Microsoft Power Automate alternatives and competitors

We use it for handling processes that involve human effort savings. We are currently focusing on processes and problems that our users are facing in their day-to-day activities. It is used for the automation of business problems that are repetitive and error-oriented with a huge number of users working on them. We list down a set of processes where users are spending a lot of time, then we verify whether the use case is valid for automation using RPA. Once that is complete, we start programming the bot based on the requirements given by the user. We try to mimic each and every action performed by a human being by using UiPath Studio. It replicates what a human being does.

In terms of setup, the development happens in Studio that's on-premise, but the deployment of the robots is done on the cloud. They have their own cloud service called Orchestrator. UiPath hosts that, and it is available at cloud.uipath.com. It is basically the UiPath Cloud. The interface is completely handled by UiPath.

The biggest benefit is that before implementing automation, the users were spending a lot of time doing mundane and manual activities. Implementing the robotic process automation for processes that they were involved in helped them to avoid doing these manual activities and focus on more value-added processes. On the whole, it has helped the users to spend their time more wisely and also get more benefits for the same time spent. It helps us to improve user satisfaction by improving their working methodology because they are only doing things that are value-adding.

We are automating all the manual activities that can be successfully handled by the robots. So, the users are really happy, and we are getting good feedback from the users in terms of time savings. We are also achieving 100% accuracy in the output, which was not the case when the users were performing these actions. When they were performing the actions, the users had to validate the outputs, and the outputs were not as per the requirement. There used to be an error rate of at least 10% to 15%, but with automation, the error rate has been reduced to zero. So, the removal of manual activity and the reduction of the error rate to zero are two of the main benefits.

We are using it in our finance operations for our accounts payable process to process invoices. For this process, we were receiving invoices at a rate of more than 50 per day, and having humans perform those actions was not sustainable in the long run. So, we developed a robot that would automatically process invoices that we received through email. It extracts and updates the data into our ERP, and then, it sends an email to the users telling them that the invoice has been received, verified, and uploaded into our ERP. Now, we have a process that saves approximately two hours for five or more users on a daily basis. At an annual rate, we can save approximately 10,000 hours. We develop the bot in UiPath Studio and then deploy it in cloud Orchestrator via an unattended bot, which is a bot that runs on a predefined schedule. We have a particular time when invoices arrive in our inboxes. We set the robot to run at that particular time, and then the robot is able to process those invoices and proceed to the next action.

We focus only on processes that can be automated end-to-end, completely eliminating human activity. UiPath is flexible, and it allows us to build robots that prevent human intervention right from the start and all the way to the end. Then, we are able to deploy it on the cloud by using the Orchestrator solution. From start to finish, we have completely eliminated human effort, supporting our mission of end-to-end automation. For process analysis, we use a UiPath tool called Task Capture to understand the business case and draw a flow diagram for the steps involved in a process. UiPath has all the solutions required to implement end-to-end automation, and we are successfully using them for all our business problems.

This end-to-end coverage is important. Basically, we select processes where we can avoid human intervention. End-to-end automation is one of the key KPIs that we check before we even start automating a process. It is the first thing that we look for because we prefer no human intervention at all, be it for any kind of input, validating the output, or checking the logs of a process. All of these are predetermined and handled by the robot.

It is cloud-based. So, we do not have any infrastructure costs for maintaining the servers, etc. That is a big advantage. Also, Studio updates for development are pushed automatically. We receive the updates and just click on them, and Studio is updated. Overall, it saves a lot of time for the IT team because there isn't any involvement from IT resources after we deploy or install Studio on our system. From there on, there is literally no involvement of the IT department. That is how beautifully they have designed the tool for the updates as well as overall maintenance.

We went for the cloud to avoid any on-premises server costs that we might need to take care of on a recurring basis. The cloud was a big advantage for us. We are able to save approximately 15 lakh Indian Rupees, which would be $10,000 to $15,000, by not going for the on-premises setup. We were able to save that sort of investment in server costs by going for a cloud-based tool.

We were able to synthesize the value of this solution right from the inception. As soon as we deployed the bots, we were getting actual analytics for the run rate of the process and the total time of bot execution. Indirectly, the time during which the bot executes is literally the time that is saved from human effort. We get proper metrics of the time being saved by using Orchestrator. The other important thing is logs. In case a process fails, from the logs, we are able to derive insights about when exactly a process is failing. We are then able to develop a solution to handle these failures and re-implement them. So, overall the cloud solution gives us insights. It adds value to even developers' time by giving us an overall metric of the time saved as well as utilizing the logs for insights about the process runtime, et cetera. Overall, the cloud functionality is a great value addition.

It affects our ability to scale up automation. When we develop and deploy a process, other users in different departments take a look at the processes, and they are getting confident about the fact that this can solve their problems. We have been receiving requirements, and in that way, we are able to scale up the automation. On top of that, we develop the robots in a way that is modular in nature so that when we implement a process, we have reusable components that can be plugged and played into the new process. This improves the speed at which we can automate processes.

It has indirectly brought innovation from the users' perspective and developers' perspective. The users are saving time, and they are getting innovative in their day-to-day activities. In terms of development, we are on a constant learning path. When the vendor releases new software updates, we are able to effectively utilize those and implement them into our processes on an immediate basis, which improves the speed of delivering a process and the quality of output.

We can scale automation without having to pay attention to the infrastructure for doing so. We don't have to be worried about the cost involved with the on-premises setup. It is a cloud-based solution. So, when a requirement comes up and a bot is developed, only then we need to apply for the license and procure a bot. It has been beneficial because we don't need to pay any upfront cost until the bot is developed and ready to be deployed, and because the bots are delivered completely through the software service, that also indirectly proved very beneficial for global deployments and scaling of processes.

Its AI functionality is helpful to learn from the existing use cases and then implement the learnings on the new and upcoming test cases. As a developer, we need not spend any time developing templates for the extraction, etc. The AI module in itself has the capability to understand new forms of data. It can then accordingly extract and plug in the data to our templates without much effort. So, AI functionality has saved a lot of our time in developing a solution as compared to doing it the manual way.

We had one process where we had to use AI functionality, and we were able to eliminate any manual efforts. Previously, we had somebody who was verifying the output of the bot and after that only processing went to the next step, but with AI, we got the confidence that the bot has the ability to complete the action without manual intervention. That is one great example where AI helped to eliminate manual effort and improve the quality of the output.

It has significantly reduced human errors. Bots have quite a high performance rate with minimal or zero errors. The errors only occur because we haven't updated the business case in the bot. Once the business cases are updated in the robot, we do not see any errors. The bots follow all the steps as programmed and do not deviate from the set of rules defined while developing them. This reduction in human error has had a positive impact on users. The users had been feeling more comfortable using the robot output rather than relying on their own output, which sometimes had errors. So, overall the confidence level has improved and the lead time in delivering the output has also improved. The time they were earlier spending on the validation of their output has reduced. 

It has freed a lot of time. We only automate processes where we find huge time savings. We count it as full-time (FT) employee benefits. We only pick processes that have three or four cumulated FT benefits. With automation, we are saving at least three or four hours on a daily basis. This time is being utilized by business users in completing any other backlog work, focusing on other important things, improving their own work skills, etc.

Excel automation is extremely reliable. Excel integration is one of the top features that I have been using. We also have a feature called Document Understanding for processing the PDF format of an invoice by a bot. It has the capability to scan an invoice and then pick out the required fields, such as the name of the vendor, the details of the products being sent, or the cost of the product. There is an AI functionality that allows a user to program the required fields to be extracted, and the bot automatically follows those rules and extracts the data. Therefore, the AI functionality of Document Understanding is another important attribute that I personally like about UiPath.

I also like the Computer Vision functionality, where UiPath provides image processing abilities for robotic process automation. This provides a big advantage because images can be automatically processed without involving any additional tools. With an API, we can automatically link the Computer Vision engine and start extracting and processing images at a quick rate.

UiPath is a low-code platform, or mostly no-code platform, where coding is minimal. We can drag and drop all the required steps and then develop a bot in very less time. I am good at programming, but even a user who doesn't know programming can easily pick up the tool. The ease at which anybody can learn it is quite high. Overall, it is a 10 out of 10 in terms of usability. It is really easy to use with the tutorials that they have in place. Everything about it is quite simple.

We use Orchestrator to keep a track of all the robots that are deployed, monitor the logs, and deploy the robots on the runner machines. We use Orchestrator to upload the bots from Studio to the cloud and then deploy them to runner machines across our virtual machines. Once a bot executes, we get the logs, and if needed, we can monitor them to check that the processes are coming in smoothly. In case of any failures, Orchestrator also has the functionality to re-execute the process. So, we are utilizing the cloud to a greater extent for managing our robots.

The UiPath community is wonderful. It is one of the best communities where we can get a solution for any question that we post in a matter of minutes or hours. Whenever we post a question about any doubt or a bug, someone from the UiPath support team or community replies. Their knowledge is useful for other users who might face the same problem in the future. They have an MVP promotion where if I answer more than 100 questions, they provide us freebies or maybe certification vouchers. That's a good thing that they're doing to grow the community. I'm really enjoying the community members' involvement as well as their support shown during any problems that we face. I have also used Power Automate, and the community support of Power Automate is not that great, but the community of UiPath is very responsive.

It is expensive. Its licensing structure should be improved. They can introduce a license structure where they charge you on a per-minute basis rather than a full upfront payment. 

In UiPath Academy, the certification that they provide at the end of every course can serve as a good motivating factor for somebody who's learning it. That is a good thing, but one of the negatives is that previously, the certification program was free of cost, which helped a lot of developers to become certified developers, but recently, they introduced a paid certification course. I wasn't expecting that move from them. I would like them to go back to their initial certification method which was free of cost.

Sometimes, we do find that the bots misbehave or there are bugs that prevent the bot from executing even when the business cases are completely listed out. It could be that the cloud Orchestrator doesn't send the trigger to the runner systems to start the process because of small internet fluctuation. Sometimes, we find that the processes are killing the execution themselves and going into a halt state without any errors in the program. So, we do see some reliability issues, but these happen once in 20 or 30 instances. They are not on a regular basis. However, when that happens, it does create panic, and we have to immediately rectify it. If they can focus on that, it would be good.

I have been using UiPath for three years.

It is great. We are able to scale at a rate faster than what we had thought of because of the way we are able to develop our processes. UiPath literally automates most of the processes that business users are doing. So far, we haven't had any use cases that cannot be handled with UiPath, which helps in scaling implementation at a faster pace.

We have about a four-member team with analysts as well as developers who work with it, but the developers basically handle all the IT-related tasks. 

We are a manufacturing company, and we have deployed our solutions in almost every department. We have finance, planning, control, human resources, sales, and supply chain. We have 15 to 20 in each of the departments, and they are saving close to three hours individually. Overall, our estimated time savings are upwards of 100,000 hours annually. 

Our current usage of it is 30% to 40%. We still have a lot more potential to tap. We are still on the journey to reach 100% of user involvement where everybody is aware of the process. We are yet to hold the discovery workshops with all the users so that they're aware of the process. Right now, it is limited to a few people within the departments, but its usage will increase with time as we continue to automate processes at this rate.

We use UiPath Academy for the certification or onboarding of new members. When we onboard new members, we tell them to go through the UiPath Academy to get an understanding of the tool. It is free of cost, and it covers all the required modules for becoming an RPA developer. We use it extensively during the initial days as a developer, and over time and with experience, we learn directly from the tool.

They have a very responsive community. Sometimes, within minutes, we get a response to our query. We are quickly able to understand the solution that they provided and implement it. If it is a complicated problem, sometimes, the UiPath moderator from the UiPath company responds to the query and resolves it. If it is not resolved, we can directly contact their customer support. We are enterprise users, and we get quick responses to the queries that we raise. I would rate their support a 9 out of 10.

Positive

In between, we used Power Automate just to see the functionality, but we did not find it as intuitive as UiPath. We gave up on Power Automate, and we are now full-time users of UiPath.

I was around when it was set up. I had personally taken care of the installation. I found it easy and not at all time-consuming. I was done with the process in a couple of hours. In about four or five hours, I was done with the installation and setup of Studio and Orchestrator, listing the licensed accounts, and deployment of the random bots. Everything was completed in a matter of no time. I am not directly related to the IT department. I am just a developer, but I was able to handle it with no external support.

We did it in-house. We only contacted UiPath. They delivered the license keys, and we just keyed in the license keys, and it started working. That's it. Nothing else.

It is lightweight in terms of maintenance. There's no maintenance at all. It automatically handles all the upgrades via the cloud. There are no issues. It requires zero effort from IT.

Overall, you don't have a lot of savings because of expensive licenses. The licenses are quite expensive, and they are not cheap. It saves money but not significantly. However, we are not focusing so much on the monetary benefits. We are focusing more on the quality of output and time savings.

It does reduce the cost of digital transformation, but that happens after a year or two from deployment. Immediate benefits are not evident, but within a period of one to three years, we are able to make a huge amount of savings in terms of time. 

This digital transformation doesn't require expensive or complex application upgrades or IT application support. We didn't have any issues, and we never needed IT to support the UiPath tool. We have been directly using it as it is without making any changes. The impact of this digital transformation on our infrastructure was zero. There were no costs involved. It was used as it is without any changes in the infrastructure.

During the initial two years, we hadn't reached a breakeven point. When the development was going on, we had both costs. On one side, the manual effort was going on, and on the other, there was the licensing cost. So, we didn't have cost savings. After the bot was implemented or after about one and a half years, we were able to receive proper monetary benefits or what we call a breakeven point. So, when we started eliminating human activity, that got converted to cost savings. The accuracy of the process also indirectly improved our customer satisfaction. All in all, we were at a breakeven point, after a two-year period. That would be the general thumb rule for most organizations. So, at an immediate level, we did not receive monetary benefits, but after a period of about two years, we received monetary benefits or savings.

We rely on UiPath Academy for knowledge during the initial days, and it saves a lot of time. We don't have any monetary spending for setting up training because it is available for free. So, we have made some savings. It has saved us time and money, and it has been helpful in getting employees up to speed on the solution.

It is expensive. Every product or component is built separately. All the components have a separate fee. UiPath Studio has a license cost. The cloud has a license cost, and bots have a license cost. These costs are recurring on a yearly basis. So, every product or component has to be licensed for a year, and on expiry, you have to renew it.

Their licensing structure should be improved. The cost of a bot is a lot. It is more expensive as compared to some of the competitors. It is probably $8,000 for an unattended bot. When I did a search on the internet, I found that other vendors offer much better plans. I would like UiPath to introduce some flexibility in the licenses. Instead of a full license, they can maybe introduce a license structure where they charge you on a per-minute basis rather than a full $8,000 upfront payment. If I'm just spending eight hours on the bot, the bot should only be charged for that time. There could be a per-hour rate. A plan like that would be beneficial.

Initially, it will be expensive, and it also won't be as per the initial thoughts that it is going to be a quick solution that saves a lot of time. With time, you can achieve cost savings but not immediately.

We had our eyes on UiPath from the beginning. We did not focus on others.

My advice would be to not use RPA as the only solution. You also have to use other complementing features, such as optical character recognition, so that the overall solution is usable. Just RPA can't solve all the problems.

There should be proper change management to bring awareness about the impact of RPA. A lot of time, people misunderstand and take it in the wrong sense that they might lose their jobs. The fact is that RPA can't automate everything, and skilled people will still be required for doing activities. We can only automate a certain set of manual activities.

I would also advise taking one step at a time. Automate a few solutions, check the user feedback, and then start scaling up rather than immediately scaling up without getting the user feedback.

I would rate UiPath an 8 out of 10. Overall, I have no complaints. Studio, Orchestrator, and all the other tools are top-notch. They are being updated with new features on a daily basis. The product is extremely good, and I have no complaints regarding that, but the license is something they can focus on. They can introduce some innovative plans for procuring the license.

Within my company, I am responsible for a line of business where we roll out automations for various internal stakeholders, and WorkFusion is the platform of choice within my organization.

Approximately 90% of our use cases are RPA-governed use cases. We have one use case now that is a machine learning (ML) based use case. While we are not adverse to using ML within WorkFusion, we are still in the process of identifying or exploring the right use cases within the organization that are the best fit for ML.

A helpful feature is the analytics capability within WorkFusion. The analytics dashboards, i.e., their Tableau dashboards, are really helpful for building a business activity monitoring layer. These are very visible to senior management and stakeholders, who can see and know what is happening within processes. They can see what benefits are getting delivered as processes, either ;daily, weekly, monthly, or quarterly. It is easy for stakeholders or senior management to understand the value for the money that they are spending.

The solution has ELK Stack with Kibana, which is useful and helpful for monitoring all of WorkFusion's infrastructures. This has been really helpful, even though we have just started using it very recently. Previously, if there was an issue, we would log into each of the servers separately and try to fix it. We were introduced to ELK stack two weeks ago, though it has always existed in the product. It has been really amazing. If there are failures, we immediately get notifications. We have been able to integrate it with our enterprise alerting system that creates tickets automatically, which is amazing. We don't have to spend and dedicate hours just to look into the infrastructure to see if there has been a failure or not. We can be reactive instead. 

WorkFusion definitely has a very strong capability to process any document using OCR and machine learning frameworks, particularly from an extraction perspective. We have just used this, deploying one use case using these capabilities. We have been happy with the results. We are getting almost an 80% automation rate. Based on this success, we have started exploring other opportunities within my organization to see if there are other use cases that best fits this AI paradigm.

It is difficult for non-technical users to use WorkFusion. If we really want to build automation, we definitely need Java developers. Their RPA is not for non-technical people. If I look at competing products, like Automation Anywhere, UiPath, Blue Prism, or even Power Automate, a non-technical person can build basic automations and deploy them. Since non-technical people can easily build basic automations, they can be deployed in no time. With WorkFusion, there isn't a similar feature that works well. One needs to write code from scratch to build automation. That is definitely a deterrent if we really want to do quick, dirty automation. I would not rate WorkFusion very high on their no-code, low-code paradigm. In this area, I would definitely expect them to improve.

From an AI engine perspective, they are currently focused on document processing. They should provide the capabilities to integrate ML models. which are just outside document processing. In the world of machine learning, there are several such models available. They should give that capability or provide those capabilities within the platform. That would go a long way.

I have been using WorkFusion for more than six years in various capacities. 

Since we are working primarily on RPA, I find their RPA nodes to be not very stable at times. The nodes may crash at times, and it doesn't send any notification that the nodes have crashed. Maybe the configuration at our end is not right, but this is what we see. From that perspective, we need to continuously monitor those nodes. If we had a better way of monitoring all those available nodes, it would be much better. That is the most fragile part of WorkFusion's infrastructure. Every other component within WorkFusion is very stable.

RPA, as a whole, is an amazing product within WorkFusion, when it comes to deploying at scale.

WorkFusion is the platform of choice for scalability. This is one reason that we are using WorkFusion compared to other competitive products, where the ease of building RPA is much better. If I look at the competitive products from a scalability standpoint, WorkFusion is the platform of choice for us. It is amazing.

We have already 50-plus processes deployed in production. We have around 50 to 70 more processes in our pipeline, and the pipeline is growing.

We have a 20-member team at the company working on WorkFusion.

From a customer support perspective, we expect timeliness of response. If we are raising a ticket, we expect that whoever picked up the ticket will respond in no time. At least, the first response should come in no time. After the initial response, if they require certain logs, then they should take them from us and come back to us within a stipulated time frame. It should have the right recommendation and a solution that should solve the problem.

Their response time is sharp. If we raise a ticket, which is a production-critical ticket, their initial response comes in less than 20 minutes. I haven't seen any tickets open for more than 48 hours before they are getting closed, however complex it may be. Their support team is doing a wonderful job. I would rate them as eight out of 10.

Positive

The initial setup wasn't complex. They definitely expected us to provision several infrastructure components, like servers. However, once the servers were available from the organization, all the ports were open, and the DNS names were set up, then the installation of WorkFusion was smooth. It takes anywhere between a day to two days at max.

It took us almost a month to implement their machine learning models for OCR and Intelligent Document Processing. This wasn't WorkFusion's problem. It was more on the data collection side. Their model requires us to bring in a lot of documents to train the model. It took time from our side to provision those documents with the needed quality. The model doesn't work if you give it 10 documents. The model won't suddenly launch. It doesn't work that way. Once we had given it the right set of data, then the initial out-of-the-box model was done in a month's time.

When we were building our first ML model, we obviously weren't able to achieve the success rate that we were aiming to achieve. We engaged WorkFusion who spent almost a month with us unconditionally, helping us with our complex document structures. The results have been amazing. 

From an engagement standpoint, we are happy with WorkFusion. Their customer success team, delivery team, and sales team are amazing to work with.

We have not yet seen ROI. We have been using this product for two years. We realized that we need to deliver more automation on this platform to get the benefit. That is a function of the use cases that we are picking up. Our success criteria for automation is a reduction in FTEs, which is because we are measuring a break-even from a FTE reduction rate. This is also a function of how we are internally finding out use cases within our organization.

The pricing is high. They should have a better pricing structure. It was not easy for me to try out WorkFusion initially. For example, if I am working on SAP, the licensing may be very expensive. Though, it is fine to use it at scale and pay for the license. We have an enterprise license now, so we are not worried anymore. We are fine with it. 

As a first-time customer who wants to engage with WorkFusion, not working for my company, then I would want to do a PoC. The cost is prohibitive because they will ask me to get infrastructure with six or seven servers. Then, you must buy a WorkFusion license to do a PoC, which is expensive. I would then have to set up a team to build the PoC and see the benefits. That is very prohibitive.

We explored other solutions, like UiPath and Automation Anywhere. We even tried Power Automate. We evaluated them almost two and a half years ago, then we settled with WorkFusion as our platform of choice due to its scaling capabilities.

When it comes to building automation using RPA, it is not very intuitive or user-friendly. We definitely require developers to build automations. Compared to using alternative products to build automations, such as Automation Anywhere or Power Automate, WorkFusion is not easier for building quick and dirty automations. However, if you want to build automation that can be deployed at scale for several transactions within a day, WorkFusion's RPA is amazing. This is one product feature that we found rather interesting.

If you are looking for building small-size, quick and dirty automation and something that you can build from scratch within two to three days to run on each of your user's desktop, then WorkFusion is not the platform of choice. However, if you are looking for building automation which can run at scale, e.g., if you are doing suspect transaction processing in a bank and processing approximately 50,000 transactions in a day, then you want to really ramp that up at scale. In that case, WorkFusion is the platform of choice.

There is room for improvement. I would rate them as six out of 10.

Our use cases are account receivables and account payable. In insurance, our use cases are for vetting beneficiaries, upgrading client portfolios, and updating customer's policies.

The entire tool is valuable because it is an enterprise tool. It is on par with other tools like Automation Anywhere or UiPath with the OCR/ICR facilities, analytics, and the entire package for enterprise-level security. It has the highest level of security as compared to any other tool. 

There are a lot of things coming up, such as Discovery Bot and Process Discovery. A lot of other aspects are also maturing. We have definitely started using it for our clients, and it is maturing as a solution, but it is all about how you integrate the enterprise with all the automation projects, such as your chatbot, Conversational AI, and robotics. How they are integrated and talk to each other creates a very good business case with all three aspects. The next level should be about integrating it with other automation tools as well. It can have integration with other tools or automation projects, such as your chatbot, Conversational AI, and robotics.

I am in robotics for the last seven to eight years, and I have been using Blue Prism for about three to four years.

Stability-wise, it is a good tool. 

It is definitely scalable. The whole market of RPA is definitely scalable, but it again depends on your feasibility and complexity when you study a particular environment and process. It also depends on whether you want to scale in the whole organization or different departments or you want to scale up into different areas. All RPA solutions are on par in terms of scalability. There is no difference between them.

I don't have any direct experience with them. My solution architect used to handle that. I haven't seen many technical issues because if you are going to deploy the solution and if you've studied enough about the organization and the architecture, then something major is not going to come up. Anything minor, such as securities, passwords, or anything else, can be easily managed.

It is completely run by the solution architects, which is the support team from the RPA side. All technical issues definitely involve the IT team, which is your internal architecture support team and the application support team. You need the support team from the architecture and the IT perspective to manage the technical follow-ups.

I have also used UiPath and Automation Anywhere. All these three solutions stand out because they are at the enterprise level. As compared to UiPath and Automation Anywhere, to use Blue Prism, you need developers who have hardcore development experience. It requires quite a bit on the development side. In Blue Prism, you can also code separately and write a script, which adds more value to it.

Blue Prism came too late into the market with its analytics and process discovery features, whereas Automation Anywhere and UiPath were the first ones in the market. Blue Prism is catching up, and it is in the Gartner quadrant, Forrester, etc. It is not lagging far behind.

In Europe, Blue Prism has captured a lot of markets. In the US and Asia, you will see Automation Anywhere and UiPath in the front race. Microsoft, WorkFusion, and Pega are also catching up now.

It is not that complex. It is about how you study an organization and how an organization's architecture runs through. If it is a big organization or an enterprise, then you have to have solution architects from the customer side and also from our side. Solution architects will go and study the customer's architecture. Based on that, we can select which tools are going to be used and how complex it is going to be. It is very much dependent on how the architecture of an organization is because you are going to place the automation tool into that particular organization. Therefore, the initial feasibility and study play a major role in defining the complexity of your design and the entire format or automation.

Initially, the deployment used to take quite long. Now, it is not client-based; it is web-based, and the installation process has been reduced. You just download, and there is no starting a client and all that kind of stuff. It is much easier now than it was before.

In terms of the staff required for the deployment and maintenance of Blue Prism, it depends on what kind of process you're managing. It is not about the tools; it is about the processes. You need to know:

• How complex they are?
• What is the risk factor for these processes?
• How do they impact the entire automation in terms of cost? That is a very important aspect of support because it is in production, and it is going to have a straight impact on the client's revenue.
  

Generally, one person can easily support around five processes if they fall into the simple category. If the processes fall into the complex category, then you need at least two people managing five processes. By complex, I mean when you have applications that are lengthy and the number of steps of the process are more than 500 or so, and you have to monitor the bots very closely. When the bot or the process breaks, the support team needs to take over and act accordingly. 

The roles and responsibilities and the kind of people needed for maintaining the solution vary based on whether you have agile project management or a lot of projects going on. Typically, you will need a solution architect. You would require an analyst only in the first two or three months or whatever is the period for taking care of the process you want to deploy. After that, you don't require the analysts because it only needs to be overseen from the business side, which will begin with SMEs and the production support team.

Any changes or optimization after 90 days, six months, or a year, due to multiple factors such as legislation changes or anything else, have to be done in the process that is robotized. At this stage, the SMEs and the support team play a very vital role. There should definitely be a very good support function because a lot of follow-ups happen in the process and the production in robotics. To manage them, there should be a very good ticketing system in place. The Agile methodology works perfectly fine, and it adds great value to run your process effectively and having an efficient process, but you definitely need the solution architect, application owner, project management team, and the COE team to manage the entire workflow, work items, or backlog items coming into the support function.

It is a bit higher in cost as compared to Automation Anywhere and UiPath. The rate also differs from client to client. Margins are also important when it comes to costing and licensing. There are some additional costs involved besides the standard licensing costs. You have the development team cost, which includes the project manager, development team, analyst, and testers. You also need a team manager. You also have the tools cost, architecture cost, platform cost, and the licensing cost of each bot.

You should suggest a tool only after you study the architecture of an enterprise. Every tool has its own features, upside, and downside. It is not about necessarily going for Blue Prism, Automation Anywhere, or UiPath. For implementing a solution, you definitely need to look in the market to find out what suits you. You can then go for it.  

Blue Prism, Automation Anywhere, or UiPath are on par. There is not much difference in those tools at an enterprise level. The early development cost and the cost of the platform differ in these three tools. There are some clients who say that "We want only Blue Prism. We don't want to look at anything else." In such a scenario, you can definitely go for Blue Prism because it is on par with other competitors. 

The biggest lesson that we have learned from using Blue Prism is that it is important to choose the right processes and the right complexity of the processes. You can't choose highly complex processes where you have around 800,000 steps or very volatile processes where the team is involved in the application layer or at the process level very frequently. These kinds of things could be avoided.

I would rate Blue Prism an eight out of ten because it is a very old tool. It has been around in the market for quite a while, and they have their own learnings. It is a complete package at an enterprise level, where you can have analytics and attended and unattended automation. You can run your scripts, and at an enterprise level, even security aspects are very strong as compared to what is generally required by a client. There is room for improvement. All the new features that are coming up are not being used by many clients, and a lot of learning has to happen.

We have used AA for telecom industry repetitive processes, public retirement firms processes, and financial bank processes. The development has been with local developer desktops, remote VDIs, EC2s, as well as RDP clients of sorts for the individual company preferences.

We are currently building an Azure environment for our A2019 solution internally, with a VDI as our developer/UAT environment. Production will be a separate VDI operating from our main control room instance, as we create Bot Runner agents out of those VDIs for production.

I also deal with many federated lines of business, as they often develop locally and use attended automation as their source of RPA for their lines of business. Others utilize EC2s as their developer and UAT environments and have a separate production import process that keeps the separation of duties intact. Though this is not as productive as that team expected, they use it temporarily until their control room can be migrated and upgraded into A2019 instance as part of another line of business currently building out a sandbox environment for the remainder of 2020.

I am a consultant and our RPA practice on a personal level has improved the efficiency of the payroll, PTO, and timecard submission process within our company. It has taken time-consuming daily mundane tasks off the plates of our talented finance teams and allowed them to dedicate more productive time to working with more thought-heavy and human-centric activities.

Outside of our company, as we work with clientele, several improvement instances have been evident for those. One company had a very tedious process of monitoring an email inbox for several business units to send emails notifying that their daily database update process was completed. This took many hours of monitoring after hours, but in place of that, the RPA bot was able to perform the monitoring for them of that inbox, perform the necessary follow-up or escalation emails needed, and finalize the process once all was complete. This was unattended automation, saving them precious time, improving morale, and accurately informing everyone of the completion. 

Both v11 and A2019 have their strengths but the cloud-based forms with Excel, Microsoft applications, scripts integration, and functionality of A2019 have really stood out above the way v11 can do those things.

It takes far less code to work with A2019 than v11 for the tasks we have in place. In v11, the Metabot features have proven a tremendous help to work with smaller tasks such as file and folder operations, datetime operations, as well as credential management operations.

I'd say the most impactful and heavily or commonly used ability of v11 and A2019 has been the ability to integrate other code types and operations within the process. For example, if someone needed a heavy data comparison process to take place, utilizing AA could work but often takes a good bit of time to work through a large Excel or CSV file. Instead, activating a pre-developed or partner-developed Python script would be my choice because of the speed and efficiency of that language. I currently use this method and it's a major time saver.

In terms of improvement, usually, I have found is not as general as people think. Specifically, as a use case, I am excited to see improvements in having an A2019 cloud control room working and improved on the Lenox environments. A good bit of our finance infrastructure for web-based applications is built in that environment.

There is a good bit of dashboard-type development going on in this type of environment already, so the ability to integrate some of the functionality, as well as keep the synchronicity of everything within it, would be a major benefit.

Having fewer connection instances would make it more secure, more simple to troubleshoot, and possibly more flexible with the type of applications in use.  

I have been using the AA desktop application versions since 2014 (v09-v11), approximately six years, and A2019 for about four months.

I've not had any instability issues but only environmental stability issues that come down to the company that created the environment. 

I find it very scalable, especially with smaller automations, as they can often grow once proven to businesses that the processes work. 

The technical support was very knowledgeable, very easy to understand mostly, their ability to work with us to meet the needs and being patient was a huge help. 

I did not previously use different versions but currently use both. I do know that going forward with v11 sunsetting in 2021, we are migrating and going through a learning phase of A2019 to fully adapt to that application. 

The A2019 setup was straightforward for the applications themselves. The environments in which they are set up is a different story but, that again is on a per-company basis and often lends itself to the expertise of the DevOps teams. Sometimes, those folks are not familiar with RPA or A2019.  

We implemented through AA directly. The availability of their support was very good. Several meetings and work with their folks went well. 

Our ROI has ranged from thousands to hundreds of thousands, depending on the type of process being automated.

I really enjoy the pricing options with Automation Anywhere, as they are able to flex their ability to adapt to the needs of the customer really well. I am sure the specifics for some pricing are on a partner-by-partner basis but providing the ability to scale the licenses, setup, and pricing to the customer is a huge benefit with Automation Anywhere.

Their technical support system and response times directly to a partner are really good.

We did review UiPath, Blue Prism, and Power Automate. 

I'd say, fully go headfirst into learning the A2019 platform and all it can do for a business. There is something for everyone in that platform. Large or small scale automations, migration processes from v11 is already in place and tested, and there is no more need for Metabots because they are now "packages" that can be made or modified by a seasoned developer, and a plethora of other benefits are evident. Just jump in!! 

We are not resellers. We implement Pega Robotic Process Automation.

Definitely, we are satisfied. It's a pretty strong product.

They are leaders in the same industry.

As part of the digital transformation, most organizations are looking for the cloud option, and Pega's cloud presence is pretty much restricted to North America and Europe. There is no cloud presence in the Middle East, India, and other regions. 

Financial customers in these regions are skeptical. They don't want to have their data outside of the geography for multiple reasons, mainly because of the government policies.

Pega should consider putting the focus on other regions such as India and the Middle East. They should also start to think about a data center that is hosted in that particular country.

It is not as easy, to implement bots in Pega with the features it carries as it is in UiPath. For example, implementing a chatbot or your email bot is not that straightforward in Pega.

When we consider OCR, the degree of accuracy is less with Pega when the data is structured or semi-structured. The accuracy of the OCR in UiPath or some other products is much high with structured and semi-structured data. The handwritten structured and semi-structured data recognition accuracy is much lower and is an area that definitely needs to improve.

I manage the practice and have a team that has been working with Pega for 15 years. 

They are not only working with Pega RPA but the entire platform, the entire suite of products that are offered such as RPA, BPM, and CRM.

Pega Robotic Process Automation is a stable product. 

We had experienced performance issues at one point, but it had to do with the infrastructure that was procured by a particular customer. We are seeing larger implementations for financial customers.

Smaller customers have also had performance issues but again, it's because of the infrastructure.

Our customers vary in size. We have small business customers to enterprise customers as well as corporate customers, and customers on a medium scale.

Our experience is predominantly with ServiceNow and Pega.

We work with multiple products. Pega and Appian are two of the key products that we are working with. It is more in the RPA and BPM space.

We also have expertise in UiPath and Automation Anywhere. Our focus is on RPA, BPM with Pega, Appian, UiPath, and Automation Anywhere. 

We also work with other products such as Salesforce, Microsoft Dynamics, and ServiceNow.

What we would recommend would depend on the customer. If it is a high scale enterprise customer who is looking for a core platform implementation, such as card dispute or claims modernization, they should go with Pega.

If a customer is looking for safe automation and easy implementation, they can use Pega, but we would recommend SalesForce because it is pretty straightforward and easy to implement. 

With many customers, we see that they prefer Appian and UiPath to go along with having Pega and Salesforce already because Appian is a product that is straightforward and low-code. Anything that is implemented in Pega is a process that takes at least three to four months as a foundation. Any changes in Pega can take a lot of time, it is not low-code. Appian can be very easily implemented because of its model. If you have an operational implementation in finance operations, legal operations, HR operations, frequent changes, and for agility, we recommend Appian. 

For customers who already have an RPA in place and already have Salesforce and they don't want a CRM but want to process data then we suggest UiPath. UiPath is pretty strong and pure RPA but it does not have a processed platform. If there are tactical solutions required we recommend UiPath.

These are the four main products we recommend to the customers depending on their current needs.

I would like to see pricing for different geography sites. Pega is predominantly US-centric with its pricing. When we see customers in the Middle East, or the APAC region where they are is definitely looking for lower pricing, Pega still more costly because they are still in the US pricing model.

Pega is pretty costly. When you look at the competitors such as SalesForce, Newgen, and multiple other products, they have India-centric pricing, as well as pricing for the Middle East.

We have many customers who are interested in a comparison with many different products. We are evaluating solutions such as Pega RPA, Power Automate, and ServiceNow to create points of view of the differences between the products.

We also want a better understanding of the differences, as we don't have a lot of experience with Power Automate.

To use Pega RPA, you have to be mature. If you are interested in RPA, I would still rank UiPath first. Pega would be the second recommendation and the third would be Appian. 

Salesforce does not have a large RPA at this point. For pure RPA, there is no question that UiPath would be the suggested product.

Pega and Appian have to achieve a certain level of maturity. They are still a part of the product line and are still excellent products similar to OpenSpan, Jira, and also Appian. The integration is not as smooth as expected and it might take a year to get seamless integration.

If I were to rate Pega as a suite, I would rate it a nine out of ten. It has CRM, process implementations, customer experience, and has RPA.

I would rate Pega Robotic Process Automation a seven out of ten.