To your second question, I do see the benefit in user input for the selection setting, but wonder how sustainable this could be for idea generation (which it seems like was a driver for the shutdown due to inefficiency). At its core, for a creative product output, it feels as though just taking ideas from others will not lead Amazon to be the leading thinker in the space at the forefront of new trends. I also think this leaves Amazon with the risk of having content that is the most “generic”, however I think to develop a blockbuster, content needs to be new and fresh. Because of this, it is counterintuitive for Amazon Studios to rely on innovation for its core competency, but it does make sense to use it to refine and improve on its core.
Thinking of the Dove case we did in marketing today – I wonder what the balance is between innovation and control of the messaging? Frito obviously does not need to take all the ideas sourced through open innovation, but I wonder if they have become so dependent on the customer for innovation that they are unable to do so themselves in the future. The balance between internal and external open innovation is one that I think could be revisited by Frito in the future if they see a slowdown in customer interest in their product, therefore a slow down in customer ideas.
Really interesting article! To your first question on how companies can leverage additive manufacturing, I think it will come down to time to market. Having also spent some time investing in the beauty industry, I saw how the smaller indie brands were winning, many times because they simply were able to come to market first with new trends given R&D cycles of 6 months to 1 year. I think that if older, more established brands with the resources to invest in 3-D printing are able to leverage this technology to shorten their product innovation lifecycle, we can start to see a really interesting faceoff between the two types of beauty products. This could be what keeps the older CPG companies more competitive in the world where they are quickly losing share.
Really interesting to see how more antiquated retailers are adapting to and leveraging technology to serve customers more efficiently. To your second question regarding the store of the future, your article had me thinking of how machine learning could further bolster the in-store experience to continue to attract customers. I wonder, could the app technology you mentioned with personalization recommendations replace much of the salesforce? Would customers want a more technology driven in-store experience, or would this alienate the customer set that still shops in store? I think that using machine learning could be an interesting way to steal back share from the digital channel, if done right.
While Coca Cola has been using machine learning for both innovation and supply chain, I think there is likely more potential for value from improving the efficiency of their supply chain. I was surprised to read that the machine learning technology being used in retailers was actually still quite manual – physical store checks with photos, which would require a lot of resources to scale globally. Given the expansive point of sale information that can be collected from retailers today, I wonder what Coca Cola is doing to leverage and learn from their selling behaviors. Perhaps a middle ground that would not require as many investment dollars would be to leverage POS data and machine learning to better optimize their supply chain management and regionalization of product assortment.