Contact us at MIMOemail@example.com with any questions, or refer to our FAQ section below for more information
Why Participate in the MIT MIMO-McKinsey Study?
The MIT MIMO – McKinsey Study provides industry executives data-informed guidance on how best to implement artificial intelligence and machine learning in their manufacturing, supply chain, logistics and operations. Our 2020 Study highlighted several key insights – notably, leaders in the application of AI/ML in manufacturing and operations achieve two to three times the results in half the operating time.
Participants receive a customized, actionable implementation plan that clearly lays out the actions required to maintain competitiveness with your industry peers and provides a roadmap to becoming a leader starting from your current status.
Example pages from the 30-page Customized Implementation Plan
Customized Machine Intelligence Implementation Plan
In exchange for completing our study you will receive a 30-page customized plan for your company containing:
- Benchmark: Benchmark showing your company’s progress on its MI implementation journey compared to industry peers.
- Roadmap: Roadmap showing which enablers to focus on to obtain parity with your industry peers and then become a leader.
- Playbook: Detailed Playbook outlining specific recommended next steps for your company.
Who should participate
Any company who aims to improve performance in operations by leveraging cutting edge technology such as Machine Learning or AI.
AI integration is difficult, and every company encounters different challenges during implementation. For some, AI improved their business across the board, in areas from efficiencies, to revenue, to responsiveness. Meanwhile, other companies have invested significant sums and still struggle to see success with their initiatives. This survey will uncover the current best practices that businesses use to leverage AI effectively at their organizations.
Toward smart production: Machine intelligence in business operations
A detailed study of machine intelligence in industrial and manufacturing operations reveals the surprisingly different paths companies can take. But a group of leaders shares similar characteristics.
What do we mean by Machine Intelligence?
Machine intelligence goes beyond predictive analytics or prescriptive analytics. When we say machine intelligence, we refer to a computer model that learns from historical or real-time data and adjusts its actions autonomously to achieve a human-set goal.
The MIMO/McKinsey MI Study featured in the Harvard Business Review
What Makes a Company Successful at Using AI?
Companies in a wide range of industries are trying to integrate analytics and data to improve their operations, with decidedly mixed results. What are top performers doing differently…
The longitudinal bi-annual survey is a collaborative effort led by McKinsey and MIT’s Machine Intelligence for Manufacturing and Operations (MIMO) group. It will be used to study artificial intelligence (AI) in manufacturing and operations- with the goal of identifying how manufacturing and operations leaders create the right organizational capabilities, prioritize use cases with the largest KPI improvements, and track trends over time.
Your company will receive customized feedback to help you determine how you can get on the path towards becoming and staying an industry leader in Machine Intelligence implementation. AI integration is difficult and every company encounters different challenges during implementation. For some, AI improved their business across the board, in areas from efficiencies, to revenue, to responsiveness. Meanwhile, other companies have invested significant sums and still struggle to see success with their initiatives. Even more, others still have trouble determining where to invest to begin the journey. This survey will help organizations understand how their manufacturing and operations AI capabilities compare to other companies. Furthermore, it will uncover the current best practices that businesses use to leverage AI effectively at their organizations.
The inaugural MIMO-McKinsey study asked companies to report their AI capabilities and performance in nine categories — strategy, opportunity focus, governance, deployment, partnerships, people, data execution, budget, and results
Gathering the data required to fill out the survey will vary from company to company. Some companies without established data collection practices will find the process time intensive; however, gathering and inputting accurate data will provide your company with an accurate roadmap to becoming a leader. Once your organization has the data compiled, the survey should take approximately 1 hour to answer the 40 questions.
We recommend the individual filling out the survey be someone with a comprehensive view of the AI efforts at your company or in their division (e.g. Chief Data Officer, CTO, CIO, VP of AI, VP of analytics, Division Director).
Can my company fill out more than one survey since I have multiple divisions that I would like to benchmark?
Absolutely! If you have multiple unique divisions within your company, each are allowed to fill out their own survey, which will provide more granular insights and feedback for your operations after data analysis.
Customized and tailored playbook that benchmarks your company's performance compared to the rest of the industry, with best practices and a roadmap to becoming and staying a leader in machine intelligence implementation.
An overview of AI in the manufacturing and operations landscape, MIMO and McKinsey will host a joint Webinar for all survey participants to present exclusive insights.
- Read about the study in the Harvard Business Review
- Learn more about the survey on McKiney’s website
- Read MIT coverage of the MIMO – McKinsey Survey at MIT News
- Control.com article discussing interview with MIMO Managing Director Bruce Lawler and the MIMO – McKinsey survey: MIT Promotes Industrial Competitiveness with MIMO Educational Program
- Harvard Business Review - The results of the MIMO-McKinsey study were published in the Harvard Business Review (HBR Article). For additional reading, please also find here a more detailed version.
- Fortune - Fortune and Fortune’s CFO Daily Newsletter covered the study: Companies are turning to A.I., but C-suite collaboration is crucial for success.
- MIT News - MIT News reported on the study and also presented additional examples of relevant research.
- Podcast - Listen here for a recorded episode of McKinsey Talks Operations where new research on what makes a company successful at using AI is discussed.
- 2022 MIT MIMO Symposium - Pete Kimball presented at last years MIMO Symposium on the MIMO-McKinsey study (YouTube link)
- MIMO-McKinsey Study Participant Webinar - Pete Kimball, Ingrid Millan, and Bruce Lawler presented on the study's findings and playbook (YouTube link)
For any additional questions or to find out more, please reach out to us at MIMOfirstname.lastname@example.org.
Thank you to our partner companies who participated in the study, including Wayfair, Amgen, Analog Devices, McDonald’s, Cooper Standard, Bayer and 100+ leaders across technology, manufacturing, aerospace, retail, healthcare, supply chain, automation, and logistics.