The sharing of data for convenience is one of the great trade-offs our generation will face – unfortunately, something that has received little consideration from users of various platforms thus far. Complex user agreements prove too much of a hurdle to be bothered by. I feel there is work the legal industry needs to do here by finding the tricky balance between usability of agreements, yet enough detail to cover all elements of the interaction. In terms of data protection, encryption is going to become more important. Users have to become more willing to pay for encryption services such as PIA VPN. Furthermore, there are interesting blockchain applications that are debated around the world that will allow users to decide on what data they share with who. As big as an industry as all these amazing innovations are, the protection around data will certainly rival that in terms of business opportunities.
This is a great piece. I would be interested to dig deeper how companies validate what feedback they are getting on these platforms – are consumers saying they like A, but they might not actually like A? What would incentivize them to do this? Can competitors sabotage the process? This may however be a very useful tool when entering new markets, where nuances in consumer taste are difficult to capture on a large scale without trial and error.
Ideally, open sourced idea generation would be great. More ideas, often by people closer to the issues. However, issues arise in the ranking of these ideas. There may be people who have little knowledge of the topic and are unable to both effectively rank ideas on merit, but are also unable to recognize their inability to do so. I would prefer government taking a more “consumer-centric” approach to governance, considering the electorate more frequently than during election periods. Where open-sourcing ideas can assist in this, I believe there may be some beneficial opportunities.
This was a really interesting, especially considering how difficult it can be for Salesforce to use feedback in a meaningful way. It seems that the best way forward may be incremental – it is about customers being comfortable with the way they interact with the company, as well as how their data is being used. I would hypothesize that companies are more sensitive to the way their data is used than individuals tend to be. A really insightful article, thank you.
What interests me is how BMW could implement 3D printing for after sales items. As an example, if a BMW is serviced in a country, say South Africa, the parts replaced often have to come from Germany. If these parts could instead be printed when needed, there could be substantial cost benefits to the consumer. Further, older BMWs may also be cheaper to service given that it can be more difficult to find original replacement parts for older vehicles.
Great article and so relevant to cities that are attracting large levels of population growth (2% is a lot of people considering the size of Toronto). The allocation of resources and efficiencies thereof are critical going forward. It was great to read of a tangible application of ML that is easy to understand and can be comprehended in the near term.
A positive impact I feel this would have on the world is to potentially lower the cost of accessing shoes. This will mean that people living in more rural, developing areas (or even in space!) will have access to products they may not have had before. Further, if one could re-use the input material to create a new shoe based on a different design, the environmental impact could be significant.