Nitin Chaudhary

Travel Writer and Photographer based in Malmo, Sweden

Books on Strategy, predicting a downturn, and Big Pharma’s struggles with managing generics

Books on Strategy, predicting a downturn, and Big Pharma’s struggles with managing generics

In last two weeks, a lot of good articles came out on the inter-related topics of rising debt (‘the world has never had as much debt as it has right now’), falling profits of American tech giants (despite Microsoft’s stunning turnaround), and how the US economy may be heading towards recession after the longest economic expansion ever (‘a full decade has passed since the end of the last recession, and the economy continues to grow’). Predicting recessions is challenging for there are several different markers that could indicate a potential downturn. Ben Casselman wrote this insightful piece on the early indicators of recession. As you would gather after reading it, there is no foolproof marker yet. Spike in unemployment is reliable, but lagging indicator. So far, the US unemployment rate has been steadily declining. What I got interested in is yield curve inversion (when short term rates exceed long term rates. In good times, long term rate are higher to compensate for the duration). This inversion has already happened, and historically, yield curve inversion has been a sound leading indicator of a recession at least in the US. I found this piece and this piece useful to learn more about it. 

Given the lack of reliability, individual opinions start gaining prominence. For example, back in 2018, Ray Dalio, famous hedge fund billionaire, had put the probability of a recession at roughly 70% before 2020. Such opinions will only become more frequent. After reading all the stories, two thoughts came: first, predicting uncertainty could feed uncertainty, and create a downward spiral. If we all believe the economy is likely to get worse, then it will get worse. For instance, even though there was no clear conclusion that we may be heading towards a recession, we may still want to protect our investments — taking those actions may feed more uncertainty in return. Second, given the enormous complexity, could AI serve as a more objective tool to predict recessions? Surprisingly, I didn’t find a lot of good articles summarising ongoing work in this area. Maybe I missed the key research here, but if you have come across any, let me know. 

A thought leader I started following last week: Vas Narasimhan, CEO of Novartis.  Vas wrote this short but super useful piece on managing energy instead of time. In this piece he writes about sleeping at least seven hours a night, intermittent fasting (‘I ask myself—why am I eating? Is it for performance, for enjoyment, or because of anxiety?’), the need to move (he exercises six days a week), and mindset (he has a personal vision, and practices meditation regularly). I came across Vas’ writings as I was reading about how Pharma majors are restructuring their generics business to either make them more autonomous (like Novartis on Sandoz) or spinning-off (like Pfizer is doing with Upjohn and Mylan). Separating innovation-fuelled drug discovery business from generics, which demand relentless focus on efficiency, makes sense. This approach almost sounds an opposite, but equally relevant, extension of blue ocean strategy where established businesses unshackle parts of businesses to let them focus on innovation. The approach taken by Big Pharma could work for other industries too that are struggling to counterbalance productivity and innovation ambitions.

This week most of my reading centred around my craft: strategy. While there is no better way of learning than building and implementing strategy in real life/projects, there is still a benefit in revisiting the theory occasionally. So I dug up some old books that I am either re-reading now, or plan to do so soon. Here is a list in case you are looking to read up on this topic too: 

  1. The Art of Strategy by Dixit-Nalebuff: A follow-up to Dixit’s earlier book, Thinking Strategically, this one goes even deeper into game theory, explaining how to employ math and probabilities to guide decision-making. Anyone interested in decision-science can read this book, for the scope is far beyond corporate strategy and has real life implications as well. I am not through this book yet but will write a summary when done.

  2. Playing to Win by Lafley-Martin: A practical book that simply, succinctly captures the nuts and bolts of strategy implementation. It helps that Lafley, former CEO of P&G, brings out examples from P&G to elaborate the principles.

  3. Good Strategy, Bad Strategy by Rumelt: Despite the plain-looking title, quite possibly one of the best books written on the topic. I read it a few years back and remember it to be full of case studies, along with commentary on what derails the strategy building process. A dense and handy book.

  4. The Art of Action by Bungay: Sourcing experience from military history, (especially, 19th century Prussian army), this book answers the question which is bane of most strategy implementation processes: What Do You Want Me To Do? I was lucky to attend a workshop by Bungay (ex-BCG) once, and a lot of learning from this workshop and the book guides my thinking to date. Thanks Jesper Klove for introducing me to it.

  5. Finally, there are several books that can serve as introduction to strategy. I browsed through HBR’s Essentials on Strategy, but it’s a very basic read and I don’t recommend it. Instead suggest reading Competitive Strategy by Porter, which, though old, captures the essentials better than most primers.

Any other book that you have found a useful read on strategy?

A quote I came across last week:

“It is amateurs who have one big bright beautiful idea that they can never abandon. Professionals know that they have to produce theory after theory before they are likely to hit the jackpot.” 

― Francis Crick 

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