Automation Anywhere (AA) Reviews

The use cases I use Automation Anywhere for are for healthcare and revenue.

From the customer's perspective, the biggest benefits are automation of the security and monitoring systems. Our automation consumption has increased considerably since we began using Automation Anywhere. Initially, we were using two or three bots. Now, we have almost 25. In terms of revenue, we can save around $10 million through automation. We still have room to expand, and we're looking to implement more bots, especially IQ bots, but we have some concerns about the accuracy level. 

Automation Anywhere is easy to learn for business users without technical knowledge. For example, I don't have much technical knowledge, but I learned how to use the solution from Automation Anywhere University. It's a user-friendly solution everyone can understand and implement in their business with the help of Automation Anywhere University. The university is more than enough to develop a small bot. It's a comfortable platform. Even the new employees who don't know about automation can gain experience. It only took me about one month to learn the solution. 

The IQ Bots have a lot of room for improvement in terms of accuracy level. We need to improvise a lot. I'm facing another big challenge with one of the use cases. We raised a ticket and did multiple follow-ups with support, but the accuracy still isn't up to the mark. 

We've been exploring FortressIQ and tools that use AI/ML in the past three or four months. We're looking at ways to implement those tools in new areas, but there is a gap because Automation Anywhere University doesn't have much information about them yet. 

We have web recording applications, so we need something like AI to be involved where we can give a verbal command, and the bot can learn to do an automated process. That's the kind of technology or innovation required from the business perspective. If a business consultant can interact with a generative AI or some other advanced AI that can act as a developer, the development cost will come down drastically. 

I have used Automation Anywhere for more than six years.

I rate Automation Anywhere support seven out of 10.

Neutral

I don't deal with purchasing, but I know that Automation Anywhere is more cost-effective than Blue Prism. I won't say the cost is low, but I can say that it's cost-effective. 

I rate Automation Anywhere seven out of 10 overall.

We use Automation Anywhere for web scraping, PDF automation, Excel automation, and API automation.

The most valuable features of Automation Anywhere are Excel, periods, database, and email action.

Automation Anywhere should improve its OCR capabilities.

I would like to see more communication between other technologies. We can directly implement some coding scripts. We already have Python, JavaScript, and VBA, but having some programming languages like Java and dot Net would be great.

I have been using Automation Anywhere for five years.

Automation Anywhere is a stable solution.

Automation Anywhere is a scalable solution.

Our company has different teams, and more than 500 users are using Automation Anywhere in our organization. More than 20 administrators use the solution.

The solution's technical support team gives you different solutions. Some solutions work, but others seem irrelevant. It would help our organization if they gave accurate solutions instead of tentative solutions. They have to improve the speed of their response time.

Positive

The solution's initial setup is easy and not very complex.

We develop the bot, test it on our local environment, and then take it to UAT and production. For simple usage, the solution's deployment may take around 30 days. We implement the solution through an in-house team.

We need only one resource for the solution's deployment. When everything looks good after the testing and peer review, we deploy the bot into production.

Automation Anywhere is easy to learn. I'm also looking at UiPath, but I'm not finding time to explore that RPA tool. Automation Anywhere is a hybrid tool, which we can see in the code view as well as in the flow chart view. On the other hand, UiPath has only flowchart diagrams. UiPath is ruling the RPA industry, but Automation Anywhere is next to UiPath. It would be great if Automation Anywhere had all the capabilities that are present in UiPath.

People who don't have technical experience can learn to use Automation Anywhere quickly because it's easily understandable. They can easily build bots by going through the documentation and videos in Automation Anywhere University. Normally, business users will run the bots and know the functionality, but if they want to learn Automation Anywhere, they can easily learn it in a couple of days.

Currently, we have more than 10 bots in production and more than 20 bots under testing.

If anyone wants to use Automation Anywhere, I won't say it is a 100% perfect automation tool because it depends on the developer and logic. Users may sometimes face hiccups in running end-to-end automation. There are chances of the bot getting hampered while working on some websites.

Automation Anywhere fails to load some objects for some old technologies or websites. It would be helpful if the solution could read every technology and clone every object on the website, even for legacy technologies.

Overall, I rate Automation Anywhere an eight out of ten.

As our business is a mortgage company that provides loans to borrowers, we use Automation Anywhere to automate business processes to help the end users process loans faster. 

The application's response time is slow when using your desktop and trying to process an application. However, when you apply automation, it can work overnight. You don't need to sit at a desk and watch what's happening. It's all automated. 

Prior to implementation, everything was manual. You couldn't inject other software, like APIs. However, with AA, you can bring in any number of tools that connect right into Automation Anywhere. This makes everything move faster. You save a lot of time and cost involved in processing the applications.

The recent update that included code analysis was very helpful. Previously, we had to go line by line. Now, inside the tool, it shows you which lines are hard-coded. 

We've saved a lot of time. How much time we save depends on the process. It's likely at least 50%. Sometimes, it's up to 70%.

We've saved on costs by about 30%.

It's reduced human error. Using Automation Anywhere, we can eliminate a lot of human error by adding exceptions and identifying what's going on quite easily.

For users who don't have technical skills, it's not that complicated. It defines what every command does. It may take a few months to understand the process; however, going through the documentation and using the community versions and forums will make it easier to learn. You can find answers to any aspect you want to understand. 

We did a POC with the automation copilot. It met some of our expectations. For some of the use cases, it will help in the future. 

The copilot's ability to integrate with our day-to-day is fine. It helps employees working with it. It helps them to make things faster. You just have to provide some information, and the background bots will run. It might help increase productivity in the future if we implement it at the enterprise level. Outside of the POC, it looks like it might help with productivity. 

The solution integrates well with other applications and third-party tools. 

There are great tools inside Automation Anywhere. 

With the automation copilot, if I have any internal tool or application and I want to pass on variables, I don't have it. Maybe the team can work on it to make it more efficient to make it work better across all automations.

I've been using the solution for four or more years. I started with version 10.x.

In the past two to three months, the support has gotten far better. Previously, we didn't have a live agent or live support, and now we do. It's great to have. They can respond immediately, and you can continue with what you are doing. You don't have to wait for support at all. 

Positive

We did not previously use a different solution. 

I was involved in the initial deployment. It took a couple of months.

It's relatively easy to upgrade. It depends on the organization. You need to add more variables and define the standards. However, it's not too complex. 

There is some maintenance needed. When you upgrade versions, devices may be disconnected. Sometimes you need to go and check if the device deployment is happening or not, or a deployment may fail. We have about two people handling the maintenance of the solution. You simply need to ensure the bots are deploying on the right schedules and check errors or disconnects. In some cases, you may need to redeploy the bot. The time spent maintaining bots maybe three to four hours per day per person. 

We also explored Microsoft's Power Automate. However, it wasn't as mature or up to an enterprise level at the time. Automation Anywhere had good standards and excellent support, in terms of architecture, design, and user interface, we chose Automation Anywhere. It also has good community support. Previously, we used to raise a ticket. Now, it's amazing - when you ask a question, people respond to it live. 

I'd rate the solution ten out of ten. 

We are a biotechnology company. We are in healthcare. We receive samples, and we need to do some of the entries. We did a PoC through Automation Anywhere. Our objective was to improve accuracy and reduce manpower.

We were able to 100% achieve our objectives. There was an increase in accuracy, and there was also a reduction in manpower. The bot reduced the manpower required. We could reduce nearly 40 members through this project in Automation Anywhere.

Automation Anywhere has helped our organization increase its automation consumption. Earlier, we did not have any automation for the labs to increase accuracy and reduce manpower. We have now achieved the same with Automation Anywhere. We have done about 60% automation. We have used it only for the lab. We are planning to use it for the marketing team, call center, and all other departments.

It improves accuracy and reduces manpower. It is easy to learn. We trained our lab people, and they were able to achieve accuracy with the technical knowledge. 

I would like it to have AI and ML capabilities.

The support can also be better. It can be faster.

I have been working with Automation Anywhere for the past two years.

There is 99.5% stability. It is very stable.

It is scalable. With a robust infrastructure, if the sample size increases, we can scale on an on-demand basis.

We plan to increase its usage. We are planning for the lab expansion. During the lab expansion, we will also increase the licenses.

After the execution, we need to have service and support. Sometimes, there is a lag in the support. We are running labs 24/7, but when we raise a ticket, they are able to call and fix the same only on the next business day. For this reason, we have planned high availability for the RPA bots in the case of any incident. We are managing through that, and we have also highlighted the concern about the service and support. They also plan to work on it.

Neutral

We did not use any other solution.

The initial setup was handled by the business owner and IT. It was done by our partner. It requires technical skills. We need to have a workflow. If we have a clear workflow, we can easily implement the same with the partner.

We provided hands-on training for Automation Anywhere through our partner. In the first phase, it took us at least three months to train the lab operations team and other teams supporting the project. We parallelly created a document for the initial phase. All the people who are now being onboarded use that document. They are able to support the bots without any additional training.

We did the implementation with the help of our partner. They first understood the workflow of the healthcare sector and our architecture. After that, they planned the solution for us. It took them a minimum of one month to understand all those things, and then we did the PoC.

They have also done the integration with the lab software. It took them nearly four to six months for integration and report generation.

In the first year, we got 20% to 30% ROI. In the second or third year, we got the complete amount that we invested. There is also an improvement in the business because of data accuracy.

It is not cheap, but we are able to get an ROI. I would rate it a seven out of ten in terms of pricing.

There are no costs in addition to licensing, but we had to pay our partner for one-time implementation.

We also did a PoC with UiPath and other solutions. We chose Automation Anywhere because we could get significant ROI with Automation Anywhere. Its accuracy and costs were better than others. We have purchased the bot with Orchestrator.

You need to have a good partner to assess the performance and get the best solution. 

Overall, I would rate Automation Anywhere an eight out of ten.

Most of our automation happens on Automation Anywhere. 

While the automation is being done, we use it as a platform. Then, depending on the number of users/ bots needed, we apply  for the corresponding licenses.

The good thing about Automation Anywhere is that any process:

1. Which is repetitive, rule-based, and only requires you to do collect/ edit information on the application frontend can be automated. 

Therefore, Automation Anywhere makes for a good use case. 

2.Wherever the process is  deterministic, with no decisions to be made, you can use it. 

It can automate any processes where 

3. Process is well established, standard, or stable, and there are not many changes in the process. For example, a simple task, such as logging into a website, launching a website and doing systematic steps on the website, can easily be captured to Automation Anywhere.  I see lot of applications, especially in finance and accounting domain.

You might have a lot of steps where you need to either extract data, repeat data, or collect data. All of those processes can be automated through RPA, and especially Automation Anywhere. You can use even automation from the server side, not just websites. The only constraint is that the process should not require human intervention and decision making.

We see the application in the 

# BPO space, 

# Finance and accounting, 

# Health care in terms of claim processing.

E.g. in F&A, if you're doing invoice processing where the entire process is manual, and the analyst has to go through the invoice to determine invoice details, discount on the payment  or a penalty should be levied. In such cases, you can scan this information through an OCR, which is an optical character recognition tool. Then, the rest of the information can be pretty much retrieved by the RPA, which means the RPA will scan the information to classify this information and fill up the  web form. This will be sent to the ERP. This is how the workflow would look like. 

Wherever you can put

# a rule-based system, you can automate all of the processes. In our company, all these processes are manual and you might have 50 to 60 people supporting this process for a mid-size company. You can automate it and reduce the manual effort by almost 40 to 50 percent, depending upon how many techs are enrolled and what is the effort being spent in order to process transaction volumes.

I have been familiar with a couple of projects where this was implemented in cash applications or invoice processing, and they could automate these steps. So, I'm familiar with some of the back-end processes and where they are getting automated.

#1.You don't have to really code anything, as it gives you a good interface (UI), because the components are already preconfigured, you  have to just a drag and drop sequence in terms of how you want to execute the steps. 

#2. There are preconfigured APIs that can be used. E.g., if you want to interact with the mailbox solution, you can have the RPA fetch attachments or email body from the mail solution. You can process attachments via test file or PDF. You can even make Automation Anywhere work around PDF, which is typically not that easy to work with in terms of extracting information.

#3. Metabots/ IQ Bots: One of the features, which we have not used too much, but available, is the MetaBot feature. These preconfigured solutions are easily downloadable, and you can just plug-and-play with a bit of customization, which also means you do not have to keep recreating and can reuse existing functionality. Some of the typical uses are that you could be regularly logging into a website. You can just download a MetaBot, as a useful webpage interface and just run it. All you have to do is maybe replace the name of the website, and in case there is a certain authentication mechanism that is being used, then provide that information.

# 4.There are multiple levels of cloning. In case screen cloning doesn't work, you can do object-based cloning or keystroke-level cloning, depending upon what parameters are available to you and what is the level of information that you capture. You can traverse between object cloning, which is the lowest, most basic form of cloning to a stroke-based cloning, which is like taking care of each keystroke-level which is made by the agent.

#1 Exception Management and Notification: When you are making a code, and there is a happy path and exception management mechanism, it would be nice if there was feedback in terms of whether this is the most appropriate way to code this. I'm not sure how this can be done, but that could be very insightful. It already gives you some screen tips, but this could be done in a better fashion, in case you are creating the workflow and then you believe a beta workflow is available or could be done. If a screen tip could be given to the coder for this sort of workflow, this would be a much better feature for Automation Anywhere. 

# 2 Type of Cloning: I've realized that sometimes when screen-level cloning is a better option, people still use object-based cloning. It would be useful if Automation Anyone could give you tips recommending fewer steps or fewer areas of exception management after you inputted your code. I'm not really sure if this is doable from a technical standpoint.

#3 Debugging: Currently, I believe the debugging of bot is a bit tricky and not very elegant, you might have to keep re-running the script to be able to identify the bug. This can be looked at, as a possible area of improvement. 

#4 Scheduling:There are two modules: the run module and the control center. In terms of scheduling and triggering, they could make it a bit more helpful and provide suggestions, e.g., if you are scheduling it, and there is a conflict, can you resolve it this way. Maybe you can get an upfront alert or something to that effect. 

#5: Stability, Workaround and fall back mechanism: When  bot breaks down, is there any of mechanisms or notifications that can be given? You can possibly choose to notify people, typically in organizations people are pretty much adverse to automation. If something breaks down, they would like to know at the earliest given opportunity that something is breaking down and piling up. They want to be able to resolve it quickly. If the resolution is going to take time, they want to be able to make some specific workaround mechanism kick in. If a bot breaks down, immediately the fallback mechanism should work too. If there could be information in terms of  when the process was out of range and somebody might need to take a look at what has happened. This is because most of these business processes that get automated are critical in nature and might have financial and operational impact. People need to know that there are working fine and not broken down. It can really have an adverse impact if they break down and nobody knows.

#6. Platform Training: My experience has been that if the person who codes the bot is not very well-trained, then they might create unstable bots. So, it's not the platform. It is just how somebody has coded the bots which can bring in lot of instability to them. I recommend that when you are using a coder that the person well-trained and have a good amount of experience already working on bots. They shouldn't be newbie or beginner who comes in to code because that will impact the quality of the code itself.

I have been working with Automation Anywhere for the last three years at two different companies.

# Business process stability: Before robotic automation, the business process itself should be stable and very well-documented. Also, anytime a change is made to the process or subprocess ensure, that the RPA gets updated too. Typically, the entire process of automation might take some time, then by that time, the initial business process might have changed a bit. There could variations in terms of volume or in the process itself.

The most important thing is that before you automate something that you must make sure that it is stable, in its steady state for whatever changes might be upcoming over the next six month to year. Otherwise, you might create a bot, which will go into production,  and fail because the underlying process itself has changed.

# Monitoring and controllership: If there is no changes in the process, bots are pretty much stable and especially, if they have been well coded. In case there have been any changes anywhere in the process or subprocess, the bot can fail. This means you must have a review mechanism with monitoring in place. Once you put a bot into production, you have to monitor it and do regular sanity checks. Otherwise, you could have situations where bots have failed and you might not know, then the process comes to a standstill. In a nutshell monitoring and control is an important aspect of RPA in the run phase.

Scalability is just scaling up the number of bots, so scalability is not a problem. You can increase the number of machines and number of bots to scale up the solution, but it can be sometimes very cost prohibitive. E.g., typically, it requires a dedicated machine, and it can't be a shared environment. This can be a bit of a constraint in terms of the number of machines being used. Otherwise, the solution is completely scalable. In case the process requires more throughput, you can just increase the number of bots which are working. Also, if you are doing this properly, then you have to make sure that there are not multiple bots running at the same time which might be at cross purposes.

I don't interact with the people from Automation Anywhere.

# Procurement of the license is easy, but depending upon what you want to automate and how you automate it that might take time. Setup is not at all difficult. You just take the license and install the application, then it's ready to go. However, in terms of what you're trying to automate, how you're trying to automate it, and the complexity of the problem, the entire automation process can take time.

# Implementation timelines:The time frame to implement depends on the complexities and number of the processes and subprocesses. In a typical process, the coding, testing, and deployment could range from a week to four weeks. However, I have seen it sometimes take longer because you have to continuously keep checking and testing it. Every time the code breaks down, you have to possibly start from the beginning.

My experience has been one to four weeks as the ideal time frame. However, depending on how well the process was understood and documented, there can be certain gaps which would only become evident during the testing phase, not otherwise.

# Resources: Depending on the number of bots that you have to create and the number of the complex processes along with the given budget and timelines that you have in mind, the number of developers range from one to multiple developers. The resources that you really need are developers because they are people who will be coding. Otherwise, from an ownership standpoint, we need some subject-matter expertise for the process. The people who are subject-matter experts will be needed on a part-time basis for the developer to be able to map the process well and be able to create their technical design. Then, you will need a technical master who creates the technical documentation of how it will be coded. The number of technical masters again depends upon the processes and complexity along with the corresponding number of developers.

The deployment team may not be very big. You need just the developers and a design architect, mostly two people. All the other people come and go per the requirement stage of the deployment. There might be people who are there only for consultation. Some people might be there only to approve the solution. Whenever you bring in automation, it has to be reviewed, monitored, and assessed from the organization's standpoint. There might be people who are just doing approvals for this process deployment in case it's a very complex project, and then there is a project manager. Otherwise, sometimes the technical design person doubles up as a project manager too.

Before implementing, you do the assessment of why the organization wants to automate:

Imperatives for Robotic Automation 

• What do they want to automate? 
• What are the key objectives  the organization wants to achieve through robotic automation? 
• Is it a process optimization or is it cost cutting? 
• Who is driving the automation? Is it client-driven or is it vendor-driven? 

Then, you have to build the business case in terms of what you want to try to automate. E.g., how much can actually be automated? That assessment should be done. Even the cost and time of automation versus that benefits that you're going to get out of it needs to be done.

# Process Degeneration: When we start automating, we do a process desegregation. This means whatever processes are under scope that we try and understand the task level, activity level, and precedence details. We make activity diagrams, then try and assess out of all of these which one can be automated. So, if the automation index is pretty high, which means that most of the process can be automated, e.g., up to 80 percent, then it might make a better business case than if the automobility is only say 30 to 40 percent. Then, the cost of automation might be way higher.

# Setting the right expectations with the client: t is also important to set the right expectations with the organization. Are they new to automation or do they some prior experience with automation? Because this helps us set the right expectations in terms of the benefits which can be had. The customer might also want to understand what are the impacts if automation fails and the fallback mechanisms. For example:

• How do you mitigate or remediate the impact of automation failure? 
• What is a criticality of the process you're automating? 
• What are your points of failure and choke points? 
• What are your backup plans if things aren't going well?

The most important thing is the business case as to the cost versus the benefits of automation.

# Legal and Compliance Regulations: Also, are any legal or compliance regulations which are applicable because technically it might be feasible to automate, but legally or from a compliance point of view, it might not be good idea to automate. You might want to still have human intervention in terms of verification and validation.

# Criticality of the process: From a financial impact standpoint, things that require a bit of background investigation might be better kept as a manual process or require a human approval rather than automating it completely.

It all depends on the scale. In one project that I have worked on, we had a savings of $200,000 over a three-year period and a payback period of 6 months. The typical ratio is that one bot will replace two people.

# Licensing: One of the components of key drivers for us to renew our contract is AI or automation. As an organization, we are moving toward smarter operations.

Our pricing a year ago was $600 per license, but I am not sure of our current licensing cost.

# Set up cost: Additional costs will be for the machines and the number of machines that you are using. You can deploy virtually as well as on physical machines. In both the situations, you do need to allocate a certain budget for securing the machines and where the software will be installed and running. 

# Dedicated Machines: The machines cannot be used for anything else, because only a certain bot can run at a certain time. You need to be very particular about your scheduling of running the bots, and while the bot is running nobody can use the machine. You cannot have an agent working on a machine and the bot running in the background. The machine  has to be completely dedicated. 

# Network Bandwidth and Disk Space: Then there are the network bandwidth requirements and  disk space requirements, which are additional costs apart from the licensing and software costs. The developer is also going to charge you for their coding time too.

There are two or three more tools in the market such as Blue Prism, UI Path, but I think the preference was given to Automation Anywhere.

I have only worked with Automation Anywhere.

Understand why you are choosing Automation Anywhere, as the platforms are pretty on the same level except for certain functionalities. Also, in some scenarios, one platform could be better than another. Pick a platform and stick with it.

It is easy to use, but I realize that the effectiveness of the platform depends on the coder and how he is doing the coding. This is my experience, because I have seen that the quality of the automation is as good as the person who is using it. In Automation Anywhere, the skill set of the coder really determines how good the automation is, which is why I am making it a eight (out of 10), not 10 (out of 10). Because while the platform is feature-rich and easy to use, it is the skill of the coder that determines how well the platform is leveraged.

I' am now mainly driving AI at my company. RPA has become a bit secondary in the sense that it is a part of my solution, but most of the time, it is AI-driven. RPA sort of helps in the execution of some of the components of that overall solution. From the organization's standpoint, automation is already a part of all our solutions. E.g., our organization is moving toward automation where almost 30 percent of any deal will be allocated to automation. It will be a ratio of 70:30, where out of $100, a total of $30 dollars will be allocated toward automation and AI.

I did my certification on version 10.4.

I use it to develop for the HR domain, where I am using Oracle PeopleSoft and Salesforce applications. Mostly, I use the object cloning command and Excel operations. 

I work in a banking company. We use Automation Anywhere for global HR payroll operations and payslip-related automation. We have also automated hedge loans and credit card approvals.

We use versions 10.3 and 11. Compared to 10.3, version 11 is good and easier to automate because they introduced more options. You can also automate complex things. They introduced the Control Room feature too. 

It is installed on-premise at our company.

We are using Automation Anywhere for our leave approval process. We used to have three FTEs on the day shift working on this process. Now, we only have one FTE working on the leave approval process. The bot supports everything else in the process. With this bot, we are saving the cost of two FTEs.

• OCR
• Object cloning
• Excel automation
• Reusable
• Scalability
• Code free

Most back-end operations start with Excel. With Automation Anywhere, we can easily automate the CSV in Excel operations. It is integrated with Microsoft Office 365.

The Control Room feature is very good.

We are using Taskbot for attended automation and unattended automation.

From the Bot Store, we can download bots. We can analyze the code. I have downloaded some bots just for coding standard purposes.

I would like more integration with Microsoft Excel. More screenshots that can be integrated with Excel would help our customers too. It is good that Automation Anywhere is now willing to partner with Microsoft.

I need to be able to work on Citrix with the solution. 

I need cloud-based applications. Now, we are manually running the application.

The stability is good.

The scalability is perfect. It is a reusable product.

We have around 200 bots in the entire company. We have allocated separate systems for these bots. We have almost 350 processors that we have automated using the bots. 

I have not used their technical support.

I was not involved in the initial setup.

For the bot creation process, we have a solution architecture team. They will analyze the process and check for feasibility before proceeding to next level. They'll check whether the process can be automated, then prepare a document which will come to me. Then, I'll try to make the SDLC. I'll check whether the process is possible, then we'll go for development. This is the structure:

1. Analysis and feasibility study.
2. Documents preparation.
3. Development.
4. UAT.
5. Deployment.

There's a process requirement. If I get request today, it will take some two to three months to develop and close the incident.

A cost savings example is processing parental leave applications. The volume per day that one FTE can do is eight or nine applications. When using Automation Anywhere, we can do 15 applications per day. Another thing is the improvement in accuracy and reduction in errors.

I like Automation Anywhere better than UiPath because you can review the drag and drop activity. You can also review the code line by line. 

We are not using any other tools as we are partners with Automation Anywhere.

I used to work on UiPath. Automation Anywhere can easily be adopted and learnt. UiPath requires some programming skills and knowledge. Compared to UiPath, Automation Anywhere is easy to learn with its drag and drop commands. In UiPath, the commands were difficult to work with and also architecture. 

Recently, Automation Anywhere introduced its cloud-based Control Room, where you can monitor the bot. Also, Automation Anywhere recently launched a mobile application, which UiPath doesn't have. 

Automation Anywhere has Credential Manager.

You can easily build and deploy the bots with it.

Train more people on a team to understand the tool to build teamwork. Share the development tasks.

Automation Anywhere has plugins for Excel, but we haven't integrated it with Oracle.

I have taken Automation Anywhere University courses. I am certified in Automation Anywhere. I have the Advanced certification and am now doing the Masters certification. The courses were good and helpful for anyone wants to learn about Automation Anywhere. Everything is on the website, e.g., information about installation, configuration, bot development, and bot assessment. 

Automation Anywhere and RPA are not that difficult to learn. It can be learnt and be adopted easily, but you need at minimum practical knowledge. You need to take courses and scenarios. E.g., even if I know about object cloning, I still have to go and work with object cloning to understand the possibilities of object cloning.

We are not using IQ Bot.

Task schedules and runs are good candidates for bot automation.

Currently, we are focusing more on finance, shared services, and interpretive related ideas. For accounting and finance statistic, we have reconciliation specific processes, such as rates uploads into systems. The majority of our development is on SAP and Excel. We are focusing on the financial services area, so our use cases are more related to finance and accounting. These are the use cases developed by the development team.

We are using an on-premise deployment model.

The main agenda for using the RPA is to see how we can get the benefit from reducing human capacity as well as quality output. These two are the major focus for us and what we are achieving.

Timeline-wise, it normally takes a long time to develop. With the AA and RPA concepts and their ready-to-use components, we can deliver a bot within couple of days or within a week time frame based on the use case.

It is easy to use and developer-friendly. The development time is very short. If any system needs to be changed or any functionality needs to be incorporated to any of the technology, it usually will be a long process, like months. With this innovative tool's automation, it is very dynamic, easy to develop, and deliver results quickly. With some of our use cases, we were able to deliver within the time frame of two to three weeks, which is the biggest plus with this tool.

There are good MetaBots available in the Bot Store. We were able to leverage them, as well as established our own reusable components. Considering that, it is easy to add on any software or applications that sits in the system.

We would like to have the Excel plug-in. We have a challenge with unattended bots in development which will be deployed on virtual machines. End users ask, "Why can't we run the bots whenever we need?" The new concept for getting attended bots as well as the Excel plug-in will solve this problem, but we'll wait for 2019 version, which may be a better solution for the business.

More structured and unstructured data collection will be a challenge. While we have the IQ  Bot tool, the success rate at the beginning will be lower. It will be around 20 to 30 percent at the start because you need to train the bot at regular intervals. Of course, this depends on the data. This area could use be improvement.

The marketing strategy is directed toward end users. These leads to confusion in the organization regarding, "Who needs to develop?" Is it IT or the business? This causes friction within the business. Whatever the approach, it is important to show how to get the most benefit out of the tool. There should be a clear roles for IT and the business when using the tool. This way teams and structure can be better established in a business.

For attended automation, there are still questions to be answered: How it is going to maintain the queue? E.g., there are 20 users who want to process their own processes, and when they trigger things, how will the Control Room react? How will bot work distribution happen? These things still need to be looked into, but conceptual-wise, attended automation is really good.

It is confusing: Who needs to develop the bot? The business or IT. At the basic level, the bots can be created. However, once they are moved into production, you have to make sure that the bot is stable and running 24/7 without any issues. Therefore, a lot of care is required due to the amount of controlling mechanisms required.

There are a few problems with deployment and maintenance. When it moves to other systems, the consistency will be somewhat lost.

RPA is decently established and stable as the market is coming up with new features. However, the unstable area is more the IT part of it where a lot of research still needs to be done, especially in the case of artificial intelligence. 

When we run bots, sometimes the systems will go down. Maybe it is because the same functionality worked once or even regularly, but then all of a sudden there will be an issue. It might be a network, latency, or some other issues. Still bot stability needs improvement. These are very rare situations. It works most the time, but one time it will fail and we don't know why.

When I talk about RPAs, it is to say, "Can this problem be solved with RPA?" Scalability-wise, we are in good shape. 

In terms of AI incorporation, this type of scalable incorporation would be benefit everyone. The trend looks like we are going to reach to this point in a good manner.

We were able to put more than 40 bots into production. There are around 20 more in progress. On average, we were able to save around 25,000 hours of manual efforts.

The technical support's response is very good. They gave back solutions quickly. We haven't face many challenges when using the tool. So, we haven't interacted much with the technical team, maybe two or three instances. 

We looked into moving into RPA because it was the trend in the industry.

We do regular acquisitions which leads to a lot of duplicate roles and resources along with similar activities. With this approach, we can streamline our processes and bring uniform processes across the organization. We have been able to establish this. If we use the bots on a lot of manual efforts, it will reduces effort. Going forward, we can use the bots in a better manner by using them for the strategy of delivery and appointments.

We started this journey with a PoC. For three months, we tried understanding the tool and its capabilities. 

The initial setup is not complex for the tool setup. The struggle points are establishing the right mechanisms to identify the candidates and prioritizing things. 

In April, we started the pilot. By July, we had the software as well as the use cases that we needed. We got the licenses in July or August. It took us at least a quarter to establish systems and resources. Then, we started delivering the bots from December 2018. It took six to eight months' time frame from PoC to first bot deployment.

For our bot creation process:

A business user, whoever is doing the manual process currently, will send their request with the details of the use case. Those details will be assessed by IT and the business functional groups to measure what will be the man-hour savings. Also, is it a possible candidate for RPA?Based on those measurements, we identify candidates for RPA, then we determine if they meet the current threshold of 500 hours. If it is more than 500 hours, we consider that a candidate for RPA. Based on that criteria, we identify and prioritize it. Afterward, it comes to the development team for development.

If we had been alone during the initial setup, might not have been that successful. However, when we partnered with the other groups, like consulting firms, then we were able to get the right mechanisms in place within a short time.

We did the deployment in-house.

We have a good dashboard to measure ROI. Whatever investment, licensing, and resource costs together are put in for development and delivery, we are still at an ROI of 250 percent.

To measure ROI, whenever we get a use case from the business when we do an assessment, one of the factor that we capture is the time saving. We try to measure and apply the country rates for the locations where they are doing manual efforts. We measure the time savings by applying the country rates and deriving the hours and value.

The time that it takes to develop and deliver is within two to three weeks.

It has good licensing costs which are average for the market.

We did try out UiPath, which is a good solution. 

We also look at Blue Prism.

We like Automation Anywhere's end user experience. We thought Automation Anywhere was the better solution for developing bots in the long run. It is a centralized tool because of its Control Room. It makes sense to have a solution where everything is in a centralized repository. AA has a more future-looking perspective which will help them in the long run.

We currently are not evaluating any other vendors.

When we saw the tool capabilities, we were so excited. We tried to start using them but we needed to have the right structure and mechanisms in place from the beginning to identify the use case for prioritizing. This plays a major role. 

If you are a big organization with a center of excellence, you need to bring all the people together. The establishment will play a bigger role than just developing and delivering bots. Developing and delivering bots is a very small portion, which is doable by any individual who has a basic technical background. To be successful in your journey, having the right structure upfront will help.

We experimented a little bit with IQ Bots, but we didn't see much use cases in this line currently.

A lot of people interact with RPA and the industry is really excited about it. However, you need to pick the right candidate to be successful in your journey, along with the right framework for the development. This will give you a good output. This is what the business needs to test. Pick a solution based on the organization's needs as well as the right approach. Have an assessment with an approach framework will help.

We have used Automation Anywhere to develop different software bots. We currently use version 10.7 for Windows 10 and we are in process of migrating our version to 11.2. We have automated important processes like creation of purchase orders from attributes that are in a Sharepoint form, and upload of exchange rates in our ERP system from data that is available in websites (central banks). We look at automating processes that are manual, repetitive, and rules based.

AA has allowed the generation of gains in productivity by automating certain processes, moving the hours from FTEs to a software robot, thus creating a digital workforce. The employees who were working on those manual activities are now focusing their time in the critical analysis of their processes. Here a few examples:

• Load of daily exchange rates - 840 hours/year saved
• Creation of purchase orders in Oracle - 1056 hours/year saved
• Processing of bank account statements - 600 hours/year saved

• The user friendly interface enables a quick learning process by any developer, and the ability to interact with virtually any system.
• MetaBots - This is an intelligent component/functionality that makes connection to websites or web forms a breeze. This functionality also works great with our corporate ERP system.
• Technical support - Very quick, efficient, and acknowlegeable. They were able to address all our inquiries very satisfactorily.

• Object cloning - This component seems to be unstable in version 10.7. We have run tests in version 11.2 and they seem to work much better there. During development/test cycles it is common to see object cloning components that were working previously stop full of a sudden. In these cases we usually migrate those components to MetaBots.
• Schedule queue - Scheduling is allowed at intervals of 30 mins. Having this interval reduced to 15 mins would allow better control of taks that run more quickly. The ability to schedule bots to run in different time zones would also be a great addition.
• Control Room - Enabling the ability to customize it would be a great addition. In version 10.7 we need to pay attention to the URL to differentiate between Dev, QA, and Prod. We could also use the function to create our own custom dashboards.
• Give MetaBots the ability to work with objects in applications running on a terminal server. This functionality would be a great help to developers.

Less than one year.

The solution in general is very stable, we haven't found any problem with bots deployed to the production server. As far as development goes, object cloning is a component of the solution that seems to be unstable, as it apparently stops working for no reason. Once deployed to production, everything is very smooth.

Scalability is associated to the number of bot runners purchased. More bot runners can be purchased at any time depending on how the demand grows, and AA offers the ability to process bots in a platform called bot farm.

AA Technical support has been contacted for different reasons, including validation of bot developments. In all scenarios, support was very responsive, efficient, and acknowledgeable, resolving all issues very quickly. Support is available 24x7 with tickets being raised either by their own ticket system or by direct calls. The customer service manager engages with the SPA in the company via phone call every quarter, to check on the customer satisfaction.

We previously used the product Automate. That product had issues working with Java forms, which were extensively used by our ERP solution.

The basic setup was straightforward. Deployment took two months. Our implementation strategy consisted of three servers, one for Dev, one for QA, and one Prod, as well as five bot runners: one for Dev, one for QA, and three for Prod. Finally, we have one administrator and one backup. AA provided the needed support to get the solution up and running quickly and smoothly.

Our company has a long-term partnership with TCS. We are currently using their consulting support, which has been good. TCS is able to engage with top professionals in the market.

We started utilization of the tool with a target of generating productivity, specifically by saving 10,000 hours between August and December 2018, regardless of the number of bots deployed.

Automation Anywhere is costlier than the general competition. I believe that it is consistent with their market share and with the benefits AA has to offer.

We evaluated Automation Anywhere vs Blue Prism and Automation Anywhere vs UiPath.

Automation Anywhere is a great platform. It is the tool that allowed us to bring back to life former plans to create our digital workforce. One suggestion is to go with the most recent release, both for the app and Control Room. Versions after 10.7 are the ones with enhanced functionalities.

We purchased ten developer licenses, all of which are in use now. The developers are responsible for deployment and maintenance along with two administrators. We have a target to be met and it requires extensive use of the product. This target will certainly be increased in 2019.