What I Enjoyed Reading This Week

In this new series, every week, I will talk about three articles or posts that I found insightful.

Here it goes for the current week:

1. How acquisition by big tech firms demotivates the early adopters to invest in the learning curve, curtailing pay-off for new bets?

This research paper by Raghuram Rajan, India’s former RBI Governer, and his team makes an interesting case about the indirect effect of acquisition by big tech. Mostly in media, we hear about big exits resulting from the acquisition, but there is another side to this story.

Early adopters, who are enthusiastic about technology, make huge investments in learning using new products. This creates a switching cost for these users. These users are critical for new products and services as an application point for the growth of these products.

For early adopters, the incentive for investing in new products is the delta between the experience of new products and current products.

That’s why, with the trend of big companies acquiring these products, this incentive is curtailed, and early adopters aren’t motivated to invest time in new products. This creates what this paper calls “Kill Zone”.

A case in point is my tryst with a smartwatch. I am a loyal android user, and in the android world, I don’t have a clear winner in the smartwatch category. I was planning to buy Fitbit, but I have been waiting for Google to launch one. With the recent announcement of Google acquiring Fitbit, I am all the more unincentivized to invest my time in Fitbit. I am sure there would thousands of users in the exact same predicament.

Link to the paper – Kill Zone

2. Python 3.8 has come out with a new cool feature – Walrus Operator

Python release it’s the alpha version of 3.8 this week. Apparently, one of the most discussed features in this release is the Walrus Operator.

This operator can be  used to assign to variables within an expression using the notation NAME := expr

virat_score = 4

# The expressesion checks whether virat_score was greater than zero 
# It also assigns this value to sachin score
if (sachin_score := virat_score*2) > 0: 
    print(f'Sachin: {sachin_score} and Virat: {virat_score}.') 

# Output: Sachin: 8 and Virat: 4

Read more about this operator here – Try out Walrus Operator in Python 3.8

3. How even an attractive industry could be doomed because of price war?

This week in one of the courses at Kellogg, I read “General Electric vs. Westinghouse in Large Turbine Generators” case.

It’s an interesting case of an industry, which should be profitable, based on industry forces:

  • High barriers to entry resulting from economies of scale in producing these heavy engineering products
  • Concentrated industry – General Electric and Westinghouse own 100% of the industry. Thus tacit collusion should be easy.
  • Almost zero threat of entry (foreign player practically not allowed) or substitute

However, the price war between the two players, especially during the low demand phase, takes toll on the profit. The opaque pricing further deters tacit collusion, as players can’t quickly identify and punish bad behavior.

It would be interesting to see how these players would reach price understanding. That’s my reading for the next week.

Many of the economic forces in this industry are similar to what B2B SaaS firms face. For example, my team at Cisco (Endpoint Protection Software) – a B2B SaaS product was in a similar situation.

Find the complete case here. It’s paid though 🙁


About the author

Product Manager at Google | Kellogg MBA '20 | IIT Delhi Graduate

I am passionate about product management, startup, and fitness not in any particular order.

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