a development perspective, like tracking data on how much a robot is at a log level, but also from the end-user level in a production environment. Reporting on productivity in a single day will show how much time the bot was run, for example, 80% in terms of time or 90% utilization, and other such details.
The UiPath App feature is something that we can use to create simple apps, and these can act as integrators. Suppose there is a process that uses 10 different screens, we can create an app that will be integrated with all of them. As a developer, all 10 screens are used in my workflow, and instead of going to each of them, I can create an app that uses all of the fields that are relevant to me on each of the screens.
The speed at which we were able to create automations for our contact center was very good. One of the reasons that we choose UiPath over other tools, such as Automation Anywhere and Blue Prism, is the ease of development. When it came to setting up the contact center, it was only the connection between different platforms that took time. The bot creation and the workflow creation were quite easy. It took approximately one and a half months to create the whole automation for the contact center, which is quite good.
What needs improvement?
The AI and machine learning capabilities need to be improved.
The task mining and process capture methods are capabilities that we use, but they sometimes miss part of the task. For example, let's say that for one of my tasks, I need to open my email 400 times a day. This is something that we can automate but for some reason, probably because it is related to email, it is not accurately evaluated. In this regard, the process mining could be improved and lead to better results.
The built-in OCR is only 60% to 70% correct if you're analyzing a PDF that has images in it, so this is an area that can be improved. Different companies use their own OCRs; Google has one, and Microsoft has one. The UiPath one requires that we use a validation step between workflows in order to improve the accuracy.
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For how long have I used the solution?
I had been using UiPath for three years, up until a few months ago when I joined a new organization.
What do I think about the stability of the solution?
From what I have seen, the biggest factor for availability is the strength of the internet connection. Whether the deployment is on-premises or cloud-based, they both are the same in terms of stability. I have not seen any deviation between deployment types.
What do I think about the scalability of the solution?
Scalability is not an issue. In my previous company, we started with 10 machines and then after one year, we had 85 machines. There were no issues and the implementation was not a headache.
How are customer service and support?
The technical support is very responsive.
Which solution did I use previously and why did I switch?
Prior to working with UiPath, I was an automation expert with Selenium for web testing. I was not able to fully automate a website because if there was an image that was used as a security check, where the person had to click an image to get through to the next page, I wasn't able to do it.
However, when I switched to UiPath, it was pathbreaking for me. I was able to accomplish what I couldn't do with Selenium and since that time, we have deployed more than 100 production bots.
How was the initial setup?
The installation is pretty straightforward. We usually get issues when we upgrade to a new version but I think that is a different discussion. Strictly from an installation perspective, we have not had many issues. We had no major issues and when we contacted technical support, the team was quite responsive.
The length of time required for deployment is about half an hour per machine. However, if you have 100 machines then you can do them concurrently.
For some of our projects, we used an on-premises deployment, whereas for others, we used Orchestrator and they were cloud-based. Cloud-based deployment gives us the ability to run bots from anywhere, including outside of our network.
What was our ROI?
Our clients with the contact center did not see a very large ROI in the first year, although that was because of the consultancy costs that we charged to implement the system. From the second year, onwards, they definitely saw a very good ROI.
We had different metrics to calculate RPA implementation ROI. The first is productivity, which increased by more than 60%. If I recall correctly, their investment was between $110,000 and $200,000 after the first year. I don't remember the exact numbers but it was a huge improvement.
It was not just productivity, but also other things like a reduced error rate. The quality of the processes improved quite drastically.
What's my experience with pricing, setup cost, and licensing?
We analyzed and compared the costs of RPA from different vendors and we found that UiPath was the most cost-effective in the long term. An unattended robot costs approximately $8,500 annually.
Which other solutions did I evaluate?
We evaluated other RPA tools including Automation Anywhere and Blue Prism. One of the reasons that we chose UiPath is its ease of development.
In terms of ROI, we found that UiPath was the best when you consider the long term.
What other advice do I have?
The length of time it takes to develop and deploy bots for a process depends on its size and complexity. We categorize processes as simple, medium, and complex. Based on how they are classified, we estimate the deployment lifecycle from one month to two months.
My advice for anybody who is planning to implement RPA is to begin by doing research on the vendors. You need to speak with each vendor and start planning, but don't think about clients at that moment. Rather, think about yourself. Consider that you want to implement internal automation, and consider the ROI you would garner during the first year or during the second year.
Once you choose a vendor, as we did when we chose UiPath, you need to make sure that at the very start of your project, it begins with low-hanging fruit. Don't start with all of the complex processes; start with some simple processes. That's why we have divided ours into three sets of processes. Then, don't think that you will achieve a hundred percent automation because that will never be the case. My thinking is that if you achieve more than 70% automation, that is a very good target. Keep your expectations clear.
Another thing to make sure of is that you secure your bot at the workflow level. UiPath provides very good security features that you can use, such as assigning permissions for who can access your workflow. Also in terms of security, be sure that you have all of the required certifications.
Once you have implemented some basic processes and you are getting good results, hyper-automation is something I suggest. Start expanding it to different technologies, such as AI. Also, engage all of your employees as much as possible.
Start with the community version of the software. Although this review is based on the licensed version, the community edition is free and you can create your bots for free. I always say that even one hour saved because of automation will yield a good return annually, and your results will be very quick.
If you keep all of these things in mind then RPA will be fruitful for you.
I would rate this solution a nine out of ten.
Which deployment model are you using for this solution?
Hybrid Cloud
Disclosure: PeerSpot contacted the reviewer to collect the review and to validate authenticity. The reviewer was referred by the vendor, but the review is not subject to editing or approval by the vendor. The reviewer's company has a business relationship with this vendor other than being a customer: Partner