ERRC Grid

Eliminate · Reduce · Raise · Create¶

Application of the Four Actions Framework

What makes a good lever?¶

Intentional strategic choice
A lever reflects something the company chooses to do or not do by design. If it would not exist without a deliberate decision, it qualifies; if it “just happens,” it doesn’t.
Fully controlled by the company
A good lever is enforced by the system itself, not by hoping users behave well. If participants can bypass it through bad behavior, it’s not a lever.
Reshapes industry behavior, not just improves efficiency
Strong levers change the rules of the game rather than helping you play the same game faster or cheaper. Incumbents resist these because they break existing models.
Upstream of outcomes
Good levers create outcomes indirectly; bad levers are outcomes. If it sounds like a benefit, metric, or result, it’s probably downstream of the real lever.
Can be plotted on a strategy canvas
A lever should correspond to a dimension of value that customers can meaningfully compare across alternatives. If it can’t be visualized as higher/lower relative to incumbents, it’s likely not strategic.
Survives imitation pressure
A real lever is hard to “bolt on” without changing core economics or incentives. If an incumbent could copy it tomorrow without self-harm, it’s not a Blue Ocean move.
Neutral in tone
Levers are descriptive, not moral or promotional. They should read like rules or constraints, not promises, values, or marketing claims.
Litmus Test
“If we removed this, would the system fundamentally behave differently?”
Yes → it’s a real lever
No → it’s an outcome, feature, or metric

ELIMINATE¶

Factors the hiring industry takes for granted that Ibby removes entirely

Applicant Volume Success Metric¶

No optimization for number of applicants
No funnel size KPIs
No “more is better” logic

What to say¶

We explicitly refuse to optimize hiring around applicant volume; volume is not a success signal in our system.

Unreciprocated Applications¶

No candidate enters a process without prior employer interest.
No resumes sent into an unresponsive system or overloaded candidate funnel.
Candidate progress is not blocked by employer inactivity.

What to say¶

Ibby is designed so employer slowness cannot harm candidates.
Employer interest is an interrupt, not a bottleneck — candidates aren’t stuck waiting for anyone to move.
Candidates don’t submit and wait; they’re notified when interest exists, so employer slowness can’t stall them.
Job boards punish candidates for employer slowness. Recruiters mask employer slowness manually. Ibby designs around employer slowness entirely.

REDUCE¶

Factors that remain necessary, but are driven far below industry norms

Human Repetition in Early Hiring Stages¶

Resume parsing
Inbox triage
Redundant early screening
Scheduling churn
Repeated self-representation and context re-entry by candidates
“Go fast” through brute-force effort

What to say¶

We reduce the need for humans to repeatedly parse, triage, and re-explain information just to move fast.

Queue-Based Candidate Prioritization¶

Reduces dependence on submission order for candidate consideration
Evaluates all available candidates for fit whenever matching occurs, regardless of when they entered the system

What to say¶

Being early in line no longer matters; fit is evaluated whenever matching occurs, not when someone happened to apply.

RAISE¶

Factors Ibby deliberately elevates well above industry standards

Canonical Profile Construction¶

Candidates and companies provide a comprehensive, structured representation once
All future interactions reuse and build on this canonical profile
Additional detail increases match accuracy rather than creating repeated work
Replaces repeated, per-application effort with a single, durable source of truth

What to say¶

We replace repeated applications and postings with a single canonical profile that compounds in accuracy and speed over time.
Move effort from repeated, per-application labor into a single, durable representation that compounds in value over time.
This is an amortized, compounding effort that replaces repeated work forever.

CREATE¶

Factors the industry has never structurally offered

Claim-Based Fit Modeling¶

System-led inference of role and candidate capabilities from raw source material
Fit is determined prior to interviews, rather than discovered during them
Capability claims are refined through iterative system-led inquiry
Independent semantic facets are weighted separately -- skills, experience, intent, landscape, mobility.
Every match is explainable and traceable to underlying claims

What to say¶

“Ibby doesn’t match documents — it infers and compares explicit capability claims across independently modeled dimensions.”

Conversational Context Exploration¶

User-led, natural-language exploration of the other party’s context
Ask natural-language questions about the candidate or the role
Explore intent, constraints, and expectations beyond resumes and job postings
Build shared context before live interviews

What to say¶

Both sides can interrogate real context in natural language before they ever get on a call.

Mutual Commitment to Engage¶

Company expresses interest in an anonymized candidate profile
Candidate sees full company and role details and chooses whether to reciprocate
If interest is mutual, both parties commit to a first conversation
A mutual commitment creates a guaranteed first conversation, not a hiring obligation, and does not restrict either party’s future choices

What to say¶

We only formalize the first conversation — everything after that remains fully optional.
A conversation only happens after both sides explicitly opt in — and once they do, it’s guaranteed to happen.
We’re not forcing outcomes — we’re formalizing a moment that already exists, and making it reliable.
Think of it as a handshake to talk, not a contract to hire.

In a nutshell...¶

Written Summary¶

Ibby restructures how hiring conversations begin.

Instead of flooding companies with applications and forcing candidates to shout into the void, Ibby only starts a process when real interest exists on both sides.

We replace repeated applications and manual screening with a single canonical profile, use claim-based modeling to determine fit before interviews, and guarantee a first conversation only after mutual consent.

The result is fewer wasted cycles, better conversations, and faster resolution — without optimizing for volume or forcing outcomes.

For pitch decks / spoken delivery¶

Shorter and sharper

Ibby flips hiring from “apply and wait” to “signal and engage.”

We eliminate unreciprocated applications, collapse repeated effort into a single canonical profile, model fit before interviews, and only commit people to a conversation once interest is mutual.

Hiring moves faster not because people do more work, but because the system stops wasting it.

Ultra-Tight Version¶

One paragraph, high confidence, founder voice

Ibby is designed around one idea: find a job (or filling a role) shouldn't be painful, and it shouldn't take long.

We eliminate volume as a success metric, remove blind applications, front-load durable signal once, and model fit before interviews. When both sides opt in, the conversation is guaranteed — everything else stays optional.

Optimal investor takeaway¶

What we want them to say after the first pitch

“Ibby isn’t optimizing hiring throughput — it’s restructuring when and under what conditions a hiring conversation is allowed to begin. The differentiation is real; the risk is execution and enforcement.”