Data Audit and Impact Storytelling for a Startup Accelerator Program

At a glance

Type of work: Data audit, impact measurement, and reporting tools
Client type: Startup accelerator and entrepreneurship nonprofit
Lead economist: Guanyi Yang, PhD
Deliverables: Clean dataset, redesigned tracking system, documentation, staff workshop, quick-win visuals, strategic roadmap

The problem

Accelerators collect a lot of data over time, but the data often lives in disconnected files and inconsistent definitions. That makes it hard to answer basic questions funders care about:

• How many jobs did supported companies create

• What revenue growth occurred

• What funding sources show up earliest

• What metrics connect to local economic impact

The client did not need a long research report first. They needed a clean foundation, a few strong visuals they could use immediately, and a clear plan for what to measure next. They also wanted to improve data quality upstream, so future reporting would not require heavy cleaning.

We delivered the work in four connected pieces.

1. Data inventory and alignment
We cataloged existing data sources, clarified definitions, and aligned on priority outcomes that the organization actually needs to report.

2. Data cleaning and audit
We consolidated the datasets into a consistent structure, flagged gaps, and documented what could and could not be supported with existing records.

3. Data collection and maintenance redesign
This went beyond cleaning. We redesigned the full data collection and maintenance workflow so the team could collect the right information the first time. That included:

• Standardized intake fields and definitions

• A clean structure for tracking companies across time

• Clear rules for updates, versioning, and ownership

• Practical checks that reduce missing or inconsistent entries

4. Training and handoff
We ran a workshop to train staff on the redesigned system, including how to maintain the dataset, how to avoid common errors, and how to produce the recurring outputs without consultant support.

What we delivered

• A clean, consolidated dataset

• A redesigned data collection and maintenance system

• Documentation and internal instructions

• A staff workshop and practical handoff

• Quick-win visuals for stakeholder reporting

• A roadmap for deeper work, such as benchmarking and longer-term impact analysis

Why this mattered

A lot of organizations try to “report their impact” before their data is ready. That often creates credibility risk, especially in grant reviews.

This project focused on building a system that makes good reporting easy: consistent definitions, repeatable processes, and a team that can run it on their own.

Confidentiality and work samples

We can share a redacted example of the tracking structure, a sample data dictionary, and an example reporting snapshot upon request.

Related service: Reporting and exhibits, program evaluation, strategic analytics