• Community Newsletter
• Community Townhall
• Company Offsite
• Partner Reporting

Sit down with key members from each of your hub verticles (i.e. community team, programmes team, events team, communications lead) and define

1. What they’re currently tracking
2. Where D&I can be baked into this process.

When defining your process be sure to outline the following

• Responsibilities/Who tracks this
• Channels to track via
• Metrics to track
• Questions to ask

In this deck you’ll find frameworks to help you identify opportunities to help you broaden how you think about D&I within your ecosystem.

• Have a measurable index of goals
• Assign responsibility and establish accountability
  • Your goals should be clearly assigned to individuals or teams who are responsible for their achievement
  • Check out this change catalyst guide for a framework on how you can do this.
• Clearly define the process for reporting and responding to findings.
• Bake D&I tracking into your hubs existing operations i.e. Members surveys, feedback forms for events etc.

Potential touchpoints:

• Registration Forms (i.e. eventbrite)
• Registration Upon Arrival
• Feedback Surveys

Note! Don’t forget to mention how accessible your facilities are at these touchpoints also. A line like “Our space is accessible for all wheelchair users. We also have some capacity to support those with visual and hearing impairments” might be the difference between someone coming to your event or not.

How

• Check out SurveyMonkey’s D&I guide which contains survey templates, stories from D&I leaders and strategies for timing, sending, and optimizing D&I surveys.

• Atomico’s “Technology tools for promoting diversity and inclusion” is a great centralised resource for D&I measurement tools
• Another option is to invest in (or create!) software products that digitally enable you to collect data seamlessly. Here’s a list of 29 D&I Measurement Tools and Technologies.

Events

Events are a great opportunity to gather data.

Potential touchpoints:

• Hard copy event feedback survey like this
• Live QR code
• Visitor check-in app to track who visits your space to meet with members or attend events. This doubles up as a security measure and a data collection method.

Focus groups

Type of data: Mixed (Qual and Quant)

Facilitate focus group discussions with your hub members to gather information on the issues and challenges facing diverse talent.

Potential avenues for collection:

• Sticky Note Feedback Sessions at events/workshops
• Dedicated meeting arranged for the sole purpose of gathering data.

Exit interviews

Type of data: Qualitative

Exit-interviews are a great way to supplement the findings you have from qualitative data collected. It’s also a great way of combating the risk of non-completion by employees who are not engaged. HR should also make a note of any grievances to spot any D&I themes. Make sure there’s a system in place for reporting on and responding to findings.

Potential avenues for collection: HR exit interviews

Type of data: Qualitative

Take the opportunity to gather feedback internally on what D&I issues are important to your Community. You can do this for example by conducting an inclusion review.

Why? These reviews can help identify differences in employee perceptions of D&I which can exist between or within demographic groups. Understanding these perspectives helps you identify your hub’s current D&I strengths and opportunities for improvement. It also helps ensure that any initiative you plan will meaningfully engage members of your community.

Have a look at Survey Monkey’s templates to get an idea of the targeted inclusion reviews you might run. 

You can find other suggestions for ways of gathering data in the Tracking > ‘Capture Your Data’ heading of this playbook.

Visual Infographics

Infographics are some of the most effective tools you can employ when reporting your D&I data, particularly to stakeholders who don’t have a technical background. They can also be used in your communications content if well designed. An example of an effective D&I infographic is from our partner Unilever, which you can see below.

Graphical Visualisation

Technical Readers You can build your own visualisation model. Here’s an example of a diversity in tech dashboard which measures employee representation across large technology companies in the US to inspire you!

Non-technical readers take a look at this open source ‘People & Culture Health’ Dashboard template

Or if you’re proficient in excel you might want to this about representing your data pictorially.

Reports

Scheduled reports act as a forcing function for measurement and accountability. Some examples include

• Embedding D&I into the bi-annual or annual reports about the hub performance report. At Dogpatch Labs documenting our D&I progress is baked into how our hub operates, with every one of our team members feeding into the big picture of what’s going on in the different verticals within our hub.
• Zaiper used a different bootstrapped tactic by cataloguing their D&I efforts and releasing it in a blog post

Use Impact Management Projects framework to help structure your impact when reporting on D&I.

You can find a simpler version of this framework which we’ve used.

What is People Analytics? People analytics is the emerging trend in talent management that replaces gut decisions with data-driven practices.

We recommend a phased approach to people analytics within a hub so you don’t overwhelm your audience.

To start you can map:

• The relative influence of individuals/positions in your hub
• The opportunities available to them
• Any explicit and unwritten rules in your hubs culture

Then you can:

• Define how those levels map on to relative power/influence within the hub
• Get a deeper understanding of existing hierarchies within your hub
• Identify where biased preferences might be creeping in and where there are opportunities to flatten out the structure

People analytics is increasingly drawing on dynamic network theory to run organizational network analysis to map D&I across different identity groups.

For deeper insights into the technicalities of this analysis, click through to the hyperlinked articles above.

Are there any specific laws which dictate the type of data you can gather?

For example, Ireland is based in the EU and as such, we need to be GDPR compliant, which you can read about in the blog article linked below.

The sensitive nature of D&I data means that privacy and respectful use of the data need to be front of mind regardless of where you’re based.

Tip! Transparency is one of the most effective ways of fostering trust and encouraging accountability within your hub. Not all metrics need to be disclosed, not disclosing an unfavourable metrics can erode trust in your hubs commitment to D&I.

Sharing results externally can also strengthening your hub’s reputation, by displaying your commitment to D&I. If your hub is lagging behind or has missed its diversity targets, you should respond honestly and sincerely, outlining a plan for rectifying these failures.

Social desirability (SD) is a well-known phenomenon that confounds research. SD bias happens because respondents answer reflect how they think they should be answering rather than how they actually feel or act (Read more here).

Some tactics for combating this bias include

• the use of indirect questions
• the use of combative scales.

Your metrics and data collection and analysis methods should be as robust as possible and aim to gather data from a representative audience.

Remember also that D&I data highlight subconscious biases that cause shame, fear, and uncertainty which generally feeds into an environment where people don’t want to get involved. Be conscious of your messaging when rallying for support for D&I. Your objective should be to minimise resistance and maximises engagement across all groups.

Data analytics is a powerful tool in helping to understand, predict and mitigate exclusive behaviours in your hub. However, algorithms are built by people and are therefore prone to the biases of their developer. Take 5 minutes to read over some tips on how to mitigate bias from analytics. Some key take aways are:

• Predictive models need large amounts of data gathered across time. Remember that less than 2-3 years of data, the validity of the model and analysis is significantly reduced.
• The accuracy of a prediction depends on the data used to create the model.
• The patterns behind why people make decisions aren’t always simple, meaning differences that arise over time can mean that a model may not maintain its statistical validity from one year to the next within the same company.