Looking back at 2011 one of the most remarkable stories has been the continued decline of Research in Motion (RIM). A recent NY Times piece speculated that perhaps some of the problem lies with the many different models (and their sometimes confusing names) that RIM developed in its push to be more consumer friendly.(1)
Ian Austen, the author, notes:
Features have proliferated on BlackBerrys as part of RIM’s move to the broader consumer market, and so have the number of models. Since 2007, RIM has introduced 37 models. The company, in a statement, said it did not know how many models were on the market.
Leaving aside the remarkable admission from RIM that even it does not know how many models are on the market, contrast RIM’s approach with that of it’s principal competitor, Apple. As Austen notes, “By contrast, Apple has introduced only four iPhones since 2008 and all were basically the same phone with differences in the amount of storage, or upgrades from older models.”
What is the relationship, one may ask, between choices and risk? Some risk strategists would argue that having many models is a sound risk management strategy and that betting the whole cell phone business on one model (as Apple has basically done) is reckless beyond belief. The contrary view would say that you take on a much higher level of risk in trying to develop a host of successful cell phones instead of just one. By focusing your resources on one or two good products, goes this line of thought, you lessen the risk of a failure cause by too many inferior products. For this latter group, RIM would be the prime example of this phenomenon at work.
So who is correct, from a risk theory standpoint? Maximizing product lines to, in effect, replicate the portfolio effect or limiting options to the few and best?
A recent draft paper by Daniel Dorn of Drexel University make some interesting points on the question of choice in selection of derivative products.(2) Dorn writes that:
This paper examines the German market for OTC derivatives, a retail market in which choices should be straightforward: up-to-date product information is available, products can be compared in electronic databases free of charge, and product pricing is well understood, at least in the case of the plain-vanilla instruments studied. Despite these features, prices are dispersed even for simple, homogenous, products. Moreover, investors buy products that systematically underperform other similar products that they could have bought. The observed mechanisms driving the underperformance (investors’ preferences for products with low nominal prices, more heavily advertised products, and the status quo) suggest that investors rely on suboptimal choice heuristics even when placing large bets in a transparent environment.
Dorn’s paper examines three possible explanations for this phenomenon:
Under the rational null, investors costlessly identify attractive alternatives; economically meaningful price dispersion across instruments reflects genuine product differentiation. Since information about product features and prices is readily available, this null hypothesis is not unrealistic. Under the alternative hypothesis of costly search, prices can be dispersed even among homogenous products and investors with lower search costs or greater search incentives make better choices. Finally, the alternative hypothesis of behavioral search admits the possibility that investors make inferior choices, on average. Unlike rational searchers, who may choose to stay uninformed and pick an alternative at random, behavioral searchers may rely on choice heuristics that systematically steer them into inferior alternatives.
One of Dorn’s main conclusions would be familiar to any experienced retail executive: “For many investors, however, product differentiation can be harmful because it complicates their search problem. If retail investors have trouble identifying attractive products in this transparent market, they will presumably do even worse in the more opaque environments that characterize many other retail financial markets. Moreover, financial intermediaries may have incentives to engage in spurious product differentiation to exploit investors’ reliance on simple choice heuristics.” In other words, the many choices, often superficial ones, among the products increases the “search costs” for investors and this cost is reflected in the suboptimal choices they make relative to derivative selection. Returning to our cell phone case, one could argue that selecting a cell phone is for the ordinary buyer an “opaque” process, since the average consumer often does understand the subtleties of data throughputs and operating system features. In this case, a too complex product line increases the search costs for consumers, resulting in their suboptimal selections. When enough consumers realize this phenomenon, they naturally seek an alternative in a simpler set of choices, assuming that within a limited selection at least one product meets their needs.
I would argue that the phenomenon Dorn observed in German OTC derivatives is more or less what has happened between RIM and Apple. RIM, seeking to broaden its appeal to non-enterprise buyers chose to offer many choices – so many in fact that it increased search costs for its products to a level the market was unwilling to bear. Apple too the opposite approach. Of course, this is not the main reason why Apple has done well and RIM has not. But it is a contributing factor, without a doubt. As such, the lesson learned is that choices, given and retracted, impact the risk profile of a company. One wonders how many other industries (tires and white goods come to mind) would benefit from a dose of option rationalization and search cost reduction.
(1) Austen, Ian, “A Bogle of Blackberries.” Nytimes.com. NY Times, Dec 16, 2011.
(2) Dorn, Daniel. “Investors With Too Many Options?” ECB Working Paper, 2011.