Facing Such a Complex Landscape, How to Forward with AI for New Product Development
Dr. Robert G. Cooper
Professor Emeritus, McMaster University, Canada, ISBM Distinguished Research Fellow at Penn State University
I was in Dublin last week at a Conference on Product Innovation at the IRDG, giving several workshops and also a day-long seminar on AI for NPD. One participant came up to me during the break and confessed that he wished he had a “friend” – perhaps an Irish Elf – to sit beside him and whisper in ?his ear to give him advice on how to move forward with AI.
As a member of his firm’s Exec Team, he explained that “we all know that AI is coming fast, and that it will affect all aspects of business… so we need to get going now!”?
“BUT!”… he went on: ”The risks are high – it’s a lot of money to acquire and install some of the application software”, and also there’s a high failure rate. He again confessed that he and his colleagues were a bit overwhelmed by the AI landscape, the choices, the number of vendors and solutions available, the costs, and the risks…. hence his desire for an Irish Elf to advise him.
Later in that session, I outlined how another company – closer to my home in NA – had a similar problem. They were further ahead, and had tried several AI solutions for various NPD applications, without seeing much value.
Their solution, according to the head of Product Engineering: “For AI projects, we simply run them thru our tried-and-proven gated new-product process – appropriately modified… and it works.”
His NPD process was created to avoid ”dumb mistakes”, and to ensure that the right work was done… why not use that process for AI projects? The main difference is that “for NPD projects, our (B2B) customer is an external one; for AI-acquisitions projects, the customer is an internal one, in this case our RD&E people.”
What a clever idea! ?
So here is that gated process for AI deployment projects – a generic version called RAPID – based on NPD and also on technology development processes. It's a great map for your AI journey! Some firms have used such a process for decades for internal technology developments and deployment.
The full RAPID article is new (2024), and is aimed at business practitioners like my Irish friend – it’s on the PDMA’ kHUB. Here is the link:
Adopting Artificial Intelligence for New Product Development: The RAPID Process - Knowledge Hub 2.0 (pdma.org)
NOTE: There are 2 other articles on kHUB worth a look – one deals with how to evaluate the “worth” of a proposed AI project (the major challenge is “preparing a legit business case’, say 37% of managers, according to a McKinsey survey). ?
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And other articles on AI for NPD are at my safe and free website…. These articles are mostly from peer-reviewed journals, not just a personal opinion-based blog from me
Like I did in Ireland and Germany for the last 2 weeks, I am available to do seminars, workshops, and talks to bring your colleagues up to speed – either in person or online. Also, my consulting colleagues at Stage-Gate International Inc. are ready and able to provide the assistance you might need to move forward with AI in NPD.
Contact me: [email protected]
Best Regards, Bob Cooper
Dr. Robert G. Cooper
Professor Emeritus, McMaster University Business School, Canada
ISBM Distinguished Research Fellow, Smeal Business School, Penn State University,
USA Crawford Fellow, PDMA
cell: (+1) 416-580-6419 www.bobcooper.ca
I help product designers with their development process through strategic use of quality and reliability methods. ★ Engineer | Senior Quality Professional | Consultant | Speaker | Podcast Host ★ Quality during Design.com
1 个月Thanks for sharing your research openly. I've worked in stage-gate NPD for years. With experienced professionals, there's comfort in knowing your stuff and having similar projects as a baseline. With AI, it's difficult to see where it's headed and its specific value. With implementing AI, I can see why using a stepped, project approach helps. It breaks down this huge question: where can we use AI? Then planning to iterate and adapt seems like the key. Dr. Robert G. Cooper, with these iterations, how are businesses setting up their teams? Do they have an 'AI team' that helps different functions? Do they have one expert that leads tiger teams?