I think the answer to your very last question depends on whether a company has an access to the targeted talent pool they are looking for. For instance, consulting firms would not have incentives to use LinkedIn to recruit a general consultant, as they already have many candidates and they have established database on their own. However, many consulting firms are now looking for a new type of customers (e.g., digital, design) in which case the LinkedIn services would be very helpful.
With regards to your recommendation, while I agree that the Apple watch adoption is a critical piece, I think the limiting factor is not so much around the lack of attractive services as you pointed out, but on the sheer cost (300-400 dollars). Therefore, I think Apple should either reduce the cost or find better way to reach to the customers who can afford the watch.
In terms of your question at the end, I believe Apple should be working more on quality of the apps by creating valuable content, rather than increasing the number of partnership. In order to gather enough data to improve its machine learning capability, Apple should be focusing on getting information in a consistent manner, rather than collecting heterogeneous data from different apps.
Your last question reminded me of the AI roundtable I organized in my previous job, where we invited C-suite executives to discuss AI’s impact on the business. All the executives were highly aware about the importance of AI/ machine learning/cyber security, but they are not necessarily sure about how to deal with it. One interesting discussion we had is that what the company is lacking the most is not just the tech-experts, but also the “translators” who can translate the needs from the businesses for the tech-experts to solve the right issue, and also translate the solutions that the tech experts developed into business values. While developing an overall strategy around cyber security is important, I think the board will also need to consider a broader view on their HR strategy.
I think it would be difficult for a government to specifically subsidize Lily’s program, but there may be an opportunity if Lilly can create a consortium of open innovation programs with other pharmaceutical companies. One slightly relevant example is GHIT, which is a program funded by the Japanese government to facilitate a group of pharmaceutical companies, academia, and individual researchers to collaborate in developing drugs for neglected tropical diseases.
To your first question, I do not think Lily should expand its focus areas because a) the results from those programs will not necessarily be synergistic to Lilly’s core business and b) there is not enough incentives for the researchers to apply to Lily’s program because so many other pharmacos are also doing open innovation programs in such areas.
I agree that the heterogeneity of the data will continue to pose challenges for the use of machine learning in drug discovery. As this is an issue that will be difficult and inefficient for a single company to solve, and I wonder if a company like Pfizer could organize a consortium of companies to jointly tackle this issue. To counter some business and legal risks, they would potentially start with the existing alliances or open innovation programs that they have with other companies (rather than starting a completely new program)