First order:
Task

Activities in energy and mining use labor and heavy equipment. Technology use focuses on communications and record keeping.

Egypt has massive amounts of naturalresources and mineral wealth. Examples of mining operations in Egypt vary from artisanalmines that use labor-intensive processes forextraction and mineral processing to largermines that use equipment for extraction. In both cases, leaders will decide based on experience. Little data is collected, and any data that is collected will not be used to inform decisions, but used to tally production and sales. Safety is a lower priority, and equipment and assets are manually maintained based on breakdowns. Technology use is largely to maintain production records for financial targets.

Second order:
Function

Historical data collection allows miners and operators to perform basic analytics to improve the quantity and quality of output, usually at individual project level. There will be the opportunity to increase unit prices based on the improvement of quality of the raw materials produced, resulting in higher revenue for the resources employed.

Third order:
System

Analytics and the use of KPIs further increase the process efficiencies of material extraction to improve quality and yield for sites, resulting in higher revenues. Additionally, companies will be able to implement programs to maintain equipment to prevent breakdowns, which cost tens to hundreds of thousands of dollars per hour in lost productivity.

Fourth order:
Organization

The emphasis on measurable performance, visibility and automation extends throughout the organization and improves exchanges with customers and suppliers. Leading organizations will be integrating with customers and suppliers to create awareness of opportunities and disruptions that may occur. This will increase the ability to, for example, find alternate supply for a chemical required for mineral extraction ahead of competitors. This will result in faster time to market for their product, meet contractual obligations, and enable the charging of a premium if supply is constrained. For automation, sites will use autonomous trucks, thereby driving site and asset profitability

Australia is known for its plentiful natural resources and mineral wealth and has large deployments of analytics and autonomy in mining. Examples of mining operations in Australia include Rio Tinto’s use of a control center to monitor autonomous mining equipment in Pilbara. The autonomous mining vehicles improve productivity and vehicle utilization as well as reduce the carbon footprint of the organization. Australian miners also operate autonomous blast hole drill rigs. Other examples include the use of real-time data to benchmark performance against best practices and develop predictive analytics models to identify opportunities to improve asset performance, increase productivity, and identify new business models.

Fifth order:
Ecosystem

The integration of data from the ecosystem will enable automated engagement between stakeholders, allowing mining companies to anticipate price fluctuations and focus on increasing productivity through automation, or on process and network optimization to save costs. Similarly, if there are constraints or disruptions, ecosystem integration will raise alerts and potentially assist with decision making that will allow companies to take advantage of early opportunities. One example might be constraints on space on shipping routes due to a disaster. Those companies that have early knowledge are able to act early to make alternate arrangements instead of holding on to weeks of inventory while waiting for the market to address the constraint, thereby being more resilient to disruptions.

First order:
Task

Agricultural activities use labor and heavy equipment. Technology use is focused on communications and record keeping.

Second order:
Function

Historical data collection and the monitoring of stock will allow for some basic analysis to improve quantity and quality of output, resulting in better land utilization or greater reproduction of livestock. Healthier crops and animals will allow producers to charge more for better quality products and increase the field/plot output.

Indonesia has diverse agriculture practices, from crop farming to small family-run plots, which are still vital income generators.

Indonesia is seeing significant efforts from start-ups and government efforts that are looking to assist the yields of small farmers. One example includes the development of a mobile phone app that collects weather data and uses a data model to help farmers make better decisions for planting, fertilizing, and harvesting. The farmers are also able to view market information and provide feedback by entering disaster reports in their villages.

Third order:
System

Farmers are wanting to track exceptions, aggregate information across multiple farms, improve field/plot yields, and analyze supply and demand for further increases in market prices and output. Additionally, farmers will be able to implement programs to maintain equipment to prevent breakdowns, which costs them lost harvests or livestock.

Fourth order:
Organization

Visibility and automation allows farmers to focus on productivity and connected asset management. Maintenance is proactive or predictive, decreasing costs and further increasing output. Site-specific application software can reduce the amount of pesticides and fertilizer used, reducing ecological impact and costs. Investments in automation that assist with milking or feeding, for example, assist in monitoring herds, ensuring animal health, longevity, and productivity. The automation of crop production can help alleviate issues with finding and retaining agricultural workers. Farmers seek alternate crops or farming techniques that allow for greater revenue or yields.

Japan is using data visualization for better yields and increased sustainability.

Examples of benefits to farmers through agrotech in Japan include the use of cloud platform for data analysis and the use of sensors (IoT) in paddy fields to detect and measure air and soil temperature, humidity, soil moisture, and soil fertility. Combined with the use of cameras for visual comparison over time, the use of data has been aggregated across multiple farms to improve the quantity and quality of rice to meet the needs of Saki brewers Asahi Shuzo.

Fifth order:
Ecosystem

An ecosystem of interconnected technology will allow farmers to uncover the nuances in each field and across farm holdings by collecting and analyzing data, helping to reduce inputs and costs. This will support farmers as they aim to conserve natural resources. Weather, soil, and other indicatorsharing and analysis platforms allow for data-sharing in region or comparisons with similar ecosystems. Connectivity to market partners including food processors will provide operational decision support, allowing for scenario analysis. Connected workers with wearables will give farmers to access to data across vast distances and multiple sites, allowing them to react quickly to natural disasters, thus reducing negative impacts and losses of crops, yields, and livestock.

First order:
Task

Activities in product and manufacturing are manually performed and paper-based. Technology use is focused on communications and record keeping.

Pakistan is known for high-quality garment production but is reliant on manual processes.

The garment industry is the second largest sector in Pakistan and companies rely on labor-driven processes fulfilled by factory workers, contract laborers, and homeworkers, who are usually paid on a per-piece basis. Because of electricity supply issues, machines are manually operated to increase productivity. Order management and cost sheets are usually handled manually or with limited computer support (e.g., using a spreadsheet to create invoices).

Second order:
Function

Data is gathered to manage inventory and identify problems and fundamental quality issues at product or line level. Improvement of quality and better consistency across batches will result in manufacturers being able to secure better and more lucrative contracts. There will be fewer errors with invoicing, which results in manufacturers being paid faster and with fewer disputes.

Third order:
System

Analytics and the use of KPIs allows for further increases in quality and output, as well as improved consistency of production. Manufacturers will be able to monitor production equipment and implement programs for maintenance and repairs, allowing for scheduling of downtime and reductions in breakdowns which cost them tens to hundreds of thousands of dollars per hour in lost productivity.

Fourth order:
Organization

The emphasis on measurable performance, visibility, and automation extends to suppliers and customers. Disruptions to supply or demand shocks will result in early alerts to more advanced organizations. This will allow them to find alternate supply sources or schedule resources to accommodate surges or constraints. Automation in the manufacturing industry results in reduced lead times, allowing producers to win contracts against those who are not able to produce as quickly. Robotics can allow greater loads or speeds than may be humanly possible, which means manufacturers can increase throughput. Asset issues on the shop floor can be addressed before they become critical, and within minutes instead of when equipment fails. Production loads can be switched to alternative lines or sites to ensure throughput is only minimally affected, and maintenance can be performed at the initial stage instead of waiting for a catastrophic breakdown.

Germany is the creator of the Industry 4.0 concept and has sophisticated manufacturing capabilities.

There are plenty of examples of manufacturing autonomy and predictive capabilities in the automotive and aerospace industries in Germany. For instance, BMW is using machine learning/AI in its smart manufacturing facility to assist in the quality inspection process. BMW has multiple models being produced on the same production lines, producing 9,000 vehicles per day and supporting up to 1 billion feature combinations (for the BMW 3 series). Platform-driven smart analytics capabilities support innovative automation and assistance systems, visual inspection for quality, process control, and asset maintenance for anomaly detection.

Fifth order:
Ecosystem

Manufacturers will be deeply integrated with their supply chains and able to automatically adapt to changing ecosystem opportunities in real-time. Constraints in component or raw materials supply or disruptions to shipping routes can be addressed through the use of marketplaces or pre-negotiated contracts. Decision automation through a connected ecosystem will allow for redirection of shipments or placing orders with alternate suppliers. In the case of demand spikes, production capacity can be scaled up through marketplace arrangements where additional factory capacity is purchased and brought online. Under-utilized factories are able to develop alternate revenue stream by making their capacity available to other producers. Products will incorporate embedded information capabilities that will extend product offerings through services, creating new business models. Examples include connected products that can predict component failure, location-enabled chipsets to track lost electronics.

First order:
Task

The services sector uses labor-intensive service provision with manual processing. Technology use is focused on communications and record keeping.

The Philippines is known for providing support services to organizations, especially English language support.

In instances in which large amounts of document processing are required or call center assistance, companies, such as Magellan Solutions, assist with outsourced labor that can perform form processing, virtual assistants, call center manning, and content creation/moderation. Systems are used to manage manpower and work scheduling, time, attendance, and invoicing. However, most of the processing work is labor-intensive.

Second order:
Function

Services are delivered according to documented processes. This results in a more consistent service offering, which increases customer satisfaction. Returning customer business then decreases the cost of attracting new ones, and resulting in referrals. This allows organizations to start to scale the improvement process to ensure service consistency

Oman's services sector has increased its contribution to national GDP from 29.4% in 1980 to 52.6% in 2019 driven in part by its logistics (maritime transport) and financial services sectors. The ongoing progress to achieve the 2030 Digital Oman Strategy (eOman) has helped build the broadband and cloud infrastructure that accelerated the digital transformation of the financial, government and transportation sectors.

This enabled the Financial services sector to develop Fintech products and services driving growth. The government, it's airports and ports have accelerated their digitalization of most of its services. It now has one of the fastest import and export compliance times amongst the Gulf States making it one of the most efficient logistics hub in the region. Data capture is facilitated through the use of barcode scanners to increase information accuracy. Cloud-based freight systems have been deployed to assist with the provision of consistent fast service experiences for their customers, including the ability for customers to log on to the customer portal and selfserve for enquiries.

Third order:
System

Analytics and the use of KPIs allows for better tracking of customer service metrics. Customer service continues to improve to become a point of differentiation. Increased service standards result in higher morale with employees, and allow businesses to attract a better quality of employee. Pride develops in the company, the levels of service offered and employees go the extra mile for customers. This results in further increases in sales, customer retention, and reduced recruitment costs.

Fourth order:
Organization

Service automation streamlines processes, therefore saving time and money. Automation of routine tasks such as work order management or bookings can reduce errors and free up staff to better focus on customer requirements. Increased productivity in this area will save costs. Reduced errors during the service encounter creates a more seamless customer experience resulting in increased customer satisfaction. Field service, for example, benefits from automation through better coordination of jobs, reducing travel time and costs and ensuring representatives have information when they need it in the field, rather than having to contact the office. Resource optimization will allow for better customer service and increased profitability. Automated processing and alerts allows for additional methods of engagement with customers, allowing them to use preferred contact methods with the organization.

Fifth order:
Ecosystem

Integration of service networks allows for service capabilities to be extended beyond the capabilities of the company. Examples in the B2C space include the ability to use a single airline app to book ride-sharing transport for the ongoing journey once the passenger leaves the airport. The same app can be used to order from a food service to arrange a meal to be delivered shortly after their arrival home. Alternative revenue streams are activated through commissions or cross payments occur to the airline for generating demand for the ridesharing and food delivery services. Companies will integrate with more partners to extend service capabilities and ensure stickiness within their network. This results in additional sources of revenue and extension of business models.

First order:
Task

Research activities are conducted with manual record keeping. Spreadsheets may be used for the tabulation of data and presentation of findings.

Second order:
Function

Data collection will be more sophisticated, with digitalization of data reducing errors and speeding up processing of results. Outcomes will be more accurate and digital data collection will allow for additional parameter collection. In the case of commercial innovation, this will increase the opportunity to include customer/market input thereby improving commercial outcomes from innovation efforts.

Fifth order:
Ecosystem

Collaboration across ecosystems – national and international – impels innovation and development networks that combine emerging technologies with the innovation process to develop new pathways for information technology, new product development, materials science, science, and more. AI/ML-driven generative design by digital twins self-simulate and self-innovate not just the physical product, but include process and ecosystem digital twins that model commercial outcomes of productas-a-service offerings.