Key terms to know

• Executive roll-up dashboard: a consolidated visual interface that aggregates data from multiple facilities, systems (ERP, MES), and processes into a high-level summary for senior leadership, allowing for drill-down into specific plant performance.

• OEE (overall equipment effectiveness): the gold standard manufacturing metric calculated by multiplying availability, performance, and quality to determine true production effectiveness.

• MES (manufacturing execution system): a software system used to control and document the transformation of raw materials into finished goods in real-time.

• Visual hierarchy: a design principle that uses size, color, and position to guide viewer attention to the most critical information first, such as aggregate downtime or safety incidents.

• Video AI agents: intelligent software that analyzes video feeds to detect specific eventslike missing PPE or unauthorized entryhelping teams use cameras more effectively for operations and safety.

Managing operations across a single facility is complex; managing them across ten or twenty distributed plants creates data fragmentation that can slow decision-making. For the VP of Operations, the difference between hitting EBITDA targets and missing them often lies in the speed of information. When you rely on lagging indicators, manual spreadsheets, or disjointed phone calls to understand why a site is underperforming, the damage is often already done.

The solution lies in the executive roll-up dashboarda centralized view that brings scattered data together into a shared, reliable summary. By aggregating insights from ERPs, production lines, and video systems, these dashboards allow leaders to monitor multi-site performance in real time. This guide explores how to build dashboards that minimize blind spots, cut manual investigation time, and support forward-looking improvements across your manufacturing portfolio.

The hurdle of multi-plant visibility

For senior executives responsible for P&L and operational excellence, the primary frustration is rarely a lack of data—it is the inability to access the right data when it matters. You might have safety metrics in one system, production schedules in another, and video footage of the shop floor completely siloed on local recorders. This disconnection creates major operational friction.

Common pain points for operations leaders

1. Reactive incident response: finding out about safety violations or downtime events days after they occur makes it difficult to address issues before they escalate.

2. Manual investigation time drain: spending hours reviewing footage or cross-referencing reports to understand why a production target was missed pulls focus from strategic initiatives.

3. Blind spots across sites: the inability to see real-time conditions across 10-20 active sites simultaneously creates anxiety about compliance and performance when you are not physically present.

4. Inconsistent reporting: different plants often use different definitions for downtime or waste, making apples-to-apples comparisons complex without considerable manual data normalization.

Spot AI addresses these pain points by integrating visual intelligence directly into your operational stack. By deploying a unified fleet-wide dashboard, Spot AI provides real-time visibility into all sites from a single interface. This allows executives to monitor operations more continuously and can cut investigation time through intelligent search capabilities.

Defining the architecture of an executive roll-up dashboard

An executive roll-up dashboard is not simply a collection of charts; it is an information architecture designed to support high-level decision-making while enabling rapid root-cause analysis.

The "roll-up" concept

The term "roll-up" refers to the hierarchical nature of the data presentation. Detailed facility-level metrics are summarized and elevated to strategic viewpoints. This design acknowledges that executives require different data presentations than floor operators. While an operator needs to know if Machine A is running now, an executive needs to know why Plant B’s efficiency dropped 3.5% this quarter.

Data aggregation strategy

To create a single source of truth, the dashboard must aggregate data from three primary layers:

1. Business layer (ERP): financials, order management, and inventory costs.

2. Execution layer (MES/SCADA): real-time production counts, machine status, and quality metrics.

3. Context layer (Video AI): visual evidence of why numbers are changing—such as bottleneck identification, SOP adherence, and safety compliance.

Modern architectures use cloud-based aggregation platforms to maintain continuous connections to these systems, translating disparate data formats into standardized enterprise metrics.

Essential KPIs for manufacturing executives

Selecting the right KPIs is critical. A common mistake is tracking everything, which leads to information overload. Effective dashboards focus on 4-7 key metrics that align with strategic business objectives (Source: ThoughtSpot).

Integrating video data for context

Numbers tell you what happened; video tells you why. For example, if OEE drops due to "Performance Loss," Spot AI can help you run a time study using video footage to identify micro-stops or inefficient material handling. By mapping video data to these KPIs, you can ground discussions in shared evidence about SOP adherence and bottlenecks.

Designing for decision-making: visual hierarchy and drill-down

The most effective dashboards employ "progressive disclosure." This means presenting summary metrics at the top level and enabling rapid drill-down to details only when necessary.

Best practices for dashboard layout

1. Summary scorecard: place the most critical enterprise-wide metrics (e.g., Consolidated OEE, TRIR) in the top-left quadrant. This matches standard reading patterns.

2. Traffic light system: use green, yellow, and red indicators to flag performance against targets. This allows an executive to scan 20 sites in seconds and identify which two require attention (Source: Factbird).

3. Hierarchical navigation:

   • Level 1 (enterprise): aggregate performance across all plants.

   • Level 2 (plant): site-specific KPIs and trends.

   • Level 3 (line/cell): machine-level data and specific video feeds.

Role-based customization

Different stakeholders need different views of the same data. A plant manager needs granular shift data, while a VP needs trend lines and cross-site comparisons. Modern dashboard platforms support role-based access, ensuring that users see the metrics most relevant to their responsibilities.

From reactive to forward-thinking: real-time monitoring and analytics

Traditional reporting is often a post-mortem exerciseanalyzing last month's failures. Executive roll-up dashboards aim to shift this dynamic toward real-time visibility and earlier detection of issues.

Anomaly detection

Advanced dashboards utilize machine learning to establish baselines for normal operations. Instead of setting static thresholds (e.g., "alert if downtime > 2 hours"), these systems detect unusual patterns, such as a gradual increase in cycle time combined with a decrease in yield. This context-aware alerting reduces false positives and highlights genuine risks.

Condition-based monitoring

Integrating sensor data allows for condition-based monitoring. Instead of servicing equipment on a fixed schedule, the dashboard monitors variables like vibration or temperature. If a bearing shows signs of wear, the system flags it for maintenance during a planned window to help reduce the risk of unplanned downtime (Source: MachineMetrics).

The role of Video AI in anticipatory safety

Spot AI contributes to this forward-looking stance by detecting safety hazards in real time.

• Forklift safety: detects forklifts entering pedestrian-only zones.

• PPE compliance: identifies workers missing hard hats or vests.

• Unauthorized access: alerts when people enter restricted areas or hazardous zones.

By surfacing these "leading indicators" on the executive dashboard, leaders can intervene to coach teams and adjust processes to mitigate injury risk and potential impact on EMR and insurance costs.

Comparison of dashboard data integration solutions

When building an executive dashboard, choosing the right integration layer is essential for getting a complete picture.

Spot AI stands out by making video footage accessible and useful for analysis. While BI tools visualize the numbers, Spot AI visualizes the physical reality of operations, SOP adherence, and safety behaviors that drive those numbers.

Implementation steps for multi-plant dashboards

Building a successful roll-up dashboard is a strategic initiative, not just an IT project.

1. Define strategic objectives: start by articulating the specific decisions executives need to make. Do not build the dashboard until you know what questions it must answer.

2. Audit data sources: identify where the data lives (ERP, MES, spreadsheets, video). Assess data quality and consistency across plants.

3. Standardize metrics: ensure that "downtime" means the same thing at Plant A as it does at Plant B. This often requires establishing standardized reason codes.

4. Design and prototype: create mockups using the visual hierarchy principles. Get feedback from the VP of Operations and Plant Managers before writing code.

5. Integrate video context: deploy Spot AI to connect visual data with operational metrics. This provides the "ground truth" for the numbers on the screen.

6. Pilot and iterate: roll out to a pilot group of facilities. Use their feedback to refine thresholds and alerts before enterprise-wide deployment.

Turning Multi-Plant Data into Decisive Action

The complexity of modern manufacturing demands a shift from intuition-based management to data-driven precision. An executive roll-up dashboard is the infrastructure that makes this shift possible. By aggregating multi-plant data into a coherent, real-time view, VPs of Operations can shift from reacting to issues to planning and prioritizing proactively.

However, data without context is often misleading. Integrating Video AI into your dashboard strategy ensures that you don't just see that efficiency dropped—you see why. Whether it represents a bottleneck in the packing line, a lapse in SOP adherence, or a safety stoppage, Spot AI provides the visual intelligence necessary to act decisively.

See how Spot AI brings video AI to your operations.
Request a demo to experience how our platform connects your cameras and delivers actionable visibility across every site.

Frequently asked questions

What are the key features of an effective executive dashboard?

An effective dashboard features a hierarchical design (roll-up summary to granular drill-down), real-time data integration from multiple sources (ERP, MES, Video), role-based access control, and visual indicators (traffic lights) to highlight exceptions. It should focus on 4-7 strategic KPIs rather than overwhelming the user with data (Source: ThoughtSpot).

How can I create a roll-up dashboard for multiple plants?

Creating a multi-plant dashboard involves connecting disparate plant systems to a central cloud-based aggregation layer. You must standardize metric definitions across sites to ensure comparability. Utilizing a platform that supports open APIs and camera-agnostic video integration, like Spot AI, simplifies the consolidation of visual data across distributed locations.

What KPIs should be included in a manufacturing dashboard?

Core KPIs typically include Overall Equipment Effectiveness (OEE), Schedule Attainment, Production Uptime, First Pass Yield (Quality), and Safety metrics (TRIR or leading indicators like PPE compliance). The selection should align directly with the organization's strategic business objectives.

How do I integrate ERP data into my dashboards?

Integration is achieved through middleware platforms or API connections that extract data from the ERP, normalize it, and load it into the dashboard's analytics database. This ensures that financial and order data can be viewed alongside real-time operational metrics.

What are the benefits of using real-time dashboards in manufacturing?

Real-time dashboards enable management by exception. They shorten the latency between an event (e.g., machine failure) and the executive response, improve cross-plant communication, and provide a single place to view data that minimizes debates over data validity.

About the author

Sud Bhatija is COO and Co-founder at Spot AI, where he scales operations and GTM strategy to deliver video AI that helps operations, safety, and security teams boost productivity and mitigate incidents across industries.