Bring siloed data together to get the best of your edge computing data


Convincing management to buy into your plan is not easy, but a potential profit increase can change their minds.

Image: metamorworks, Getty Images/iStockphoto

The edge computing market is expected to grow from $2.8 billion to $9 billion by 2024. But leveraging edge technology for best business benefit—and convincing executive management of the value of the edge—are still works in progress. 

“A major pain point for IT teams trying to implement edge technologies is the lack of buy-in from leadership,” said Larry Wilson, senior director of innovation and digital ecosystems at Splunk, a cloud-based data management platform. “Many initiatives are started with lofty goals, then they are are shut down under the rush of everyday operational strain.”

SEE: 5G: What it means for edge computing (free PDF) (TechRepublic)

Wilson said he believes that one way to circumvent this pain point is to build a momentum-generating plan that can continually feed off of bringing siloed data together.

Silo busting is something that executive management relates to. Too often, high-level questions have gone unanswered because data was fragmented, and it was impossible to create a holistic picture of a situation.

While the COVID-19 crisis has been a disaster in almost every way, it has created a fortuitous opportunity to break down silos as employees work remotely. “When remote work became our new reality, leaders were forced to recognize that when linked together, the data from silo investments could produce more informed insights,” Wilson said. “This has enabled business operations across industries to run smoothly during the pandemic, and it’s set a good path for post-COVID operations.”

That’s important. But for digital transformation to advance throughout the business, management has to buy into the strategy, with a clear understanding of the business benefits that digital transformation will deliver. To facilitate this, IT should be teaming with systems integrators, subject-matter experts and others so projects can keep moving forward and maintain management support.

“The experts are needed because they will accelerate your organization’s success and ensure that you are optimizing new technologies to reach peak performance,” Wilson said. Also, choose projects where it’s easy to see the financial and operational returns on investment.

SEE: Is AI just a fairy tale? Not in these successful use cases (TechRepublic)

“For example, reducing downtime can have a huge impact on profit since downtime can cause losses up to $22,000 per minute. Besides, a major cost component of every organization is maintenance and support,” Wilson said. “You especially want to reduce the most expensive type of maintenance and support, which is unscheduled support that is needed for any assets that are critical to maintaining production and operations. Machine data from the systems can be harnessed to monitor asset performance, diagnose any performance issues and ultimately predict when maintenance should be performed. Correlating data from the asset with work order reports, network system performance and performance sensors measuring heat, vibrations, speeds and other data sources can create a cyber and physical operating picture of the asset lifecycle.”

SEE: 5 edge computing predictions for 2021 (TechRepublic)

So, if you’re a production manager or a support person, you get an immediate picture of what’s going on. Additionally, IT can look to leverage this information by “de-siloing” it and sending it to finance to assess asset life cycles for purposes of amortization schedules; to engineering for purposes of workflow redesigns in the plant if needed; and to purchasing to look at new equipment to replace those assets that are downtime-prone.

“When you leverage edge resources, you want to look for areas of natural extension of IT capability and asset visibility,” Wilson said. “You also want to take a proactive approach to solving business problems. Above all, you want visibility. Without this technology, you have thousands of devices sending data, and it can take a lot of time to find the problem.”

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