Autonomous ERP – Are You Ready For This?
The widespread readiness of Australian businesses for autonomous ERP is coming, as result of widespread use of integrated peripheral technologies across many businesses operations. However it is the mature companies with well established business processes and established ERP systems that will fare better in this technological transition, compared to those with outdated or fragmented systems, this is because autonomous ERP relies heavily on real-time data and integration.
What Is Autonomous ERP?
Autonomous ERP is based on the concept of AI and machine learning. In the same way that manufacturing plants were transformed by robotics and automation it is fair to say that Autonomous ERP will also transform office, administration and management functions.
What is interesting about the current development of the technology is that the take-up of Autonomous ERP will now be driven by the 3 factors that have traditionally been blockers or limiting factors;
- Capability & Computing Power
- Connectivity
- Trust
Limiting Factors To Autonomous ERP
Capability & Computing Power
Simple – the rapid development in this space means that computing power and capability of software continues to expand. It is now possible to process the myriad of variables, transactions, information and inputs necessary for many AI applications and capabilities are becoming more and more sophisticated. In addition, innovations such as shared cloud infrastructure, IAAS, PAAS and SAAS mean that companies can access cost effective and easily scalable IT infrastructure and capability.
Connectivity and the Internet of Things (IIoT)
Connectivity relates to the Internet of Things (IOT). IOT is driven by the proliferation of Bluetooth and Wi-Fi combined with Internet connectivity, coupled with the low cost of embedding equipment, vehicles, machines, and components with electronics, sensors, and software. This allows them to collect, connect and share data with the Autonomous ERP or AI Engine.
Trust
Trust is a factor that builds over time from familiarity and proof of concept. A sound basis for analysis of where individuals or organisations are on the AI acceptance curve comes from thinking about comfort with different levels of AI decision-making – basic, intermediate, and complex.
In basic and intermediate decision-making, the Autonomous ERP will make “day-to-day” decisions based on a pre-determined set of inputs. Machine learning means that the system can monitor human decision making and collect the data to set the parameters for those inputs. In more advanced decision-making, the AI engine can learn from the decisions made by management in the same way, however the number of variables to be considered may increase dramatically.
So What Does Autonomous ERP Mean For You Today?
While management may not want to completely hand over complex or critical decisions to an AI engine it is likely everyone will be happy to use Autonomous ERP for basic or routine functions such as ordering out of stocks, monitoring vehicle maintenance requirements or running exception analysis.
There is also still the opportunity for human intervention – for example the system can do the complicated analysis or keep track of diverse of locations and operations and then flag the recommended course of action for human checking and ratification.
As with most things, the key is to find the practical applications for the technology to drive business improvement and efficiency.
Many Ndevr customers are already taking advantage of the “autonomous” or “smart” capabilities of Oracle and JD Edwards to drive greater efficiency, relieve administrative workloads, create safer working environments and generate real cost savings across their businesses. The JD Edwards Orchestrator tool enables JD Edwards to take advantage of these AI technologies and support Autonomous ERP processing.
Our approach is to focus on the practical applications and we apply our expertise to deliver real business improvement – making the most out of your investment in your business system.
