How to Use ERP Data for Root Cause Analysis in Production Issues?

Small perturbations in the manufacturing can be propagated all the way through production and impact the delivery times, quality of the product being manufactured and customer satisfaction.

Be it higher scraps, deadlines being missed, or machine breakdowns when you are not expecting them, once you have eradicated the problem at the top level, at best, what is achieved is some respite.

A long-term change needs the cause of the problem to be discovered and treated. This is where root cause analysis becomes essential. With strong ERP systems available, manufacturers should be able to leave guesswork behind and move towards superior levels of efficiency with data-hosted decisions.

Manufacturing ERP also centralises the data of all aspects of the production process, such as materials, labour, machine operations, quality inspection and scheduling.

Such end-to-end visibility will allow the manufacturers to trace the cause of the production difficulty back to the source of the problem based on facts and not assumptions.

As a result of the ERP data being available in real time, root causes may be investigated quickly, more precisely, and more intensively across departments. So, how to use ERP Data for Root Cause Analysis, let’s understand here.

How to Use ERP Data for Root Cause Analysis?

Using ERP (Enterprise Resource Planning) data for root cause analysis involves systematically examining integrated business information, such as inventory levels, production logs, sales records, and quality control data, to identify the underlying causes of operational issues.

By leveraging real-time and historical data across departments, organisations can detect patterns, anomalies, and bottlenecks that may not be immediately visible.

Tools like dashboards, data visualisation, and automated reporting within the ERP system help decision-makers trace problems back to their source, whether it’s a supplier delay, process inefficiency, or data entry error, enabling faster, evidence-based corrective actions. What more can help, let’s see.

Understanding the value of accurate production records

Root cause analysis relies on the possession of credible time-stamped data of what went on in production. This type of detail is a challenge to accumulate in a paper type or manually operated environment.

It is commonplace that handwritten notes or disjointed spreadsheets will not have the precision required to infer a conclusion, particularly when a production line is either complicated or in continuous operation.

This is solved through manufacturing ERP systems because they automatically capture the real-time data from the computer, or the operator can also feed data into the computer software.

All the production processes, including issuing materials, the time that machines are used, and checking the product quality, are recorded and kept in the ERP framework.

It is a good recordkeeping system that gives a detailed account of what has happened that could be referred to when a problem arises. Consequently, teams are able to compare the chronology of events that might have resulted in a problem and explore factors that led to the problem.

Tracking production issues to specific work orders

Among the most potent functionalities of manufacturing ERP, the ability to connect problems with the particular work orders is included. Once a quality concern or a process failure has been detected, a work order that corresponds to it is the point to start in investigation.

ERP systems keep records that identify the machines, materials, operators and processes involved in that particular order, and because of this, there is a clear area to investigate.

The manufacturers will not have to sort past a clutter of information since they can isolate data under a particular work order. In the case of always making parts off-tolerance with one shift, or having defects only when a certain lot of material is being used, these conditions will be manifested in the work order information related to the parts.

This narrow vision speeds up the identification of the root causes and also assists teams in rapidly testing correction measures.

Analysing trends using ERP reports and dashboards

Although not all production problems are isolated, a good number of them occur due to repetitive actions which cumulatively occur as time goes by. To identify these patterns, the manufacturing ERP systems offer several analytics tools such as custom dashboards and historical reporting.

These tools enable the teams to act as benchmarks to compare the rate of defects, equipment downtimes or operator performance between time windows, shifts or products.

As one example, say that a particular machine is seeing more downtime on Mondays, downtown logs of the ERP and maintenance histories may make it clear that preventive maintenance is not taking place during the weekend.

Likewise, part number analysis of scrap reports may suggest that a given component design is causing increased waste. This knowledge may not be realised without analysed data, but ERP platforms are built to provide it.

Investigating supplier and material variability

The production issues can be related to incompatibility between the raw materials or components. The PHA platforms supplied by manufacturing ERP have information on the suppliers, their performance rates, and even on the batches of materials, which is essential in the attempt to find fault with quality.

When products that have already been finished are not passed during inspection, teams will be able to trace back to the materials that have been used and determine whether it is a one-time situation or a structural one.

Most ERP systems have lot and serial tracking capabilities; a manufacturer can trace final products to the original material batch. In cases where the materials of a given supplier are always participating in the rework cases, this observation can be pointed out via ERP information.

This will assist it to make supplier management decisions that are better informed and avoid the same problem in future since it will only use suitable materials to produce its products.

Evaluating equipment and machine performance

Failure caused by a machine may be hard to detect without regular checks. ERP systems that track the activity of equipment can be integrated with manufacturing execution systems or safety appliances that use the Internet of Things (IoT).

Such parameters as uptime, cycle time, machine error codes, etc., are monitored and retained, and a comprehensive picture of machine health and performance over time can be reviewed.

ERP analytics will be able to assist when the issue in a production system can be traced to a particular machine to decipher whether it was a one-off or a general period of deterioration. Take an illustration of a machine that indicates a trend of an increment in the cycle time before failing, the maintenance teams can utilise this knowledge to implement more efficient proactive measures. This type of use of ERP data shifts maintenance strategy into the predictive as opposed to the reactive plane, minimising future downtime.

Examining labour and operator activity

Another key variable in the root cause equation is people. ERP manufacturing systems monitor work assignments to individual operators, shift records, and labour-based performance.

Otherwise, in case particular issues are recurrent during certain shifts or when particular operators are involved, this information can be used to discover training, communication, or process discrepancies.

To give one example, should a product defect be generated only on the night shift, ERP data will help to show variation in a process approach as compared to the day shift process.

It can indicate the lack of following work instructions or the necessity of additional advice to a specific operator. Viewing these issues detachedly with the help of ERP records will enable managers to act constructively and make corrections.

Linking quality control to production performance

Root cause analysis cannot be done without quality management. The ERP systems, which have been integrated with quality, have the capability of recording inspection results, non-conformance and corrective measures throughout the production process. These quality records are usually referenced to a particular work order, material or machine, which makes a complete work of responsibility.

In good usage, ERP quality data shows the point of failure within the quality control procedure. In the event of missing or inaccuracies in the recording of inspections, it may indicate poor quality control rather than the quality of the product.

Checking the inspection records, which are done on ERP, will also make sure that the quality assurance process has not been left out in any aspect, and all gaps have been taken into consideration during the investigation process.

Improving collaboration across departments

In many cases, root cause analysis needs to involve efforts on the part of several departments such as production, maintenance, engineering and quality. Manufacturing ERP systems can enhance cooperation because all people will have access to the same centralised data.

This common visibility prevents the subsequent process of communicating back and forth by relying upon fragmented records or reporting inconsistencies.

For the team working with the help of an ERP, it is easier to come to terms regarding the cause of an issue and coordinate the measures on it. Dashboards and reports help in presenting data in a neat manner, thereby steering the attention towards objective results rather than subjective opinion.

This means speedier tackling of problems and reduced duplication because all departments are in sync with each other as far as perception as well as reaction to problems are concerned.

Documenting corrective actions and continuous improvement

After the correction of a root cause, the last thing to do is to record and estimate the effectiveness of such corrective action. ERP systems that are manufactured enable the user to take a note of the changes performed, to have accountability, and to trace subsequent results. Audits, compliance and internal quality programs depend on these records.

ERP data can be used to determine the success of the solution through the future production runs associated with corrective actions. In case scrap rates decrease or machines operate more reliably, it is a sign that the defect was solved at the source. In the long run, such an organised process builds a feedback loop that helps the continuous enhancement and solidifies the entire production process.

Conclusion

Root cause analysis using ERP data will provide the manufacturers with the means of tackling the production problems on a deeper level. Instead of making certain assumptions or working with fragmented data, teams will be able to use real-time and detailed information, leading them to the source of the issue.

The ERP manufacturing systems consolidate the information in all production, quality, maintenance, and labour activities, thereby enabling more informative and correct investigations.

Using this knowledge will help manufacturers minimise the same challenges, drive down costs, and establish more dependable operations that can be delivered to customers and help achieve business objectives.