Shifting Left and North: The New Frontier in Industrial Automation for Smarter, Faster, and Scalable Operations

In the fast-evolving world of industrial automation, the ability to accelerate innovation while maintaining high reliability and operational efficiency is critical for long-term success. Two emerging strategies—shift left and shift north—are transforming how companies design, deploy, and manage automation systems.

Shift left focuses on integrating testing, simulation, and optimization early in the development cycle, enabling faster detection of defects and smoother system deployments. By leveraging model-based design, hardware-in-the-loop testing, and CI/CD pipelines, companies can reduce commissioning times, minimize costly rework, and improve system resilience.

On the other hand, shift north pushes automation beyond the factory floor by integrating operational technology (OT) with information technology (IT). This vertical integration enables real-time data flows between shop-floor devices and enterprise systems, driving smarter, data-informed decisions. By adopting IIoT platforms, edge computing, and cloud-driven architectures, businesses can gain deeper visibility into their operations, optimize resources, and scale effortlessly in response to demand.

Together, these strategies provide a technical edge that enhances both system performance and business agility, equipping industrial automation companies to thrive in the era of Industry 4.0.

Shift Left in Industrial Automation

From a technical perspective, shift left in industrial automation focuses on integrating quality, testing, and optimization processes earlier in the system development lifecycle (SDLC). This approach leverages a variety of advanced tools and methodologies:

1. Model-Based Design and Simulation:

- Tools like MATLAB/Simulink, ANSYS, or Siemens Tecnomatix allow for the creation of digital twins and virtual prototypes of automation systems. Engineers can simulate process flows, PLC logic, and hardware interactions before deploying physical equipment.

- This early simulation helps in detecting bottlenecks, inefficiencies, and control logic issues without the need for physical hardware, thus saving time and costs.

2. Continuous Integration and Continuous Deployment (CI/CD):

- Automation companies are increasingly adopting CI/CD pipelines in software development, such as for PLC programming or SCADA system configuration. Tools like Jenkins, GitLab CI, or Azure DevOps allow for:

- Automated building, testing, and deployment of control system code.

- Early detection of integration issues by running tests against simulated environments (e.g., using containers like Docker or virtual machines).

- This reduces lead times and minimizes integration risks as each code commit is automatically tested against predefined criteria.

3. Early Hardware-in-the-Loop (HIL) Testing:

- HIL testing allows automation engineers to test control algorithms and PLC logic against real-time physical models of machinery or plant systems.

- By shifting HIL testing earlier into the development phase, potential issues related to hardware integration can be identified early, ensuring that the system works seamlessly once the physical components are connected.

4. Predictive Maintenance Design:

- Incorporating sensor diagnostics and predictive analytics early in the design phase, automation systems can integrate with condition monitoring tools such as OSIsoft PI, ThingWorx, or IBM Maximo.

- Predictive maintenance frameworks are built into the automation infrastructure early on, allowing real-time monitoring of equipment wear and tear, thermal performance, and vibrations. This approach not only helps with early fault detection but also ensures that the overall automation system is robust and adaptable to real-world changes.

Shift North in Industrial Automation

Technically, shift north means driving more vertical integration between operational technology (OT) on the shop floor and the overarching business systems (IT). This integration involves creating a unified architecture that spans both the physical production processes and higher-level business logic, using key technologies and frameworks:

1. Industrial IoT (IIoT) and Edge Computing:

- Devices at the edge (e.g., sensors, actuators, PLCs) are increasingly connected via IIoT platforms such as Siemens MindSphere, GE Predix, or AWS IoT Greengrass.

- These systems allow edge devices to process data locally in real-time (via edge computing), while sending only the necessary data to the cloud for further analysis. This ensures reduced latency and near-instant decision-making on the shop floor while still feeding critical data to enterprise-level systems.

2. Integration of SCADA and MES with ERP Systems:

- Industrial companies are connecting Supervisory Control and Data Acquisition (SCADA) systems and Manufacturing Execution Systems (MES) with higher-level Enterprise Resource Planning (ERP) platforms like SAP or Oracle.

- OPC-UA, MQTT, or other industry-standard protocols are used to facilitate seamless data exchange between OT and IT systems. This enables real-time monitoring of production KPIs (like OEE, energy consumption, or cycle time) while feeding actionable data into financial, inventory, and supply chain management modules.

- For example, real-time data from machines can trigger automatic replenishment orders or adjust production schedules based on demand forecasts.

3. AI-Driven Analytics for Operational Optimization:

- AI and machine learning models are increasingly being integrated into automation systems to predict trends, optimize processes, and adjust operational parameters in real-time.

- Platforms like Azure AI, Google Cloud AI, or IBM Watson use data from production lines to feed predictive models, allowing systems to automatically adjust variables such as temperature, speed, or pressure for optimal performance.

4. Cloud and Edge-Cloud Hybrid Architectures:

- Companies are deploying hybrid architectures where critical operational decisions are made on the edge (e.g., in real-time PLC controllers), while larger-scale data processing and analytics occur in the cloud.

- By shifting north, companies are adopting cloud-native industrial platforms like AWS IoT Core, Microsoft Azure IoT Hub, or Google Cloud IoT, which offer scalable infrastructures for managing complex multi-site operations while allowing remote monitoring, diagnostics, and optimization.

Impact on Industrial Automation Companies...and beyond

For industrial automation companies, adopting shift left and shift north has several technical advantages:

- Faster Time-to-Market: By moving testing, simulation, and optimization earlier (shift left), companies can reduce commissioning times and catch bugs early in the development lifecycle.

- Improved Interoperability: The shift north approach connects traditionally siloed OT and IT systems, enabling data-driven decision-making across different layers of operations. This improves not only machine-to-machine (M2M) communication but also machine-to-business interactions, enhancing overall agility.

- Scalability and Flexibility: With cloud-based architectures and integrated IIoT platforms, companies can scale their operations globally while maintaining centralized control and visibility, adjusting to changing production demands dynamically.

- Resilience and Predictive Capabilities: Shift left ensures systems are more resilient by focusing on early fault detection, while shift north enhances predictive maintenance and operational optimization, reducing unplanned downtimes.

What's in it for me?

From a business value perspective, integrating shift left and shift north strategies into industrial automation delivers several key advantages.

Shift left reduces the risk of costly late-stage defects and rework by emphasizing early validation through tools like model-based simulations, HIL testing, and automated CI/CD pipelines. This approach leads to faster development cycles and a more robust deployment of automation systems. The result is lower total cost of ownership (TCO), reduced downtime, and higher overall equipment effectiveness (OEE)—crucial metrics that directly impact a company's bottom line.

By shifting north, companies can unlock real-time, data-driven insights that extend beyond traditional operational layers. Vertical integration between OT and IT systems allows for seamless data flow from the production floor to ERP, MES, and SCADA platforms. This level of integration ensures that strategic decisions are based on accurate, real-time operational data. Businesses benefit from improved supply chain efficiency, predictive maintenance that minimizes unplanned downtimes, and enhanced resource optimization.

Adopting cloud and edge computing architectures further increases agility, allowing for scalable deployments across multiple facilities while maintaining centralized control and monitoring. This flexibility reduces the cost of infrastructure expansion and enhances the company’s ability to respond dynamically to market shifts, ensuring alignment with business KPIs such as time-to-market and cost-per-unit.

In essence, shift left accelerates development and deployment, while shift north enhances operational visibility and decision-making. Together, these strategies enable industrial automation companies to build more scalable, efficient, and adaptive systems, positioning them for sustained competitive advantage in a rapidly evolving marketplace.