Digital-driven Business Landscape

Transitioning to digital operations for a Company involves strategic decision-making to either incrementally evolve existing systems or significantly revolutionize them. This process entails comprehensive mapping to identify improvements while leveraging analytics to map the "As Is" environment and formalize the "To Be" future. Enhancing global efficiency and effectiveness requires a deep understanding of all systems and processes, along with optimization through process-based analytics and correlation.

Overall Operations Effectiveness (OOE), Total Effective Equipment Performance (TEEP) and Overall Equipment Effectiveness (OEE) are crucial metrics in the realm of "manufacturing", providing invaluable insights into the efficiency and productivity of production processes.

These metrics are indispensable tools for both CEOs and Factory Managers, offering a comprehensive view of operational performance and its direct impact on the P&L statements of both organizational levels. Digital-driven industries can utilize similar concepts to assess and optimize their digital operations.

P&L | OOE | TEEP | OEE

OOE, TEEP and OEE can impact the P&L relative to Revenue, COGS (Cost of Goods Sold) and Expenses:

OOE (Overall Operations Effectiveness)

• OOE goes beyond OEE and includes other operational factors like labor efficiency, material usage, and maintenance effectiveness.
• Improving OOE can lead to better coordination between different aspects of the manufacturing process, reducing waste and optimizing resource utilization.
• Higher OOE can result in lower COGS as it reduces wastage of materials and resources, leading to higher profitability.
• Conversely, low OOE can increase COGS by inefficiently using resources and materials, leading to decreased profitability.

TEEP (Total Effective Equipment Performance)

• TEEP measures how effectively a manufacturing operation utilizes its equipment time when it is scheduled to run, including both planned and unplanned downtime.
• Improving TEEP can lead to increased production capacity without additional investment in equipment.
• Higher TEEP can result in higher revenue due to increased production capacity and reduced idle time.
• Lower TEEP can lead to increased COGS as fixed costs are spread over fewer units produced, reducing profitability.

OEE (Overall Equipment Effectiveness)

• OEE measures how effectively a manufacturing operation utilizes its equipment during production. It's calculated as the product of Availability, Performance, and Quality.
• Higher OEE means better utilization of equipment, leading to increased production output without necessarily increasing costs.
• Improved OEE can result in higher revenue due to increased production efficiency, as more products are manufactured in less time, thus increasing sales.
• Conversely, if OEE is low, it may result in lower revenue due to production delays, missed deadlines, or defective products that lead to customer dissatisfaction.

In summary, improving OOE, TEEP, and OEE can positively impact profit and loss by increasing revenue through higher production output, better quality products, and reduced costs through improved resource utilization and decreased downtime. Conversely, low OEE, TEEP, and OOE can lead to decreased revenue and increased COGS, negatively impacting profitability.

World-class Scores

Typically, a company starting on OOE, TEEP and OEE might have scores lower than what would be considered world-class. However, these scores can vary widely depending on the industry, specific processes, and other factors. Here's a general overview:

OOE (Overall Operations Effectiveness)

• Program OOE measures the effectiveness of the entire manufacturing process, including equipment, personnel, and materials.
• A starting Program OOE score might be around 50% to 60%. This suggests that there are opportunities to improve overall operations by optimizing various factors such as workflow, resource allocation, and process efficiency.
• World-class Program OOE scores vary widely depending on industry and specific processes but typically exceed 85% to 90%. Achieving such high scores indicates excellence in overall operations management, with minimal waste and maximum productivity.

TEEP (Total Effective Equipment Performance)

• A starting TEEP score might be around 50% to 60%. This means that the equipment is being utilized effectively, but there is still room for improvement in terms of availability, performance, and quality.
• World-class TEEP scores are typically above 85% to 90%. Achieving such high levels indicates optimal utilization of equipment with minimal downtime and maximum efficiency across all aspects of production.

OEE (Overall Equipment Effectiveness)

• A starting OEE score could be around 40% to 50%. This indicates that there are significant opportunities to improve equipment performance, availability, and quality.
• World-class OEE scores are often above 85% to 90%. Companies with such high scores are maximizing the potential of their equipment and achieving high levels of productivity, quality, and efficiency.

It's important to note that achieving world-class scores requires a comprehensive approach to continuous improvement, including implementing best practices, leveraging technology, investing in employee training, and fostering a culture of excellence throughout the organization. Additionally, benchmarks for world-class performance may differ across industries and specific manufacturing processes.

Digital | Manufacturing | Analytics play a critical role in several stages

Analytics helps manufacturers understand their current operations by analyzing data from various sources such as production lines, supply chain, and equipment sensors. This analysis provides insights into inefficiencies, production bottlenecks, quality issues, and resource utilization. By identifying areas for improvement, manufacturers can optimize their processes before implementing digital solutions.

• As-Is environment analysis: Analytics helps manufacturers understand their current operations by analyzing data from various sources such as production lines, supply chain, and equipment sensors. This analysis provides insights into inefficiencies, production bottlenecks, quality issues, and resource utilization. By identifying areas for improvement, manufacturers can optimize their processes before implementing digital solutions.
• During system implementation: Analytics guides manufacturers in implementing digital solutions by providing data-driven insights into the impact of changes on operations. For example, predictive analytics can forecast the effects of process modifications or equipment upgrades, helping manufacturers make informed decisions and mitigate risks during implementation.
• Post-implementation monitoring: After the digital system is implemented, analytics continue to play a crucial role in monitoring and optimizing operations. Manufacturers can use real-time data analytics to track key performance indicators (KPIs), detect anomalies, and identify opportunities for further improvement. This ongoing analysis ensures that the digital system operates efficiently and delivers the expected benefits over time.

Analytics guides manufacturers in implementing digital solutions by providing data-driven insights into the impact of changes on operations. For example, predictive analytics can forecast the effects of process modifications or equipment upgrades, helping manufacturers make informed decisions and mitigate risks during implementation.

Overall, analytics are essential in the manufacturing process for both understanding the current state (As-Is environment) and optimizing operations before and after implementing digital solutions, ensuring continuous improvement and competitiveness in the industry.

Early Adopters Driving Digital Transformation Advancements

• Oil and Gas Industry: Oil and gas companies have heavily invested in digital technologies for decades, leveraging advanced measurement systems for exploration, production optimization, and refining processes.
• Automotive Industry: Automotive manufacturers have embraced digital measurement technologies for quality control, precision engineering, and performance optimization in both production processes and vehicle design.
• Aerospace and Defense Industry: Aerospace and defense companies rely on digital measurement technologies for aircraft design, manufacturing, and maintenance, ensuring strict compliance with safety and performance standards.
• Healthcare Industry: In healthcare, digital measurement tools are used extensively for diagnostics, patient monitoring, and treatment planning, leading to more accurate diagnoses and personalized care.
• Telecommunications Industry: Telecommunication companies utilize digital measurement technologies to monitor network performance, optimize bandwidth allocation, and enhance the reliability and efficiency of communication systems.

These industries have demonstrated the transformative power of digital measurement technologies, setting benchmarks for innovation and efficiency across various sectors.

Oil and Gas Industry Example

In the oil and gas industry, digitalization has revolutionized both upstream and downstream operations, as well as chemical mixing processes. Here are some key points for each aspect

Upstream Operations:

• Exploration and Drilling: Digital technologies such as 3D seismic imaging and drilling automation have improved the accuracy of geological assessments and optimized drilling processes, leading to more efficient extraction of hydrocarbons.
• Production Optimization: IoT sensors and data analytics are used to monitor well performance in real-time, enabling predictive maintenance and proactive intervention to maximize production rates while minimizing downtime.
• Reservoir Management: Advanced simulation software models reservoir behavior, facilitating enhanced reservoir characterization, optimal well placement, and improved recovery rates.

Downstream Operations:

• Refining Processes: Digital control systems and predictive analytics optimize refinery operations, ensuring efficient processing of crude oil into various refined products like gasoline, diesel, and jet fuel, while minimizing energy consumption and emissions.
• Supply Chain Management: Digital platforms integrate supply chain functions, from procurement to distribution, enhancing visibility, inventory management, and logistics optimization.
• Product Quality Control: Advanced sensors and data analytics monitor product quality parameters in real-time, enabling rapid adjustments to ensure compliance with industry standards and customer specifications.

Chemical Mixing and Blending:

• Precision Mixing: Digital control systems precisely regulate the composition and proportions of different chemicals in mixing and blending processes, ensuring consistency and quality of the final product.
• Real-time Monitoring: Sensors continuously monitor key parameters such as temperature, pressure, and viscosity, providing real-time feedback to operators and enabling timely adjustments to optimize mixing conditions.
• Quality Assurance: Automated sampling and analysis systems verify the quality of the blended product, with data seamlessly integrated into quality management systems for traceability and compliance purposes.

By leveraging digital technologies, the oil and gas industry enhances operational efficiency, improves safety and environmental performance, and remains competitive in a rapidly evolving global market.

Digital-driven Industry Examples | Similar Concepts

Digital-driven industries can utilize similar concepts to gauge their operational efficiency and impact on profit and loss. Here are five industries along with examples of how they can apply similar concepts:

E-commerce Industry

• Instead of measuring equipment effectiveness, e-commerce companies can focus on website uptime and performance metrics such as page load times, checkout completion rates, and server response times.
• Operational effectiveness can be assessed by analyzing order fulfillment times, customer service response times, and inventory management accuracy.
• Total effective performance could involve assessing the efficiency of digital marketing campaigns, conversion rates, and customer retention strategies.

Software as a Service (SaaS) Industry

• For SaaS companies, uptime and reliability of their software platform are crucial metrics similar to equipment effectiveness.
• Operational effectiveness could involve measuring customer onboarding times, support ticket resolution times, and software update deployment efficiency.
• Total effective performance might include evaluating subscription renewal rates, user engagement metrics, and lifetime customer value.

Telecommunications Industry

• Telecom companies can measure network uptime, latency, and bandwidth utilization as equivalents to equipment effectiveness.
• Operational effectiveness could involve assessing customer service response times, network maintenance efficiency, and service provisioning speed.
• Total effective performance might include analyzing subscriber growth rates, customer churn rates, and average revenue per user (ARPU).

Finance and Banking Industry

• In the finance sector, uptime and reliability of digital banking platforms are critical, akin to equipment effectiveness.
• Operational effectiveness could involve measuring transaction processing times, fraud detection accuracy, and customer account management efficiency.
• Total effective performance might include evaluating customer acquisition costs, customer satisfaction scores, and loan approval turnaround times.

Healthcare Industry (Digital Health)

• Digital health companies can measure uptime and reliability of telehealth platforms and medical devices as equivalents to equipment effectiveness.
• Operational effectiveness could involve assessing patient appointment scheduling efficiency, electronic health record (EHR) system usage, and medical data security compliance.
• Total effective performance might include analyzing patient engagement metrics, health outcomes improvement rates, and healthcare provider satisfaction scores.

These industries can adapt similar concepts from manufacturing operations to assess and optimize their digital operations, ultimately impacting their profitability and overall performance.