Evolving on the grounds of technology, followed by a global push to be digitally active, businesses in industry 4.0 must take human-machine interactions and data derived from it to the next-level.
Predictive-insights has been a long-standing buzzword. It is a gray area for some, for others it is the future of business summed in one word. What it truly means for businesses and business stakeholders is attaining a superpower of making flash-speed decisions. People in various departments would not have to lift a finger to get accurate, futuristic insights that would otherwise take days or at times, weeks and months to realize. All with the data collected at various touch-points from human-machine interactions using technologies like IoT (Internet of Things), machine learning, and robotics among others, and processed by human-like intelligence, in other words, artificial intelligence. That’s the opening premise of industry 4.0, driven on the grounds of data.
To understand it better, let’s take the example of a ready-to-eat snack brand. This brand aims to achieve higher sales with the most effective schemes for their retail partners. Where a traditional brand would simply run discounts across the zone, this brand takes the lead of data derived from the market to reach an efficient strategy bound to deliver results. They start by using image recognition technology in the mobile apps that their salespeople use while visiting a retail outlet. On this application salespeople capture every retail shelf space. Here the image recognition technology recognizes the brand’s products and separates it from the competitors, like wheat from chaff. Over a period of time, the artificial intelligence in the application records the wide range of product placements, compares it with the orders received from respective outlets and analyzes performance. Based on this data, it delivers accurate insights on which product placements deliver maximum orders. With this predictive insight, the brand runs schemes for retail outlets who would place its products at specific shelf space only. Following this, the said brand gains competitive advantage and increases sales of its products.
This is just one side of the story. The same can be said for other functions of industry 4.0, from manufacturing to distribution, warehousing to delivery. A slow yet steady transformation of businesses from physical to cyber-physical is the imminent future. In most likelihood, the market in industry 4.0 is expected to grow to $337.10 billion by 2028. However, considering the fast pace of evolution and shifting consumer demand, it cannot grow as expected without standing strongly on the pillars of data and digitization.
Data-embedded decision-making, and aforetime resolutions
While capturing market demand is one side of the story, the other is smart distribution. It is a common story of the day where distributors run out of brand’s stock and face delays in fulfilling retail orders. But this situation will soon be resolved using IoT- a technology designed to connect physical objects with mobile devices. To start with, physical shelves at the distributors warehouses will be connected with sensors. These sensors will capture movements of stock in real-time. The moment it reaches the minimum, pre-coded threshold, the distributor will receive an alert on their mobile device instantly, nudging them to raise a purchase order. A more futuristic stance would see the brand’s personnel receiving a new demand alert directly on their device, quite like the distributor because of a centralized application.
One of the major challenges with modern-day processes is disconnectivity in applications, leading to division of data-sets in silos. Every business function, be it manufacturing, sourcing, warehousing, distributing and selling are connected to their respective technologies. None of them are interconnected and that is one of the most difficult problem statements of industry 4.0. Interconnectivity of individual functions with one centralized technology, all the while remaining connected to their respective individual technologies is going to deliver the most valuable predictive insights every business can vouch on.
To put it in an example, we have robots assembling components in a manufacturer’s assembly line. The individual activity of each robot is recorded in the computer. These activities are analyzed and scrutinized by artificial intelligence. Based on this data, an efficient AI can easily predict the most time-efficient assembling technique. The manufacturer, upon receiving this insight, will be able to deliver more final products in less time. Because this insight is received well in advance, the interconnected application will predict new warehousing requirements, inform the stakeholders about the accelerated time-to-market for their products and simultaneously pass this information to other applications used by stakeholders in various departments. Management at various functional levels therefore will be able to plan future distributions, sales, promotional activities, new channels of selling and so many other things.
Data-driven digital transformation in industry 4.0 is not just a foresight for businesses, it is soon to become a hindsight, exemplifying how adoption has progressed and not how adoption is required. It is a mandate because industries across the globe are already on their way to embed modern technologies in their critical functions. All to attain a competitive advantage in their time-to-market, route-to-market, penetration in the market, and capturing opportunities in the market.
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ARTICLE BY THE TIMES OF INDIA
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