Skip to main content

5G Core and Edge Networks Fuel Digital Transformation

Many progressive CIOs and CTOs would agree, fifth-generation (5G) wireless communications have the potential to support new use cases that were not possible with earlier mobile infrastructure deployments.

Moreover, 5G and edge computing technologies can transform legacy business models within several key industries, including manufacturing and associated Industry 4.0 verticals.

The emerging market for 5G cellular connections in manufacturing is expected to reach $10.8 billion by 2030, at a Compound Annual Growth Rate (CAGR) of 187 percent, according to the latest worldwide market study by ABI Research.

5G Core and Edge Networks Market Development

"But, to capture the value at stake, ecosystem stakeholders will first need to evaluate how to measure the impact of 5G and edge deployments," said Don Alusha, senior analyst at ABI Research. "The current Industry 4.0 digitalization discourse centers around conventional financial metrics -- e.g. return on investment, net profit, and cash flow -- as the yardstick to measure 5G and edge computing effectiveness."

However, these metrics are financial measurements to gauge profit and do not lend themselves to the factory floor. Therefore, Industry 4.0 ecosystem entities must consider an alternative set of measurements that look at how 5G and edge deployments aid manufacturing and establish operational rules to run a plant.

According to the ABI assessment, they are throughput, inventory and operational expense for the incoming flow of capital, for capital located inside, and for capital going out, respectively.

These three measurements enable Industry 4.0 technology partners to institute a direct connection between the 5G network's utility and what takes place on the manufacturing factory floor.

In turn, they will be able to use that connection to find a logical relationship between daily plant operations and the overall company’s performance. Only then, will Industry 4.0 verticals have a basis for knowing the real benefit of 5G and edge computing.

Furthermore, equally important is the ability to measure risk when looking to adopt 5G and edge computing assets. Discussions on new technology adoption have always been based on an assessment of risk and reward.

"If the reward is truly compelling, adopters will take the risk. 5G and edge offer unprecedented commercial opportunities, but they inherently constitute new technologies and therefore there is a risk attached," says Alusha.

Continued attempts to keep up productivity growth, increase process automation to meet changing client demands, and the need to establish a reliable supply-chain that spans multiple geographies are forcing manufacturers to be more flexible.

According to Alusha, "To understand the importance of supply chaining and its significance in terms of competitive advantage, one need not go any further than Wal-Mart. They are the largest retailer in the world (Amazon being second) and it does not produce a single item. All it 'makes' is a hyper-efficient supply chain."

ABI analysts believe that the capacity, reliability, high-quality service, and speed provided by 5G and a hyperconverged edge compute can optimize operations for a super-efficient supply chain.

Outlook for 5G Applications Growth in Industries

With greater reliability and data speeds that will surpass those of 4G networks, a combination of 5G and local edge compute will pave the way for new business value. Commercial benefits will accrue along three broad aspects: agility and process optimization; better and more efficient quality assurance and productivity improvement.

The implications for solution providers are that they must enhance their value-add by complementing their deep technical expertise with business expertise including vertical industry knowledge, new functional expertise, solution design and consulting expertise tailored at niche use cases.

Popular posts from this blog

The AI Application Integration Challenge

Artificial intelligence (AI) has rapidly become the defining force in business technology development, but integrating AI into applications remains a formidable challenge. According to a recent Gartner survey, 77 percent of engineering leaders identify AI integration in apps as a major hurdle for their organizations. As demand for AI-powered solutions accelerates across every industry, understanding the tools, the barriers, and the opportunities is essential for business and technology leaders seeking to evolve. The Gartner survey highlights a key trend: while AI’s potential is widely recognized, the path to useful integration is anything but straightforward. IT leaders cite complexities in embedding AI models into existing software, managing data pipelines, ensuring security, and maintaining compliance as persistent obstacles. These challenges are compounded by a shortage of skilled AI engineers and the rapid evolution of AI technologies, which can outpace organizational readiness and...