Many pioneering private and public organizations today are on a fast track to make breakthroughs that will revolutionize their respective industries and research fields. They’re using powerful technology to drive advancements in disease treatments, sustainable energy solutions, manufacturing processes, and beyond.
Of course, research and development (R&D) plays a huge role in this progress. In 2020, U.S. spending on R&D increased by $51 billion, taking the total to $717 billion, and ongoing estimates for 2021 indicate further increase up to $792 billion. But one area that has not gotten the attention it deserves for the role it plays in advancing discoveries and supporting R&D is the IT department.
Data drives innovation for any organization. This couldn’t be truer for research teams that are processing and analyzing enormous amounts of data to make groundbreaking discoveries. That means IT infrastructures must be carefully designed to support the data boom that’s fueling business growth and research initiatives. Storage technologies in particular must support many increasingly complex and resource-intensive applications being fed by ever-expanding amounts of R&D data at companies and universities across the globe.
But one of the most common issues that I’ve noticed in my experience helping organizations deploy high-performance computing (HPC) solutions is a fundamental disconnect between the IT department and the researchers they’re supporting. I’ve often heard researchers complain that their data storage was too slow, unreliable, or couldn’t scale to meet their growing research needs. On the flip side, the IT teams would counter that the researchers don’t properly plan or communicate their data performance and capacity requirements. This results in IT departments making storage decisions that don’t support research initiatives, and researchers reporting that an infrastructure decision is severely reducing their productivity.
Here are three ways companies and research universities can better balance IT demands with researchers’ needs:
Get stakeholders, IT, and researchers on the same page
When IT staff and decision makers lack baseline knowledge of the research team’s goals, they will focus on upfront costs and tend to select cheaper, less flexible solutions. A solution that saves a significant amount of money upfront may seem like a smart choice, of course. But making a technology decision based solely on upfront savings often doesn’t adequately serve the research, let alone promote long-term growth.
The most successful organizations will be the ones that make sure that IT, the stakeholders, and the researchers are all in lockstep on mission goals so that the right technologies – the ones that can scale to support current and emerging applications – will be selected the first time around.
Don’t let the wrong questions guide you
An organization with a mission to advance the causes of science and engineering should not be asking how they can save money first. The primary question needs to be how they can better serve the research and the future direction on that research.
Singularly focused solutions simply cannot support research at scale. Take a look at your infrastructure and identify areas to modernize. Select solutions that support your existing infrastructure and can scale without disruption to support research missions as they evolve and grow.
Don’t let data storage be an afterthought
Here’s a reality that’s overlooked too often: Storage is a bedrock of research.
For instance, let’s look at the life sciences industry. Every month, labs produce terabytes of data from genomic sequencing and cryogenic electron microscopy (cryo-EM). Failure to take storage infrastructure seriously here has big consequences, including data loss, performance bottlenecks, rising maintenance costs and, most importantly, slowing the research momentum from a fast track to a crawl.
As research has boomed, so too have the accompanying storage and compute requirements. Researchers are analyzing genomic and molecular data on a large scale and in real time. As such, performance and capacity scaling have become critical factors.
An example is The UC San Diego Center for Microbiome Innovation (CMI), a world-leader in discovery on a mission to develop new methods for manipulating microbiomes to improve human health and the environment. CMI’s data-intensive research required analysis of dynamically growing volumes of data among multiple team members. Their growing number of I/O-intensive tasks resulted in storage performance and manageability issues, leaving the IT team unable to support innovative research methods.
After investing in a high-performance storage solution, CMI built the data foundation they needed for continued research excellence, including the power to expedite data exploration and discovery with better control, usability, and optimal uptime. This is just one example of how the right storage technology investment successfully addressed the challenges faced by both the IT teams and researchers alike.
Technology should never be viewed as a barrier to R&D; rather, it should be viewed as a catalyst. Research is only going to accelerate, and so too will its storage and computing requirements. IT teams must work closely with researchers, align on priorities, and make adjustments as needed to drive research forward.
About the author
Jeff Whitaker, VP, Marketing and Product Management, Panasas
Jeff leads the Product Management and Marketing teams at Panasas, with a focus on making inroads into new markets and expanding the company’s revenue growth.
Jeff is a veteran technology leader with more than 25 years’ experience developing innovative storage, semiconductor, and networking solutions. He was previously VP of Product at Excelero and a founding member of the cloud team at NetApp. For over a decade, Jeff designed products that helped customers around the world transition their complex IT environments to run on the top three public cloud providers.
Jeff holds a Bachelor of Science in electrical engineering from California State University at Chico.
