Legacy Meets IoT: Leveraging SaaS for Smarter Manufacturing

When the old and new converge in the Internet of Things, the familiar anchors our confidence. Joseph Zulick of MRO Electric and Supply notes that the greatest challenges arise when solutions lie outside our existing mental models.

Software as a Service (SaaS) ranges from industry titans—Adobe, Amazon Web Services (AWS), Microsoft—to niche startups. Traditional wired systems and bespoke software have given way to modular hardware that streams data over networks and plugs directly into cloud‑hosted services.

Today, sensor manufacturers are designing interfaces that aggregate data through fewer endpoints, enabling richer analytics while reducing complexity.

SaaS: Robust, Flexible, and Ever‑Updating

SaaS platforms deliver resilience and adaptability that on‑premise solutions rarely match. Take Waze—user‑generated reports feed real‑time traffic updates, illustrating how collective input refines navigation. Likewise, CRM giants such as Salesforce and collaboration tools like Slack and Basecamp keep evolving to meet remote‑work demands.

Zoom’s growth exemplifies the power of continual iteration: its revenue rose 77.93% year‑over‑year in 2020, a figure verified in the company’s annual report. The platform’s frequent updates are a hallmark of SaaS’s commitment to rapid improvement.

Mission‑Critical in Manufacturing

Remote monitoring has become essential in modern plants. SAP offers cloud‑based solutions that merge IoT data with enterprise resource planning, enabling real‑time oversight and predictive maintenance.

Companies like Xometry have flipped the model by offering manufacturing as a service: they provide software that quotes, schedules, and connects clients to standardized production partners, streamlining the entire workflow.

Manufacturing Focus

By embedding quotation engines into a SaaS platform, Xometry eliminates manual paperwork and aligns pricing across diverse manufacturers. The result is a frictionless, data‑driven marketplace.

AWS has long monetized excess compute, storage, and analytics capacity, offering it as a service. A flagship partnership with Netflix demonstrates AWS’s scalability: the streaming giant can spin up thousands of servers and petabytes of storage within minutes, ensuring uninterrupted content delivery.

Big data analytics on AWS further refines user experience by profiling viewing habits and predicting demand.

Modern SaaS solutions also embed Machine Learning—pattern detection, image recognition, anomaly identification, and segmentation—into their core. Advanced techniques such as deep learning automate model tuning, reducing the need for manual intervention.

Benefits of SaaS

Scalability: Modular architectures grow with your business without disruptive migrations.

Lower upfront costs: Pay-as-you-go pricing eliminates large capital expenditures and allows continuous refinement of features.

Bias detection: Built‑in analytics can surface hidden biases in data or processes, supporting fairer outcomes.

While hidden upgrade costs can arise, the predictable subscription model simplifies budgeting and frees organizations from depreciation accounting.

Author: Joseph Zulick, writer and manager at MRO Electric and Supply.