How HuoLaLa Built a 0‑to‑1 Stability Metric System in 2 Years

Background

HuoLaLa operates a large‑scale logistics platform covering 360 cities with hundreds of thousands of drivers and millions of users, making technical stability essential.

Why Measure Stability?

Stability leaders need quantifiable performance results to demonstrate value, turn vague impressions into concrete KPIs, and drive continuous improvement.

How to Build a Metric System

The process starts with defining clear goals, establishing measurable and comparable indicators, and aligning them with business objectives such as fault count, SLA, and availability.

1.1 Goal: Quantify Subjective Feelings

Transform vague descriptors like “stable” into concrete numbers (e.g., fault count, downtime).

1.2 Value: Advance the Stability System

Metrics serve as monitoring tools, early‑warning signals, and risk‑cost assessments, enabling proactive issue handling.

Analyzing Pain Points

Indicators are scattered and lack traceability.

Definitions are ambiguous across teams.

Data collection is difficult and error‑prone.

Metric work is not treated as a systematic, ongoing effort.

Principles for Metric Design

Metrics must be long‑term, goal‑driven, and supported by platform tools to avoid manual overhead.

Core Tasks

2.3.1 Define Indicators

Each indicator should have a clear purpose, be hierarchical (from high‑level KPIs down to detailed metrics), and be documented for stakeholder feedback.

2.3.2 Collect Data

Move away from Excel‑based tracking to automated platforms that ensure accuracy, efficiency, and historical retention.

Platform Construction

A unified stability dashboard aggregates global and domain‑specific metrics, supporting trend analysis, milestone tracking (e.g., consecutive fault‑free days), and detailed reporting.

Practice at HuoLaLa

HuoLaLa defined fault‑count targets, distinguished severity levels, set milestone goals like 180 consecutive fault‑free days, and built detailed processes for incident timing and documentation.

Results

After two years, fault count dropped 78%, SLA improved from three‑nines to four‑nines, and the team received the highest internal honor for stability work.

Future Plans

Focus on deeper data analysis, smarter early‑warning detection, and richer platform capabilities for flexible metric composition and dimension analysis.

Q&A

Questions cover quantifying stability work, governance of stability metrics, scope of stability construction, and prioritization of initiatives.