As data availability continues to surge, companies must refine their data collection and analysis methods to enhance decision-making processes. This is where process mining comes into play. By providing a detailed view of business processes, process mining allows companies to leverage their data effectively, uncovering hidden patterns and generating actionable insights. Thus, process mining connects the vast world of data with the practical needs of business decision-making.
So what can you do to make the implementation and execution of process mining run smoothly and successfully? Let’s explore the main steps.
Preparation For Process Mining
While the need and benefits of using process mining become more apparent, the implementation process has its challenges. But with the right strategy and approach companies can successfully implement process mining and reap its benefits. Some preparatory steps companies can take include the following:
Set clear objectives
Before companies begin implementing process mining, they need to set clear goals and KPIs. This involves identifying the processes to be analyzed and determining the desired outcomes. Whether it’s improving operational efficiency, reducing costs, or enhancing compliance, having clear goals will help guide the process and ensure the implementation aligns with the company’s overall objectives.
Manage process complexity
As processes in large organizations get increasingly complex with numerous variations over time, making it difficult to model and analyze, it might be better to start with a phased approach and choose a less complex process. Then, as the teams gain more experience and confidence, gradually tackle more compressed processes with multiple variants or involvement of multiple departments and stakeholders.
Ensure data quality
Process mining relies heavily on data from even logs and various other sources. So if the data is incomplete, inaccurate, or inconsistent, it can lead to misleading results. At the beginning of their process mining initiatives, companies should obtain the necessary permissions and access to the data required for process mining and ensure that their data is accurate and complete.
Manage resistance to change
Employees may be reluctant to accept the changes proposed based on the process mining results. Therefore, assembling the right implementation team comprised of people in diverse roles, armed with the right mix of skills and perspectives can be the key to effective change management and successful implementation.
Choose the right tools
There are numerous tools available on the market, each with its strengths and weaknesses. However, the tool(s) of choice should be able to accommodate the size and complexity of the company’s processes and the volume of data. And most importantly, be aligned with the specific needs and objectives of the company.
Pilot test
Before rolling out process mining throughout the whole company, it is advised that they conduct a pilot test on a small scale. This can help identify potential issues in specific processes and make necessary adjustments before full-scale implementation. A successful pilot test can serve as a proof of concept, demonstrating the value of process mining to stakeholders and helping to secure their buy-in for the larger implementation.
Implementation of Process Mining
Once the preparations are complete, the stage is set for the actual implementation of process mining. This phase is where the real action begins, transforming raw data into valuable insights. The steps involved in this phase are methodical and sequential, each building upon the previous one and shaping the outcome of the process mining initiative. Let us walk you through them.
Data collection and preparation
The first phase of process mining concerns collecting the data from all relevant systems and tools. It can be done in the most basic form of simply exporting .csv files and uploading them to the process mining tool. Or it can be as advanced as real-time data ingestion to continuously sync process data. Next step is to clean and transform the collected data into a format suitable for process mining. This might involve dealing with missing values, ensuring data consistency, and mapping data to the correct process stages. Data preparation work is often considered as the most challenging part of the whole project.
Process discovery and visualization
Now that all relevant data is collected, the real process mining work can begin. Using the data, the tool creates a visual reconstruction of the analyzed process. This visual reconstruction provides a clear and detailed view of the process flow from beginning to end. It shows how tasks move from one stage to another, how long they spend at each stage, and where bottlenecks or delays occur. As well as each of the different ways that tasks move between the stages till they reach the end is called a variant. And the variants that don’t follow a standard or accepted way are called deviations. Process discovery allows companies to explore their process map and see all the different variants and how the process is actually running.
Process analysis and benchmarking
The next step is to analyze the process. One way to do it is by comparing discovered processes with predefined models or rules. During this comparison, companies can identify deviations from the expected process flow, and quantify and prioritize opportunities. Another important part of this stage is process benchmarking. Comparing the process performance against industry standards or best practices can help identify areas where the process is lagging and needs improvement. But it can also help identify areas where the process is outperforming the benchmark. These are areas of strength that you can leverage and build upon. Advanced process mining techniques for deeper analysis can help companies identify or verify the root causes of inefficiencies or bottlenecks, allowing them to implement targeted improvements.
Improvement implementation
This is where the real value of process mining comes into play. It involves taking the insights gained from the analysis and using them to make meaningful changes aligned with the objective. This could involve making small adjustments or completely redesigning the process flow, changing organizational policies, implementing new technologies, or making modifications to the tools and systems used.
Continuous monitoring and improvement
Process mining is not a one-time project but rather an ongoing practice. Companies should establish continuous monitoring of their processes. This will allow them to track the impact of the implemented changes, identify and address issues as they arise, and adapt day-to-day work based on the results, ensuring that processes remain efficient and effective over time.
Implementing process mining can be a game changer for many companies. It provides granular insights into processes, helping them identify and address inefficiencies, bottlenecks, and compliance issues. But it is not a one-off task, but an ongoing commitment to data-driven decision making and continuous improvement. It requires a strategic approach, the right tools, and a commitment to action. By following this key steps, companies can harness the full potential of process mining to drive business success.
