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Our new habits generate an explosion of data …and data centers
The digitization of our world has had a profound effect in every aspect of our daily lives, and that trend is expected to continue and accelerate. That trend has been the basis for the massive buildout out Datacenter buildings, where the entire building is the Datacenter. Over the past two decades, these buildings have grown in both physical size and electrical density, now averaging >100,000 sq ft and 10s of Megawatts.
Arguably, this market represents some of the best designed, built, and operated buildings in the world. Datacenters are optimized around the highest efficiency and sustainability practices and do so while being incredibly resilient to provide the uptime required by the most demanding of customers. North America is the epicenter when it comes to the Datacenter builds with 5X more buildings than anywhere else in the world. Not only is there an extraordinary rate of new datacenters being built, there are already thousands of Datacenter buildings in existence – all built with the latest technology at the time, but as we know, technology evolves.
One of the biggest challenges is the complexity to operate and maintain them
One of the biggest challenges in this market is the complexity of the sophisticated system built matched with the skill set needed to operate and maintain them. Typically, the experts that built the Datacenter are not the ones maintaining it. There are many options for datacenter owners on who they can leverage for Services including their own staff, the manufacturers of equipment installed, third party Service companies, etc. Regardless of which path a datacenter operator takes for service, there is a common challenge of a workforce shortage that we are up against. Many service technicians are reaching retirement age and causing a knowledge drain within the industry. These exits are putting pressure on the continued resiliency and effective operation and maintenance of the facility due to the “tribal knowledge” native to those sites and personnel – and that knowledge is not easily passed down due to complexity.
There is not one solution for this challenge, it will require a multi-dimensional approach.
Luckily, the Datacenter space has a long track record of embracing and testing new, effective technologies and processes to advance their capabilities.
Let’s explore 3 innovative ways to solve for this challenge
Connectivity
First, if we start in the design and build phase of the datacenter lifecycle, the existing infrastructure must advance to enable actionable intelligence, and this starts with connectivity. To be able to analyze, you need the data – and that requires connections where available. Reigning in this data is no easy feat and involves several criteria, including cyber security and data sovereignty, that need to be addressed. But the technology exists today and can be effectively deployed. Yet data alone is useless without the right domain expertise that can help turn the data into outcomes for the datacenter business and industry. Those outcomes include problem diagnosis before failure occurs which enables a reduction of service dispatches to a site. Anytime a dispatch of a human to enter a datacenter environment occurs, there is an increase in risk and cost. We must build to avoid these dispatches whenever possible.
Remote Expertise
Further, to address the shrinking pool of talent to analyze as well as react to these data driven outcomes, the industry needs to adopt a network of remote experts in a “bureau” architecture. It is becoming impossible to have experts physically available at every site. The approach here is like the medical industry where you can get an x-ray taken at a local clinic – which is then sent to an expert in that category (arm, leg, etc.) for review. This gives the ability to provide a best-in-class experience without an expert in every clinic. This approach in the Datacenter space not only allows for the collected data to be analyzed by a resident expert remotely, but this centralization of knowledge also enables machine learning. Capturing these events/diagnosis/resolution enables the creation of an actionable knowledge base that can not only lead to faster resolutions but also the predictive and preventative exercises that eliminate failures and downtime.
Extended Reality
Advancements in Extended Reality (XR), virtual reality with augmented reality, will help to solve the actual on-site presence for diagnostics and repair. Leveraging that central bureau knowledge base supported by machine learning over time, these XR tools will enable readily available talent that do not have to be experts in a specific field to address safely and reliably many of the on-site requirements through digitized step-by-step virtual operation or maintenance procedures. This all translates to having the right capabilities with the right parts and solutions at the right time. These new approaches directly support a more sustainable business as there a fewer truck rolls and otherwise waste in the process.
Imagine the datacenter of the future capable of self-diagnosis
Workforce shortage challenges do not only exist in the operate and maintain phases of the datacenter lifecycle, but they also exist in the design and build phases. As mentioned above, the growth of the datacenter market has no signs of slowing down. The best way to avoid workforce shortage challenges in the future is to design the system to be as smart as it can be to self-diagnose. Data is king and every byte of information that can be leveraged should be captured. XR is extremely valuable at this stage as well, where you can create virtual models and digital twins of the build where they can be leveraged into “as built” models for operational excellence. This not only eliminates waste in the design and build phase (faster cycle times, more sustainable, etc.) but also enables the machine learning and benefits outline above in the operate and maintain phase. Hardware technology plays a key role in the overall reliability and circularity of the system. It is accepted that hardware failures will happen, so the key is to design and build a system that proactively identifies when and where it will occur and ensure that it will not result in downtime. The next key is the ability to modernize and repair that hardware without need to rip and replace the entire unit. The ability to effectively modernize or repair has several benefits that include faster cycle time, think about supply chain constraints on entire units versus parts repair, as well as sustainability (specifically circularity where modernizing increases life expectancy and lowers carbon footprint).
Preparing the new talents of tomorrow
Finally, one of the most obvious ways to mitigate risk of the workforce shortage is to develop new talent to enter the Datacenter workforce. We need to support programs that are focused on the unique dynamics of the datacenter market, providing the right curriculum and tools to ensure we develop existing talent and bring new talent into the market. Programs like SMU’s Masters in Datacenter Engineering program are focused on building talent that will take this industry to the next level. SMU’s program was designed by leaders in the Datacenter industry and focuses on developing talent that will innovate to design, build, operate and maintain datacenters more effectively in the future.
The Datacenter market continues to be one of the fastest and most interesting segments in the world but is not immune from the market challenges around sustainability and serviceability. Luckily, we are seeing technology advance at a rapid pace to help solve for these challenges. However, this problem cannot be solved by any one entity, it will take an ecosystem of industry leaders working together to proactively address, innovate, take risks and drive change. This ecosystem includes academia and the development of specific Datacenter practice and education to enable a new generation of experts in this space. With this holistic approach throughout the lifecycle, Datacenters can continue to hold a leadership position around best practices in the industry.
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Other related blogs:
The Way to Predictive Analytics: Creating Data Infrastructure (se.com)
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