In fundamental investing, the true constraint on alpha is not capital, data access, or modeling sophistication. It is time per idea. Every investment process begins with first-pass diligence: reading filings, identifying changes, understanding disclosures, and deciding whether an idea deserves deeper work. This step is unavoidable, but it is also the least differentiated use of high-cost human attention. When analysts spend hours determining what changed, they have less capacity to determine what matters. The result is not just inefficiency — it is fewer ideas evaluated, slower kill-rates, and missed opportunities.
What makes first-pass diligence uniquely problematic is that it sits at the intersection of scale and repetition. Public company disclosures follow predictable structures. The questions analysts ask on the first read are remarkably consistent across sectors and market cycles. Yet firms continue to apply bespoke human effort to a task that is largely mechanical. As coverage universes expand and information velocity increases, this mismatch compounds: idea throughput grows linearly at best, while cognitive load grows exponentially. The bottleneck is not intelligence — it is workflow.
The funds that outperform over full cycles are not those with the most data or the most complex models. They are the ones that allocate human judgment where it creates the most leverage. Automating first-pass diligence does not replace analysts; it preserves them for the work that actually generates alpha: hypothesis formation, variant perception, and capital allocation decisions. In a world where attention is the scarcest resource, protecting it is no longer an operational choice — it is a strategic one.