UiPath Process Mining Reviews

We are mainly using UiPath Process Mining for process conformance and process efficiency, with use cases related to supply chain, finance, etc.

UiPath Process Mining impacts our company positively by providing us with a lot of insights. It helps us optimize our shared services operations. We can see where the process bottlenecks are and address them. It's useful for optimization and reducing bottlenecks across the business processes.

UiPath Process Mining helps to free up staff's time for other projects. UiPath Process Mining helps save 10% to 12% of our time.

UiPath Process Mining helps us reduce our total cost of ownership (TCO). It helps us reduce our TCO by approximately 5%. It has potential, but we are not using it fully.

UiPath Process Mining takes two to three months to implement and another two to three months to adopt. We could see its value within four to six months.

UiPath Process Mining comes with quite a few connectors and tools, so its integration capability is decent.

UiPath Process Mining provides excellent end-to-end visibility as long as you have the right data source systems and quality. Many times, we struggle with data quality, but if you have good quality data, it provides you with good end-to-end results.

The process graph stands out as my favorite feature of UiPath Process Mining. We can look at how exactly the processes are navigating, where they are stuck, the task time, etc.

It is excellent in its ability to help us turn raw data into actionable information.

It is meant to provide us with transparency. We do get that benefit from it.

Adoption is the key. The solution can give great results, but many times, we struggle to drive adoption.

We have been using UiPath Process Mining for the last three to four years.

The stability of UiPath Process Mining is pretty good.

It is easy to scale.

They provide good support for UiPath Process Mining.

Positive

We started with ProcessGold, which is the legacy version of UiPath, and we are now using the cloud version.

The initial setup of UiPath Process Mining is straightforward; it is not complex.

Its implementation in a complex organization requires understanding and adapting the business rules. It takes time. It can take two to three months.

We work with service integrator partners for the deployment of UiPath Process Mining. We did not face many challenges with them, so my experience was satisfactory.

The return on investment with UiPath Process Mining depends on the use cases, but if we truly utilize it, within a year or two, we should be able to recover the investment we have put in.

UiPath Process Mining is better priced than Celonis, which we found to be on the costlier side.

We did not evaluate any other options before choosing UiPath Process Mining.

UiPath Process Mining is an excellent tool; if you have the right ERP systems and you have good data quality, then you can apply Process Mining for the best results.

We are doing some POCs with Agenetic Automation, but we don't have any in production yet.

Many of the process bottlenecks we encounter might be due to certain regulatory complications and legacy organizational issues. Some challenges are straightforward, whereas others become human or regulatory dependent.

I would rate UiPath Process Mining a nine out of ten.

The use cases for UiPath Process Mining vary, but it is recommended where companies have a level of maturity in understanding their processes, yet haven't fully mapped them and utilized data. 

We use it to capture data in specific areas where they have good structure in their processes but not necessarily good understanding. We use it to highlight potential improvements and can recommend other technologies to support. We are also examining how it fits with whole business process orchestration aspects to get better mapping and control, while looking at other tools that support broader orchestration. It is a specific tool that can be used at the right time. 

For customers who aren't very mature, it shouldn't be the first implementation - they need to be able to capture the data easily. The types of processes that UiPath Process Mining helps to automate and streamline includes common business processes, especially in logistics and traditional ERP type processes, finance ERP processes, and back-end logistics. For manufacturers or retailers with supply chains, the supply chain processes work quite well, along with certain sales processes. In general, it works across most standard business processes as long as there are structured processes where performance evaluation is desired.

My impressions of the product's ability to help turn raw data into actionable information indicate that we are using it for consulting to show companies where they can make improvements. 

For the right customers, improvements are achievable. It is reasonably successful, but it requires time and energy to set up, utilize, review, work with, make changes, and follow up. It is definitely useful and has the ability to improve performance, but effort must be invested. 

We have found that customers engage with it for a while and then discontinue updating things. It requires continuous work, updating, and ensuring it captures updated processes correctly.

In future releases, better integration towards overall business process orchestration would be beneficial for UiPath Process Mining.

I have been working with UiPath Process Mining for approximately three years, as we adopted it reasonably early when discussing with UiPath three to four years ago and have continued our work since then.

The overall technical support of UiPath Process Mining is rated as a seven. When addressing someone who thinks streamlining processes with automation is not cost-effective, the reality is that when done correctly, it is effective. Today, it is necessary to examine how to use different technologies to streamline processes, whether through AI agents, RPA, or back-end automation. While it won't eliminate large percentages of the workforce as suggested five years ago, it remains important to keep up with competition through process streamlining. However, poor implementation can result in significant expenses without benefits. Mature structured processes are essential - if a company lacks mature processes or strong process owners, it should first focus on gaining process control.

Neutral

The timeframe for configuration, setup, and data collection typically spans several weeks for a project phase. Getting the product operational with initial data can take a few days. However, deriving value, assessing data, and validating correctness requires running it over several weeks with ongoing tuning. The product offers overall simplicity of use and serves as a valuable tool, though it isn't a magical solution. Companies need good process maturity to benefit.

Experience with HR and workforce management processes, particularly seasonal staffing and onboarding, demonstrates that high-volume repetitive tasks are necessary to trust the data. The tool proves most useful with higher volume tasks.

The average number of people needed for deployment within an organization depends on scale and whether the implementation focuses on one business area or complete coverage. We mainly work in specific areas with small teams, sometimes collaborating with existing system integrators. Generally, three to four people are needed for pilots and prototypes rather than full implementations.

Process mining provides better visibility, and if improvements are implemented, the impact on employee efficiency is challenging to measure. 

When assessing total cost of ownership, business cases are built by tying improvements to other aspects. Cost benefits are more easily measured in supply chain efficiencies, reduced claims processing times in insurance, and improved customer experience. For retailers improving their supply chain, there is definite value addition that can be linked to total cost of ownership.

Regarding pricing and overall licensing cost, for existing UiPath customers, it is reasonable. However, for those solely interested in process mining without existing UiPath usage, Celonis is generally recommended. Standard pricing can be quite expensive for non-UiPath customers, but for existing customers, pricing becomes quite competitive.

We maintain a partnership with UiPath, having a strategic support relationship with both Blue Prism and UiPath. The end-to-end visibility offered by process mining dashboards is effective when all data can be captured end-to-end. It is particularly useful when processes span multiple systems. 

The tool definitely increases process transparency, though improvements in orchestration integration would be beneficial. Regarding employee decision-making empowerment, success depends on having good visibility and process owners who are committed to making improvements. While the tool can support visibility and employee empowerment, the right organizational structure must be in place. I would rate UiPath Process Mining as a seven overall.

We use UiPath Process Mining to identify and analyze business processes to understand and pinpoint bottlenecks and inefficiencies. It involves integrating with ERPs and CRMs to analyze event logs and discover areas for improvement in our business processes.

UiPath Process Mining is valuable for its ability to automatically identify bottlenecks and inefficiencies in business processes. It provides root cause analysis, which identifies delays and deviations in processes, visualizes bottlenecks, and assesses their impact with insightful visualizations. It integrates easily with ERP and CRM systems, offering a comprehensive view of business procedures.

One area for improvement is the integration with legacy systems, which can be challenging, especially with older and in-house developed systems that lack good event logs. The setup for process mining is also complex. 

Moreover, UiPath Process Mining is associated with a high cost and a difficult learning curve for those unfamiliar with process mining tools.

We have used the solution for around two or three years.

We find UiPath Process Mining to be generally stable, particularly with the current build. UiPath offers a stable environment with compatibility across versions, providing support for processes developed in both UiPath Studio and StudioX.

UiPath as a whole is scalable and works well for large-scale organizations. 

However, for process mining alone, scalability can be challenging due to the volume of data in larger organizations, receiving a rating of six to seven out of ten.

UiPath provides exceptional customer service and support, primarily due to its active community forum, community.uipath.com, which offers 24/7 support from developers and community members. The technical support is comprehensive and highly rated.

Neutral

Setting up UiPath Process Mining, particularly when integrating with legacy systems, can be quite complex and challenging.

In our deployment, typically two engineers are involved—one working on the server side and another managing the platform side, ensuring a comprehensive setup.

Our return on investment varies depending on the client and is often measured in terms of man-hours saved. For instance, one client in the fintech sector saved about 120 man-hours per month for one team alone.

UiPath Process Mining is positioned on the expensive tier, with enterprise-level plans being costly. Compared to other solutions such as Power Automate, UiPath is significantly more expensive, with its pro plan starting at $420 per month.

We evaluated other solutions in the process mining space, including Solenoid and Minit. While Solenoid offers direct integration with SAP and Oracle, it can be costly for smaller organizations. Minit, on the other hand, is suited for smaller organizations yet struggles with large-scale operations.

The overall rating for UiPath Process Mining is a seven out of ten. Its suitability depends largely on the organization's scale; I recommend it for large organizations able to bear the cost, however, not for smaller ones due to financial constraints.

We used Process Mining for identifying and automating an invoicing process in the banking domain. Process Mining helped in understanding data complexity and security, determining if human validation was required before dispatching credits or debits in SAP, and creating a comprehensive blueprint of the process.

Process Mining provided a comprehensive blueprint of the whole process, which helped us understand security perspectives because we didn't need to maintain logs. We were able to handle data securely, and the end-to-end flow became more transparent. It also helped us analyze if a human presence was needed in the loop for high-complexity tasks.

Process Mining provided us with a detailed view of the workflow through the process graph, showing real-time steps and a potential automation dashboard. These elements allowed us to effectively understand and improve client interactions and manage complex data, especially in the context of banking operations. The dashboard gave real-time insights and historical data for financial processes.

Process Mining could improve in optimization of resources. It should focus on identifying opportunities for automation and resource allocation efficiently. Better options for managing digital footprints, especially for high-security data that can't be shared, would also be beneficial.

I have been working with Process Mining for about four to five years.

I would rate the stability of Process Mining at seven or eight out of ten. There are still opportunities for improvement.

Scalability receives a rating of five. There's significant room for enhancing process integration, data accuracy, and the general applicability of Process Mining.

The tech support from UiPath is good, however, they prioritize support based on the number of licenses purchased by an organization.

Positive

The initial setup for Process mMining is complex and not straightforward for all clients due to the need for specific licenses and the deployment complexities.

The pricing is high, falling around two or three on a scale where one is high and ten is low. UiPath has recently increased licensing costs, reducing the number of available license types, impacting organizations.

I have heard of Blue Prism and Automation Anywhere launching something similar, but I haven't had a chance to explore these solutions.

Overall, I would rate the solution a seven out of ten. While Process Mining is beneficial for complex processes, it might not be necessary for simpler ones unless there are conditions that warrant its use. For an organization with numerous complex projects, Process Mining can be a valuable tool.

Our primary use case is for the accounts payable procure-to-pay process.

We are trying to see the KPIs for the procure-to-pay process. The solution helps us know how long it takes for invoices to get cleared, why a huge backlog of invoices is not being cleared, and what the bottleneck is. We use the solution for areas where automation can help, such as what is the issue with the process, where it is stuck, and where the process needs improvement.

Suppliers need to get paid on time, and we found that the suppliers' payments got delayed in one of the projects. That happened because the invoices were stuck. Some of the invoices were pending for a long time, and a large percentage of invoices were not getting through within the accounts payable time. This caused a lot of dissatisfaction with the suppliers.

We used UiPath Process Mining, identified and removed the bottleneck, automated some of the steps, improved the process, and retrained the employees who were part of the process. As a result, we could pay the suppliers within the agreed-upon accounts payable time. Our suppliers turned out to be happy. We are improving the suppliers' experience and getting their payments on time.

The most valuable feature of UiPath Process Mining is the process graph, which gives you a depiction of the process and lets you know where the issues and delays are occurring. The solution's dashboard has a lot of insights. It shows a bubble diagram in the process chart that shows the bottlenecks.

UiPath Process Mining has a cloud-based version and doesn't have a desktop version like Celonis. Celonis has a desktop version, which is very easy to use. The latest version of UiPath Process Mining has recently integrated task mining. However, Celonis has something called the Execution Management System, which is much more advanced and powerful.

Some of those capabilities can be built into UiPath Process Mining. Data integration should be made easier in UiPath Process Mining.

I have worked with UiPath Process Mining for eighteen months.

UiPath Process Mining is a very stable product. We got very good support, and I am very happy with the solution.

I rate UiPath Process Mining a nine out of ten for scalability.

UiPath Process Mining’s technical support is very good.

Positive

I have previously worked with the Celonis tool.

Pricing-wise, UiPath Process Mining is a winner. Celonis is very expensive. Compared to Celonis, UiPath Process Mining offers value for money. UiPath Process Mining is not very expensive, and that is where it beats Celonis. Celonis has been a market leader with its product for 10 to 12 years. UiPath Process Mining is much, much more affordable than Celonis.

The solution is deployed on UiPath’s Azure cloud in our organization.

If we are doing the procure-to-pay process, UiPath Process Mining is used in only one department. Depending on the use case, you can technically use it across multiple departments. Procure-to-pay and order-to-cash are very low-hanging processes. The solution could be used for many other processes, like manufacturing and PLM. Generally, it is used for procure-to-pay and order-to-cash within the finance accounts payable and accounts receivable departments.

UiPath Process Mining requires minimal maintenance because we have to monitor the process. You first configure the process, make the corrections, and ensure that your corrections give you the desired KPIs. For that, you have to keep monitoring the process and fine-tune the process until you get the right KPIs. So, constant process monitoring is required to ensure everything is functioning.

Choose your process wisely, do the analysis properly, and pick the right process for process mining. Otherwise, process mining will not give you the desired results, and you will blame the process mining technology for not working for you.

Understand the process at length, choose the right process, and then apply UiPath Process Mining. Make sure the requirements for UiPath Process Mining are met for that process before starting it. Don't jump start in a very haphazard manner. Otherwise, you will end up saying that the solution is not good for me.

UiPath Process Mining has helped us to automate and streamline procure-to-pay and order-to-cash processes. The solution is used for SAP systems, ERP systems like Oracle E-Business Suite, PeopleSoft, JD Edwards, and PLM systems where structured log files are available.

It isn't very easy to utilize the solution for streamlining processes because you need to map log files in a particular format. Humans leave a digital footprint when they interact with enterprise systems. Based on details such as user name, date and time stamp, and the screens they navigated, we need to test the log file and convert it into a format.

Once it is in this format, you can forward it to the process mining tool. Then, it will generate insights and a dashboard. I wouldn't call it a very easy deployment. You need to have some SQL, data analysis, and data transformation skills.

Different process graphs are available, giving you an end-to-end 360-degree view of the process. Firstly, it will show the process and then add the different deviations from the process. You can measure many KPIs, like how many days it takes on average to process one invoice, which invoices take the longest time, and which users have the longest pending invoices for a long time.

A lot of such end-to-end dashboards are available. It gives you a very 360-degree view of the entire process. So, you can identify the bottlenecks and then fix them through automation, process improvement, or training.

UiPath Process Mining is a very powerful tool because it is based on the AI ML model. So, the artificial intelligence machine learning pre built models are deployed. Since the models are already pre-tested and trained, they confuse the data we give in a structured format from the log file. Once the data fits the model, the model is able to come up with all the insights and the graph.

UiPath Process Mining has a lot of transparency. An SME may remember only the key points or key paths followed. They may not remember how all the different cases were solved. With the UiPath Process Mining tool, you are backing the graph with data. For example, based on data evidence, you can tell that an invoice was processed 90% of the time through a normal channel, but 10% of the time, it went through a different non-compliant route.

The audit teams can look at that data and understand the reason for the 10% deviation. The audit team can then create some more rules to avoid such deviations. UiPath Process Mining gives you visibility based on which you can follow the complaints and regulatory rules. You can also know where and why deviations happened, fix those, and make corrections to avoid similar deviations in the future.

We can integrate the solution with other systems. UiPath Process Mining needs data from other systems. We can't find the data if it doesn't have data from other systems. You can automate based on automation opportunities shown in the data. When you automate, you can automate the systems involved in the process, such as SAP system, web-based application, Java application, or Windows application.

These different systems through which humans perform tasks can be automated. Automating these systems can realize savings and reduce the time taken to complete the end-to-end cycle for one case.

UiPath Process Mining helps empower the decision-making of the senior management team, product team, and accounts payable team. They can know what's really happening with the process. After making corrections, they can monitor the process and check whether the set KPIs are met.

So, you have a complete picture of what's happening in the process, and it is based on data. It is not based on an SME's memory but on actual data in the last few years. It is evidential information backed up by good-quality data. It is very easy to use the data to correctly predict and proactively fix things.

We were doing a project for the accounts payable team where 40 people were manually checking every invoice to see whether it had a matching purchase order. They had 1,00,000 invoices from different suppliers every month. With automation provided by UiPath Process Mining, we were able to release 35 employees to do some other work.

We repurposed them across different groups to create additional efficiency. Using only five employees and the solution's automation, we were able to generate significant savings every year. Also, the 35 people's time is additional capacity, which can be leveraged for other value-oriented tasks.

Although not entirely, UiPath Process Mining does reduce the total cost of ownership. This is because we are doing a lot of automation, improving the process, and doing everything on one platform tool like UiPath. We are not buying multiple tools from multiple vendors where the cost of licenses is different. Since it's all one platform, the total cost of ownership can be controlled and kept as minimum as possible.

We have seen time to value and return on investment with UiPath Process Mining. You will have a good time to value when you pick the right process and involve the right business stakeholder. Otherwise, you might end up delaying the project, thereby increasing the time for realizing a return on investment.

So, pick the right process, do the analysis properly, and then pick the right process for process mining. Then, you will have a very good chance of realizing the values much faster.

There are different ways you can approach the problem. You can use process reengineering or BPM (business process management) tools. You can use Six Sigma techniques to reduce waste and make the process lean. Before applying automation, do a process analysis, process reengineering, apply Six Sigma methodology, and reduce the waste.

Make the process as lean as possible before applying automation, and then you can magnify the benefits of automation. However, if you directly automate the process without fixing it, your automation will magnify the inefficiencies in the process.

Overall, I rate UiPath Process Mining a nine out of ten.

I use the solution primarily for the BFSI domain, and the processes I implement are used for the banking and finance industries.

The valuable features include analytics and dashboards. I am a solution provider, and I am associated with a solution provider company. Whenever I deliver this product to the client, I receive reviews from the end user. If the end user is happy, it means I am happy.

Maybe adding some competitor analysis would be beneficial, especially if I am using multiple tools. I do not have many statistics there. Let's consider I am using two tools in one organization due to the criticality of the process. At that time, I am mining, and definitely, the cost is a mining factor.

I have used the solution for the last two years.

I have connected with a few SMEs. Even the SMEs are not knowledgeable enough to understand their products thoroughly. When I speak with the product managers, they have a good understanding and can explain each aspect. However, from a technical support standpoint, the SMEs are not confident enough in deciding what should be done. I would rate the customer service six out of ten.

Neutral

I have used Celonis as well.

I would say the initial setup is simple.

I rate the setup cost as four to five. It is a high price for a low rating.

Celonis is one of the solutions we evaluated. SAP was also introduced in collaboration with IBM.

Even Microsoft has also released a similar solution recently. I would say they are just baby-born products. It will take time to reach the level of UiPath. Celonis, SAP, and ABBYY are the alternatives, with ABBYY being the third one we evaluated.

If a company is cost-sensitive, then I do not recommend it. If a company is not cost-sensitive and really wants to adopt these types of technologies, then yes, definitely go for it. 

I rate the product eight out of ten.

I was in the working group of my firm, and we were onboarding UiPath Process Mining as a product. The use cases for the solution were sometimes driven by the management and sometimes by us. Three to four systems were involved in a team's daily tasks. The performance of these systems had been decreasing down the line. They were not performing as expected, causing delays in client deliverables.

We analyzed two of the applications in which we found major issues. We did some groundwork research and shortlisted two in-house applications developed by our firm's team. It was a hard journey to get the logs for those applications. We did some groundwork again to understand how the application is supposed to work and how it was designed.

We considered the efficiency points of UiPath Process Mining, which we can grab quickly. We generated the logs, linked the process graph, and understood three loopholes related to the log-in part and the user's behavior on the first attempt. There were some issues with the accuracy as well. For the login, there is a chain in which the prerequisites should be completed, and then the next task will be processed. However, the person processing the next task is logged in already.

When two people log in, as soon as the mail is ready, they'll process it. You should log in when required because of the load-balancing team. More than 20,000 people use one application. You should keep in mind that not everyone is supposed to log in and click somewhere to stay logged and avoid the time delay. Login will take time, according to human behavior, but that is not supposed to be the ideal behavior. The teams were educated to log in whenever required and sign off. This was one of the behavior changes, which may seem small. However, when more than 1,000 people do it, it would cause a considerable impact.

There were other issues related to the login. Sometimes, we have seen in the process graph that without going to the credential screen, the system would go to the main home page and log out. There was some bug, which was taken as a crucial security breach, and a build change was suggested to the application team. More than 100 instances in the last six months have been observed. After the user enters the username, it should ask for a password, but there is no linkage between them.

Team behavior regarding login was analyzed in the process graph, and then the teams were educated that they should log in when required. The major thing was to understand if there was any security loophole. It has been the case with a few other applications for which we have the logs. We understood that as soon as an application is open, it opens the whole screen sometimes for a few of the applications, which is again a security breach and a very deep concern for someone working in the banking sector.

We observed that the login part, which we had designed with all the security and vigilant behavior taken into consideration, was not performing well, had a loophole, or had some abnormal behavior that needed to be corrected. This is one of the examples where UiPath Process Mining has improved your organization.

The most valuable feature of UiPath Process Mining is the comparison feature. When we got to know that reading OCR was taking time, we altered the lock and uploaded it again by making some adjustments at that stage. If we reduce three to four minutes to five to six seconds on average, what will the graph look like, and what will be the increased overall efficiency? There is a comparison feature that is very, very helpful for people to understand and visualize the impact of a particular task.

For the Instabase solution, we first visualized, made some adjustments for logs, and uploaded it again. Then, the people were able to see that if we did this, the timeline would be met beforehand, and there wouldn't be any delays. Honestly, that was the first thing we did after the security breach related to a login issue. Some other actions were done, but as a solution, this was the first solution that was implemented. It was successfully implemented, and it had a good impact.

UiPath Process Mining is as lightweight a tool as it is new. It's not able to handle a lot of logs in one go at high speed. The solution's speed is fairly good, but it should be further increased to make it more powerful to process large amounts of logs. Logs should be as much as possible. We have taken one year's and sometimes two years' logs to understand the behavior.

We are not here solving small problems because a lot of money is invested. I have observed that handling a large amount of logs slows down the solution's performance. This area is improving because we are now observing a new version of UiPath Process Mining with improved speed. As a developer, I'll be happy to see that happening more quickly, and I am sure the solution is heading there.

I have been using UiPath Process Mining for one year and four to five months.

UiPath Process Mining is quite a stable solution. We have never seen a loss of data, breakage, or hang issues. We have also not seen data suddenly changed or loaded incorrectly. The solution's stability is very, very good. It's a bit slow, but the stability and robustness of data and the visual aid we have to understand things better is very, very good.

Since we have a direct connection to the cloud, UiPath Process Mining is quite easily scalable. We have to follow a very definite set of steps already mentioned by UiPath if we want to scale the solution. It is quite easy to follow those steps.

Around 75 users use UiPath Process Mining in our organization. Out of these 75 users, only 25 are developers, and the rest are SMEs with different views.

The solution's technical support is great. We were sometimes confused because it's a fairly new product with no information on the internet. It was very helpful of UiPath to come into the picture and help us with proper information, training, and guidance, which they have also recently got because it's a new product for them. It has been very fruitful for us to engage with the solution's technical support to understand the solution better.

Positive

I've used other process mining tools to analyze which tool is better to onboard. I analyzed two tools that had their own pros and cons. However, I have always preferred and suggested UiPath Process Mining because it has a link with automation, and I'm from the automation sector. I better understand automation-related capabilities of process mining in UiPath Process Mining.

The solution's deployment was done by COE, which is native to our firm and the presales department of UiPath. I was not actively involved in the deployment but was updated with that call. I'm not deeply into infrastructure, but I was involved in it just for information. Currently, UiPath Process Mining is centralized in our firm.

I have seen a decent return on investment with UiPath Process Mining. There were timelines related to multiple processes, and we have reduced around two to three hours of the timeline. Overall, two to three hours were saved when the processing was done for 21 days a month. That has impacted the overall SLA.

Secondly, although not quantifiable, it has reduced the risk of the application. We have lowered the risk of security breaches by guiding the users and considering the change for the login part. It may not be quantifiable, but the security has been handled.

In my opinion, UiPath Process Mining is a bit overpriced. Maybe I'm saying this because I've never seen the actual end-to-end ROI calculation. I've seen the solution to be fruitful. I've been in discussions with managers willing to have UiPath Process Mining, but they want to see whether it is fruitful.

UiPath Process Mining is a bit overpriced for someone considering the solution without knowing for sure whether it will help them. If its price is lowered, people will consider UiPath Process Mining more.

Before choosing UiPath Process Mining, I evaluated the Celonis and Percipere tools.

UiPath Process Mining does require maintenance because there are a couple of instances where you try to change or delete the environment. Sometimes, you mess up some of the information or steps and need to create a new environment or repository.

The solution requires some maintenance so that its dashboard and workflow list are always clean and have no redundant or unnecessary values and workspaces. It's just a cleaning activity, and the developer should do it in the first go. It is a best practice to have maintenance for UiPath Process Mining. Our firm deployed the solution to have an evaluation every two weeks.

I advise users to get the right people involved, get the right logs analyzed, and then decide as soon as possible. Don't have a timeline of two to three weeks. It should be done quickly so that you can go ahead and have a fruitful result.

Overall, I rate UiPath Process Mining an eight out of ten.

We use it to enhance our business processes by automating certain steps. 
We aimed to save resources, particularly human resources, by significantly reducing manual input.

It facilitated the automation and streamlining of our financial processes.

Using Process Mining for process streamlining wasn't too challenging. We had a UiPath consultant who provided valuable assistance in the initial stages. While there were some difficulties due to the unfamiliarity with certain aspects of the process, we had to uncover specific details. This led to a series of meetings to address these challenges. The communication between our team and the vendor was effective and successful.

The end-to-end visibility provided by the Process Mining dashboards is excellent. We can now precisely track the data entering the system, understand the step-by-step processing, and configure outcomes accordingly. This enables us to customize outcomes based on specific needs. Overall, it has been a positive and valuable experience.

The capability of Process Mining to transform raw data into actionable information has proven highly beneficial. Initially, it allowed us to identify bottlenecks and areas with redundant work, enabling us to enhance speed and efficiency in various steps.

Process Mining's capacity to eliminate bottlenecks across diverse processes precisely indicates the areas that require closer examination and drilling down. For instance, in a recent project, we identified numerous rework and redundant steps. Utilizing Process Mining, specifically NPA, effectively addressed and resolved these issues. This insight was gained through a combination of data mining and process mapping, guiding us to pinpoint where the application of the API would be most beneficial.

The extensive transparency that Process Mining brings to our end-to-end processes signals the commencement of a substantial venture for us. We've recently begun delving into the possibilities of data mining. The journey ahead is filled with excitement, and we foresee gaining numerous advantages from it. We conducted a pilot to assess its effectiveness for our specific needs, and now, having received positive results, we have the green light to integrate it into our workflow seamlessly.

We've experienced tangible benefits, primarily in terms of time savings, which translates into increased efficiency for the team to focus on other activities. The primary advantage lies in the effectiveness of time utilization, leading to cost savings. Post the initial three months of implementation, we began to witness the positive outcomes and benefits.

The capacity of process mining to empower employee decision-making is incredibly valuable. Currently, employees can swiftly access results, enabling them to make real-time decisions with ease. It resulted in a time savings of two to three hours daily, equating to more than a fifty percent reduction.

The automation has proven to be immensely valuable as we now have a running bot handling everything. This has resulted in significant time savings, allowing us to redirect resources from manual data compilation towards more meaningful data analysis activities.

It would be beneficial to improve the cost since it is quite expensive.

I have been working with them for six months.

The system is stable and functions well. Data comparability is ensured, allowing us to analyze results across different periods, be it year-to-year, month-to-month, or any desired timeframe for cost comparison.

I'm quite impressed with the scalability; we are utilizing it on a global scale. We have a substantial user base, with at least three hundred individuals utilizing the information as end users. It encompasses a significant number of people.

The technical support is effective. If there are any issues with functionality, they promptly address and resolve them. Occasionally, we encounter challenges with mapping or similar issues, but overall, the support team efficiently resolves such matters. Overall, I would rate it nine out of ten.

Positive

The initial setup was straightforward, but it later became somewhat more intricate.

In terms of development, it took six months, and if you consider the implementation and resolution of additional issues, it was completed in three months. During the three-month hyper-care period, all outstanding matters were addressed. The deployment process was relatively straightforward since the end-users were already familiar with the system they were working in. They had a good understanding of the data and the desired outcomes, requiring minimal training. We did everything in-house, with a team of five DevOps.

The analysis is centrally managed by a global team, while the end users are distributed worldwide.

Maintenance is overseen by a single engineer who is responsible for its upkeep.

Our return on investment is evident in reduced employee costs, as we no longer require extensive overtime for manual processes.

The pricing is on the higher side. Our maintenance expenses are tied to the frequency of our operations and the level of support we receive. I understand that there is a fixed fee, as well as a variable component based on the volume of our usage.

We evaluated Salome as well, and have been using it both.

For those who believe that streamlining processes with automation is not cost-effective, I would suggest gaining a better understanding of the concept. It's apparent that someone expressing such a view may not be well informed. Engaging in data mining, process analysis, and implementing continuous improvement initiatives typically leads to noticeable cost-effectiveness. In my perspective, this becomes evident as a positive outcome.
Overall, I would rate it nine out of ten.

As a developer, I manage a process mining team and have a development team reporting to me.

We use UiPath Process Mining for over-the-counter, code-to-invoice, and purchase-to-pay processes.

In over-the-counter processing, there is a process called accounts payable. Within accounts payable, there is a process called three-way matching. Three-way matching involves matching three things: the purchase order number, quantity, and price; the goods receipt quantity and price; and the invoice quantity and price. These three things must be matched based on a set of rules. We were able to identify areas where all three-way matching could be automated using process mining. This significantly reduced our lead time by around four to five hours.

We wanted transparency in our development process. Our large organization is spread across 18 different regions, and each region performs the same process in its own way. UiPath Process Mining gives us transparency into how these processes perform. We can also compare each region to the others. The level of transparency is very high with this tool. This helps us to identify and implement best practices. For example, if EMEA performs better than APAC one week, we can replicate its practices in APAC. UiPath Process Mining can help us achieve transparency and identify best practices.

From a development perspective, UiPath provides connectors that allow us to connect to source systems, such as SAP and Salesforce. UiPath Process Mining also provides certain connectors, which are essentially customized API configurations. Once we connect a source system directly to UiPath Process Mining, all of the necessary configuration is automatically imported, so minimal development is required. 

The end-to-end visibility is great. When we connect to UiPath Process Mining, we can use the dashboards to see a process map that is readily available. We have multiple data sets that are actually stored in another room. Once we connect all of the digital footprints to UiPath Process Mining, provided they have the necessary connectors, we can see the complete process map in a list format. We can also immediately see certain analyses that have been automatically generated, such as the lead time, where the lead time is high, which vendors are causing the high lead time, and which customers are using the process. This information is populated automatically when we connect to UiPath Process Mining. This is one of the strengths of UiPath Process Mining. 

UiPath Process Mining can help us turn raw data into actionable information for standard systems. However, it can be difficult to use for systems that require customization, due to the lack of connectors.

It helps us identify and remove bottlenecks in a wide range of processes. Its transparency gives us visibility into where bottlenecks occur in the process, and we can see the lead times for each step. This allows us to immediately focus our efforts on reducing lead times, whether at the auto management stage, factory, warehouse, or last-mile delivery. Once we have a complete process map, we can clearly see where our efforts need to be directed to reduce overall lead times. We can achieve this through automation, following best practices, or training users to follow certain protocols to prevent spills or core leakage in the process. UiPath Process Mining makes all of this possible to some extent.

We have actually achieved hard savings of approximately two million euros this year, exclusively using UiPath Process Mining for the O2C process alone. However, this is just for O2C. There is still a lot of room for improvement. We could actually save much more. The technology itself is great, so there is a lot of potential for savings, both hard savings and soft savings. As of now, we have actually saved two million euros for O2C. For B2B, the approval process is still ongoing, so I cannot provide an update on the numbers. I really don't know the numbers right now, but it will also be close to one million euros. So we can conservatively estimate that we have saved around three million euros using UiPath Process Mining this year alone.

UiPath Process Mining empowers employee decision-making based on each person's role. For example, it gives other managers access to data so they can clearly understand what is going wrong. We also talk to them and provide them with information on the hub feed, allowing them to see which hubs are performing much better than theirs. They have the same data, regardless of their management group or product. We also provide them with the product category, and we bucket products together. For example, we bucket MR machines and CD machines together. We do this by setting criteria. We also see how well the computers are performing and how well we are giving orders at the right time. UiPath Process Mining helps us make informed decisions based on this data.

The savings we predicted of three million euros were primarily in FTEs. We were able to reduce a large number of FTEs using UiPath Process Mining. This is a double-edged sword because we can either free up FTEs for other tasks or remove employees from the organization altogether. In our organization, we have chosen to free up approximately 200 FTEs in the Latin America region. None of these FTEs were terminated; they were instead reassigned to other useful tasks. UiPath Process Mining has therefore been very helpful.

UiPath Process Mining's conformance feature allows us to upload our standard processes and compare how well our actual processes deviate from them. This reveals all of the variants in our processes. UiPath Process Mining also has a feature called tags, which allows us to create our own tags or filters to identify violations in the process. I haven't seen any other process mining tool on the market that does this. Other tools have their own ways of identifying violations, but UiPath's conformance feature with its Tag Analysis Console provides a better user interface. We can immediately click on violations to see all of the instances of those violations in the process.

UiPath Process Mining should focus more on developing connectors to source systems. In fact, I worked on an interesting consulting project for UiPath Process Mining when I was in another service industry. This was when they acquired the process mining tool Process Code in 2019 and rebranded it as Way Beyond Process Mining. They came to us because they wanted to compare their tool to the top five process mining tools on the market. We conducted a consolidation project and presented our findings on the strengths and weaknesses of UiPath Process Mining. UiPath Process Mining has come a long way since then, but I believe there is still room for significant improvement.

UiPath Process Mining has not been adding new API connectors as frequently in recent years. As of now, there are only around ten to twelve source connectors available. In contrast, other market tools, such as Celonis, offer much more extensive connector libraries. This means that UiPath Process Mining can only connect to a limited number of systems, even though it can connect to standard systems like SAP and Salesforce. If we need to connect to a new or less common system, we will need to develop a connector from scratch, which can be time-consuming.

UiPath's UI and assets could be improved. Celonis performs better in terms of UI, even though it uses fewer colors. However, UiPath's process maps are congested. While I understand that organizational reasons may require complex processes, I believe that Celonis provides better visibility in this regard. Therefore, I recommend that UiPath improve its process maps along these lines.

The number of file formats that can be uploaded should be increased. For example, the BPMN file format is very important, but it is not currently supported by UiPath Process Mining. 

Multiple users with different access levels need to use UiPath Process Mining. For example, if I develop a UiPath Process Mining dashboard for the leadership team, they need a certain level of access that allows them to view the dashboard without seeing all of the details. I also need to provide access to end users who are auto managers, but who may not be technically proficient enough to navigate the tool. Therefore, the current number and types of user profiles available in UiPath are not sufficient. We need more flexibility in providing user profiles to meet the needs of different users.

I have been using UiPath Process Mining for four years.

UiPath Process Mining is generally stable. We rarely experience issues. If there is any downtime, we are notified well in advance. Downtime is very rare, perhaps once every six months, which is equivalent to two or three times per year at most.

UiPath Process Mining is scalable.

The technical support is good.

Positive

I use a variety of other process mining tools in my team. If we take a single process and mine it using Celonis Process Mining, which is the current market leader, I always rate Celonis better than UiPath. In 2019, 2020, and 2021, I would have ranked UiPath second, but SAP Signavio Process Intelligence has since surpassed it. According to Gartner reports, a number of other tools have also surpassed UiPath Process Mining, which was previously ranked second. As a result, I believe UiPath will need to step up its game to compete with these rivals.

We have two servers. We have the UiPath Process Mining server deployed for us, and we make sure that we have different instances of it: one for acceptance testing and one for production. We ask the owner of the request to test any development in the acceptance instance before we deploy it to production. We use Azure DevOps to log issues and complaints, and we then take action on them.

The initial deployment was complex, but the complexity was in the process, not in the tool. The tool is good, and of course, it has the standard connectors for the source systems that we already had. This is why our UiPath Process Mining is top-notch. 

From a development perspective, the implementation strategy was to start with a small part of the process and then gradually add more processes. The initial setup of UiPath Process Mining involved a project manager from UiPath, who still has a dedicated team for our organization. UiPath's team consisted of three people, and our team consisted of four or five people. We also needed experts from UiPath who had already connected to our source systems. We all came together to work on the project. Once we received all the necessary approvals, it took us about four months to get the bandwidth we needed. Once we had the bandwidth, we began connecting to the systems one by one and adding the different layers of the process. There are six layers to the process, so we added one layer at a time. We then expanded the implementation to two more processes.

We implemented the solution in-house.

The return on investment of process mining depends on the size of the process. For very large processes with high cardinality and granularity, the ROI can take significantly longer to realize. However, in pilot projects with small processes, the ROI can typically be realized within two to three months. For larger processes, the ROI will depend on the specific size and complexity of the process. In general, it can take one to two years to realize the ROI for large processes.

Licensing costs for UiPath are very reasonable, in my opinion. This is because most companies already have a UiPath ecosystem in place, meaning they have deployed UiPath bots. UiPath offers both process mining and task mining capabilities, which are relevant to any automation team that uses UiPath RPA bots. Compared to other players in the market, UiPath's licensing costs are very reasonable. I would not say that UiPath is very cheap, but it is a good value for the price.

We tried comparing the top five market leaders and ended up choosing UiPath since our automation ecosystem is heavily dependent on UiPath. They provide us with the capability to connect process mining with an automation hub.

I would rate UiPath Process Mining a seven out of ten.

Before automating any processes, they must perform process mining. If a process is inefficient and we try to automate it on top of that inefficiency, our automation will obviously be inefficient as well. We will not realize the return on investment. This is why we need to start with process mining. We can use UiPath Process Mining or any other tool on the market, but we need to understand what our process really is, see it end-to-end, visualize it, and then decide which areas to automate. This is the best way to do it, and if we do it this way, we will definitely realize the value.

For maintenance, we have an agreement with UiPath. We have monthly calls with UiPath, where they discuss new features and initiatives, and we discuss the challenges we faced that month. They also have quarterly calls to share their vision for the quarter and how we can leverage their offerings. There is a maintenance cost associated with this support, but I am not aware of it. I think it is low because the licensing cost is also low. We also have a bandwidth for acceptance and protection services. We own, maintain, and deploy these services on a monthly basis, loading the full data each month. We do all maintenance in-house. However, if we encounter any issues with the cloud-hosted services, we go to the UiPath team for assistance, and they try to resolve the issue as soon as possible.

First, we need to ensure that UiPath has connectors available for all of the source systems. Before starting the process mining exercise with UiPath, we need to sit down with UiPath and understand the process itself. Then, we need to define the process using certain metrics before proceeding with the mining process. Finally, we may not see a good return on investment because there could be multiple challenges in the process. We may need to stay with the process for other reasons. Therefore, we need to decide whether the process is suitable for mining. If the process is suitable, we need to get the potential return on assets from UiPath and verify the process.

Our organization has applied UiPath Process Mining to automate and streamline key business processes such as Purchase to Pay and Sales to Order.

Utilizing Process Mining for streamlining processes is relatively straightforward. While it does require an initial time investment, once you've spent some time with it, you gain a better understanding of the system, making your use of it more effective.

The end-to-end visibility provided by Process Mining through its dashboards is highly beneficial, and I find it very user-friendly. Designing dashboards is a straightforward process, and the clarity they offer is exceptional. While there could be room for improvements, such as expanding the design options, overall, it's easy to create dashboards according to your specific needs.

It aids us in transforming raw data into actionable information.

The disability of Process Mining is significant because, in vast amounts of raw data and numerous events, it adds value by making this data more meaningful. We don't lose valuable insights within the event logs, allowing us to trace and comprehend the data, and enabling informed decision-making. This is a major advantage as it empowers everyone, regardless of technical expertise or educational background, to grasp the insights derived from the data. Process Mining plays a crucial role in democratizing understanding and making it accessible to individuals with varying levels of technical or educational backgrounds.

The overall transparency provided by Process Mining to our end-to-end processes is evident and has proven to be helpful. I can confidently state that the clarity it offers has led to tangible outcomes.

We have integrated Process Mining with various systems, specifically for importing data from SAP. The integration was facilitated through a connector provided by the tool. Additionally, our RPA department is utilizing Process Mining, but at present, there are no integrations with other systems beyond SAP. For instance, we currently lack integration with Salesforce.

I find it quite satisfying as the process of exporting data from SAP using Process Mining has been remarkably easy and efficient. We quickly completed the integration, thanks to the clear and well-designed connectors provided by the tool. Furthermore, the flexibility to add tables from SAP, including those outside the standard set, has been beneficial. This allows us to incorporate specific tables that may be developed within SAP for our analysis.

The empowering ability of Process Mining for employee decision-making is apparent, though our department hasn't fully utilized it due to time constraints. There is potential for improvement, especially through the integration of AI. By leveraging AI capabilities, the tool could go beyond presenting data and diagrams, offering proactive suggestions to guide decision-making.

It has allowed us to allocate our employees' time more efficiently, freeing them up for other tasks or projects. By identifying variations in our processes, we've pinpointed areas where significant time was being spent. Subsequently, we undertook several RPA projects to address these inefficiencies, and the results were notable. In total, we completed around six to eight projects, leading to a reduction in time spent of approximately three FTE hours.

The time to realize value with Process Mining varies, and from my perspective, I recognized its value from the outset of our project. However, for our company, the overall time to derive value took approximately four to six months. This duration includes the development phase, along with the time required for people to understand, wait for results, and manage various aspects of the implementation.

Automating and streamlining processes is cost-effective, considering the adage "time is money." Saving time equates to saving money. With the introduction of robots or automation tools, people realize they have more time for meaningful and impactful tasks. This increased availability can boost motivation, encouraging employees to engage in research, negotiations, or other value-added activities. For instance, in departments like Purchase to Pay, automation can empower employees to focus on strategic aspects rather than repetitive tasks.

One of the most valuable aspects of using UiPath Process Mining for our ERP, specifically SAP, is the comprehensive overview it provides. This tool allows us to visualize the entire process landscape, highlighting various process variations within the project. It proves beneficial for comparing our initial documentation, outlining steps like purchase requisitions, approvals, and process diagrams, with the actual occurrences in the SAP system. The comparison capability enables us to identify critical variations and discrepancies between our designed processes and real-world system executions. It empowers our team to address these variations, ensuring that our processes align with the intended design. Furthermore, the feature of tagging compliance issues has been instrumental for us. We've defined specific tags to flag instances where, for example, a single individual both requests and approves a purchase. Such deviations from the established processes trigger alerts, allowing us to address these issues promptly. In the course of our ERP project, we identified and documented thirty-eight audit topics. Utilizing UiPath Process Mining, we focused on twenty of these topics, implementing necessary design changes and conditions in the ERP system to prevent their recurrence. This has been crucial in enhancing our system's compliance and preventing undesirable scenarios from reoccurring.

The inability of Process Mining to address bottlenecks across a variety of processes suggests potential for improvement. While the tool provides details at the bottom of the page that can be adjusted for more or less granularity, there is room for enhancement. It would be beneficial if the program incorporated AI suggestions, such as recommending decreases in certain approval points. By leveraging advanced AI algorithms, Process Mining tools could potentially offer proactive insights and recommendations for optimizing processes, contributing to further improvement in their capabilities.

While exploring other Process Mining tools, I found that most of them effectively handle processes like Purchase to Pay and Sales Order, but they lack features related to manufacturing or production processes. Specifically, there is a need for connectors that can integrate with production parts. This gap represents a valuable opportunity for improvement in these tools.

Improvements could be made in educating a new support team for enhanced efficiency and effectiveness.

We have been working with it for two years now.

We engaged with tech support during the initiation of the Process Mining project. While occasional queries on specific topics may arise, particularly in complex areas, we generally do not require ongoing assistance. Notably, we faced no issues with data exporting or transferring throughout the process. While the services provided are satisfactory, there is a notable shortage of technicians. I would rate it eight out of ten.

Positive

Although we haven't engaged in projects with other tools, we did conduct a Proof of Concept to compare them with UiPath. These alternative tools demonstrated their competence, but our familiarity with UiPath and its integration into our system provides more advantages at present.

We continuously evaluate other tools, engaging in discussions and negotiations to explore potential benefits and assess if there are compelling reasons to consider alternatives or potentially transition from UiPath in the future.

Overall, I would rate it nine out of ten.