A multi-case study approach

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Step 1

Across the US & Canada, I visited companies of varying age & size where CSR & corporate volunteerism practice are considered to be strong. I would often speak with both senior leadership and in-the-field programme managers to get a sense for both the strategic and operational side of things.


Step 2

Having completed these studies, alongside a review of the available business & academic literature on corporate volunteerism strategy & practice (linked to throughout this website), I made a judgement on what ‘good’ practice looks like. This comes in the form of ten benchmarks identifying the various aspects of strong corporate volunteerism execution.

Step 3

To supplement the first- and second-hand evidence, I then interviewed multiple thought-leaders in the space (incl. charity partners, impact investors, schools/universities).


I also spoke with companies where CSR wasn’t so prominent or was still emerging as a force within the business, or where they had an interesting use of tech for good. The goal was to test and refine the key aspects of strong corporate volunteerism.


Step 4

I then used the rich data collected from interviews, alongside information from company Annual Reports, press and websites to see how my sample of companies sized up against the ten revised benchmarks as well as the extent to which they used technology within each area.


Note: I will not be discussing individual results of the companies in the sample. Rather, these ratings served purely as the basis for anonymised, aggregate correlation analysis as discussed further below.


The companies were scored out of 5 for a variety of sub-indicators within each individual benchmark (see the benchmarks page for detail), the average of which translated to an overall score for each benchmark. They were also scored out of 5 for their use of tech within each benchmark.


This highlighted where each tier of companies (see section below) were doing well across the entire lifecycle of corporate volunteerism, the extent to which tech was helping, where gaps might lie, and whether any learnings across tiers could be had to fill them.

Step 5

For each tier, I also used Pearson’s correlation analysis to test both the overall relationship between the use of tech and high performance on each of the benchmarks, as well as the driving indicators of performance within each benchmark.


The aim was to highlight typical strength and development areas and where tech might be particularly effective.

How did I select & group the companies?

I posited that performance against the benchmarks & use of technology might in part be influenced by:

  • # of employees a company had
  • revenue of the company
  • age of the company

so decided to select companies that varied according to these characteristics.


To avoid drawing parallels between larger, mature companies (with potentially stronger overall benchmark performance) and their smaller, younger counterparts, I divided companies into three tiers, according to their percentile performance for size (revenue & # of employees) & age:

Tier 1

American Express
Booz Allen
McKinsey /
Major League Baseball (MLB)
Walt Disney Company
Warner Bros

Tier 2


Tier 3

Panorama Ed

*SME = Small & Medium-sized Enterprise

Next: Read onwards to  Key Findings >>