While getting set-up with a gym membership recently, the salesperson asked a question that made me pause:
“What is the barrier to you signing up today?”
It was a really good question and a good example of bottleneck thinking—namely, that you must first focus on the limiting factor, the part of the system that is most restrictive to the overall system’s output (i.e. the bottleneck).
Bottlenecks can often be spotted by looking for queue formation (queues of people, inventory, information, etc.). For a familiar example, if the security screen at the airport is the slowest part of getting on a flight, there is little benefit in speeding up any of the other steps leading to that moment (e.g., the check-in process), as any extra time created will only result in more waiting at security—i.e., the bottleneck. At the moment of my gym membership sign-up, it was a bit pointless for the salesperson to concentrate on the added benefits of a sauna when one of my primary concerns was how I was going to find parking anywhere nearby.
Even when the system in question is a decision-making process, focusing on alleviating the largest bottleneck is the surest way to speed it up. Our research team has found that the process of identifying bottlenecks can be helpful when discussing potential investments. As an observational lens, bottleneck-thinking can quickly uncover specific pressure points people may have, such as a holding’s valuation or current management.
One of the ways we try to identify so-called bottlenecks is with our quarterly matrix process, whereby we rank all the companies we have invested in across five categories:
- Business Model
The rankings combine into a Quality (business model, management, risks) and Return (valuation, skew) coordinate that we then plot onto a 2D grid (known internally as the “Matrix”). In general, companies that plot high return and high-quality—the upper right area of the matrix—will be weighted more heavily in our portfolios than companies plotted lower left (lower quality and lower return).
Aside from helping us evaluate whether we need to adjust the weights in our portfolio, the matrix process also reveals everyone’s perspective of a company—via a visual tool grounded in a shared language. We can then easily scan each individual matrix score across the five categories to look for the largest deviation.
For example, on our Global Small Cap team, Karan, Christian, Paul, and I may plot the same company in two different locations within our matrix. On closer inspection, it would seem we share the same rankings across all categories with the exception of valuation. We can then fairly quickly narrow-in on what our conversation should address: how the other person thinks about valuation, and the inputs, assumptions, and confidence ranges driving their viewpoint.
By incorporating bottleneck-thinking into such a structured, familiar process to us, we find that our discussions become more focused, and can ultimately move forwards more efficiently.