An ambulance speeds down the highway to take a critically ill patient to the hospital. Employees in a crowded retail store help shoppers find just the right gift. An airplane cruises at 500 miles per hour, 30,000 feet in the sky. A factory produces specialized military equipment.
What do these scenarios have in common?
You may be thinking, “they have nothing in common.” However, these scenarios each represent an important place where valuable data is created and acted upon. This data, harnessed the right way, can create immediate, essential value and positively impact not only business outcomes, but critical health and safety outcomes, too. We call these places where data can be acted upon near the point of creation the “edge.”
What is the Edge?
The edge is everywhere and can be hard to define. As you can see from the examples above, your edge could be just down the hall from your data center or flying around the world on a jumbo jet. Most definitions of edge computing agree that it refers to moving compute power closer to data sources, although the specifics can vary widely.
No matter what you call it or where you put it, the right approach to edge computing is specific to your industry and to your organization. When the right edge computing strategy is put in place, it can transform your business operations and outcomes.
For example, healthcare organizations may wish to build remote clinics to serve customers in rural areas. This requires the ability to process data close to the source to provide clinicians with near real-time patient information while also complying with healthcare guidelines. Edge computing for healthcare could include analytics systems capable of processing data from patient monitoring systems or solutions that consolidate and transfer insights used for population health tracking. These solutions deployed at remote locations with limited IT staff need to be compact and simple to deploy and operate, with intrinsic security, advanced automation, and remote management capabilities.
Manufacturers can deploy sensors and video cameras to monitor the overall effectiveness of equipment on the factory floor and the quality of products coming off the assembly line. Edge computing takes the various sources of data and analyzes them to look at general trends. Data insights can be used to improve output quality and speed the system to make it as efficient as possible. A manufacturer could try to transport their data to a data center, but it would require massive amounts of time. With an edge strategy, the data is analyzed on the factory floor, providing the manufacturer better data insights and accuracy so they can make faster decisions and improve efficiencies.
A retailer may aim to provide better shopping experiences by tracking how products are moved throughout a store to manage inventory and supply or helping customers more quickly. With edge computing in a retail location, combined with AI, retailers can track what inventory is paid for or ensure employees are in the part of the store where they are needed most.
These edge scenarios are so different in design and outcome that lumping them under the common term “edge” seems like a misnomer. The IT infrastructure footprint, network, input sources, security, data storage, data protection, and architectural considerations all will be driven by several factors. These include the characteristics of the data that must be analyzed at the edge, how fast insights must be derived to align to the desired business outcome and what portion of that data or metadata will need to be sent back to a centralized environment.
How to Tackle Your Edge
The process of implementing and operating edge computing isn’t always straightforward either. Edge initiatives often have unclear objectives, involve new technologies, and uncover conflicting processes between IT and operational technology (OT).
Here are three tips to help you kick off your edge strategy:
1. Design for Business Outcomes
Successful edge projects begin with a focus on the ultimate prize — the business outcomes. Clearly agree upon and align your targeted business objectives up front, well before you start talking about technology. If you’re in manufacturing, for example, you might ask if you want to improve your production yields or reduce costs by a certain amount by proactively preventing machine failure and the associated downtime.
If your project is going to require a large investment with an initial limited return, document these business considerations and communicate them clearly. Having specific business goals will enable you to manage expectations, measure your results as you go, and make any necessary mid-course corrections.
2. Consolidate and Integrate
Look for opportunities to consolidate applications onto a single infrastructure to help your organization realize significant savings on edge computing initiatives. Think of your edge not as a collection of disconnected devices and applications, but as an overall system that enables efficient operations. Virtualization, containerized applications, and software-defined infrastructure are key building blocks for a system that can enable consolidation.
In addition to being more efficient, edge consolidation provides greater flexibility. You can more easily reallocate resources or shift workloads to achieve your business needs. Consolidating your edge also opens opportunities to share and integrate data across different data streams and applications. This will enable new applications to easily take advantage of the existing edge data without having to build new data integration logic.
As you consolidate, ensure that your edge approach leverages open application programming interfaces, standards, and technologies that don’t lock you into a single ecosystem or cloud framework. An open environment gives you the flexibility to implement new use cases and new applications and to integrate new ecosystems as your business demands change.
Not only technologies need integration. Bring together IT and OT organizations to compare best practices and drive your edge strategy forward. These teams can’t be working in siloes when it comes to the edge. Encourage IT and OT to find what commonalities they share versus focusing on what’s different. Take what IT uniquely knows how to do well and marry that with what OT uniquely knows how to do well, while leveraging common standards, practices, and a shared goal or outcome. More mature organizations have already built these bridges and are successfully designing for edge outcomes together.
3. Plan for growth and agility
Take the long view. Plan for your initial business outcomes, but also look ahead and plan for growth and future agility. Think about the new capabilities you might need and new use cases you might want to implement for growth.
For example, are you doing simple process control and monitoring today that you may want to use deep learning for in the future? If so, make sure that your edge infrastructure can be expanded to include the networking capacity, storage, and accelerated compute necessary be able to do model training at the edge. Taking an as-a-service approach with infrastructure can give IT more control of their environment and make it easier to put IT resources where they can reap the greatest value.
Capture Your Edge Opportunity
The edge can be anywhere. And the data that can be captured and analyzed from the edge can deliver business-changing and life-changing outcomes. Look for a partner that can help you define your edge, simplify your edge computing solution through consolidation and integration, and plan for growth with a strategy designed around outcome-based benefits. Now is the time to maximize the value of the data your business is generating and drive your business forward with actionable insights. Go capture your unique edge opportunity.
About the author: Gil Shneorson is a senior vice president of Edge Solutions at Dell Technologies. Gil is a business and technology executive with over 30 years of leadership experience. In his current role, Gil leads Edge solutions strategy and execution for Dell Technologies, working with customers, partners and product groups to ensure Dell delivers solutions that address customers’ Edge computing challenges. Gil previously led Dell’s hyper-converged systems business VxRail, from inception to market leadership and was responsible for EMC’s VSPEX reference architecture program, creating over $4B of value for EMC and its channel partners. Before joining Dell Technologies, Gil held various professional services positions at DEC/Compaq and software development positions in the federal space. Gil holds a B.A. degree in Economics and Business Administration from the University of Bar-Ilan in Israel and a high-tech MBA from Northeastern University in Massachusetts.