Automation IIoT

Improve ERP With IIoT

EP Editorial Staff | May 27, 2019

Given the benefits, making ERP and IIoT play together should be a top priority in your plant.

By Vinay Nathan, Altizon Systems

Enterprise systems are supposed to exchange information and help with decision-making in plants. Beyond increasing some work efficiencies, though, the fact is such systems rarely work together. This, in turn, creates difficulties for key stakeholders when it comes to accessing data, seeing the big picture, and making critical decisions. 

Enterprise resource planning (ERP) software is among the key systems that host important data across industry. In most organizations, management relies on ERP systems for critical planning and operations decisions. In the manufacturing arena, the Industrial Internet of Things (IIot) is now helping connect machines to enterprise systems. This integration, wherein machine data can be accessed and processed in real time, is finally starting to make enterprise systems more intelligent. However, overlap between the two is still rare. According to a 2017 survey of 200 marketing and contracting executives, conducted by IFS, Itasca, IL (, only 16% consume Internet of Things (IoT) data in their ERP software. As one researcher concluded, “The ability of ERP and other software applications to support IoT is still not robust enough.”

It isn’t just a matter of two different systems existing independently. Larger organizations were more likely to report that ERP impeded their digital transformation. These were the same organizations that were more likely than others to have sensors on their equipment. The solution for this dilemma is simple: Fuse ERP with IIoT, which fills many of the gaps that make ERP a less-than-perfect solution.


ERP is an artery of data within an enterprise, as platforms such as SAP and Oracle meet the needs of common processes. On a plant floor, ERP is for planning, strategizing, and decision making. 

Given ERP’s long history, it’s not surprising that some archaic elements persist. For instance, because data entry may not be automated, an organization can incur indirect labor costs, and the system’s visibility into inventory will be delayed, rather than real time. It also means that data in the system can be inaccurate, thanks to human error. As a result, instead of being agile, an organization using ERP is reactive in its planning. 

Another limitation of ERP is a lack of process-level traceability. For example, if a plant produces motorcycles and has to recall a part, it would have to initiate a mass recall for all models that include that part. Product-level traceability is available with ERP, but in a limited fashion. When a manufacturer sells directly to the end user, it’s possible to link a serial number to the customer. Products sold through dealers present more of a challenge. With the IIoT as part of the process, factories that produce the part and the models that include it can be easily traced. 

It’s difficult to map issues and vendors in a traditional ERP system, and there is often a lack of critical KPI (key performance indicator) integration. Because of the reliance on data collected from different silos within an organization, ERP is also often based on outdated master data. 

In case of business-process re-engineering (BPR) projects at greenfield ERP installations, organizations need to collect baseline data to benchmark the system. Post BPR process, this data becomes extremely important to ensure there are no deviations or that deviations are as expected. The information is then used to set up master data in ERP. In a typical BPR project, such data usually is gathered through a manual process, which can lead to ineffective sampling. 


The IIoT addresses many of ERP’s shortcomings. Linking IIoT and ERP provides a much-needed real-time data feed that offers visibility into inventory and a constant feedback loop.

In a recent analysis of IIoT systems, connecting more than 100 industrial plants comprising 276 projects to date, the Smart Manufacturing Almanac for 2019 revealed that higher and quicker return on investment (ROI) from IIoT projects can be realized through integration with backend systems such as ERP.

If IIoT is implemented across the value chain, i.e., OEM, Tier I, Tier II, and elsewhere, it specifically makes addressing product traceability and genealogy easier. Every part of the product can be traced to its manufacturing roots. As a result, organizations have better control in the event of product recalls or compliance audits. 

The IIoT also provides up-to-date master data. This type of data contains the key properties of manufacturing elements, including information on production orders, material types, planning requirements, goods issue, and goods receipts. Typically, once this information had been fed into the system, there was no mechanism to look back and update it, causing a disparity of data, among other issues. However, the IIoT provides opportunities to refresh master data/records to ensure that the information is kept in sync with operational realities.

Normally, production planning, such as shift level, executed daily, weekly, or monthly, is processed in ERP systems and actual production count is updated manually after a shift/day ends. Any difference in planned versus actuals is a trigger for the next day’s planning. Additionally, the reason codes for downtime analysis are maintained in ERP and used during the downtime booking. With IIoT integration, such bookings are done automatically right from edge machines to ERP systems through the IoT. For example, a leading automotive tire manufacturer in Asia has integrated its IoT data with ERP systems, allowing its management to look at planned versus actual production and machine downtime in real time. This has significantly reduced redundancy and improved planning. 

There are multiple and significant benefits from integrating IIoT and ERP, including a boost in financial performance from more actionable data by linking real-time machine information to ERP. Historically, ERP systems could not identify operational failures or their causes. But, with IIoT, using sensors and real-time data, the ERP system is capable of identifying anomalies within seconds. 

Should the production of a specific item have a higher-than-expected conversion cost, an IIoT system that is properly set up will quickly identify the portion of the manufacturing process that is failing. This enables target process improvement while decreasing the impact of variation, thus lowering operating costs and creating greater profits. Having the IIOT and ERP work together can also lead to better service levels for customers because sensors and resulting real-time information can signal outages in a billing cycle. Other benefits include faster sales and operations planning including current master data that includes updates for stocks, yields, batch size, and capacity, in addition to an improved management information system (MIS) and performance evaluations of machines. EP

Vinay Nathan is the CEO and co-founder of Altizon Systems, Scotts Valley, CA, a platform provider in the IIoT space. For more information, visit



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