Aptology: The Science of Fit
Jocelyn Goldfein is a Managing Director at Zetta Venture Partners, where she leads investments in AI-first startups with B2B business models. She was previously a technology executive with Facebook and VMware, and is an adjunct lecturer at Stanford University, her alma mater.
Aptology is announcing the launch of their new platform today and it’s a game-changer for execs of high growth companies. Very simply put, Aptology helps their customers make more money. It also helps them to be better employers, improve employee retention, and build a more diverse workforce, but it starts with making them more successful in their core business by hiring the right people for the job.
Most of the time “right people for the job” is a fluffy, qualitative, cliche. But in revenue-generating jobs like sales, we can measure it in dollars and cents - targets hit or missed - and all of a sudden “right fit for the role” becomes a very objective statement of fact.
I spent the first decade or so of my career leading teams in high growth tech companies and if you’ve been in that situation, you know you have two full-time jobs: your day job and recruiting. Whatever else you are charged with doing (building a product, selling a product, supporting a product…) you can only succeed if you hire the right people into the right roles at the right time. Hiring is a science and an art - a numbers game where creativity and relationship building count. I became so passionate about hiring, that while I was an engineering leader at Facebook, I spent a year also leading our technical recruiting organization to strengthen our processes, tools, and partnership. So it was natural that as my career shifted into investing in AI-first startups, I was closely watching the many entrepreneurs working on applying AI to hiring.
To be honest, I quickly became jaded. Hiring is a fairly subjective process, from selection to offers, and for many roles, on the job performance is also subjective. Fit is comprised of so many variables, quantitative and qualitative, I became skeptical that it was a suitable target for machine learning. Ultimately, while I’m sure we can improve on recruiter productivity with better tools, I don’t see AI replacing the human element of recruiting anytime soon.
In comparison, Aptology is doing something very different. Based on decades of research in organizational psychology, they have zeroed in on the behavioral traits that actually are predictive of on-the-job performance. They have proven with science something we all intuitively knew: that the traits that make you successful vary from company to company and role to role, and there is no universal “high performance” template - stardom requires fit. Aptology has demonstrated this in a way that can be validated objectively with roles like sales, in which job performance can be measured with facts: did you make quota or not?
As an industry, we tolerate a status quo in which* more than half of revenue-generating employees fail to make quota in their first year on the job. *Employee churn under these circumstances is incredibly high, with managers struggling to know who to nurture and who to manage out, high potentials leaving for greener pastures in frustration, and every departure setting you backwards on hitting the next revenue target and hiring target.
Aptology’s customers don’t live in that world anymore. One customer I spoke with told me that they’d historically found only 40% of new hires achieving their first-year revenue goals. After deploying Aptology, they found that 80%+ of the candidates identified as a “good fit” by Aptology were successful at achieving at least 80% of quota. And when they hired against the Aptology recommendation, they found that every single one of those was a mis-hire that Aptology could have helped them avoid.
The difference between 40% and 70% on target execution of new sales employees was massive for this rapidly growing business.
Aptology has performance benefits beyond recruiting. Armed with fit-to-role insights, managers can pinpoint behaviors for a borderline performer to improve, or help employees out of a badly fitting role and into a good one. While the results are most objectively measurable in revenue-generating positions, Aptology can help you hire more successfully in any role where behavioral traits are a big driver of success (that is to say, every role, yes, even engineering.)
Last but far from least: Aptology can help customers achieve their diversity hiring goals by providing an objective and bias-free input to the hiring decision. AI-based systems for decisions like hiring have rightly come under scrutiny for amplifying bias, but Aptology does not train models on data that itself might encode past hiring bias. With Aptology’s data set (behavioral traits and on-the-job performance) they have been able to demonstrate that their system has no adverse impact across a variety of crucial dimensions, including gender, age, and ethnicity.
I’ve been working with the Aptology team for the past 6 months, and it’s exciting to see the product momentum culminating in today’s GA release, but more importantly, the value they are driving for their customers. Aptology’s customers are reaping the benefits of a diverse workforce, reduced attrition, superior management and cultural impacts… and did I mention that they are making a lot more money? If that sounds good to you, check out the 1-minute demo at https://www.aptology.com/.
- AI-First Companies: Flipped
- The AI-first startup playbook
- AI adoption is limited by incurred risk, not potential benefit
- AI-First Companies
- Data rights are the new IP rights
- The Intelligent Enterprise Stack
- Beating Behemoths
- Don't sell your data
- Framework to grasp industrial analytics opportunities
- Beyond systems of record
- Positioning a machine learning company
- The intelligence era and the virtuous loop
- Vertical beats horizontal in machine learning
- Zetta Bytes AMA: Questions to ask about pricing
- Zetta Bytes AMA: Hiring a CTO
- AI Entrepreneurs: 3 things to check before you pursue a customer
- There are more data scientists than you think
- Stages of funding in the intelligence era
- Could data costs kill your AI startup?
- Measuring AI startups by the right yardstick
- Finding the Goldilocks zone for applied AI
- Data is not the new oil
- Machine Learning in the Deployment Age
- Innovations of the Next Decade
- Zetta Bytes: Privacy Preserving Machine Learning
- GDPR panic may spur data and AI innovation
- Computing like a human
- New opportunities for hardware acceleration in data analytics
- Hardware acceleration in data analytics
- Skan: Visualizing the Future (of Work)
- Announcing Zetta Fund III, a $180M fund for AI-first companies
- Aptology: The Science of Fit
- Verusen (The intelligent supply chain)
- Opsani: What's Next? Continuous Optimization
- Promethium: Starting a Fire
- Lilt: Translation for all