“Code on a computer” by Markus Spiske on Unsplash

Augmentation-of-Work: An Analyst’s New Best Friend

Christopher Eng
Aug 31, 2018 · 3 min read

An investment theme that I am particularly bullish on and which I briefly talked about in my last post is Augmentation-of-Work (“AoW”) software. AoW software refers to a technology solution that enables a desktop analyst within an enterprise to either complete a given process/procedure more efficiently or automate a process/procedure entirely.

Why Augmentation-of-Work

AoW solutions represent applications of artificial intelligence and machine learning that provide meaningful cost savings and ROI for enterprises, making the buying decision for companies more palatable and the product/market fit more tangible. That is, it is not AI for AI’s sake. A second reason I love AoW solutions is the TAM, or more appropriately, the ubiquity of their application both across and within industries. Specifically, the middle and back-office functions (e.g., human resources, compliance, legal, accounting) across industries stand to benefit from software solutions that augment an analyst’s capacity or reduce an analyst’s marginal costs. Aside from financial services, which I previously talked about ad nauseum, legal services and healthcare appear to me as the top candidates for AoW solutions (as much as I love using a fax machine to send medical records between hospitals).

Where to Focus within Automation-of-Work

AoW software solutions typically fall into one of the following three areas:

1) Function-agnostic/industry-agnostic solutions (Avoid);

2) Function-specific/industry-agnostic solutions (Pursue); and

3) Function-specific/industry-specific solutions (Best).

Function-agnostic/industry-agnostic solutions represent general AI-enabled chatbots and intelligent virtual assistants such as those offered by X.ai and Zoom.ai. Startups in this subsector of AoW lack defensibility, particularly as natural language processing and artificial intelligence become increasingly open sources. Such startups do not have the subject matter or process-specific expertise that provides natural moats against new entrants in the market. Avoid investing in startups within this subsector of AoW technology.

Function-specific/industry-agnostic solutions automate/augment specific processes within common functions of the back/middle office (e.g., HR/recruiting, procurement, and accounting). These startups benefit from huge TAMs and tangible ROIs for enterprises as they target inefficient, manual processes. An example of a leading startup in this subsector that offers a function-specific/industry-agnostic solution is LawGeex, an automated legal contract review startup based out of Israel. LawGeex’s AI engine results in 90% cost savings for enterprise legal departments by automating the review and approval of incoming contracts.

The most successful AoW companies will be those focused on function and industry-specific solutions that train their machine learning models on proprietary datasets (e.g., bank transaction data, trade finance documents, car or property damage images). These companies build high barriers-to-entry by improving the accuracy of their models on proprietary datasets and developing domain expertise on complicated, industry-specific process flows. Further, by establishing oneself as a (successful) industry-specific solution, you becomes a scarce resource that provides a competitive advantage for those customers within the industry using your product. As an illustration, think of the number of recruiting/HR-tech solutions (many) in the market compared to say trade finance automation solutions (few). All else equal, your exit opportunities through an acquisition are more attractive compared to a function-specific/industry-agnostic AoW company that competes against a wider range of companies. Scarcity increases the impetesit of a large corporate to acquire you. After all, why would a company acquire a great legal services AoW solution as a competitive advantage if it knew its competitors could go into the market and acquire a company with a similar offering. A great example of a function-specific, industry-specific AoW company is Intelligo, which is augmenting the background check/know-your-customer process for the financial industry. Specifically, Intelligo applies artificial intelligence to automatically (and quickly) scan the open web (e.g., blogs, social media), government sanctions lists, court filings, etc. and surfaces relevant, de-duplicated alerts/red-flags for review by compliance analysts that pertain specifically to the individual/entity searched. When conducting a background or KYC check on an individual/entity with a common name, Intelligo can be a powerful tool augmenting an analyst’s desktop process and procedure.

Data Driven Investor

from confusion to clarity, not insanity

Christopher Eng

Written by

University of Chicago MBA interested in early-stage enterprise technology investing.

Data Driven Investor

from confusion to clarity, not insanity

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