Enterprises capture more data and compute capacity at the edge. At the same time, they lay the foundation for a distributed business that can capitalize on a multiplier effect to maximize intended business results.
The number of peripheral sites (factories, retail stores, hospitals and countless other locations) is increasing. This gives businesses more opportunities to gain insights and make better decisions across the distributed enterprise. Data tracks customer, employee, patient and process activities. Pushing computing power to the distributed edge ensures that data can be analyzed in near real time, a model not possible with cloud computing.
With centralized cloud computing, due to bandwidth constraints, it takes too long to move large datasets and analyze the data. This introduces unwanted decision latency, which in turn destroys the business value of the data. Edge computing addresses this need for immediate processing by leaving data where it is created by instead moving compute resources alongside those data streams. This strategy enables real-time analysis of data as it is captured and eliminates decision delays. Now, the next level of operational efficiency can be achieved through real-time decision making and automation. At the edge: where the activity takes place.
Industry experts predict that 50 billion devices will be connected globally this year, with the amount of data generated at the edge expected to increase by more than 500% between 2019 and 2025, reaching 175 zettabytes worldwide. The tipping point comes in 2025, when, according to experts, around half of all data will be generated and processed at the edge, soon exceeding the amount of data and applications processed by centralized cloud and center computing. of data.
The deluge of cutting-edge data opens up opportunities for all kinds of actionable insights, whether it’s correcting a factory issue affecting product quality or offering a product recommendation based on past buying behavior. client. On its own, such an individual action can have a real business impact. But when you multiply the possible effects across thousands of locations processing thousands of transactions, there is a huge opportunity to leverage insights into revenue growth, cost reduction, and even business risk mitigation.
“Computation and sensors are doing new things in real time that they couldn’t do before, giving you new degrees of freedom in running businesses,” said Denis Vilfort, Director Edge Marketing at HPE. “For every dollar that increases revenue or decreases costs, you can multiply it by the number of times you take that step in a factory or retail store – you’re basically building a money-making machine…and improve operations.”
The multiplier effect at work
The rise of edge computing is essentially transforming the conventional notion of one large, centralized data center into more much smaller, everywhere-located data centers, says Vilfort. “Today, we can pack computing power for the edge into less than 2% of the space that the same firepower occupied 25 years ago. So you don’t want to centralize computing, it’s mainframe thinking,” he explains. “You want to democratize computing power and give everyone access to small but powerful distributed computing clusters. Compute needs to be where the data is: at the edge. »
Each location leverages its own information and can share it with others. These little bits of information can make a location work better. Spread across sites, these seemingly small gains can quickly add up when new learnings are replicated and repeated. The following examples illustrate the power of the multiplier effect in action:
- foxcon, a leading global electronics manufacturer, moved from a cloud-based implementation to high-resolution cameras and edge-enabled artificial intelligence (AI) for a quality assurance application. The change reduced the pass/fail time from 21 seconds to one second; when this reduction is multiplied over a monthly production of thousands of servers, the company benefits from a 33% increase in unit capacity, which represents millions of additional revenues per month.
- A chain of supermarkets leveraged in-store AI and real-time video analytics to reduce shrinkage at self-checkouts. This same edge-based application, implemented in hundreds of stores, prevents millions of dollars from theft annually.
- Texmark, an oil refinery, was pouring more than $1 million a year into a manual inspection process, relying on workers to visually inspect 133 pumps and miles of pipeline on a regular basis. After moving to a smart edge computing model, including installing networked sensors throughout the refinery, Texmark is now able to detect potential problems before anyone is put at risk, not to mention benefiting from doubled production while halving maintenance costs.
- A big-box retailer implemented an AI-powered recommendation engine to help customers find what they need without having to rely on in-store experts. Automating this process has increased revenue per store. Multiplied across its thousands of sites, the edge-enabled recommendation process has the potential to translate to more than $350 million in increased revenue for every 1% increase in revenue per store.
The HPE GreenLake Advantage
The HPE GreenLake Platform brings an optimized operating model, consistent and secure data governance practices, and cloud-like platform experience to edge environments, creating a solid foundation on which to run the multiplier effect across all the sites. For many organizations, the preponderance of data must remain at the edge, for various reasons, including data severity issues or because there is a need for autonomy and resilience in case a weather event or a power failure would threaten to halt operations.
HPE GreenLake’s consumption-based as-a-service model ensures that organizations can more effectively manage costs through pay-as-you-go predictability, while also providing access to buffer capacity to ensure easy scalability. This means organizations don’t have to foot the bill to build expensive IT infrastructure at every edge location, but can instead contract capacity based on specific business needs. HPE also manages the day-to-day responsibilities associated with each environment, ensuring robust system security and performance while giving internal IT organizations the flexibility to focus on higher value activities.
As the benefits of edge computing multiply across processes and sites, the benefits are clear. For example, an additional monthly net profit increase of $2,000 per location per month is easily achieved by an HPE GreenLake compute service per location at, say, $800 per location per month. The net profit is then $1,200. When this is multiplied over 1,000 locations, the result is a cumulative profit of an additional $1.2 million per month, or $14.4 million per year. Small positive changes in a distributed enterprise multiply quickly, and tangible results are now within reach.
As companies develop their edge capabilities and sow the seeds for a multiplier effect, they must remember to:
- Evaluate what decisions can benefit from being made and implemented in real time, and what data is critical to providing that insight so edge environments can be built accordingly
- Consider scalability – how many sites could benefit from a similar setup and how difficult it will be to deploy and operate these distributed environments
- Identify success factors that drive revenue gains or cost reductions at a specific edge site and replicate that setup and workflows at other sites
Ultimately, the multiplier effect is about maximizing the potential of edge computing to achieve more efficient operations and maximize overall business success. “We’re moving from an old way of doing things to an exciting new way of doing things,” says Vilfort. “At HPE, we help customers find a better way to use distributed technology in their distributed sites to enable their distributed business to run more efficiently.”
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