R Waitumbi's Profile
Thanks for the article! This one hits close to home for me, especially since it sometimes hard to think of open innovation as a valuable tool for “old school” industries when in many cases it can be.
At my previous employer we owned a old cleaning chemicals company and one of the issues that the company suffered from was product innovation. In an interesting turn of events, one of the most significant changes in innovation came from a an executives’s wife who claimed she loved the product, but that the packaging was a major pain point – it always toppled over. One day at dinner, she drew out on a napkin what she thought a new, more stable design could like. Her husband (the executive) brought it into work and a few months later that new packaging hit the retail shelf in mass!
I think as industries and companies evolve it is easy to forget the purpose for which they were created – to serve the needs of the customer. Sometimes the customers know best and open innovation is a fantastic way to tap into the wealth of ideas that long term users of a company’s products or services have.
The issue then becomes how to qualify ideas and select the ones with the greatest impact. It’s interesting to think what kinds of organizational changes are needed to embrace open innovation kn an organization that is very set in its ways.
Interesting read. One thing that specifically jumped out at me was the hiring of Manuel Velasco to lead JPM’s machine learning research team. This draws strong parallels to Bridgewater’s hiring of IBM’s Ferrucci to head up their machine learning initiatives. It seems to me that at least in machine learning’s current form, financial institutions represent a premier employment opportunity for individuals focused on machine learning.
This raises further questions, in addition to the ones you posed above. Are there enough machine learning data scientists to go around? Is machine learning talent the true scarce resource when it comes to using machine learning to improve the operational efficiencies of an organization? If so, how would JPM change its HR initiatives in the coming years to make sure that it’s growth strategy doesn’t fall short due to shortages in employee supply?
Jane D., awesome read. It’s interesting to think about this kind of information as a public good! Honestly, as I was reading your submission, the first thought that came to mind was parallels with the movie “The Imitation Game” and their use of computers to decipher “The Enigma” code system during World War II: https://en.wikipedia.org/wiki/The_Imitation_Game
There are definitely ethical concerns with associated with knowing a catastrophe will likely occur and what you do with that information especially when human livelihood is on the line. At the same time, without the appropriate monetary incentives, does continued innovation in this area go away?
This is a really tough question for organizations like AIR but I think that bringing this discussion front and center is necessary in the evolution of advances such as these.
Your final thoughts around incremental vs transformational changes in AM for GE and the trade-offs associated with both is an important one. Especially since AM is receiving so much mind-share, it is not ludicrous to think that we could see another transformation in the way we think about AM. Even more concerning is that GE might miss out on it if it is focused too much on just small incremental changes to business processes.
In your suggestion to allocate a portion of R&D’s budget to long term technological innovations however, I couldn’t help but draw parallels to the IBM Watson case. In particular, is R&D for the sake of R&D (i.e., innovation without a particular business case or end state in mind) a good use of cash or would the organization be better suited to improve their current processes, keeping an out to make sure that the industry doesn’t side step them while they focus on incremental changes internally. Perhaps a better use of their cash might be to strategically identify advances in AM that could be transformational and bring those in house (i.e., acquire) on a opportunistic basis?
Curious to hear your thoughts!
Nikhil. Interesting read! Additive manufacturing is one of those topics that is frustrating because despite all the potential, technologically we are just not there yet to make it viable at a large scale. You pointed out a couple of these frustrations: allowable materials, talent availability, regulation (especially in air travel regulations are pretty stringent even in relation to allowable materials), and technology maturation. I would be interested to get your thoughts on another issue. Perhaps most interesting is the quality / consistency trade off with additive manufacturing vs. traditional manufacturing. While traditional manufacturing is indeed “less sexy” than AM, traditional manufacturing plants are run pretty efficiently (one might even say surgically) and we can be pretty certain about quality and consistency.
See this article: https://www.digitalengineering247.com/article/industrial-issues-additive-manufacturing/
Given the high costs of airplane manufacturing as we have seen in some of our cases, does going full bore on additive manufacturing now (in a world where consistency and quality are still questioned) the right move for Boeing? Or is their current strategy in backing organizations that try to address these issues the right move?
In the long term there is little doubt that AM is the way to go. The question of timing is always an interesting one!