Notice that in the input layer there is another aspect of the investor’s identity: the thumbprint. This identity layer is effectively immutable and includes existential characteristics such as geography and organizational type, for example a state-level pension fund in the US Midwest or a sovereign wealth fund in the Middle East. Generally, footprints come with restrictions on what an investor can and cannot do. Yet footprints shouldn’t be seen as just obstacles: being a county-level pension fund in Silicon Valley can give unique access to venture capital funds; and A$70 billion ($46 billion) Cbus Super, an Australian superannuation fund for construction workers, uses the specialist knowledge of its board members (many of whom come from the construction industry) to build a best-in-class investment program for properties. In short, thumbprints – and identity in general – can be turned into competitive advantages, which is a key reason why investors should aim to match patterns to their identity, not the other way around. Another (related) reason for investors to choose models that are consistent with their identity (as opposed to trying to change their identity to fit a particular model) is that each model is like a combination lock: it has a specific set of inputs and activation elements (and in some cases fingerprints) that are required for it to work. But if any of these are missing, the model will not “unlock” for the investor, no matter how excellent its other inputs and enablers are.
For role models, one or two focal inputs or factors are the main points of the model, and it is these main points that are emphasized when the model is mentioned by other investors. Yet in any case, all other inputs and enablers must be “just right” to support these anchor points and make the model work. Moreover, many investors treat the set of role models as an exhaustive and mutually exclusive menu of models to emulate – as if these are the only worthwhile “career paths” available. This is partly understandable, as these models have clearly performed well in the past, albeit through input configurations and triggers that may be difficult (if not impossible) for other investors to replicate. For most investors, it is best to use the role models as inspiration in designing their own form-fitting models, rather than using the role models as paint-by-numbers recipes to be followed precisely.
A final complication in investors’ identity crisis is the presumption that role models are static and do not change or merge over time. The fact is that the investors who pioneered these role models have been so successful in part because they have not stuck tenaciously to their models: for example, the Yale Foundation sometimes embraces components of the collaborative model, and Australian pension funds sometimes emulate parts of the Norwegian model. By analogy, it may be a good idea for funds to look for hybridizations, selecting elements of known models that can blend together (and match their identity). But it’s vital to make sure these elements are actually compatible: It would be very difficult to be a rock star and a surgeon at the same time (which would give a whole new meaning to the phrase “rock star surgeon”); but it’s perfectly plausible to be both a scientist and an astronaut – in some cases being both might be better than just being one or the other.
Yet, no matter what model an investor chooses – whether a hybrid of existing role models or something entirely new – there is an imperative need for that model to match their identity. Otherwise, the investor is flirting with failure. And that failure may not come immediately; it can happen when some future shock hits. This is one of the most damaging things about an identity crisis: its severity can only become clear during other kinds of crises (eg a fireball of rising inflation and cross-market takeovers…like now). But it’s a negative surprise that can be avoided as long as investors are willing to take a long look in the mirror and analyze their inputs, incentives and footprints in depth. We hope they will use our framework to do just that.
Ashby Monk is executive and research director of the Stanford Research Initiative on Long-Term Investing, and Dane Rooke is a research engineer, also at Stanford. Both authors are based in Palo Alto, California. This content represents the views of the authors. It was submitted and edited according to P&I guidelines, but is not a product of the P&I editorial team.