A Data Analyst‘s Guide to Process Mining Best Practices for the Automotive Industry in 2024

Hey there! As a data analyst and process mining expert, I wanted to share some insights on how automotive manufacturers can transform their business with process mining. In this guide, we‘ll explore the top 6 best practices for effectively applying process mining in the automotive industry in 2024.

But first, what exactly is process mining? Process mining is an analytical approach that utilizes data in IT systems to provide fact-based insights about your business processes. It visually maps out your end-to-end workflows, pinpoints bottlenecks and deviations, and highlights automation opportunities. Leading automotive firms have already embraced process mining to optimize their operations.

Now let‘s get into the key ways you can leverage process mining to drive transformation in automotive manufacturing:

1. Discover Areas to Automate Processes

One major benefit of process mining is identifying processes that can be automated. By mapping out workflows from end to end, you can clearly spot inefficient manual work and repetitive human tasks.

For instance, over 75% of automotive companies use process mining to find back-office processes to automate with RPA bots. This includes high-volume tasks like billing, invoice processing, and importing supplier requests. Automating these mundane tasks with software robots increases efficiency and reduces operating costs.

In one case study, an automaker automated their parts ordering process with RPA after discovering 72% of the process was manual work. This led to a 65% reduction in full-time employees required and $4.2 million annual savings.

Process mining can also pinpoint automation opportunities in shop floor and inventory management processes. Automating inventory management with bots reduces stock-outs, improves turnover, and frees up employees for value-added work.

2. Gain an End-to-End View of Processes

Producing vehicles involves highly complex workflows across numerous departments, systems, and external partners. Process mining provides complete visibility into these end-to-end processes.

By mapping the flow of activities from start to finish, you can identify bottlenecks, waste, variability, and improvement areas. This holistic perspective is impossible to obtain from traditional reporting.

Over 80% of automotive process mining initiatives focus on production processes and supply chain workflows. This end-to-end view helps spot inefficiencies and delays in production sequences or material flows.

For example, one manufacturer used process mining to improve their production line changeover process. By analyzing the actual process flows during changeovers, they identified waste activities. This allowed them to optimize the process and reduce changeover time by nearly 40%.

3. Optimize After-Sales Service Processes

After-sales service is a key touchpoint and revenue source for automotive brands. Process mining helps optimize critical after-sales processes like maintenance, warranty, spare parts management, and customer support.

By comparing actual after-sales processes against ideal models, you can measure process conformance. Deviations from the ideal process likely represent inefficiencies and waste.

Over 50% of automotive companies use process mining to improve maintenance and warranty processes. One European automaker reduced warranty claim processing time by 30% and lowered service costs by analyzing warranty processes to identify and fix bottlenecks.

Another manufacturer optimized their spare parts inventory management by using process mining to model the actual processes and pick ideal stock levels, reducing inventory costs by 18%.

4. Monitor IT Systems to Prevent Disruptions

Vehicles production relies on numerous IT systems like ERP, MES, CAD, and CRM. Process mining lets you continuously monitor and analyze the processes within these systems. This allows you to detect inefficiencies and risks before they disrupt production.

For example, process mining can uncover insufficient database capacity, performance lags, and process errors caused by IT systems. You can then proactively optimize the systems and avoid unplanned downtime.

In one case, a major automaker used process mining to find that 50% of delays in their ERP order process were caused by an interface issue with their parts ordering system. By fixing the interface error, they reduced order delays by 45%. This prevented disruption of their just-in-time inventory system.

5. Redesign Supply Chain and Logistics Processes

Smooth production requires an efficient, lean supply chain. Process mining enables you to redesign supply chain and manufacturing logistics processes based on data-driven insights.

By modeling the actual flow of materials and information, you can reshape workflows to eliminate delays, variability, and deviations. Any broken processes can be redesigned from scratch the optimal way.

Over 35% of automotive process mining initiatives focus on supply chain processes. One manufacturer redesigned their inbound logistics processes using process mining-driven insights. This improved planning and material handling, reducing inbound parts delays by 55%.

6. Develop a Digital Twin of Production Assets

Process mining generates a digital twin of your production system, including lines, machines, and equipment. This virtual model maps the actual throughput, utilization, and performance of your physical assets.

By comparing the digital twin to ideal models, you can precisely identify production bottlenecks. The digital twin also enables predictive maintenance by detecting abnormal asset behavior.

Automotive companies like Volvo, Ford, and Mercedes are using process mining to create digital twins of their plants. One automaker optimized product changeovers by virtually modeling machine efficiency and uptime. This led to a 20% improvement in overall equipment effectiveness (OEE).

As you can see, process mining has immense potential to drive transformation across the automotive value chain. Leading manufacturers have already embraced it and are reaping major benefits. So be sure to incorporate these best practices of process mining into your improvement roadmap as you head into 2023! Let me know if you have any other questions.

Similar Posts