A Brief History of ERP
ERP history started with material requirements planning (MRP) systems in the 1960s, when J.I. Case, a manufacturer of tractors and construction machinery, worked with IBM to develop what is believed to be the first MRP system. Thereafter, large manufacturers built these MRP solutions themselves.
While they were expensive to create, required a team of experts to maintain, and took up a lot of space, early MRP systems enabled businesses to track inventory and production. That helped manufacturers manage raw materials procurement and delivery of products to the factory so they could better plan production runs.
Although the adoption of MRP systems gained traction in the 1970s, the technology remained limited to large companies that had the budgets and resources for in-house development. Eventually, several large software providers, including Oracle and JD Edwards, set out to make this software accessible to more businesses.
History of ERP in manufacturing: The ‘80s marked a milestone in the history of ERP systems when the first manufacturing resource planning (MRP II) systems appeared. These more sophisticated solutions supported manufacturing processes beyond inventory and raw materials procurement. MRP II systems allowed the various departments involved in manufacturing to coordinate, and they had more advanced production scheduling capabilities.
It wasn’t long until other industries realized that manufacturing firms were onto something.
Evolution of ERP Systems
By 1990, research firm Gartner coined the term “enterprise resource planning.” The new name recognized that many businesses—not just manufacturing—were now using this technology to increase the efficiency of their entire operations.
This is when ERP systems took on their current identity: a unified database for information from across the company. ERP systems brought in other business functions, like accounting, sales, engineering, and human resources (HR), to serve as a single source of accurate data for all employees.
ERP systems continued to evolve throughout the ’90s. One major breakthrough was the advent of cloud ERP, first offered by NetSuite in 1998. With cloud ERP, widely seen as an improvement over on-premises systems, businesses could access critical business data through the web from any device with an internet connection. Cloud solutions meant companies no longer needed to purchase and maintain hardware, reducing the need for IT staffers and leading to easier implementations.
This cloud model made ERP systems, once limited to enterprises, accessible to smaller companies that lacked the capital to launch and support a resource-intensive on-premises solution. Small and midsize businesses across industries could enjoy the same benefits as their larger counterparts, including automated processes, improved data accuracy, and greater efficiency.
In 2000, Gartner introduced the idea of ERP II to refer to internet-enabled systems that could pull data from other sources, including front-office applications, like customer relationship management (CRM), e-commerce and marketing automation, and back-end applications like supply chain management (SCM) and human capital management (HCM).
This was a significant advance because the more information that feeds into the ERP system, the easier it is to identify and resolve issues and capitalize on opportunities for improvement.
Today, leading ERP systems are vast repositories of information able to generate reports that can spotlight the performance of every aspect of the business, from sales and marketing to product development to HR and operations. There are countless applications available, designed for different industries, business models, and challenges, and ERP acts as command central for what can be a vast network of software.
Future of ERP
Major technology trends, like artificial intelligence (AI) and the internet of things (IoT), will shape the future of ERP systems. In the nearer term, ERP solutions can take advantage of machine learning—a subset of AI where a system learns to identify patterns in data to draw conclusions—to eliminate manual tasks and predict future business trends. Machine learning assimilates new data and feedback to become smarter and more effective over time.
Machine learning requires a large volume of data that is both granular and diverse, which an ERP solution provides, and leading ERP providers already leverage this capability. When an ERP system can mimic human behavior, it creates new opportunities for automated reporting, reconciliation, and error detection.
The tremendous amount of data a machine can process and analyze generates a treasure trove of new insights. Think reviewing customer buying patterns to predict future shifts in demand or suggesting optimization opportunities, like personalized emails or site experiences, that will increase conversion.
On the back end, an ERP with this capability can quickly detect anomalies that could signal fraudulent transactions or identify processes that are responsible for a disproportionate amount of damaged goods. In short, machine learning empowers businesses to make rapid adjustments that drive success.
Connected IoT devices like sensors, cameras, tracking systems, and scanners have become another key source of information for ERP systems. IoT has started to carve out a place among manufacturers and distributors because it helps businesses assemble a comprehensive, real-time picture of their supply chains. For example, IoT devices can monitor the status and usage of industrial machinery to quickly alert managers to broken equipment so they can fix it before it becomes a bigger problem. An IoT scanner can automatically track products as they enter or leave the warehouse. That not only ensures accurate inventory counts but can trigger restocking by an employee or automatic reorders from suppliers.
ERP systems have come a long way, and machine learning, and other innovations will lead to continued advancements and shape ERP history in the years to come—65% of CIOs anticipate integrating AI into their ERPs by 2022.
ERP History FAQ
Who invented ERP?
Tractor and construction machinery manufacturer J.I. Case worked with IBM to develop what is believed to be the first MRP system in the early 1960s.
What’s the difference between an MRP and ERP system?
MRP systems preceded ERP systems. Early MRP, or material resource planning, systems offered basic inventory control to help manage procurement and delivery of goods. ERP systems first appeared in the ’90s and pulled in information from other parts of the business, like accounting, sales, and HR.
What is manufacturing resource planning, a.k.a. MRP II?
Manufacturing resource planning (MRP II) systems arrived in the 1980s and were a significant step up from first-generation MRP systems. They incorporated additional manufacturing processes and got other departments involved in manufacturing to improve production efficiency and scheduling.
When did ERP systems become popular?
This software became more accessible and affordable in the ’80s and ’90s as companies like Oracle and JD Edwards developed and sold solutions. This meant businesses no longer had to build these systems themselves.
What is cloud ERP?
Cloud ERP is an ERP solution delivered through the internet that doesn’t require on-premises servers or other infrastructure. It first appeared in the late ’90s, gained traction in the mid-late 2000s, and has become extremely popular in recent years.
What is ERP II?
ERP II refers to internet-enabled ERP systems, including cloud solutions, that use web connections to send and receive information from various applications. Gartner came up with the term “ERP II” in 2000 to christen a new generation of ERP systems.
How do ERP systems use machine learning?
Machine learning technology uses data and feedback to learn patterns and make judgments that inform additional analytics and insights. In the context of ERP, machine learning can automate reporting, reconciliation, and the flagging of inconsistencies or errors.