Friends,
I hope all is well with you and yours, and that this e-mail finds you on a boat with shoddy connection, in the tropics, three months after I sent it.
Some quick updates before we go-go
A rather short(ish) newsletter today again. I apologize. I am yet to fully recover from my full house of maladies, nor have my wife and daughter recovered from theirs.
In a week or two, there will be a separate email discussing the future of Strategy in Praxis. Do not worry, it is not going way, but some changes are coming. At the moment, I feel a bit like butter scraped over too much bread, and the newsletter is suffering for it. It is time to step up the game.
In the news
Walmart is cleaning out its DTC portfolio, selling a number of recent acquisitions including Bonobos and Eloquii. Although there usually is more to a story than meets the eye, it sure appears as if the company is coming to the same conclusion that James and I have for years: pure-play digital DTC often costs more than it is worth.
Amazon’s retail media is growing and it is growing faster than the advertising arms of its biggest rivals. In Q1, the firm reported a 21% ad revenue increase, slightly improving upon the previous quarter’s growth rate, but beating the other big ad-selling firms by some distance. Of course, in absolute numbers ($9.5B), it is still nowhere near Alphabet ($54.5B) or Meta ($28B).
Remember Clubhouse, the supposed Twitter killer? Well, it seems nobody else does either. The company has struggled to remain relevant and recently announced that it is laying off more than 50% of its workforce.
Item of the week
Melanie Mitchell is a professor at the Santa Fe Institute, working in artificial intelligence, cognitive science, and complex systems. To say that she is an intellectual heavyweight would, in other words, be to put it very mildly indeed. In this Substack column, she breaks down the recent debate around ChatGPT and similar Gen-AI in a refreshingly nuanced analysis.
Ultimately, to figure out what we really need to worry about, we need better AI literacy among the general public and especially policy-makers. We need better transparency on how these large AI systems work, how they are trained, and how they are evaluated. We need independent evaluation, rather than relying on the unreproducible, “just trust us” results in technical reports from companies that profit from these technologies. We need new approaches to the scientific understanding of such models and government support for such research.
Indeed, as some have argued, we need a “Manhattan Project of intense research” on AI’s abilities, limitations, trustworthiness, and interpretability, where the investigation and results are open to anyone.
Moving on.
PEST: a simple framework with obvious value
But complications lurk beneath the surface
Although the topic remains one of some debate, many would agree that the PEST (Political, Economic, Social, Technological) framework was first created by Francis J. Aguilar in Scanning the Business Environment (1967). Designed to take an external view, it seeks to define the context in which the organization acts:
Political aspects are those affected by government intervention, be it policy, legislation, or what Stewart Brand would have called “governance”. Examples include both that which may affect the market and that which may affect the company (e.g., tax or employment legislation, merger limitations, and environmental regulations).
Economic factors are macro by nature; interest and exchange rates, GDP growth rates, demand shifts, inflation, recession, stagflation, and so on.
Social variables cover social, cultural, and demographic changes, such as attitudinal shifts, movements, or trends in gender roles, living standards, or educational standards.
Technological factors, lastly, include new technological infrastructures, incentives, innovations, and developments.
Notably, all of these are beyond the immediate influence of a firm (one could perhaps make an argument for certain political aspects being exceptions via lobbying, but let us ignore that for the moment). Rather, the point of the PEST exercise is to establish the competitive environment so as to facilitate more effective strategic planning; at its theoretical best, the framework should help organizations recognize opportunities and risks around them, thereby enabling preparation of appropriate responses.
The problem - and stop me if you have heard this one before - is that the practical reality is rather more difficult to accurately define than PEST proponents will admit. From my experience teaching clients how to do competitive analysis, managers often struggle with establishing what their environment is, either because they take a very narrow view or because they simply do not know where to draw the line. This issue only grows as the company does.
Further, like all frameworks of similar generality (McKinsey’s 7S model being another recent example), filling in the gaps properly requires what one might call submodel understanding; each letter contains a library’s worth of additional theories, hypotheses, and perspectives. To illustrate, as Bensoussan and Fleisher note in Strategic and Competitive Analysis: Methods and Techniques for Analyzing Business Competition (2003), there is the Industry Structural Model perspective, the Cognitive Model perspective, the Organizational Field Model perspective, the Ecological and Resource Dependence Model perspective and the Era Model perspective, to name but a few. Each may not only generate wildly different conclusions, but also cause confusion between analysts.
Then, there is the predictability problem. For PEST to have use for strategic planning, risks and opportunities have to be visible to whoever is creating said plan. Needless to say, managers often lack such insight, either because they fail to see the trees for the forest, or because they are dealing with an adjacent possible that does not allow it.
We thus find ourselves in far too familiar waters, dealing with a framework that appears simple in theory, but can quickly become anything but in practice. Does this mean that PEST analysis is useless? Absolutely not. It is yet another tool in the proverbial bag that can provide an introductory snapshot and reminder to those looking to gain an introductory understanding of a business environment. Marketers in particular have a tendency to forget about the reality in which they act, and PEST may serve as a handy reminder.
But any strategist worth their salt will also remember the interconnectedness of the constituent parts, as well as all of that which will be left out. More often than not, the true danger lies not in the risks we see, but in those we do not.
Next week, we are going to discuss the impact of planning on employees. Until then, have the loveliest of weekends.
Onwards and upwards,
JP
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