Welcome to the new age

22 May, 2023

How long we've come...

From Descartes’ automata to the Turing Test, and today’s CAPTCHA*, many have focussed on how we can define “the intelligence” and compare it amongst the living and the non-humans. The debate has certainly gone beyond being a mere philosophical exercise evolving into a scientific query and here we are at the era of AI.

As expected, the accumulated knowledge blended with the technological advances turned the evolution into a revolution. The future is nearing faster than time as the unprecedented machine capabilities are being employed to create new ones in such a fashion that no one has ever imagined. Here we are, on the verge of a leap, but some are still being late to take the step forward.

This hesitancy seems completely humane since, part of the four generations from the Silents through the Gen Ys, grown up reading and watching sci-fi, make up most of today’s C-suite versus the Gen Zs and Alphas who were born into the evolution and lived through the AI revolution are working together at arm’s length with each other. The kind of science fiction the former has been exposed to has not envisioned the world in a very fancy fashion. Take Capek’s R.U.R. for instance, the influential play which popularized the word “robot” by being translated into thirty languages in only three years. The man-made robots, supposedly serve man, rise, and revolt, ending the humanity in a bloody way. Thus, why not be sceptical? Are we still afraid that artificial intelligence, machine learning, or the robots will replace us in our jobs? Take-away number one: People need to be trained as well.

The fourth industrial revolution marked the dissemination of artificial intelligence in almost every aspect of modern life. IT is different from the first three in the sense as it’s been irrevocably changing the way human-technology-human interaction. Scepticism remains and paves the way for collective requests of governance and regulations from both public and private sectors. Keeping those in mind, the most pragmatist way to approach this revolution is to embrace it as fast as possible because resistance will result in nothing but relegation.

Artificial intelligence has been transforming the way we work, with the immediate impacts manifested in multiple KPIs such as increasing revenues, balanced supply and demand, reduced inventory costs, decreased need for irreplaceable resources such as humans, time, and energy. The early adopters are playing it smart by starting off process digitalization projects step by step. Improving operational capacity and lowering costs through automation enable the early adopters to become category leaders.

Retail industry is a very distinguished example of early movers. The effects of the global pandemic have demonstrated how vulnerable the industry indeed is. The store closures, followed by lay-offs, unexpectedly boosted e-commerce costs, the deadlock in shipments affecting the delivery of both raw materials and finished goods, changing customer personas and shopping habits, the demand for new products all contributed to the chaos and the post-pandemic economic recession. Now the shoppers and their behaviours are again aligning with the post-pandemic conditions, yet they are becoming more demanding than ever. This is where artificial intelligence, along with machine learning and forecasting algorithms come into play.

To remain competitive, not only in the competition, but the retailers also need to adopt new ways of doing business. The fundamental issues to be dealt with seem to remain predictable: Personalize the shopping experience to keep the cash flowing in.  To do so, first step should be having data to take on action. Starting from transaction data, for instance, you can build a system in which you can have accurate demand forecasts to act upon. Automating workflows is another brilliant approach to keep the business going, as it would allow you to keep up with your KPIs (such as availability, first allocation, stock transaction workorders, etc.) as a starter. This would lead to inventory optimization which reduces your costs.

Another benefit would be synchronization of demand and cost forecasting to come up with pricing recommendations. Thanks to Getron Forecasting Engine backing up all the Getron Services, cost of factors can be synchronously forecasted along with demand. This allows for adaptive pricing.

Automating your workflows would include your stock transactions. The intelligent Getron Services would be supporting you with automatically generated stock transaction workorders, allowing you to have the right product, in the right assortment, in the right quantities, at the right place. Increasing availability while decreasing number of transfers, these add up to cost savings resulting in increased revenues. The results are not only monetary of course, optimizing the number of transfers means decreasing the number of actual transfers resulting in the contribution of decreasing our carbon footprint.

So whatever your first step will be, it will have a huge impact, as making a blueprint will get you closer to your goals in the middle term. Everything mass-customized by you, for you, through our No Code Mass Customization Interface.

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