Process Mining is an innovative and proven technology that is improving business operations and customer experience outcomes. Consider it as a vital component of big data analytics, which essentially deals with collecting, organizing, and analyzing large amounts of structured data.
It helps make well-informed decisions that can impact business growth and profit. Process mining is heavily backed by artificial intelligence and machine learning, which assist in effectively optimizing business processes.
Process mining comes in handy when companies with complex organizations and processes need to evaluate and assess each task/process in the operational workflow to ensure maximum efficiency.
Applying process mining technology for your business can help you:
In addition to the points mentioned above, process mining also helps clearly point out triggers of processes that aren’t performing as per plan, reasons for compliance violations, if any, and monitoring performance.
How process mining is beneficial to manufacturing?
Manufacturing involves large-scale production processes which invariably require some level of planning, management, communication, implementation, division of work, and monitoring. Earlier, management consultants and the operations team helped in improving core operations and collecting data. This unfortunately comes at a higher cost of time, effort, and money.
An easier, more affordable, and constructive approach, in that case, would be process mining. Here are a few advantages:
Expectation Vs. Reality
Process mining helps evaluate tasks in real-time by making use of the digital footprints left behind by IT systems. This provides a sense of transparency, as well as clarity. Actual results often deviate from the business plan as a result of unseen process issues. Process mining can help identify these differences and align your plan with the respective implementation strategy.
Reduced Cost of Inventory
It assists in locating and eliminating gaps or redundancies in your manufacturing environment, as well as lowering overhead costs by optimizing your procurement process.
Pin-point Hidden Inefficiencies
There is a multitude of things that can be lost in translation when a large-scale production process takes place. All the managerial functions of a business come into play then, but since human error is almost unavoidable, process mining ensures thorough tracking of every step involved in the process with the help of performance tracking software.
Faults and/or inefficiencies in any of these areas can be quickly recognized and corrected by revamping processes such as Purchase to Pay, Order to Cash, Production, Logistics, Accounts Payable, or Accounts Receivable utilizing Process Mining.
Reduces or Eliminates Delays
Process mining helps bring about an improvement in responsiveness by offering modern-day performance intelligence spread over various manufacturing locations.
Often, strategized plans don’t pan out as planned. Duplication of work or redundancy of tasks is enough to cause a delay in the entire process. Process mining helps pick up these delays whilst offering constructive solutions.
Smooth & Organized Flow of Work
Process intelligence can be considered the be-all and end-all of digital business transformation. It constitutes aspects of business intelligence and process mining, which help in the collection and optimization of relevant data which can further improve manufacturing processes.
By clearly laying out the tasks involved, accountable representatives carrying out the tasks, time of delivery, and plan of execution, everyone has a better understanding of client requirements, possible obstacles, and deviations. This level of transparency gives better direction to the plan and helps attain an organized flow of information.
Process Mining helps arrive at efficient & effective solutions for such issues! It also plays a vital role for fast-growing manufacturing companies as it can lower inventory costs, identify problems in the production chain, improve on-time delivery efficacy, optimize logistics between production sites, and reduce scrapped inventory due to process failures.