Process mining has been a hot topic over the last years - not only in the corporate world but also in academia. The global market for process mining has reached USD 421.9 million in 2020 and has definitely grown this past year, demonstrating exponential growth.
It can reveal to us one thing - companies nowadays understand the value of being lean and optimized more clearly than ever. Many organizations have long been engaged in the digitalization of their processes and operations. Not only that, most of them have already been initiating large projects and making the steps towards full automation.
Without knowing the status quo, it’s impossible to know what to improve in the first place. Therefore, more and more digital leaders are focusing their efforts on understanding the business processes and finding the optimal ways to see the processes inside their organization. This exploration brings some of them to trying process mining tools, as it is a technology that is getting more traction and interest from people.
What does process mining offer companies?
Process mining software helps companies see how their process data flows within a particular information system. One would be able to get the event log information extracted from an IT system, e.g., SAP, and analyze it further to find if the process is going as “planned.” Through that, process mining can help to get data points to steer a process, measure its performance, and identify the deviations of the process from the ideal one. Overall, it helps to see and analyze the parts of the process within log-producing information systems.
However, what’s next? How to effectively turn process mining into “real” actions that transform the company, increase ROI and make work better as a final result. In other words, how to maximize its benefit?
We’ve found process mining insights, so what?
Well, in this blog, we’ll be discussing exactly that, more precisely - how “process intelligence” can help you and your company make the most use of your process mining efforts in different stages of the digital transformation process. For simplicity, we’ll be discussing it from two different perspectives: 1. before the company has started engaging with process mining activities and 2. when it has already been using it.
1. Before using process mining
Whether to get started with a particular technology/tool/software is always hard and can be a terrible headache for the leadership team. It’s understandable because most such projects require huge investments, yet it remains unclear if the outcomes are as expected.
Workfellow’s process intelligence platform can be the first step for you and your company to prepare for any process mining project before you even engage with it.
How? In two fundamental ways:
- Deciding whether it is even worth getting started with process mining.
- Finding which areas of your business might benefit the most from using process mining.
Process mining is one of the mapping tools, and thus, it is undoubtedly not omnipotent and has its limitations. If most of the work is done outside the log-producing information systems, then it doesn't make sense to use it in the first place because that would result in distorted results.
Process mining gets its data from so-called “event logs” that store the information about a particular action that happens within the IT systems. This data is essential as it is used for later analysis that is based on that data. Unfortunately, not all the systems produce logs; customized and industry-specific software, as well as personal productivity apps don’t have pre-qualifications for process mining. Considering the increasing amount of personalized SaaS software for a certain use or specific teams, this might be found as a significant limitation.
Even when the logs are available, sometimes essential data might be missing from them, resulting in a skewed understanding of the processes. Further understanding of the data, its validation, and cleaning might also be found to be complicated and take a lot of time and require heavy reliance on humans.
Most of the processes are actually done across multiple different apps and platforms. Especially now that many companies are becoming highly modular and work in smaller independent teams, it is essential to capture teamwork as a whole because a considerable part of the work is done collaboratively in shared documents. This makes the use of process mining limited in such areas and thus, makes it ineffective to deploy in some instances.
Make sure that investments pay off.
Workfellow can essentially be your insurance in making sure that investments and efforts do pay off. You first find the issues within the data structures and identify if the work is streamlined within a particular system. Only then decide whether it’s worth deploying process mining as it is a large-scale initiative and requires some upfront development and support from IT and other units.
Workfellow is very easy to get started with, doesn’t require any integrations or development support, and is fully self-service. Most importantly, Workfellow is the first app that provides a digitalization ratio that shows exactly how prepared your company is for process mining initiatives. If most of the processes happen outside business apps and the digitalization ratio is as low as 30%, it doesn’t make sense to get started with process mining. With Workfellow, you can see the first insights in days, and that will surely ease your decision regarding the roll-out of process mining.
2. When using process mining
Numbers say for themselves - the demand for process mining has skyrocketed in the past few years, and that is for a reason. Many companies are implementing process mining and other process/task discovery tools as the first step before rolling out automation technologies such as RPA. Naturally, you would want to get the most out of your investments and start your digitalization journey the best way possible.
Process mining is typically centralized around the core system. This makes process mining a perfect tool to analyze the processes that are mainly done within bigger information systems. For example, some units' work might be completely based on a particular ERP system, making most of the work evolve around the single software. However, if a large portion of the work is done on non-preferred applications/systems, then it might get tricky and deviate the process mining findings from the truth.
When the process mining reveals bottlenecks in certain parts of the business process, for example, deviations in the invoicing process within the Finance & Accounting AP unit, it might not have the complete picture of the process and miss the parts with shared work outside the invoicing system. Workfellow, as a complementary solution, can help you build a holistic view of how the AP team works and collaborates to find the root causes of the problem.
Process mining is a powerful technology to understand where the main blockers may lie within the particular processes. Process intelligence, in turn, can base on that and pinpoint what those problems actually are, quantify them, find the root causes and provide viable solutions on how to fix them. Workfellow helps companies find the biggest problems with the highest value and helps to solve those to achieve operational excellence.
Process mining is part of the larger picture. The end goal for the companies is to have streamlined processes that are optimized all the time. They might use various automation scripts or RPA bots as the next step in the digitalization process. Workfellow can help increase the impact of process mining by capturing the work of those automation tools, e.g., RPA, in real-time. It can analyze and help to understand if those are actually bringing the value or they are not benefiting much and some other alternatives would be needed.
One or the other - great technologies
Process mining and Workfellow’s process intelligence platform are both great technologies whose goal is to make organizations perform better. As we proved, these technologies can work in tandem, supporting and strengthening each other, and building further on each others’ findings.
Process mining is an amazing tool that has been around for over a decade, helping companies steer the large processes in their work. While it’s powerful in certain cases, in some it needs support from the technologies that are more capable of analyzing the shared and teamwork. Process intelligence is exactly what’s needed to capture the parts of the process that can’t be observed through process mining.
That being said, no technology can survive in a vacuum. Different systems and tools need to rely on each other to build truly data-driven organizations and shape the future of work.
