Between 2013 and 2019, GALI partnered with dozens of accelerators to collect standardized data from early-stage ventures that apply to their programs. Based on this experience, GALI has compiled guidance on how to plan your data collection strategy, suggested survey questions, and an interactive benchmarking tool that allows you to compare your ventures’ performance against GALI’s global dataset.
Have a question about the tool or want to see the data visualized in a different way? Reach out to our team
This page includes tools to help accelerators plan, collect, and compare venture-level performance data from their cohorts. Answer the following questions to find out where to begin.
Your answers to the following questions will help you know where to start in using this tool.
Collecting and using data effectively can help you understand and increase the impact of your program, but it can be hard to know where to start. The materials in this section will help you understand how to define success and develop a useful data collection plan that gives you meaningful, actionable insights.
GALI developed an extensive survey to track ventures at the application stage and in the years after acceleration for both accelerated and non-accelerated ventures. This section provides accelerators with the ability to replicate the full GALI survey, as well as a simplified and shortened set of survey questions that can be used to collect only the data needed for the benchmarking tool.
After collecting performance data from your supported ventures, use this benchmarking tool to compare outcomes to GALI’s global dataset using a range of filters and metrics.
Accelerator program managers and M&E staff who are seeking any of the following:
The resources available on the “PLAN” tab will help you define what success means for your program and work backward from there to understand which metrics you should use to measure that success.
If your program is not at the stage where it has the capacity/resources to execute a data collection plan, you may want to start with exploring Measuring the Value for Money of Acceleration brief, which offers a template for programs to measure their effectiveness based on a single indicator or set of indicators.
The GALI team has created survey “starter-kits” in two commonly-used survey platforms: Survey Monkey and Google Forms (for access, send a request through our contact form).
You do not have to use the GALI surveys to use the benchmarking tool. However, there are some key metrics that you will need in order to use the tool, and you will need to have collected this data pre- and post-acceleration. These metrics are listed in the Benchmarking Prep Template.
You do not need to collect all the information that GALI collects. The full GALI survey is available so you can choose questions relevant to your program. If you are only interested in the questions that will allow you to benchmark, refer to the GALI Benchmark Survey.
The GALI site does not store or have access to any of the information you input in this tool. Your data and resulting benchmarks are only available to you.
The tool can be used to explore the GALI dataset, without inputting your data. Simply click “I don’t have data” on the top right corner of the “Input Your Data” tab.
You likely will only be able to select 3-5 filters before the sample size becomes too small to produce a meaningful benchmark. We suggest selecting the filters that are most crucial to ensuring the benchmark ventures are similar to your cohort.
This tool is designed to benchmark venture-level data, not program/operational data. We also keep all data anonymous, so ranking is not possible.
The full GALI dataset contains all ventures for which we have application (baseline) data, while the benchmarking tool is limited to ventures for which we have application and follow-up (1 year later) information, along with adequate program-level information.
The GALI data is all self-reported. However, the GALI team removed 139 ventures from the benchmarking data set due to revenue, employee, or investment information that was irreconcilable with the rest of the sample (i.e. likely incorrectly entered).
All self-reported data is provided in USD, so any currency inflation/deflation cannot be taken into consideration. Potential impacts of currency changes on the benchmark should be mitigated by using the filters moderately (therefore keeping a large benchmark sample size).