10x has become a well-worn saying in Silicon Valley. As over-used as it may be, it expresses some hidden truth about product disruption. For those that aren’t consumed by the subject, the saying goes that if you want to bring a novel product to market, it won’t gain traction if it is marginally better than existing options; it must be an order of magnitude better. The reason is that a sort of energy of activation is required to unseat an incumbent and overcome consumer switching costs. There are different degrees to this varying by product and industry. For a consumer looking for a 45-minute plane flight from New York to Boston, a new budget airline will not require an order of magnitude difference in experience. It may come down to a marginal difference in price and availability, as well as a good blog review about safety and comfort. The dynamics of plane travel exhibit small switching costs, and a perceived commodification (i.e., limited differentiation) in the mind of the consumer. Compare this to a social media entrant, which may indeed need to be 10x better to pierce the network effect of a Facebook.
Asset management adds additional wrinkles to “energy of activation” beyond network effects and commodification. Sure, there are commodity dynamics at play and word of mouth, but also regulatory considerations that are more involving than most consumer-facing products. Perhaps most importantly, counter-party trust is paramount in asset management, given the impact asset management has to a client’s livelihood, versus Snapchat. This makes start-up disruption quite a different equation than two entrepreneurs in a garage. Even though it’s different, it exemplifies the need for 10x differentiation. We’ll provide a case study to explain why:
Let’s assume that a startup asset management firm has developed a novel investment strategy that roughly mirrors the constituents and broad characteristics of domestic equities (e.g., the S&P 500 Index). It does so while delivering an average of 75 basis points of added net performance per annum, with an equal amount of tracking error. This is, in effect, a product that delivers an information ratio of 1.0. While 75bps sounds marginal, through the power of compounding, such an investment is to some capital allocators Nirvana. A few caveats of course: the offering is through a no-name ETF provider (not a BlackRock or Vanguard), is an active ETF rather than a passive ETF (more on that later), and has 5x the turnover of the conventional lineup of comparable products (e.g., SPY, VOO, SCHX).
One could argue that an information ratio of 1 to the SPY is an order of magnitude better than SPY. As a result, this product should summarily disrupt SPY and the hundreds of billions of dollars it and its stunt-doubles have under management. The reality is it won’t, at least for an extended period of time. Why is this? At it’s root, the value proposition is marred by some of the strings attached. But to better understand adoption curves, we have to connect these strings across the landscape of capital allocators. Rather than going through the segmentation of all flavors of capital allocators, here is a simplified distillation of across two2 principal traits:
- Taxable vs Non-taxable Allocators
- Alpha-oriented versus Beta-oriented Allocators
The first differentiation is clear-cut. Certain allocators are taxable (individuals, family offices, private wealth management, non-pension corporate balance sheets, et al.) and thus their investment behaviors are impacted by this cost. The phenomenon is recursive, meaning that taxable investors shape market dynamics.
There is interestingly enough diseconomies of scale to taxable investing. By that, I mean the larger and more sophisticated the taxable investor (e.g., billion dollar family office, ultra-high net worth, et al.), the higher the marginal tax rates are on short-term capital gains. This, to a certain extent, provides less incentive for these investors to wade into esoteric / higher turnover investments. We see this clearly in the trends of family-office investing. Allocations continue to barbell between tax consideration (passive tax-loss harvesting for betas) and tax-friendly alpha-orientation (private equity).
The other side of the coin is non-taxable1 allocators (IRA/401k accounts, pensions, endowments, foundations, sovereigns). These investors have expanded addressable markets in terms of tax-insensitive strategies. They can exploit the market-distortion caused by taxable considerations to their advantage. Here there are economies of scale for exploitation. Sophisticated strategies that require resources and subject matter expertise to either implement or diligence can be better understood by high-sophisticated non-taxable investors.
Alpha / Beta
The second factor is a bit less clear. What I mean by alpha-orientation is an ability to tolerate pain (under performance, deviation from benchmark, fees, added counter-party risk, basically all the mess) in the pursuit of excess risk-adjusted performance. While every investor hypothetically wants to be a benefactor of alpha, not all have the requisite sophistication (e.g., retail) alignment (e.g., certain politically motivated institutional investors), or philosophy (i.e., those that believe in a zero-sum alpha and thus choose not to join the arms race) to generate alpha. This distinction is meant to bifurcate the appetite of certain capital allocators to financial innovation.
If we plot these two axes, we unpack four quadrants within the allocator landscape:
Going back to our Information-Ratio 1 SPY product, we can segment the viability of adoption across these groups.
Quadrant 1 is often guided by intermediaries: financial advisors, word-of-mouth, advertising, CNBC, family suggestions… Familiarity is key. This makes new product launches without distribution and marketing very challenging, irrespective of how lucrative the value proposition may be. Steady marginal alpha isn’t necessarily what sells. Bright shiny things are often the investment du jour. While taxes are clearly a consideration, new product adoption across retail is simply a dead-end without deep pocketed sales/marketing.
Quadrant 2 is on average more sophisticated than Quadrant 1 by virtue of its comparative advantage. Not only does Quadrant 2 have a dedicated staff towards dilligencing investments, it is more cost effective for new fund start-ups to flock to Quadrant 2 for capital, creating a virtuous cycle. As mentioned before, this group is extremely tax conscious. Without proof of net-of-tax alpha, there is significant uncertainty in the value proposition of our novel product. Uncertainty drives reluctance, and reluctance puts an idea at the revisit pile. The default is wait-and-see rather than early adoption.
While early adopters exist in quadrant 2, these innovators tend to be a smaller portion, and once it becomes known who “likes to be early”, they tend to be inundated with requests, heightening competition.
Perhaps most unbeknownst, new product risk is a serious consideration for organizations in Quadrant 2, specifically intermediaries (e.g., Private Wealth Management). You can see this in the data, such as the marginal adoption of active ETFs compared to passive ETFs. Why you ask? Because novel products compound the risk of a new firm with the operational risk of a new product. It’s one thing to offer innovation in the passive ETF space, (e.g., smart beta, tax efficient products). It’s another to wrap your value proposition in an active ETF, which has limited traction and thus amplifies counter-party risk.
Moving into Quadrant 3, the tax problem is no longer a barrier to entry, but counter-party risk is a huge problem. These institutions have deep ties with large financial institutions, which believe-it-or-not, have their own products which they cross sell along with services. These behemoths tend to choke-out start-ups through their economies of scale. If they find interest in the product, they try to buy it out or incorporate it in their line-up, rather than acting as a distribution partner. This makes quadrant 3 penetration without exceptionally specialized relationships almost impossible for start-ups. Actors in quadrant 3 are simply less willing to take on risk for the pursuit of outperformance.
That leaves us with Quadrant 4, which appears to be Goldilocks. This is in some ways the incubation ground for many alpha-oriented products such as hedge fund launches. As a result, competition is brutal, and network effects are paramount. These institutions are constantly pitched novel products that all sell the same idea (better alpha). Quadrant 4 allocators must optimize around finite resources: time to spend dilligencing every new start-up, capital available to deploy, start-ups to hand-hold. Their existing investments which have passed the gauntlet over the years are often a high hurdle to beat. Spin-outs from existing institutions take priority, as they have familiarity. Ported track records are a plus.
To add insult to injury, these institutions are often limited by their ability to be truly early. A modest investment by one such institution may constitute the majority of AUM for a start-up, which is a faux pas in most circles. This creates a chicken-and-egg problem for many startups where a product/market fit may be there, but the timing is not (“come back to us when you cross $250mm”).
To make matters truly grim, the biggest challenge in vetting new product is the nature of measuring the efficacy of process. Unlike other goods and services, asset management is one where skill is highly intertwined with luck, and the separation of the proverbial wheat from chafe requires live success, above all else. In cases of complexity with regards to process or edge, the most common antidote is time and demonstrate success. Time is, of course, the enemy of the start-up.
Opportunity & Reality
There is niche opportunity for differentiated capital to enter the market place and fill voids where good product fails to match-make with hungry capital. While in other product verticals this is often filled by angel/venture-capital, in asset management this is fed by seeding platforms and early adopters. Early adopters are often institutions that accrete positive externalities from innovative thinking. Sometimes they simply have a predisposition to new rather than tried and true. These institutions also understand the heightened risk of differentiating early wheat from chafe and thus extract favorable terms through economics interest and/or extremely favorable fee arrangements. Their organizations must be structured in a way to avoid endowment effects, and they generally must be better at judging relative attractiveness.
On the flip side, startup firms must be surgical in understanding their addressable marketplace and pitching solutions to fit those needs. One size fits all fits none, and carrying forward existing relationships is a must. This often means tailoring messaging that checks the specific boxes for early-adopters, and finding a bridge for core products to meet their natural product/market fits at the right time (talk about Goldilocks!). They must navigate a meandering path to success. It’s not good enough to produce; they have to be able to sell a vision. That’s a true 10x.
1 –setting aside the endowment tax; that is a topic for another piece
2 – an argument could be made that SRI (Socially Responsible Investing) is asserting itself as the third paradigm. It’s a bit too early to tell, but this will provide a fascinating new wrinkle to this framework
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