Building for small business through data-driven account-tech
Small business has a big problem. They’re high risk. They’re so high risk that the majority fail within five years of incorporation. The reason that the majority of small businesses fail is complex. Some simply fail because their owner isn’t good at business. Some fail because the market rejects their offering. But if you have a business that is viable - and you have some business acumen then your biggest risks are - making bad decisions and a lack of access to capital.
Most business owners make bad decisions, not because they don’t seek out good advice - but because they don’t have the right numbers in front of them to make a good decision.
Most business owners lack access to capital because, as a whole, small business is high risk. For a bank or lender, the general risk is often not worth engaging with. For a viable business, they lack the ability to de-risk themselves from their contemporaries. Risk is a numbers game, and the house always wins.
Quota was founded to resolve that weighted bet, and it resolves it through providing small business owners with SPOT - a single point of truth in their business data, that can be verified by banks and lenders and underwritten by accountancy professionals.
Accountancy professionals are uniquely placed to validate small business data. They’re also uniquely trusted by banks and lenders. Accountancy professionals are also in a race to the bottom - stagnant pricing and the threat of AI is undermining their business models, and their only respite is to move up the value chain towards offering services that mom and pop bookkeepers cannot offer.
So the problem space Quota finds itself in is rather unique and multi-sided. It serves the small business owner, it serves the lender. But it also serves the accountancy professional. And it is the accountancy professional who ultimately drives Quota - in both its legitimacy and reach - to the small business owner and the lender.
Quota is a heavy data product. It’s also a finance product. It’s a product where precision wins and errors can cause real life pain. It relies on complex data connectivity with dynamic ledgers and bank APIs, and it requires incredibly deep categorization models to provide the insights required by those making large capital decisions.
In short, Quota is Bloomberg Terminal for SMB. But it’s a Bloomberg terminal simultaneously used by a highly qualified accountancy professional and a business owner with a financial knowledge largely limited to ‘number go up’.
My role on Quota was broad and it encompassed leading Product and Design from the position of co-founder.
Quota allows Accountancy professionals to quickly onboard businesses through automatic connections to QBO and Xero.
From there, Quota automatically maps the history of the company using a proprietary codec called QCS. QCS is a complex beast of a codec that required very stringent information architecture. That architecture then is able to generate a parser logic, which can be leveraged by AI query engines.
This complexity is hidden in Quota - the categorization, the logic paths - to generate a smooth onboarding experience where the Accountancy professional is able to input, connect, sync and categorize any small business in under four minutes. Quota is also able to handle interdependency between types of businesses, industries and connected businesses, such as franchises and groups of companies.
This means for the Accountancy professional, businesses can be compared, reports generated and up-market advice created at-a-glance. However the big win for most Accountancy types is the way which, thanks to the QCS codec, any business on the platform is instantly compiled. A compilation in most industries is the financial standard for investment of any type, and for most Accountants, a compilation is (a) time consuming to produce (b) has very slim margins and (c) is immediately out of date at the point on compilation. Quota provides real time compilations for every connected business.
QCS also powers the finite details behind equations. It’s able to show past and future trends per equation with tabular detail.
For analysts who require additional details into individual numbers and QCS outputs, X-Ray mode provides the granular breadcrumbs. With X-Ray in QCS the analyst is able to leverage QCS to ‘no code’ the ledger. The AI agent QAI also leverages this X-Ray layer, able to allow for general prompts by both the Accountancy professional and small business owner.
What’s fascinating about Quota, and QCS as a codec in general is the power that exists within the codecs ability to find patterns within the abstracted data - and for that I thank the analytic mind of my PM Jay Dort. This allowed us to build smart budgeting tools based on prediction models, effectively running spread-bets against a company ledger, and allowing QCS to amend its variables when the budget was made actual.
The most interesting thing for me with Quota was the creation of flows. In product design and product generally, we talk about flows in terms of usability and execution. What you can see. What is tangible. What is human. In Quota those flows are the data itself, and the usability is determined by the way by which that data is not only presented but how that data is referred to, architected and made accessible in a variety of deep-use cases. The product challenge then becomes understanding the data layers, understanding where the leverage is and understanding what is possible.
In many ways QCS - and Quota - is a pure design product, but a design product with no true visible render. Where the aesthetic is the function and that function can be anything.
I intend to write more about QCS and Quota in the near future.
