UiPath Process Mining Reviews

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.

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.

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.

There are multiple use cases. For example, we have automated shipping process for the operations department, including shipping repairs, production line assembly, and line automation using attended robots. 

Using unattended bots, we have done Engineering, finance, accounts receivable, invoicing, invoice validations, and reconciliations. For sales, we have automated order management and order inquiries. We also have proactive monitoring bots for IT. So daily IT jobs are monitored, and the robot automatically takes action by triggering tickets in ServiceNow. 

Every human-dependent task has been automated and is now entirely done by a robot. Still, the people who formerly did the job are part of the process. They check if the robot is doing it right or wrong. And then, we keep on retraining the robot for any new exceptions that come up, so we are fully equipped to handle new scenarios. So this has fostered a culture change within the organization where people are coming up with ways to automate what they were spending several hours a day doing. Once these tasks are automated, they can focus more on the company's strategic initiatives. And that's a win-win for the company as well as the employees.

With UiPath in place, we are moving away from training people on the core applications, which are pretty complex. We've built a headless frontend (Touchless ERP), so it's really easy for anybody to join our company and be productive. A robot handles shipping, repair, and the assembly line instead of a human. Plus, these processes are executed with high accuraccy, removing human error from the equation. That's how we are mitigating a lot of our human-related problems.

Furthermore, the culture that we've built has helped in terms of the principle of retire, recruit or resign. So when someone quits, retires, or we need to recruit, we first determine if we can automate their job functions. The RPA governance team tries to digitize the person's tasks as well as their knowledge and experience in the organization.

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.

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.

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.

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.