This is a really interesting way for a government and it’s citizens to interact. Given the traditional lack of engagement and trust, I’m curious what metrics the government was using to measure the success of the open innovation project. Additionally, how were they able to encourage participation on a broader scale? I agree with the recommendation that the feedback loop should be strengthened to not only get feedback throughout the project life cycle but to also give feedback about what was actually implemented to those who participated. This would encourage continued participation and engagement.
I think that additive manufacturing will really have the ability to transform the medical industry and greatly help with product innovation. Thinking through your second question, I can’t imagine that additive manufacturing will have the ability to replace doctors. I would recommend that the medical device companies form partnerships with leading research hospitals so that the physicians are well versed and on board with their new products. This will also help companies like Stryker prove the efficacy and safety of their products. Without buy in from the physician, who is typically the person a patient trusts and interfaces with, I think it would be tough to really disrupt the industry.
I agree that this technology could have big implications for the construction industry. One big challenge the industry is currently facing is labor shortage and increased costs, so this could actually be beneficial if it will reduce the labor required on each job site. Although the technology reduces the construction time, it is still not proven to reduce the costs for a developer. It will be interesting to see if this technology becomes widely adopted but I am concerned about how companies will scale since construction zoning/permits vary by locality.
I do not think that GE should continue investing in Predix for a couple of reasons. GE is facing competition from much more nimble start up companies like C3 IoT and Palantir that have a core competency in software development. These companies are able to develop software at a quicker pace and gain a competitive advantage. Additionally, because the nature of the space, it will be very difficult to create a “one size fits all” solution. Even within one industry, there are serious challenges when looking at data availability, uniformity, and sources. These will vary by customer and therefore require individualized solutions.
I agree with your concerns about patient and population bias especially because this is sensitive medical data that can impact how a patient seeks treatment. There wasn’t any mention of any data governance or controls that PLM has implemented to attempt to protect against false data. Did you think about any type of review system or verification process that each submission would have to go through? Another concern regarding data is the input and formatting. The platform is only effective if all users input their data in a standardized format.
I am curious how effective the duplicate review tool is at identifying duplicate postings of an item. It seems that this tool is heavily dependent on the data entered by the user and therefore its effectiveness could be limited. One way to overcome this obstacle is require certain data fields to be entered before a user can list an item. This would ensure identification of duplicates and also improve the strength of the product catalog. Additionally, what kind of communication does Wayfair send to a seller before the postings are consolidated? The seller might have a preference on which price is taken for a duplicate listing or have legitimate reason for posting an item twice. Since Wayfair is a marketplace, I think it should be up to the sellers discretion how many times an item is listed.