The ’90s were a pivotal time for the tech sector. These were the years of the dot-com generation, the buildout of the internet and cellular networks. A time of AOL and CompuServe, nerds getting online for the first time via copper wire dial-up connections and chatting with fellow nerds on equally nerdish topics. It was also a time of business process reengineering (BPR) where the mantra was “don’t automate — obliterate.”
The thought was that IT was used to automate previously manual activities (it still is), but those activities didn’t add any value — so why digitize them? Obliterate them instead.
The Long-Term Legacy of the BPR Movement
Twenty-plus years on, it’s hard to grasp just how big the BPR movement was, how big an impact it had on business, how many jobs were lost and what a lucrative disaster for many it turned out to be. The design and implementation of enterprise resource planning (ERP) systems went hand in hand with this evangelical era of downsizing, right-sizing and change management — all euphemisms of course for job losses.
First in line to go were people working in financial departments such as accounts payable, receivable and expenses. Next in line were the multitude of clerks who managed stock inventory or procurement. The message at the time from both ERP vendors and consultants alike was that all standard business practices could be codified and automated. Organizations eliminated entire departments once the ERP system went live.
Yet in many cases, these same employers begged those made redundant to return once it became clear that the automated business practices were not quite as standard as first thought, and when they realized they’d shown the door to the corporate knowledge and expertise that understood the many exceptions and nuances.
A few clear winners emerged from this era. It spawned a legion of consultants who descended en masse to organizations to reengineer them and somehow bring them into the digital age. Consulting firms generated billions in revenue for both themselves and the technology vendors they championed at the time. The value to the organizations that picked up the bills was less easy to calculate. For some, it resulted in losses. For others, it resulted in a new but arguably no more efficient or cost-effective norm. Trust me, I know. I was there, I was part of the problem. I spent countless hours drawing up flow charts and advising clients on how to automate manual activities with the new and extremely expensive ERP software we were installing.
Business Now Runs on ERP
ERP and digitization went hand in hand in the late ’90s. Very few change management projects didn’t involve the implementation of an ERP system back then. All that being said, realistically there is no going back. We had to learn how to live with those mistakes. But that doesn’t mean we should make them again. Virtually every mid- to large-organization in the world today operates an ERP system of some form or another.
Though they have come a long way since the ‘90s, ERP systems were and to a large degree still are highly complex, fixed workflow systems. They are designed and deployed to control the most critical and core business processes within an enterprise. Accounting, supply chain, procurement, production planning, etc. It’s not too much of a stretch to say that in 2021 the global world of business now runs on ERP. And despite all the negativity expressed so far in this article, ERP systems do work pretty well now.
Running payroll in even a small firm once took a day or two every month. With ERP systems, this happens automatically. Managing the stock and supply of parts across large warehouses was nightmarishly complex and error-ridden. Today, ERP systems have to a large degree taken charge of that work and run it efficiently in the background. To put it another way, ERP systems are analogous to modern-day RPA (robotic process automation) systems — if the process or task is unchanging, they can effectively automate those processes and tasks at scale. But just like RPA systems, ERP systems were never designed for unexpected change. They are not designed to adapt to organic transformation or innovation.
Hence in 2021, we see ERP systems increasingly starting to embrace the use of AI (artificial intelligence), or to be more accurate, ML (machine learning). Conceptually though, AI and ML are the diametric opposite of ERP systems. Where ERP systems are designed to do things in a fixed and correct manner, AI and ML are designed to learn and adapt to constant change. One is fixed (ERP), the other is fluid (AI). Therefore in theory, they should be able to augment one another to build a better mousetrap.
What Happens When AI and ERP Meet?
Make no mistake, AI can bring a lot of value to ERP. But it’s still early days in many regards, and so we need to tread with caution. Firstly, we need to be wary of “AI washing.” Just because a business application uses some AI or ML does not mean it is now an AI system. Secondly, we must always remember that AI is reliant for its training accuracy on access to accurate data. ERP systems are large data stores, but it’s not always accurate data.
By definition, ERP systems only store data relevant to the task it is undertaking, data that often lacks a broader context. What this means in practice is AI can be used to predict future demand more accurately or verify the accuracy of statements and reports, or used very effectively at the front-end of an ERP system to enable a chatbot or virtual agent. It can also be used to improve customer and sales insights and predictions, improve the accuracy of data collection and more. But AI can’t reengineer the core ERP system. Used smartly though AI can augment ERP, and feed it with more accurate data, make better decisions and reduce the amount of manual data entry work.
Vendors like Infor, SAP, Oracle, NetSuite, Microsoft Dynamics and more have all now embraced the use of AI for their ERP-related products, a trend that is certain to grow over time.
Fixed Systems (and Mindsets) Won’t Succeed in the Long Run
ERP has become the bedrock of enterprise software despite its controversial start and will remain so for the foreseeable future. The relatively recent embrace of AI in the world of ERP is a good thing. But it also serves to remind us of the limitations and history of ERP.
In the ’90s and ’00s there was the belief that there were fixed and ideal ways of working and that these working methods could be encoded into ERP modules to function efficiently. But if the past few years of a pandemic, political and geographical upheaval have taught us anything, it’s this: be cautious of fixed mindsets. Things change, often unexpectedly and sometimes dramatically. We need IT systems and applications that can adapt to change, just as we and our businesses need to adapt. No one in their right mind is going to throw out their venerable ERP system, but the right way for one may, in turn, be the wrong way for another.
ERP systems aren’t going away any time soon. They are far too well embedded to rip and replace and decades of development mean they now run complex, repetitive processes effectively. But I do predict in a world that is increasingly open to adopting IoT, blockchain and AI, that more beneficial, adaptable and affordable solutions to common process challenges are not far off. These solutions will in turn reengineer, reframe and rethink our dependence on traditional ERP systems. And I live in hope that we remember the harsh lessons of the past, that we recognize the value of human knowledge and expertise, and not kid ourselves, once again, into believing that technology alone is the remedy to our corporate problems.
Alan Pelz-Sharpe is the founder of Deep Analysis an advisory firm focused solely on disruption and innovation in Information Management. Deep Analysis provides research and guidance to firms looking to leverage new technologies and to make a digital transformation.