UiPath Process Mining Reviews

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.

We use UiPath Process Mining to determine if there is an opportunity to automate processes using UiPath.

I have used UiPath Process Mining for data capture and documentation, while also performing business analyst tasks. Currently, I serve as an RPA business consultant, covering all phases of RPA. To strengthen my expertise, I seek in-depth knowledge of documentation, table testing, deployment, and different types of case support. My experience encompasses various automation processes I've explored through process mining.

UiPath Process Mining's end-to-end visibility empowers us to document and create a clear process plan.

In process mining, we collect high-level information to characterize processes as either repetitive or involving repetitive data entry, and whether they handle structured or unstructured data. Our focus is on identifying the type of application and the nature of the process, using a high-level overview.

For end-to-end process transparency, the process prioritizes meticulous planning before embarking on any automation initiative, regardless of the specific business process(es) targeted. This extends to source-to-pay, back-office processes, and financial operations. By creating a detailed plan for the current or upcoming year, we can assess the development scope, feasibility of automation, and potential return on investment for each process using UiPath Process Mining. This plan will also include the estimated delivery timeframe for the entire project.

UiPath Process Mining up to certain levels has helped to enhance employee decision-making.

UiPath Process Mining has helped free up 70 percent of our team's time to work on other projects.

UiPath Process Mining helped to reduce our TCO by 30 percent.

Streamlining processes using UiPath Process Mining can be challenging, as it requires initial clarity on various aspects. We need to understand the process scope upfront, including whether UiPath has the automation capabilities to address it effectively. With this transparency, UiPath experts can provide guidance, facilitating a more efficient process mining experience.

We encountered difficulties when trying to integrate UiPath Process Mining with SAP. I would like to have greater integration capabilities.

I would like UiPath Process Mining to utilize more AI in the process.

I have been using UiPath Process Mining for one year.

Before utilizing UiPath Process Mining we did all the process mining manually.

The initial deployment was straightforward. We used a clone repository.

The deployment time depends on the complexity of the process.

We look at the environment and the process being automated and create a process to fit that timeline.

One person is required for the deployment.

The cost of UiPath Process Mining is costly but there are no additional costs in addition to the licensing fee.

I would rate UiPath Process Mining eight out of ten.

Streamlining processes with automation is extremely cost-effective using Uipath. There are other automation tools on the market but Uipath is the leader with many capabilities.

UiPath Process Mining requires maintenance that can be done by one administrator.

Our primary use case is identifying complex reports, such as monthly reports that take more than seven to eight hours to execute, and working with clients for automation. It is particularly used for discovery in other processes in SAP, including utility and entertainment clients.

We are able to identify which processes can be automated more easily, and then work with teams, thus saving a significant amount of time. Process Mining has helped avoid the need to sit with different clients to understand processes as it allows us to see via dashboards where automation is feasible.

The most valuable feature of Process Mining is its ability to highlight the points where automation is required and where decisions are needed. It allows us to clearly identify automation opportunities for complicated processes and displays the output in a simple manner.

The tool could be improved by making integration simpler with most applications. There are challenges with browser and legacy applications that need to be addressed.

I have been working with UiPath Process Mining for around six months.

I would rate the stability of the solution around eight out of ten.

Integration is the biggest scalability issue, especially with older applications. Overall, the scalability rating would be affected by integration challenges.

The customer service and support provided by UiPath is quite good, with some room for improvement. They typically provide the necessary details when a high-priority ticket is raised, but technical support could be improved by having more skilled resources available.

Neutral

There was a separate team within our organization that handled the installation on the server, so I was not directly involved with the deployment.

Process Mining saves time in implementing automation, with an estimated twenty to thirty percent time savings. The overall cost reduction might be around ten percent.

The licensing costs for Process Mining are considered expensive. They are dependent on orchestrator and bot licenses, and even with negotiation, the approximate cost could be around fifty thousand dollars per year.

For organizations with complex applications and a need for extensive automation, Process Mining is a helpful tool to identify areas that can be automated.

I worked on a use case for a pharmaceutical client. Their goal was to understand their current processes and identify automation opportunities to improve their day-to-day operations. I focused on a couple of quality-related processes within their quality stream. This was the primary use case for UiPath Process Mining in this project.

Our client lacked clarity in understanding their processes. They were unsure of the exact workflow and the stakeholders involved. While they had a general idea, they were unfamiliar with specific key performance indicators such as throughput time and the various hand-offs that occurred throughout the process. Therefore, they sought to gain visibility into their day-to-day operations.

Our initial deployment was cloud-based, taking advantage of the POC's flexibility. Given that the data provided was solely in CSV flat files, cloud implementation was feasible. However, the actual live connection was established on-premise due to client skepticism regarding cloud data storage. For live data, most clients still prefer on-premises. However, cloud deployment remains an option for POCs where flat files are provided.

Since the process I worked on was quality control-oriented, it primarily involved a significant number of required approvals. This allowed us to identify which approvals were essential, which were less so, and which could be eliminated. Additionally, the manual nature of the approvals presented an opportunity to streamline the process and establish workflows for approvals. We were also able to automate the assignment of approvals to the appropriate stakeholders, which was previously done manually, sometimes leading to errors or excessive time consumption. By comprehending their business case, we were able to automate this process for them. These are just a few of the outcomes that UiPath Process Mining helped us achieve.

The end-to-end visibility provided by the Uipath Process Mining dashboards is good.

In comparison to other BI tools like Tableau or Power BI, UiPath Process Mining has proven to be more effective in providing business users with the specific information they require. It readily delivers key performance indicators and registries, along with actionable insights into process execution, identifying potential gaps, understanding the various steps involved in the process, and uncovering compliance issues related to time. These valuable insights can be extracted from process planning data, a capability that traditional BI tools lack.

UiPath Process Mining is an excellent tool for identifying process bottlenecks and devising solutions to address them. The tool itself is highly effective, but implementing the proposed solutions to eliminate bottlenecks can be challenging, particularly during migrations. This is often due to a lack of expertise to implement the solutions or a reluctance to embrace change. While providing these solutions is beneficial, I acknowledge that implementing them and realizing their full value can be challenging.

UiPath Process Mining is a transparent tool that provides valuable insights. However, its effectiveness is contingent upon the availability of live data connections. While it is an excellent tool for understanding and optimizing processes, some organizations, particularly those in sensitive industries like banking or pharma, may hesitate to upload their entire data set to a cloud platform for process mining. Therefore, the tool's efficacy hinges on the organization's comfort level with data sharing and access.

Most process mining tools, including UiPath, are versatile in connecting to a variety of source systems. Even if we use SAP as our ERP system and have additional applications running on Oracle or Salesforce CRM, there are numerous integrators available to connect to these source systems. Therefore, connecting to various source systems is not a challenge at all. The available connectors are generally very good. However, connecting to legacy or heritage systems, particularly in the banking industry, may pose some challenges due to their custom environments. For mainstream processes, however, connecting is generally straightforward.

They have been able to automate many of their day-to-day processes, leading to increased efficiency and the introduction of numerous checks and balances. Previously, these issues were undetected within the company. They have also streamlined their processes for clients by identifying areas where approvals were missing or incorrect. Automation and additional checks have replaced many manual tasks, resulting in a significant reduction in processing time. By understanding which areas of their processes were time-consuming, they have been able to implement solutions and improve overall efficiency.

The insights provided by UiPath Process Mining are invaluable. It provides a deep understanding of our operational tasks and processes. When we interact with operations managers or members of the leadership team, they are consistently impressed by the depth of insights we can extract. For example, we can provide detailed profit planning compared to our traditional dashboards. Additionally, while some operations managers may not have access to complete sales or key player data, we can leverage customer data to provide them with more comprehensive insights and KPIs related to their respective offices. This has already assisted them in making informed decisions about aligning their workforce in the backend and enhancing their productivity.

UiPath Process Mining helps to save employees time to spend on other projects. We approach all of our process planning problems with the goal of reducing employee time or helping them identify repetitive tasks that can be easily automated. This has been one of the main use cases we've worked on for most of our processes.

I find the root cause analysis and the reference models to be valuable features of UiPath Process Mining.

UiPath Process Mining is not as user-friendly as Celonis. While Celonis offers a drag-and-drop functionality for building dashboards, UiPath requires some coding expertise. Additionally, the navigation in UiPath Process Mining can be confusing for beginners. This makes the learning curve steeper and the time it takes to build a process mining project longer, especially for those who are just starting. However, once users get the hang of it, the tool becomes easier to use. Nevertheless, for non-technical users or those who have not worked with process mining tools before, the learning curve can be significant. While a technical background helped me pick up the tool quickly, others may find it more challenging.

I have been using UiPath Process Mining for one year.

I would rate the stability of UiPath Process Mining seven out of ten. When we first started using it we experienced minor bugs.

Regarding scalability, we can connect to major SOAR systems like SAP and Oracle, which are quite scalable in our experience. However, we are less certain about the scalability of UiPath Process Mining with other platforms or SOAR systems. That said, the major SOAR systems and major processes, such as CP2P and hire-to-retire, are generally scalable.

I have not had to contact the technical support team of UiPath because I can find all the answers I need in the helpful discussion forums.

Regarding features, Celonis stands out with its extensive array of capabilities, including object-oriented process mining, and its continuous release of new features. UiPath Process Mining excels in reference model generation and root cause analysis. While UiPath Process Mining also offers these features, Celonis' advancements in newer features and innovations place it at the forefront of the process mining landscape. UiPath could benefit from further innovation and enhanced feature development to keep pace with Celonis.

The initial deployment time depends on the size of the data and the dashboards required. It can take about one week, but for a simple data upload and dashboard, it can be done in a couple of days.

UiPath Process Mining pricing is comparable to other tools in the market. I believe Celonis offers a three-month licensing option, but I think it's on par with the other tools. I'm not entirely sure about the field licensing as I primarily work as a partner. I'm not certain about the specific pricing tiers, but I'm confident that it's in line with other market offerings.

I would rate UiPath Process Mining seven out of ten.

If someone believes that streamlining processes and automation are not cost-effective, I would suggest that their approach may not be optimal. Perhaps their implementation strategy was flawed, their chosen processes were not suitable, or their contract was overly expensive. In my experience, I have consistently achieved positive or highly satisfactory outcomes for clients. Therefore, it is likely that they need to refine their approach to address the issue effectively.

Our clients are enterprise-level.

UiPath Process Mining requires ongoing maintenance due to the dynamic nature of data and evolving business requirements. While the initial implementation may involve comprehensive requirements gathering and a robust solution, ongoing maintenance may be necessary to accommodate new data sources, data analysis perspectives, or additional tables and dashboards. However, these maintenance efforts are typically routine updates and dashboard refinements rather than major overhauls.

I would rate the UiPath Community eight out of ten.

I recommend implementing UiPath Process Mining, but it's crucial to have a well-defined strategy in place beforehand. Since it's a relatively new technology, it's often misconstrued as reporting. Therefore, we must carefully select the use cases we pursue and how we present them to the business or clients. Process Mining is distinct from traditional reporting and KPI dashboards, which often leads to confusion. It's essential to clearly articulate the distinction and emphasize that Process Mining delves into the intricacies of their processes, not merely providing KPI data.

UiPath is deployed when there are large numbers of processes.

We currently get no benefits from process mining because our team has been shut down.

We haven't automated processes based on UiPath Process Mining, but we've used it to gain insight into our processes. It also helps us refine and speed up our standard operating procedures. I rate UiPath Process Mining seven out of 10 for transparency. 

Unlike scan.ai, UiPath Process Mining doesn't provide high-level insights. It isn't easy to integrate. They should stop selling and try to bring more value into the system. A person can have only 10 UiPath Process Mining licenses, but nobody uses them, so in hindsight, everybody feels like UiPath is a failed product.

We have used UiPath Process Mining for three years.

I rate UiPath support five out of 10.

Neutral

Celonis and Scan.ai are 1000 percent better than UiPath Process Mining.

Deploying Process Mining is a complex process. We hired a consultant, but they also failed. Four people are needed for maintenance.

UiPath Process Mining is expensive. Celonis is cheaper and offers more value. It's highly effective, but they need to use the right tool in the right way. If everyone buys a Ford but no one drives it, people will feel that Ford isn't a good car. However, if everyone is driving a Honda, it may be a less well-known car, but everyone thinks it's great because they see it on the road. 

I rate UiPath Process Mining five out of 10. Process mining is an excellent tool, but if the support and implementation are weak, no one will appreciate it, or they will say the wrong things about it. UiPath can improve because no one is perfect in this world. If you go to the server, you will find nobody is using UiPath. All the numbers are fuzzy. No case studies are coming in, so nobody is using it.

I used the solution for one of our pharmaceutical clients based in Japan. It was a typical process mining project. They gave us their data, and we fed the data to UiPath. We then prepared dashboards and provided the clients with valuable insights, like the bottleneck for the process and where they could save money.

Our clients were quite shocked at the issues in their processes. They realized that there was a lot of time consumption on approvals. They were very happy with the outcome of the project. They decided to make the changes and observe whether they saw any benefits. If they see any benefits, they will implement it as a live project. It was a typical process mining project.

We use both BasicConnector and AppOne features. We dump our data in the server data and create files in it. In BasicConnector, we do the necessary transformations. In AppOne, we prepare the dashboard based on the best way to represent it.

UiPath has an in-built feature that calculates rework. In most cases, this calculation by UiPath is wrong. UiPath intelligence does not consider that the definition of rework varies for every process and firm. It just considers the normal definition that if a step is repeated twice, it will be a rework. Sometimes, repetition might be necessary for the process.

When we understood the issue was with UiPath intelligence, we deleted it and created our own single-value KPI for rework. The intelligence KPIs offered by the solution are not up to the mark. I don't know if this feature was changed. I am not sure about the current situation.

I have been using the solution for almost a year.

We haven't had any downtime. The product was highly stable, and the data flow was very smooth. It was very fast, too. Even though we were working on virtual machines, the solution was very smooth and fast. I rate its performance a ten out of ten.

The technical support is amazing. If I'm stuck anywhere, I can get the solution within 24 hours. I can totally rely on UiPath's support team.

Positive

We access everything through our Superadmin access. We use the SaaS version. The initial setup is quite easy. It's just a URL. You can contact the vendor and get the credentials. It's very straightforward. It's just like logging into a portal. It's as easy as that. We just have to enter our username and password and start working.

Two business value architects and two data engineers, including me, worked on the solution. All four of us had Superadmin access. We shared the business view link with the clients.

Celonis is a market leader. Celonis does not offer anything outside process mining. If I have identified a bottleneck that can be solved through automation, I cannot do that using Celonis even if I know how to do the automation. I would have to rely on another RPA tool. If I use UiPath, it will be an end-to-end solution for me. If a bottleneck can be solved through automation, I can use UiPath RPA to implement the automation.

The product is very compatible with other UiPath tools. It is the biggest pro. In process mining, the main objective is to determine and identify automation possibilities because we can save money only by doing automation. UiPath RPA is one of the best RPA tools in the market. Getting all these features with one license is beneficial for the people who license the solution and the developers.

I worked as a functional guide and data engineer for our client. The client's team was not sure about what they were lacking. Every process has some bottlenecks, variations, and inefficiencies. The client wanted to understand the flaws in their processes and streamline them. We also helped them understand how they can save money by streamlining the process through automation capabilities.

It's not cheap to implement process mining. We suggested to our clients that they could automate certain processes, but we did not implement them. We only gave them suggestions. We told them about the projected savings they could achieve if they implemented them according to our recommendations. It was a POC. The clients didn't know the concept of process mining. They were just exploring what process mining generally offers and whether it would be wise to implement process mining in all their processes. At the core, it was a typical incident management process. Most of their processes were very closely related to ITSM. They might have other processes like supply chain management and order to cash, but we were not exposed to those processes.

If someone has enough budget, they should choose Celonis because UiPath's process mining is not up to the mark. It's a bit difficult to get data in UiPath. When I used UiPath, there were no connectors to extract data from databases or data warehouses. We were using Databricks. We had to extract data from Databricks in Excel file format manually. Then, we dumped the data into UiPath's server. There are better tools when it comes to process mining. However, if we use UiPath RPA along with UiPath Process Mining, it could be used to its full potential. If someone is not using UiPath RPA, they should choose a different process mining tool.

The end-to-end visibility offered by the Process Mining dashboards was good. Whatever we were trying to build was quite straightforward. If we are comfortable with HTML, then it is quite straightforward. If we are uncomfortable with HTML, we'll face some initial hiccups. However, we will get a hang of it eventually. It won't be a huge roadblock. I have used other process mining and visualization tools. Initially, it was a bit difficult for me.

If we are using UiPath Process Mining in addition to AI Fabric and UiPath RPA, it will deliver the most value. UiPath Process Mining is not a good standalone solution. It is a good solution when we use the whole package. Data visualization tools like Power BI, Tableau, Celonis, and Signavio have drag-and-drop facilities. We just have to mark our dimensions, and the dashboard is complete. In UiPath, we have to do everything by ourselves. We will have to write proper HTML codes. There is a positive aspect to it, too. UiPath allows users to do white labeling. It is a unique feature of the tool. No other product allows users to put a client's logo or change the color scheme.

The ability of the product to remove bottlenecks from a wide range of processes depends on how we mine the processes. It depends on the dashboards we prepare and the analysis we build. It totally depends on the capability of a business value architect. As a data engineer, it doesn't matter to me which tool I'm using. I just do the transformation. It is up to the business value architect and how they derive information from the visualized data to deduce the business cases, values, and bottlenecks. At its core, every data visualization tool is the same.

The overall transparency offered by the solution in our end-to-end processes was great. It was a new experience for us. We also got continuous support from the product's technical team. UiPath generally offers the UiPath Forum. The process mining tool was new last year. Certain questions were not posted on the forum. So we had to read all the documents. Most solutions are available in the documents. We can raise a ticket in the support portal when we face issues. The support team is very helpful. The team helped us with everything, so the project went smoothly.

We didn't integrate the tool with anything. We just dumped the data in the form of flat files. We did all the transformations in SQL Server before dumping the data. Before we feed to our visualization tool, we need to do a basic transformation like handling duplicates. All the other process mining solutions provide users with a space to do the transformation. However, UiPath does not give us that liberty. We must have the final files to start process mining in UiPath. It is a big disadvantage. To overcome this, we must put additional cost for another transformation space like SQL Server.

The project went on for almost two months. There were many hiccups, and the client was new to UiPath Process Mining. In the end, it went smoothly. It took some time because it was a new experience for all of us. The documentation was very helpful. The support team and the people training us in the product were also very helpful. They helped us with all our doubts.

Someone who thinks that streamlining processes with automation is not cost-effective might be someone who doesn't know how processes work. Streamlining processes is the best thing we can do with the processes. Otherwise, we will lose money and won't even notice. We'll just be frustrated and wonder where we are losing the money. We won't earn anything. Every time we receive a project, we focus more on automation because it helps us save money and resources and reduces the risk of human error.

If the process is a standard ERP process, like O2C, AP, AR, or P2P, there are live data connections in UiPath. However, we still cannot do transformations. We must look for a different tool for transformation. People considering using the solution must have some knowledge of HTML and JSON. Certain things do not make sense in UiPath, like the data flow between the backend and frontend. It does not make any sense, and we won't be able to figure it out by looking at the tool. We'll definitely need someone's guidance. If someone is working on traditional process mining tools, UiPath could seem different to them.

All in all, it is a great solution. Every product has some drawbacks. If someone is looking for a full end-to-end solution that includes automation, they should use UiPath. Otherwise, there are better tools in the market.

Overall, I rate the solution an eight and a half out of ten.