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Human-Machine Collaboration: How Ready is Your Organization?

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Human-Machine Collaboration: How Ready is Your Organization?

The future of work will be based upon how well companies blend and extend human strengths (cognition, judgment, empathy, etc.)...

8 Minutes Read

The future of work will be based upon how well companies blend and extend human strengths (cognition, judgment, empathy, etc.) with machine capabilities (accuracy, endurance, speed, etc.) to tackle common business goals. At the heart of human-machine collaboration is the simple idea that every employee, and every role, can be improved with smart tools and technology, unlocking entirely new performance thresholds. In fact, 76% of companies we recently interviewed agreed that human-machine collaboration will be the top business driver over the next five years.

The transition to this collaboration, however, raises some critical questions: Will humans and machines work as a single team within organizations? How do we prepare the current and future workforce for hybrid work? And how do we address employees' fears of bots taking their jobs? These and many other questions leaders face today don’t have clear answers. That’s why we’ve developed the five T’s framework to help traditional businesses systematically transition to the new world of work with machines — tasks, talent, technology, training, and trust. While the five T’s framework illuminates a path forward for achieving human-machine collaboration, it’s critical first to understand (and admit) your current state of preparedness around the five T’s, and identify the steps you must take to create the future of work.

We have developed a five T’s self-assessment framework that businesses can undertake to determine their human-machine collaboration maturity level, and identify the next steps in their journey. There are five statements under each of the five T’s below. Rate each statement on a scale of 1-5, where 1=Do not agree at all, and 5=Completely agree.

Spoiler warning: Don’t get discouraged if you find your rating to many of the statements below on the lower side. The human-machine collaboration is still a highly nebulous area, and not many companies have mastered the art and science of it. The key is to start early, learn from your initial steps, and continue to refine your human-machine approach.

Human-Machine Collaboration - Five T’s Self Assessment (Scale = 1-5; 1 = Don’t agree at all; 5=Completely agree)
Tasks – Allocating work between humans and machines  
1. Our employees have a clear understanding of the difference between “jobs” and “tasks”  
2. Our leaders use task allocation systems/tools to identify, allocate, and manage tasks between humans and machines  
3. We have redesigned jobs, organizational structure and operations for optimum human-machine collaboration  
4. Our employee performance evaluation metrics focus on combined human-machine performance levels  
5. We have redesigned/restructured our business processes to embed task-driven systems/tools for human-machine work seamlessly  
Talent – Skills needed to collaborate with machines  
1. We have a clear understanding of the knowledge, skills, and mindsets required to work with intelligent machines in the future  
2. Our leaders and managers have the knowledge and skills to effectively lead, manage, engage, and develop the human-machine collaborative workforce  
3. We use talent intelligence (employee data – internal and external) to match people’s skills and interests with specific tasks to enhance human-machine collaboration  
4. New talent requirements are always mapped with specific tasks, not jobs, within our organization  
5. We frequently move people and teams across roles and functions to address talent needs  
Training – Learning to collaborate with machines  
1. We have a clear understanding of workforce training requirements to enable individuals to collaborate effectively with intelligent machines in the future  
2. Our employee incentives, rewards, and career growth plans are directly linked to learning/reskilling/upskilling  
3. Our learning and development approaches are focused on speed, agility, and flexibility  
4. The use of data analytics is deeply embedded in the development and execution of our workforce training programs  
5. Our leadership teams have been tasked with ensuring each and every employee is trained to work with intelligent machines  
Technology – Building the IT foundation for the future of work  
1. We have a clear understanding of how to seamlessly integrate AI-systems with our IT infrastructure  
2. Our IT infrastructure is agile, secure, and scalable  
3. We use AI/Machine learning algorithms to predict and manage IT infrastructure requirements  
4. Enterprise security automation is a core element of our IT defense mechanism  
5. We use augmented reality/virtual reality (AR/VR) to enable workers to collaborate meaningfully with machines through a simple and intuitive interface  
Trust – Building trust with humans and in machines  
1. Our employees have a clear understanding of the changes in roles, responsibilities, and reporting structures  resulting from human-machine collaboration  
2. We measure the impact of machines in elevating the employee experience in our organization  
3. Employees in our organization are open to and excited to work with machines  
4. We have a clear understanding of the potential consequences of machine failures/ biased outcomes and are fully prepared to mitigate them  
5. We’ve made ethics a key performance indicator for every employee involved in the creation and management of intelligent machines  
Total  

How to interpret your score?

  • > 100: You are a frontrunner embracing human-machine collaboration and are already transforming the way work is performed and delivered
  • 75-100: You are progressing well in the early phase of human-machine collaboration. Now is the time to focus on execution and accelerate your journey towards creating the future of work
  • < 75: You haven’t yet fully begun with human-machine collaboration in your organization. As with any big change, discretion is the better part of valor, so start small—for example, identify a subset of the human job you want to augment with a machine. Analyze the results. What have you learned? What went well? What didn’t go so well? Be honest; be critical. Look for reasons to say, “No, this isn’t working.” Pivot; adjust; recalibrate. Stay resolute.

The future of work will be shaped by two inevitable, powerful forces: the growing adoption of the intelligent machine, and the future partnership between humans and machines. Striking a balance between the two will be both the biggest opportunity and challenge for organizations. While it is true that intelligent machines will increase productivity, allow us to solve big problems, and invent entirely new products, services, and experiences, it is also certain that machines will replace some jobs and make some people’s skills and capabilities irrelevant, leaving behind those unable to keep up and compete.

To succeed in this age of intelligent machines, businesses must embrace the five Ts to reimagine tasks, restructure training, remix talent, reinvent IT infrastructure, and reestablish trust between workers and machines. How ready is your organization for the human-machine collaboration journey?


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