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6 thoughts on “DeliveryHero: Managing over 150,000 restaurants in 40 countries using machine learning

  1. You did a great job of clearly articulating the challenges to each stakeholder in the process. Additionally, I really appreciated the use of questions and examples throughout. I would be curious about what you think the challenges are over the next year or so? And what you think the challenges are longer term?

  2. What an interesting read! I agree with you about the challenge of empowering sales employees when data and algorithms are driving the decision-making. There needs to be a delicate balance of data and intuition, applied together. I think that it’s important for companies to establish guidelines on certain instances when the latter can override the former.

  3. Awesome post! Your essay, and in particular your open question at the end, led me to think about the use of machine learning as a spectrum. Does using machine learning to identify leads mean the algorithm has to output exactly the list of restaurants Deliveryhero would go after? What kind of process could Deliveryhero put in place that would allow the machine learning algorithm to supplement the work of their employees, but not completely eliminate it if it’s not additive to the business?

  4. Great article @EmperorOfJapan! One additional area that the article/algorithms mentioned do not identity is the ability of improving the experience of a customer by providing them food options that they are “most likely to enjoy”. This can definitely be done by combining multiple data sets (e.g., typical target customers for restaurant, customers background/order pattern, etc.).
    Thank you for sharing these great thoughts!

  5. Your post made me re-think the delivery ordering experience. It sounds like DeliveryHero’s use of machine learning will make its sales employees’ lives easier, and allow them to allocate their time more efficiently. However, I wonder if the machine learning algorithms would be able to identify new-concept restaurants that don’t fit previous trends for an area. The oversight could result in another delivery service signing the restaurant first, and a loss of future revenue for DeliveryHero. I think that human intuition and judgment could still be relevant and necessary in such cases, and DeliveryHero should make sure that their sales reps don’t stop acting on these kinds of intuition.

  6. Thanks for an interesting article! Different from most of papers or articles are about how to use machine learning as an engineer or the leader of the company, it is really interesting to think about the issue as a sales manager of food delivery services that has valued the insight and knowledge of people on what food/restaurant consumers might love. I don’t think machine learning algorithms would make sales employees demotivated about their roles. Of course, some of AI technologies would replace sales employees, but still, ‘Food’ is strongly linked with each person’s preference. Sales team can use their time on analyzing and finding the opportunities for hidden charms in local area and delivering the best message to its customers. It is up to the company’s decision on how to use just the ‘right’ level of machine learning technology on the context of the business.

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