Summary

Digital twin engineers create a virtual representation of both the physical elements and the dynamics of how an IoT-connected product operates and interacts within its environment, throughout its entire life cycle. Ranging from a jet engine or aircraft to a shop floor, an assembly line, or even an entire factory building, digital twin engineers make it possible to virtually see inside any physical asset, system, or structure that could be located anywhere, thereby helping to optimise its design, monitor its performance, predict its maintenance, and improve the overall experience. View the complete persona of the Digital Twin Engineer.

Employee profile

The digital twin engineer plays a crucial role in building the relationships and communication lines across silos to create a network that marries the physical and digital worlds throughout the manufacturing value chain.

Digital twin engineers must be proficient in creating virtual replicas of major industrial products and helping companies predict and respond to customer problems using real-time data analysis and advanced technologies.

Skills include:
– Simulations
– Analytics
– Sensors
– Software development
– Systems engineering
– Research and development
– Algorithms
– Image processing
– Cross-functional team leadership
– Programme management

Toolbox

The toolbox supports the worker in achieving external outcomes such as productivity as well as internally focused ones such as decision making and learning. View complete toolbox of the Digital Twin Engineer.

Productivity
Venus: Artificial intelligence (AI)-powered, voice-enabled digital assistant provides a conversational interface for all productivity-related tasks.

WeAR: Augmented reality (AR) wearable device that connects digital twin engineers to IoT devices and receives work instructions and training.

InstaCap: Captures data automatically using digital technologies such as radio frequency identification (RFID) and speech recognition.

Decision-making
Smart Dash: Visual display that presents data, live information and analysis from multiple sources to facilitate informed decision-making.

Envision: uses machine learning to identify potential problems as well as opportunities to devise solutions that make a positive impact.

RealConnect: Enables an engineer to seamlessly interact with suppliers, partners, customers, and the broader ecosystem.

Learning
SkillsPro: Smart learning assistant that helps digital twin engineers refresh existing skills as well as learn new emerging skills.

SmartLab: Facilities classroom learning using virtual reality headsets and simulation.

Summary

Predictive supply network analysts of the future are a connected and integrated part of the broader digital supply network (DSN) at their organisation. Skilled in data sciences and big data modelling techniques, they use digital tools to move materials and finished goods through the DSN for just-in-time deliveries. With a portfolio of digital tools, these analysts rely on machine learning and cognitive computing instead of “gut feel” and static reports to identify opportunities for calibrating demand and supply to maximise performance based on metrics, including customer satisfaction, productivity and margin. View the complete persona of the Predictive Supply Network Analyst.

Employee profile

An analytics professional with expertise in multiple analytics platforms, predictive technologies, machine learning tools and connected inventory management. Helps companies achieve optimal inventory and network health management per ongoing and anticipated supply demand scenarios.

Skills include:
– ERP
– Demand analytics
– Sensors
– Inventory optimisation
– Network planning and optimisation
– Replenishment analytics
– Logistics and warehouse management
– Analytics
– General tech fluency
– Visualisation

Toolbox

The toolbox supports the worker in achieving external outcomes like productivity as well as internally focused ones such as decision making and learning. View the complete toolbox of the Predictive Supply Network Analyst.

Productivity
DSN Tower: Surfaces relevant information from all the connected supply chain applications across the enterprise and provides a customised interface by role and experience.

CrowdWise: Online dashboard collects textual data from all the social websites a company use for feedback, complaints and issues using text mining and web scraping. It then creates word clouds and highlights the customer sentiment around the company's products and services.

Share Smart: An enterprise social and mobile technology tool that helps in sharing digital 3D designs and images as digital files to improve the collaboration necessary to build a new product, supply network configuration, or assembly line right the first time.

Decision-making
Sixth Sense: Incorporates machine learning, cognitive computing, and AI to detect macro trends in the broader environment.

Smart Dash: AI dashboard that presents live data and information from multiple sources along with recommendations to enable informed decisions.

Envision: Uses machine learning to identify potential problems as well as opportunities to devise solutions that make a positive business impact.

Learning
Career Coach: This personal bot performs strength assessments and understands the broader talent picture at the company. It can use AI to suggest different career pathways and coordinate with SkillsPro training course to create a programme for the user to accomplish their pathway. It also links in real time to the talent management system at the company to alert the user of job openings and opportunities for advancement.

Summary
The increasing penetration of robots in manufacturing production and distribution is driving demand for robot teaming coordinators (RTCs), professionals who train humans and robots to work together collaboratively. RTCs are an evolution of the typical process engineer and change management experts in manufacturing enterprises. They typically design business processes that integrate robotics into production and distribution operations while also considering the enduring human skills that employees bring to the value stream. View the complete persona of the robot teaming coordinator.

Employee profile
The RTC is responsible for monitoring robot performance and providing feedback to programmers to optimise robot value, while enabling a collaborative human-robot working environment. The RTC applies a mix of digital, social and human skills to enable humans and robots to leverage each other’s strengths for increased productivity and growth.

Skills include:
– Behaviour analysis
– Robot management
– Administration
– Customer service
– Technical training and orientation

Toolbox
The toolbox supports the worker in achieving both external outcomes such as productivity, as well as internally focused ones such as decision making and learning. View the complete toolbox of the robot teaming coordinator.

Productivity
Visually Trainable Robot (VITRO): A personal, multipurpose humanoid robot whose size and capabilities make it suitable for individual use and can be programmed through motion capture software and trackers to perform household tasks.

rMIMIC: A motion-capture AI tracker that can scan and track the sensors placed on a human body and create coordinates in a digital space that can be translated into a set of commands for VITRO to execute.

VizWizard: A visualisation tool that can create graphs and infographics with minimal text inputs from the user.

Decision-making
Smart Dash: AI dashboard that presents live data and information from multiple sources, along with recommendations to enable informed decisions.

RealConnect: A tool that enables engineers to seamlessly interact with suppliers, partners, customers and the broader ecosystem.

Learning
LNP: A social media interface that allows individuals to express their desire to augment a specific skill; in turn, other users proficient in that skill can act as a temporary buddy.

Summary
Fast forward to 2025 and big data is the new normal and growing exponentially. With a plethora of customer data at their disposal, companies have started using it to create customised data offerings, leading to demand for professionals known as digital offering managers (DOMs). DOMs have evolved from the product manager career path. Their key responsibilities revolve around identifying and creating new product offerings for companies that are entirely digital–built from data, code, analysis and delivered virtually–making them wholly different from the physical products a company traditional makes. View the complete persona of the digital offering manager.

Employee profile

The DOM is responsible for contributing to the expansion of new digital offerings in the company’s portfolio of smart precision machinery. The role requires proficiency in networking and sales, client management, cross-team collaboration, project management and problem-solving in order to generate new data offerings and business expansion opportunities for the company.

Skills include:
– Sales and marketing
– Behaviour analysis
– Customer experience
– Communication
– Networking
– Collaboration
– Client management
– Social skills
– Change management
– Project management

Toolbox
The toolbox supports the worker in achieving both external outcomes such as productivity, as well as internally focused ones such as decision making and learning. View the complete toolbox of the digital offering manager.Productivity
Rosetta:
An AI-based real-time language translator that listens to speech, converts it into text, and then translates that into the desired language, enabling collaboration among different regional markets.

Gen4-Conservatory: 
Smart meeting rooms for teams that are co-located but are from different functions. Smart-glass boards plugged with AI-enabled devices can pull data from multiple sources and conduct basic data transformation. Voice-activated, these devices can operate with basic sound commands decision-making.

CuSu–Customer supporter:
An AI and natural-language-processing client management tool that keeps track of client offerings along with state-of-the-art data security.

Sixth Sense:
A tool that incorporates machine learning, cognitive computing, and AI to detect macro trends in the broader environment.Learning

ELWIE:
Standing for “enabling learning, wellbeing, (personal) interest, and (overall) excellence” is a mobile bot and personal smart wellbeing assistant that takes care of professional and personal wellbeing. It can suggest new learning opportunities as well as help to plan vacations or leaves based on personal interest.

Summary
The construction sites in 2025 are different than in 2019—autonomous drones, cranes, robots, and other automated equipment perform repetitive, heavyweight, and hazardous tasks. This has created a new human role, a coordinator to exploit data from fleets of drones. Drone data coordinators (DDCs) have on-site and off-site responsibilities, including coordination with drone service providers and life cycle responsibility for the data the drones capture.

DDC is a new full-time role for many engineering, procurement, and construction (EPC) firms. As data has become the digital thread across the job site, this role has emerged to coordinate the data that leased fleets of autonomous drones can capture for safety, inspection, operations and risk managers. DDCs work with the contracted drone service provider on a project basis. View the complete persona of the drone data coordinator.

Employee profile
The DDC must be proficient in project management, resource and equipment management and plays a key role in the expansion of drones into the company's life cycle data management model; has executive responsibility for managing and networking with drone service providers to create new efficiency, safety, and risk management opportunities for the EPC firm.

Skills include:
– Data life cycle management
– Resource optimisation
– Analytics
– Communication
– Networking
– Automation
– Client management
– Collaboration
– Change management
– Project management

Toolbox
The toolbox supports the worker in achieving both external outcomes such as productivity, as well as internally focused ones such as decision-making and learning. View the complete toolbox of the drone data coordinator.

Productivity
Venus:
An AI-powered, voice-enabled digital assistant provides a conversational interface for all productivity-related tasks, from scheduling to finding answers to questions and checking the status of products and projects.

VirtuMeet:
An AR smart-glass conference room with AI capabilities allows global partners to meet and collaborate, overcoming the barriers of physical separation. With built-in AI, AR screens can present short bios or other relevant information about attendees as the user pans across their faces.

Decision-making
Smart Dash:
A visual display that presents data, live information, and analysis from multiple sources to facilitate informed decision-making.

Real Connect:
This application enables an engineer to seamlessly interact with suppliers, partners, customers, and the broader ecosystem.

Learning
SkillsPro:
A smart learning assistant that helps digital twin engineers refresh existing skills as well as learn new and emerging skills. Its conversation mode shares tips and tricks about the tools/techniques that an engineer has learned recently. When synced with an engineer's project planner, it shares a list of skills to be learned for implementation in upcoming projects.

SmartLab:
A tool that facilitates classroom learning using virtual reality headsets and simulation. It tests trainees on a defined skill framework and measures subjective aspects based on their response style. Each trainee receives customised learning objectives.

Summary

In the smart factory of 2025, the changing nature of when, where, and how parts, subassemblies, and final products are made has transformed the role of the human manager at its helm. The smart factory manager (SFM) wears many hats: production operations and quality responsibilities, as well as DevOps (product design/engineering), along with expanded IT and cyber responsibilities. Their expanded responsibilities place them in the unique position of integrating advanced manufacturing, secure connectivity, and actionable data analytics together to drive a new level of overall equipment effectiveness (OEE).

In their expanded role, SFMs are responsible for more of the manufacturing value stream than in traditional manufacturing sites. SFMs determine build schedules and inventory levels based on demand forecasts that have been derived from artificial intelligence (AI) and machine learning algorithms. With their widened aperture, SFMs apply their judgement to set parameters related to allocation of product, profitability, or new product introductions, for example. View the complete persona of the smart factory manager.

Employee profile

The smart factory manager must be proficient in applied technology, automation, connectedness, and driving OEE. Leader of factory innovation via smart use cases. Experienced in change management and robust value chain integration.

Skills include:
– Operational excellence
– Deep learning
– Innovation
– Automation
– Digital prototyping
– Industrial technology
– Client management
– Collaboration
– Change management
– Project management

Toolbox

The toolbox supports the worker in achieving both external outcomes such as productivity, as well as internally focused ones such as decision making and learning. View the complete toolbox of the smart factory manager.

Productivity
Venus:
This AI-powered, voice-enabled digital assistant provides a conversational interface for all productivity-related tasks, from scheduling to finding answers to questions and checking the status of products and projects.

Gen4-Conservatory:
Smart meeting rooms for teams that are collocated but are from different functions. Smart-glass boards plugged with AI-enabled devices can pull data from multiple sources and conduct basic data transformation. Voice-activated, these devices can operate with basic sound commands. These capabilities help the data team in ideation and offering formulation.

Decision-making
Smart Dash:
A visual display that presents data, live information and analysis from multiple sources to facilitate informed decision-making.

Sixth Sense:
A tool that incorporates machine learning, cognitive computing, and AI to detect macro trends in the broader environment.

Learning
ELWIE:
Standing for “enabling learning, wellbeing, (personal) interest, and (overall) excellence” is a mobile bot and a personal smart wellbeing assistant that takes care of professional and personal wellbeing. It can suggest new learning opportunities as well as help to plan vacations or leaves based on personal interests.

Summary

The smart scheduler uses smart and connected technologies to develop and maintain program schedules on construction work. In the construction site of 2025, many scheduling tasks are automated; the tracking of labour, equipment, and raw materials are digitalised; and performance is captured in real time. A smart scheduler creates a digital thread from these activities using custom applications or off-the-shelf digital tools—from mapping construction site progress to ensuring just-in-time availability of materials, labour, and construction equipment. With the rise in automated scheduling tasks, the smart scheduler’s role now includes higher-value functions such as constraints management, resource optimisation, schedule optimisation, planning for unexpected events, and real-time persona-based visualisation. View the complete persona of the smart scheduler.

Employee profile

The smart scheduler must be proficient in developing and maintaining program schedules using advanced data analytics and visualisation to identify relationships, logic, milestones, and constraints for construction projects of various types; leverages predictive analytics and cognitive tools for understanding bottlenecks for dynamic replanning to improve schedule adherence.

Skills include:
– Analytics
– Data life cycle management
– Demand analytics
– IoT tools
– Resource optimisation
– Inventory optimisation
– Logistics and warehouse management
– Materials and supplier management
– Project management
– Visualisation

Toolbox

The toolbox supports the worker in achieving both external outcomes such as productivity, as well as internally focused ones such as decision making and learning. View the complete toolbox of the smart scheduler.

Productivity
Symphony:
This software suite connects smart schedulers with other resources—people, machines, and systems—for data-driven connected construction. Using real-time analytics, it can help smart schedulers analyse and track project and site performance.

AuRo:
An AR tool that is designed to assist maintenance personnel in maintaining and repairing equipment using vision and picking to produce a faster, hands-free solution for precarious or delicate tasks.

Decision-making
Envision:
This tool uses machine learning to identify and rectify potential problems. It also helps discover opportunities to influence business decisions that drive financial or other key results.

DST:
A digital scheduling tool that provides updates on the status of machinery, equipment, and material required or in-progress at the site. It helps with real-time status updates on labor availability.

Learning
SkillsPro:
This smart learning assistant helps smart schedulers refresh existing skills as well as learn new and emerging skills. Its conversation mode shares tips and tricks about the tools/techniques that a scheduler has learned recently. When synced with a scheduler’s project planner, it shares a list of skills to be learned for implementation in upcoming projects.

Summary

With autonomous equipment, unmanned drones and advanced materials at construction sites, managing the environment, health, and safety (EHS) aspects of engineering and construction (E&C) projects would be just one responsibility for the smart safety supervisor (S³). In their expanded role, S³s are expected to work with operational, logistics and technology teams to find new synergies that can improve the safety of the construction site. S³s are fluent in advanced technologies, and they serve as a conduit to match applications such as augmented reality (AR) glasses, smart helmets, and connected clothing with use cases for creating a safe and efficient work site. View the complete persona of the smart safety supervisor.

Employee profile

The S³ must be skilled in environment, health, and safety (EHS), workplace safety, inspection, and risk assessment; proficient in digital tools and EHS technologies; has developed and implemented multiple health and safety programs for various construction projects; leverages predictive analytics and cognitive tools for incident investigation and corrective measures.

Skills include:
– Construction safety
– Safety management systems
– Occupational and health
– Applied technology
– Communication
– Workplace safety
– Resource optimisation
– Internet of Things
– Wearables for safety management
– Data analysis

Toolbox

The toolbox supports the worker in achieving both external outcomes such as productivity, as well as internally focused ones such as decision-making and learning. View the complete toolbox of the smart safety supervisor.

Productivity
Symphony: This software suite connects smart schedulers with other resources—people, machines and systems—for data-driven connected construction. Using real-time analytics, it can help smart schedulers analyse and track project and site performance.

AuRo: An AR tool that is designed to assist maintenance personnel in maintaining and repairing equipment using vision and picking to produce a faster, hands-free solution for precarious or delicate tasks.

Decision-making
Envision:
This tool uses machine learning to identify and rectify potential problems. It also helps discover opportunities to influence business decisions that drive financial or other key results.

DRT:
A digital requirement toolbox is a central request repository for digital initiatives and support, which the company’s innovation team can use to plan and pilot their digital/smart initiatives.

Learning
HeMoSite:
This enterprise health monitoring site helps to track the working conditions and environment of each professional, highlighting any exposure to potential hazardous elements or heavy-duty machinery.

Summary

By 2035, the urban air mobility (UAM) ecosystem could see commercial success of remotely managed air taxis, paving the way for autonomous vehicles. Though autonomous air taxis would eliminate the need for a pilot in the vehicle, it would be essential to have a controller, situated in operation centers, who can remotely manage and monitor passenger (and cargo) mobility vehicles. UAM flight controllers would be expected to manage multiple aircraft, since these aircraft would largely be able to operate independently. They would be certified aviation and UAM professionals who would be capable of remotely communicating with autonomous systems equipped in air taxis and be able to control and guide them, whenever required. View the complete persona of the UAM flight controller.

Employee profile

The UAM flight controller is an experienced civilian pilot with demonstrated history working in the aviation industry; must be highly skilled in airline operations, training, and aeronautics, with proficiency in project, resource, and fleet management; plays a pivotal role in the expansion of UAV operations.

Skills include:
– Aeronautics
– Flight planning
– Civil aviation
– Flight control (remote operations)
– Team leadership
– Change management
– Route optimisation
– Flight operations
– Wearables for safety management
– Resource allocation

Toolbox

The toolbox supports the worker in achieving both external outcomes such as productivity, as well as internally focused ones such as decision-making and learning. View the complete toolbox of the UAM flight controller.

Productivity
Air Talkies: 
This voice-enabled, wireless headset can connect to air traffic controllers through voice commands in a fraction of a second.

AuRo:
An AR tool that is designed to assist maintenance personnel in maintaining and repairing equipment using vision and picking to produce a faster, hands-free solution for precarious or delicate tasks.

Decision-making
Flight Analyser:
This predictive tool monitors air taxi performance, by capturing and analysing flight data from routine operations. It also helps improve flight operations safety as well as operational efficiency.

UAV NavCom:
A virtual version of a cockpit that allows remote flight controllers to communicate and navigate UAVs. It also allows flight controllers to take complete manual control of the vehicle.

Learning
UAV Sim X:
This training simulator helps train UAM flight controllers in a virtual environment that is realistic, but eliminates the risks of a real flight. Through simulations, it allows controllers to prepare for situations that may arise while air taxis are being remotely managed.

Summary

It is 2025. The manufacturing industry has automated production processes and assembly lines. Quality control, which relied on human inspection and intervention, is now an automated, intelligent process enabled by vision systems and real-time analytics. A “smart quality assurance (QA) manager” manages product quality, making full use of digital technologies. This role oversees an ecosystem of machine and work center sensors, artificial intelligence (AI)/machine learning–powered analytics dashboards, and virtual reality support technologies. This enables the Smart QA manager to proactively detect quality escapes and machine maintenance issues and develop solutions to address the root causes of quality issues. View the complete persona of the Smart QA Manager.

Employee profile

The Smart QA Manager is experienced and trained in leveraging smart technologies to reduce the number of defects per part produced and helps enhance overall productivity of the firm.

Skills include:
– Operational excellence
– Deep learning
– Innovation
– Automation
– Digital prototyping
– Industrial technology
– Client management
– Collaboration
– Change management
– Project management

Toolbox

The toolbox supports the worker in achieving both external outcomes such as productivity, as well as internally focused ones such as decision-making and learning. View the complete toolbox of the Smart QA Manager.

Productivity
Venus:
This AI-powered, voice-enabled digital assistant provides a conversational interface for all productivity-related tasks, from scheduling to finding answers and checking the status of projects and people.

Share Smart:
An enterprise social and mobile technology tool that helps in sharing digital 3D designs and images as digital files to improve the collaboration necessary to build new product, supply network configuration or assembly line right the first time.

Decision-making
Smart Dash:
A visual display that presents data, live information, and analysis from multiple sources to facilitate informed decision-making.

Envision:
This tool uses machine learning to identify and rectify potential problems. It also helps discover opportunities to influence business decisions that drive financial or other key results.

Learning
ELWIE: (enabling learning, well-being, (personal) interest, and (overall) excellence)
It’s a mobile bot and a personal smart well-being assistant that takes care of professional and personal well-being. It can suggest new learning opportunities as well as help to plan vacations or leaves based on personal interests.