Can data disrupt its own data model? The new investors dilemma.
We know and love the original thinking from Clayton Christensen - however is this model about itself to be disrupted? https://en.wikipedia.org/wiki/The_Innovator%27s_Dilemma
Investing today into an early stage high growth business is largely predicated on the target having a product or service that collects and stores data. They have a proposition the market wants and enabling the business to collect unique data is critical to funding (growth and defence) and there is a foreseeable route to exit. As a business you combine your data set with anything else you can buy, enabling you as a business to refine your proposition, grow customers, improve satisfaction, increase engagement, uplift revenue and create more value by having better data and analysis. It is virtuous circle based on collecting, storing, analysing and using data.
Essentially we are still very early in this thinking and investment cycle. The majority of early stage venture money is following this process in their analysis. The thinking (own and control data) is based on the same economic model that lead to growth in assets needing to be controlled and funded. We like the model as it makes sense.
However is this thinking, much like Uber (no taxi's), Spotify (no music), AirBnB (no rooms) has changed our views on the need to own and control assets (good for classic B/S but rubbish for multiple); are we about to see that decentralisation of data is going to change the perception and need to collect and store (centralise) data.
It can be argued the centralized (collect/ store and control of data) model is being disruption as critical regulation across key markets is forcing collectors and store'rs of data to give a copy of that data back to the user. The principal may be driven from the ideals of better user choice, more competition, users are entitled to a copy, freedom of movement etc. However when users have their data back the power balance and rules will change.
There is an assumption that data will stay in both places. The user will have a copy. Compliance means a copy stays with the collector) But let's now assume that the best and most authoritative version of data is with the user, everyone else has only every parts, but the user may have access to it all. Those parts of data that an enterprise has on any user are by definition incomplete. User also don't appear to be that ready to share data sets across corporates, as evidence shows that the corporate data lakes are a massive magnet for hackers and since the economics of hacking a centralised store are highly attractive. QED on-going leaks and hacks destabilize the public thinking for more and bigger centralised data stores.
With a bold/ rash assumption that the user complete mashup of their own data is the best, and the user can control via consent who has access to their data; the very model of collecting and storing becomes a liability and not the asset. The belief was this data provided control, but the power has shifted to the user. The user still wants services but can now pick the service provider with the best (in their view) UI/UX, exceptional customer care, puts them first, has an alignment on ethics and offers what the users wants. Boom - focus on AI/ ML and analysis.
The investment dilemma is subtle. Venture tends to steer away from plays that demand a large marketing spend (for a lot of good reasons - remember BOO!) preferring platform economics, data control, Analysis, ease of scale and aspects of control. Marketing to attract users is not seen as important a spend as an investment in the tech - get the tech right the user will come. With a large part of the data tech decentralized to the user (collection, storage, consent and compliance) the company has to focus on many more of the softer (behavioural psychology) aspects of getting the product/ service right in the eyes of the user. These analysis skills are improving but there is still are requirement to attract the user.
Will we see what happened in the mobile world ( mobile web 2.0 thinking of 2007) repeat itself in the creation of "apps" on top of decentralised open source user data technologies with decentralised Identity and a decentralised tokenised coin for trade? Apps will do the analysis but the key will be the user experience and putting the user first and the user is in control of the companies access to the data they need.