Guidance Tracking

Measure Management Quality via Guidance Tracking

Evaluating managerial skill from the outside is both challenging and essential. Traditional assessments rely heavily on soft factors and often lack consistency. For a comprehensive guide on evaluating management quality, we explore multiple frameworks beyond guidance tracking.

Evaluating management quality in a consistent, reproducible way is the holy grail of investment research. Don’t rely on the firmness of a handshake or the cut of a suit—focus on repeatable, measurable indicators of management quality.

Research shows a clear link: executives who make more accurate public predictions tend to demonstrate stronger managerial skill, and their companies outperform peers in both operations and share price.

Why does forecasting quality matter?

• Analytical rigor: Producing accurate forecasts requires synthesizing data from diverse formal and informal sources.
• Selective disclosure: Because most forecasts are voluntary, executives reveal judgment and discipline by choosing which predictions to share publicly.

Track and Measure Every Forward-Looking Statement

Official guidance is tightly managed, widely tracked, and easy to source from other data vendors. But executives also make less formal predictions about production volumes, user growth, or factory openings that carry meaningful signals for investors. These remarks appear across press releases, earnings calls, investor presentations, interviews, and capital market days, all of which are automatically captured and ingested.

Executives rarely make off-the-cuff remarks about next quarter’s revenue. But they often comment more freely on operations, milestones, or customer adoption. Tracking these statements is essential.

Manually capturing and organizing these predictions is inconsistent and prone to gaps. Marvin Labs Guidance Tracking automatically collects every forward-looking statement, structures it as a testable forecast, and evaluates it when results are in.

Turn Forward-Looking Statements Into Testable Forecasts

Analysts need a scalable way to turn management’s words into measurable outcomes. Notes and generic AI summaries miss context and break under scale. Marvin Labs Guidance Tracking captures every forward-looking statement, converts it into a testable forecast, and evaluates it at maturity.

Guidance Tracking covers two statement types:

• Metric-based: Quantitative forecasts tied to financial or operational measures for a specific period. These can cover the whole company or break down by segment, product line, or geography (e.g., revenue growth, margins, production output).
• Event-based: Predictions about milestones and when they will be met. Some are externally visible (e.g., product launches, factory openings, regulatory approvals), while others are internal but strategically important (e.g., reorganizations, hiring plans, technology rollouts, cost-reduction initiatives).

Each statement is standardized with a clear metric or event, timeframe, scope, and target. Vague language (“low to mid single digits”, “flat q/q”, "later in the year"") is translated into bounded ranges with documented assumptions, making even imprecise forecasts testable.

Automatically Evaluate Forecasts

When the period arrives, Marvin Labs automatically evaluates each statement as "met", "exceeded", "missed", or "dropped" when there is insufficient data to evaluate the statement.

Event-based predictions are validated against trusted public sources to speed up the feedback loop. Some outcomes are highly visible: companies often publicize product launches or factory opening, yet may not trigger formal filings or press releases.

Workflow Integration

Guidance evaluations are seamlessly embedded in Material Summaries and included in every full earnings review. They can also be queried directly through AI Analyst Chat for on-demand analysis, or monitored continuously using Deep Research Agents.

For deeper review, evaluations are available as structured data tables in the Marvin Labs platform showing each statement, its context, and its outcome in a transparent, auditable format.