Note: As a standard practice, I will include a plagiarism detection link in all the articles on my blog site. You can use the online tool below to evaluate any article published on the web for plagiarized content. All you have to do is to paste the url of the article there and it will go through every sentence in the article and flag any plagiarism. I believe as a follower of “writer’s integrity” I should include this tool in all my articles:
Prof. Scott Galloway recently coined the term “Algorithmic Commerce” in one of his posts on LinkedIn. The image from that post is below:
Now this term was coined with specific reference to exploring the reasons behind why Walmart has decided to accquire a stake in TikTok with Oracle. I will cover the particular scenario mentioned in the post in a subsequent section but to start with, I believe Prof. Galloway has essentially predicted the future of eCommerce in two words- Algorithmic Commerce. If you followed my “Viral Chain” newsletter, in more than one episodes, I used the phrase- “In the future, It will be Algorithms competing against algorithms“. So my perception of businesses is that most of the businesses will now be Algorithmic Businesses. Not just eCommerce- The world of business is entering the era of Algorithmic Businesses.
Can it be done ?
Now before I discuss what I mean by Algorithmic Businesses further, the nerdy side of me wants to dissect the specific use case of TikTok data suggested in Prof. Galloway’s remark above. As soon as I read it, I couldn’t stop myself from digging into how it can be done. Can it be done ? Yes- let me tell you how in simple terms- You can leverage AI (technologies like Neural Networks, Speech to Text and NLP) and Analytics Algorithms to identify:
- Who has voiced that they are definitely going to buy a certain product in your store or website
- How serious they are on the committment they are making on this buy
- When do they plan/ expected to plan to buy the product.
While the three high level aspects are simple English, the plethora of Algorithms that you will have to leverage is not so simple. However, you can indeed get an “Expected Probability” of a Customer ID making a Buy. But the other real challenge starts there. How do you leverage this information now ? And this is where I disagree with Prof. Galloway- No, you should not be shipping directly to a customer. And let me be more direct here- The cost of error in shipping directly to customer is high. Extracting buying sentiments from videos even with high probability, will still be not as concrete as that derived from browsing patterns (Like Amazon’s predictive shipping).
The best bet, for Walmart will be to ship it to the nearest store of the customer. And even in that scenario, it needs to leverage a heuristics to make sure that it is using pre-existing lanes and capacities for these moves, so as to not incure any additional costs. Sorry if you were not interested in the details and I still ended up sharing them. I got carried away since this is the type of stuff that excites me. I can see some more realistic ways an Omnichannel retailer like Walmart can leverage TikTok data but that is not within the scope of this article.
But let us come back to the Algorithmic Business aspect
So coming back to our Algorithmic Business-take any Industry. Say Bio Pharma for example, and pick top three players. They may have different drugs in pipeline and portfolio but their basic Value Chain remains the same. They operate the same way. So if you think about this from an Operating excellence differentiator example (excluding competitive edge from R&D edge and innovations), there are hardly any differentiators between the top players.
And that is where the power of Algorithms comes into play.
Algorithms, AI, ML or Heuristics, can help you gain operating excellence edge, like executing processes faster and more efficiently, or in some cases, transforming the entire processe(s). And in some cases, helping develop standalone Digital products and services as well that can be commercialized. This will take the heat away from the constant New Drug pipeline pressure and this reduced pressure may lead to actually more innovation. Now you can replace BioPharma with any other Industry (like CPG for example) and the fundamental aspects of what I have described above remain the same. Value chains of top players is very similar and even the processes are similar. The current existing technologies that they use across their value chain is also commoditized. The only way for one player to gain a competitive edge over the other is to build a unique Algorithms, that transforms their processes so efficiently that they respond to customer demands or Market much faster, efficiently and in more innovative ways.
And hence my phrase that- In the future, it will be Algorithms of the companies that will compete with each other.
Views expressed are my own.