Machines are here to stay, and we should embrace them, not fear them
An organization's competitiveness is determined by how its 'plumbing' - such as inventory and human resources - are analyzed in order to accomplish more with less. Many have focused on the Digital Transformation movement in recent years, especially in the wake of the pandemic.
The 'transformation', however, is designed to reorganize culture and processes with ever-progressing technology. Control over factors of production and virtually every process still lies with the management, and to a lesser extent, a few 'empowered' employees.
The term Enterprise Resource Management, or ERP, emerged almost thirty years ago as a way to manage resources, balance books, and perform functions such as procurement and delivery, with the addition of bells and whistles such as sensors and Internet of Things (IoT) over the years.
However, there is now a tectonic shift that requires firms to move on from the old paradigm. We must no longer readjust processes and factors of production after a post-mortem data analysis, but instead usher in a self-learning, self-healing enterprise.
Artificial intelligence/machine learning (AI/ML) and 5G connectivity are maturing owing to smarter chips and software, amid the urgent need to retool business models in a post-COVID-19 world. Prolonged periods of working from home have led many employees to question the purpose of work itself. The way firms steer through these trends will determine whether they will be victors or losers in the new paradigm.
The notion of operating the enterprise in a ‘review the past' mode is embedded in ERP as we know it. To better future results, software controls the input of factors and measures the output of previous actions and judgments. ERP is commonly thought of as a digital 'dashboard' that can measure, evaluate, predict, and possibly provide options.
It gives top management the insights to make better decisions. However, even in highly developed organisations that are capable of successfully gathering and harmonising data, decisions are made based on past data. The C-suite, not the software, has the power to make and modify decisions.
The forces of change have reached a tipping point, necessitating a thorough examination of the current ERP paradigm. Instead of simply pushing our better insights or more educated options, post-COVID-19 ERP must let the software take some control and make decisions for itself.
This is not a case of daydreaming about the future. Aspects of such futuristic ‘machines' have already seeped into smart automobiles and aviation- two fields that have advanced in R&D. Due to the intrinsically competitive environment in which companies in these fields contend, their digitalization skills are quite sophisticated.
But why should this power be restricted to Tesla and manufacturers of next-generation planes? What functions can be empowered – at least in stages – for critical industries such as power, cement, and chemical plants, which have high-value assets that must not fail?
To pivot away from traditional ERP and Enterprise Asset Management and toward AI/ML-enabled software that decides and implements specific functions, a mindset shift is required.
Take, for example, the time-consuming procurement procedure. By going through prior records and market data to rate vendors by price, quality, and delivery periods, software can be trained to identify essential providers. Shortlisting is a decision that can be assigned to software, which can also order low-value things such as cleaning cloths, drinking water, and components automatically.
Similarly, a piece of equipment that has seen a lot of use and has been told by the software (through sensors) that dust and humidity levels have been abnormally high lately, can tell the shop floor mechanic to take action sooner than usual.
AI/ML-enabled software can also address payroll challenges around data hygiene, payroll fraud & leakage. Infused with Artificial Intelligence (AI) and Machine Learning (ML), the application can analyze data, question a user and recommend optimum solutions to implement, helping them to think, predict and prompt. The AI engine will predict any anomaly thus averting anything that will harm the business operations.
In the future, software may be able to make more and more decisions on behalf of the company. The enterprise's beating heart can now rely on a self-learning brain that can think and act within approved guidelines.
For businesses, the payoff is not only achieving more with less. Employees, particularly millennials and Generation Z, can feel more content about getting on with the genuine purpose of their jobs.
Because the software has already made certain decisions, the procurement manager may devote more time to developing strategic vendor partnerships. The mechanic can carry out other work orders after taking software-directed actions to prevent future difficulties.
It's time to free the company from hierarchical decision-making, rigid processes, silos, and the monotony of repetitive work.
Let the machines stay.