HPE commissioned Forrester Consulting to conduct a Total Economic Impact™ (TEI) study and examine the potential return on investment (ROI) enterprises may realize by deploying HPE Nonstop Compute.¹ This abstract will focus on organizations with smart manufacturing operations, their use of HPE Nonstop, and its value to their organizations.

The interviewees are in the manufacturing industry and included:

• A business leader at an EMEA-based organization with $50 billion to $99 billion in annual revenue.

• A data and AI product manager at a North America-based organization with $25 billion to $49 billion in annual revenue.

• A director of industrial automation at an EMEA-based organization with $10 billion to $24 billion in annual revenue.

HPE Nonstop systems provided their organizations with a fully integrated, fault‑tolerant platform designed to keep mission‑critical workloads running continuously without service interruption, and failover at the millisecond level. It combines fault tolerance via a shared-nothing, full-system clustered architecture; built‑in high availability; and modern system interfaces. The platform also delivers high scalability, which is the capacity to ensure consistent, always‑on operations with high uptime SLAs, even as the solution grows in volume and use cases.

Interviewees noted that prior to using HPE Nonstop systems, their organizations’ environments experienced challenges like latency inflation, packet loss, and timing drift across long distance and wireless links, which required additional middleware and data‑path monitoring. They faced performance strain from physical‑equipment cycles, unpredictable IoT conditions, sensor loss, remote‑site data gaps, and balancing loads across widely distributed middleware and edge layers.

They deployed HPE Nonstop systems across a broad physical footprint, spanning hundreds of sites including factories, renewable‑energy facilities, and remote locations where data traveled long distances across optical networks or low‑power IoT links. Their HPE Nonstop environments managed continuous data flows across industrial automation systems, IoT sensors, and edge devices. Their workloads covered shop‑floor coordination, manufacturing execution systems (MES) and quality management system (QMS) functions, renewable‑energy telemetry, AR/VR‑enabled quality systems, and enterprise‑scale inventory and e‑commerce data processing. The interviewees described a broad set of HPE components for their smart manufacturing organizations, including middleware balancing, pathway monitoring, distributed processing, remote database functionality, and features supporting hundreds of unique operational contexts.

Investment Drivers For Smart Manufacturing  Organizations

The interviewees’ organizations adopted HPE Nonstop systems to mitigate the high costs of downtime for mission-critical workloads. Prior to deploying Nonstop, interviewees described how their technology ecosystems lacked the resilience, security, and scalability demanded by high‑volume operations. Core industrial systems showed signs of structural fatigue, creating exposure across performance, risk management, and operational continuity. A lack of available local troubleshooting resources as well as supply chain and geopolitical impacts all exacerbated the interviewees’ organizations’ pain points around maintaining high availability.

Across these industrial environments, interviewees noted how their organizations struggled with common challenges, including:

• Operational and brand impacts due to performance lags and downtime of critical systems. Interviewees described operational slowdowns and disruptions that occurred due to latency, delayed data updates, and synchronization failures between central and site-level databases. The consequences cascaded into  production losses, wasted energy, quality‑assurance failures linked to delayed or incomplete data flows, and other significant operational and downtime-related losses.
  The business leader at a smart manufacturing conglomerate said their organization needed to transmit data across distances of up to 30 km from edge devices to middleware, which caused significant latency and data loss even after relocating middleware closer to the source. Data expected within 10 seconds often arrived after 30 to 35 seconds with substantial gaps, creating major operational challenges. They then described the cascading impacts of downtime in their prior environment: “If there is interruption, the [manufacturing execution system] (MES) and the [quality management system] (QMS) will definitely become impacted, so the quality of the product will be impacted. If the complete latency is coming in, the data volume has been large, [or] the data frequency is being delayed, the operation will be impacted. The quality will not be achieved, and that non-quality product will be served to the people and the customers — that will impact your brand. The first realistic impact of your latency is the brand value reduction.”

• Security gaps. Interviewees shared how cyber incidents in their organizations’ prior environments exposed deep weaknesses in older system layers. Insufficient segmentation allowed cyberactors to penetrate deep operational layers, revealing weaknesses in legacy systems and insufficient isolation across critical operational technologies (OTs). These gaps complicated recovery efforts and increased reliance on manual governance, reporting, and forensic activities. At the same time, data collection pipelines across manufacturing sites suffered from inconsistent protection. The distance between physical and edge layers, combined with outdated gateway architectures, had created vulnerabilities in IT/OT integrations and increased the likelihood of misrouted signals, data leakage, corrupted data flows, and insecure exchanges across distant sites and gateways.

• Constraints to operational and revenue scalability. The interviewees reported that capital and operational costs also magnified scalability constraints. Aging legacy hardware required costly resource optimization and expensive capacity cycles. Additionally, operational environments lacked real‑time, high‑resolution data inputs necessary to scale connected operations across diverse sites and support predictive analytics, autonomous decisioning, and large-scale digital transformation.
  The director of industrial automation at a smart manufacturing conglomerate shared: “We did not have standardized databases, so for AI purposes, we could not really do analytics on a global scale. The other big pain point for us was the costs at a plant level. They were not manageable at an enterprise level because we had disparate systems with disparate contracts and different versions and different vendors in play.”

HPE Nonstop Features

The interviewees discussed how their organizations searched for a solution that could support uninterrupted, continuous operations of critical workloads, align with modernization goals, and enable scalable, data‑driven capabilities across complex environments. They required large‑scale data‑governance structures, such as industrial data fabrics, industrial knowledge graphs, remote database facility (RDF) migrations, and automatic storage‑management features, to manage highly heterogeneous datasets. In particular, the solution needed to ensure:

• High‑performance uptime across critical workflows. Interviewees noted that their organizations selected HPE Nonstop systems because of the ability to operate continuously without downtime, sustain workload‑intensive processing cycles, deliver predictable throughput, and manage failures without impacting live services. The interviewees’ organizations required consistent performance, redundant components across all system layers, and mechanisms that maintained processing during failures. In distributed and industrial settings, the platform needed to support steady data capture; manage latency across long distances; and maintain reliable communication between physical equipment, edge systems, and central platforms.

• Enterprise modernization and platform security. Interviewees described how their organizations sought a more unified operational model with HPE to replace fragmented legacy environments. The platform needed to enable parallel workloads and maintain predictable performance across diverse locations. The interviewees’ organizations also required centralized administration, flexible deployment options for on‑premises and IoT edge devices and systems, as well as diagnostic visibility and predictable cost structures that aligned resource use with workload demand.

• Insight‑driven architecture for advanced analytics. The interviewees emphasized the importance of HPE Nonstop systems’ capabilities to support real‑time and near‑real‑time data access, with robust data‑collection pathways and monitoring tools to improve visibility and decision confidence. In particular, they noted the need for an advanced data layer to enable and scale AI and big data initiatives without disrupting core operations. Integration across multiple operational tiers was essential. The platform needed to coordinate data effectively, operate stable middleware, and support load‑balanced pathways without introducing bottlenecks.
  The director of industrial automation at a smart manufacturing conglomerate told Forrester: “In order to begin to use big data and AI, we needed to standardize our platform to be able to get to the point where we could do analytics that were meaningful on a global level. … We’re looking to have zero downtime because downtime for us is money.”

Key Results For Smart Manufacturing Organizations

The results of the investment for the interviewees’ organizations include:

A 90% increase in uptime for 24/7 mission-critical systems. Interviewees reported that HPE Nonstop systems consistently delivered higher stability, stronger performance, and more resilient operations across different environments. These systems supported continuous availability, reduced operational incidents, and provided a stable foundation for critical workloads that required uninterrupted throughput and predictable latency. Additional benefits for smart manufacturing organizations included:

• Broad-based improvements in uptime and availability. Interviewees reported that the HPE Nonstop systems increased total processing efficiency by improving transaction throughput, reducing latency, and strengthening system responsiveness, even at peak load. The data environment also became more consistent, as parallel processing and fault‑tolerant database structures reduced corruption risk and supported reliable real‑time analytics. As a result, overall uptime increased into the 99.99% to near-100% range, and once-common unplanned outages were effectively eliminated.
  The director of industrial automation at a smart manufacturing conglomerate shared how their organization significantly reduced downtime for mission-critical systems with the investment in HPE Nonstop: “[Now, our downtime is] approaching zero [with system availability] at >99.999%. … The reality is [that Nonstop] has massive parallel processing capabilities such that before, when we had to update 43 locations, it would take us a week, and now it takes us a couple of hours. That’s part of the whole availability equation. … The latency of the system itself is near zero, [and] these particular systems can handle up to 8 TB throughput, so that’s a lot.”

• Faster and more seamless failover capabilities. Nonstop’s fault‑tolerant architecture enabled instantaneous failover between system components, which reduced and removed bottlenecks and operational delays.
  The director of industrial automation at a smart manufacturing conglomerate shared that the platform’s built-in fault tolerance allowed instantaneous, seamless failover and ensured uninterrupted operations compared to the prior environment, which required up to an hour. They said: “[If] one instance of the OS goes down, the other one takes over flawlessly with no recovery or downtime. You can’t even tell the difference if one went down, with zero downtime in between.”

• Improved system performance. These gains in uptime and failover also contributed to better performance, lower variability during high‑demand periods, and a more predictable user experience. Manufacturing operations benefited from real time visibility, which improved production efficiency, supported predictive maintenance insights, and reduced downtime.

A 75% decrease in exposure to breach costs. Interviewees shared how the use of HPE Nonstop strengthened the overall security posture and created a more resilient operational environment by reducing alert volume, lowering unauthorized access attempts, and decreasing severe attack exposure. The platform reduced exposure to threats, improved incident stability, and supported more efficient oversight of large‑scale environments. Its architecture enabled consistent protection across data‑intensive workflows. With HPE Nonstop systems, smart manufacturing environments further benefited from:

• Proactive and reactive security optimizations. Interviewees described how the Nonstop platform reduced exposure to threats, improved incident stability, and supported more coordinated disaster recovery for cyber incidents across large‑scale smart manufacturing environments. Security patching and update cycles became faster, reducing downtime windows by 18% to 20% and minimizing operational vulnerability during maintenance. The consolidated security stack reduced the need for multiple third-party security tools, lowering operational overhead while maintaining protection.
  The data and AI leader at a smart manufacturing firm shared: “[We had a] cybersecurity incident where there were criminals that had … penetrated through to the deepest level of all manufacturing systems. … [With HPE Nonstop systems in place during the aftermath], there weren’t any delays in getting our MES system, our reporting, our parts tracking, all of our IoT and related infrastructure, and associated connected services [back up] whether that’s the manufacturing sides or related to our [products] in terms of usage and diagnostics data. There was no sort of delay in getting these systems back up and running.”

• Improved data protection. HPE Nonstop systems supported structured data protection from plant floor devices to enterprise systems, with early anomaly detection helping secure operational workflows.
  The business leader at a smart manufacturing company shared how HPE Nonstop systems helped close data security gaps that had previously occurred during data flows from their manufacturing facilities’ physical layer to and from their organization’s middleware, noting that any anomalies were now detected at a much earlier stage.

• Streamlined adoption of Zero Trust security principles. HPE Nonstop systems’ centralized security controls established more consistent governance across distributed facilities, which improved compliance and strengthened Zero Trust alignment.
  The director of industrial automation a smart manufacturing firm shared: “Security is always complex, right? However, with the more standardized and more centralized HPE Nonstop systems, we were able to achieve what’s called Zero Trust Access Control. It helped us to simplify our compliance for both our customers and our insurance carrier. They base how much we pay in premiums for cybersecurity insurance based on our ability to achieve a Zero Trust Access Control environment and to integrate our identity management systems and also at the same time, ensuring the highest availability with sensitive types of transactional data.”

Improved operational and revenue scalability worth $23.3 million for the composite. Interviewees shared how HPE Nonstop systems provided their organizations with stable data foundations and centralized control. The platforms supported pay‑as‑you‑go capacity models, which reduced barriers to launching new revenue streams and sustaining service quality at scale. Interviewees further highlighted how HPE Nonstop systems:

• Augmented operational agility. Interviewees noted that Nonstop’s elastic clustering scaled capacity on demand, allowing their teams to direct resources to hot spots without long procurement cycles. Provisioning, regression testing, and post‑scale normalization completed in less time, which reduced the window between scale‑up and revenue realization. Pay‑as‑you‑go models aligned cost with utilization, supporting profitable scale. Multisite operations provisioned and updated in hours rather than weeks, and new instances replicated in about an hour, which accelerated the expansion of production capacity. The increase in overall equipment effectiveness rose by roughly 10% to 12%, which increased available production time and throughput, directly supporting revenue scaling. Large headroom in centralized MES capacity supported expansion across many additional locations before hardware growth became necessary, preserving scale momentum while containing cost.
  The director of industrial automation at a smart manufacturing conglomerate described the dynamic scalability of their organization’s HPE Nonstop environment: “With HPE, we like the [scalability and pay-as-you-go setup]. It’s like the equivalent of having your own hyperscaling system with even better system availability than cloud providers. … Right now, we are provisioned at about 25%, [so] we would have to scale up to 160 locations before we would even need to talk to HPE to increase our hardware capacity. But the great part about that scalability is that we’re only being charged for pay-as-you-go. So, yes, we have the scalability, but we’re only paying for what we’re using.”

• Improved revenue and margin. Interviewees noted that the data foundation their organizations gained through HPE Nonstop systems helped them scale faster and normalize more rapidly. Stable, real‑time data across production flows reduced cancellations, rework, and leakage, which reinforced both top‑line and margin outcomes. By removing IT bottlenecks from the critical path, the platform enabled continuous availability and predictable performance, which sustained customer‑facing services at higher volumes.
  The business leader at a smart manufacturing conglomerate shared that their organization grew from $48 billion in annual revenue to $65 billion in the three years following their initial deployment, attributing a measurable portion of this growth directly to their investment in HPE Nonstop systems: “I would say around 0.23% of the complete growth is coming from the data foundation, AI/ML capabilities, the governance of data, and how we are actually utilizing the data [and] the good insights [it provides]. We have seen benefits for productivity, for energy efficiency, for sustainability, for governance, and [for] data privacy.” 

• New AI-developed product and operational innovations informed by Nonstop’s real-time data analytics. HPE Nonstop systems delivered low-latency, live data pipelines that supported preparation of high-quality data layers and consistent, scalable integration across enterprise and industrial systems. These capabilities enabled AI/ML, agentic AI, and analytics to run reliably and at scale. Interviewees noted how the Nonstop environment sustained real-time data quality, which expanded AI use cases across process, quality, engineering, and maintenance functions. Continuous connectivity supported anomaly detection and operational analytics, which strengthened decision accuracy during demand growth. Stable data governance and real-time insights helped reduce cancellations, rework, and revenue leakage.
  The director of industrial automation at a smart manufacturing conglomerate shared that, prior to the HPE investment, their organization was decentralized and their database structures were not standardized. After the HPE investment, their organization was able to leverage the platform’s capabilities to standardize data and provide the ongoing transactional accuracy needed to be consumed by large language models. They shared, “From the standpoint of fault tolerance of our databases — since these databases are running on multiple copies of systems simultaneously — these databases are flawlessly updated, and the potential for data corruption within those particular instances is near zero.” The director of industrial automation a smart manufacturing firm shared: “[HPE Nonstop systems] have given us a competitive edge to be able to use our data for creating LLM models and for the capabilities to do digital twinning of our particular products in order to [enhance] overall quality improvement.”