There is an ongoing global memory chip shortage that is having a ripple effect across industries — what tech media and analysts have dubbed “RAMageddon.”
Some businesses have chosen to purchase ahead of schedule or consolidate purchases to mitigate any impact from rising costs. Others are considering services that could extend lifecycles, or they’re working with what they have or holding off on any wholesale refreshes.
In healthcare, research-heavy institutions may be especially affected as they rely on storage and analytics that are supported by large compute infrastructures. They may decide to grin and bear it, and buy now, or push their assets for as long as possible. All of these are tough financial and operational decisions to make as future supply and pricing dynamics remain unclear.
The bottom line is that this isn’t a temporary problem. We’ve heard from strategic manufacturers that customers, across industries, should prepare for persistent volatility rather than waiting for things to get back to normal.
This is normal for the foreseeable future. Demand is not going to slow, and the interconnected issues will not self-correct.
But healthcare organizations should know that they are not alone in experiencing supply-chain issues. Instead of trying to solve concerns themselves, they should connect with their peers and other partners to find the best path forward.
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Evaluating Healthcare Infrastructure: Workloads for On-Premises, Cloud and Edge
Many healthcare organizations have shifted their focus from endpoint refreshes — which may feel easier to handle — to prioritizing lifecycle management for servers, storage and networking hardware. That has led to re-evaluating hybrid infrastructures, with concerns not just about performance but also as an approach to mitigate risk.
This raises the question: Which workload is served best by which infrastructure?
- On-premises: Organizations that are moving latency-sensitive or high-volume data (such as medical imaging) that require high speed and performance to on-premises infrastructure, while leveraging AI to optimize and navigate accordingly
- Cloud: These will be the workloads less dependent on speed. We expect certain data analytics and modern contact centers to leverage more cost-efficient cloud solutions.
- Edge: Workflow optimization processes that leverage AI in patient rooms (such as ambient listening) will use in-room edge components.
As AI-powered solutions and features become more normalized, organizations are evaluating whether they have the infrastructure ready to support high-performance demands. Healthcare systems are making big bets by saying, “If I’m going to spend very strategically for the future, I’m going to want an AI-ready infrastructure.”
READ MORE: Follow this five-step action plan for achieving clinical care resilience.
The Critical Role of a Strategic Partner
At CDW, we’ve helped various enterprises with strategic planning to determine which workloads fit best with which infrastructure. We can help organizations navigate through different assessments to make the right choices for their environments.
A strategic partner is especially useful for logistics and operations, including for adaptive procurement models. At CDW, we can help organizations leverage our logistics capacity to configure and stage equipment to meet go-live events, cutovers or deadlines tied to platform upgrades. Such planning allows us to get ahead of potential price increases while also making sure that organizations have the equipment needed for project rollouts so milestones can be met in a timely manner.
In evaluating their current environments, organizations may also want to call on a partner to do an application rationalization assessment and look for areas of duplication that could help to reduce costs so that that budget can be reinvested in standardizing across the enterprise.
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We work with top-tier vendor partners at CDW, and we’re having similar conversations about volatility and cost controls. We understand the complexities of product and supply. We have an overview of hybrid and multicloud architectures, and we understand the implications of AI. We have the visibility, scale and agility to help our partners through this unprecedented time.
Building Healthcare Supply Chain Resilience in a Volatile Environment
Because of how fast-paced change has been, AI integration could easily outpace the technology investment organizations have. They may not be able to take advantage of emerging AI solutions because they’re dealing with ever-accumulating technical debt. But they can’t just buy more capacity — there’s a limit to that.
DISCOVER: How to manage a virtualization migration in healthcare.
Organizations must plan for capacity and for risk, and have a clear picture of their goals over the course of the next one to three years. What is the measurable outcome they want to deliver with their current investments? What additional investments are needed to deliver those outcomes? Have they overextended?
Modernization must go hand in hand with discipline, with clear strategies for governance, investment and predetermined metrics on how impact and outcomes will be measured. A growing number of enterprises are less likely to sign multiyear agreements for solutions unless there is clear near-term ROI and long-term clarity on strategic outcomes.
Emerging technologies are moving incredibly fast, so organizations must achieve the outcomes that align with their strategic goals to ensure future investment in innovation.
This article is part of HealthTech’s MonITor blog series.
