Gartner define the purpose of a diversity and inclusion manifesto, as a means of ensuring that the organisation is comprised of diverse individuals (based on individual characteristics, values, beliefs, and backgrounds) to foster a work environment in which all employees feel respected, accepted, supported and valued.
As such, diversity and Inclusion (D&I) is becoming increasingly important for employers and employees alike. There are at least three good reasons why this is that come to mind:
- More diverse and inclusive organisations will likely attract and retain a wider pool of talent (check-out our article about data analytics and talent retention)
- A diverse workforce fosters innovation and resilience
- As a result, diverse and inclusive organisations will perform better financially.
There is plenty of research that backs-up these claims. Whatever the reasons, it is evident that promoting Diversity and Inclusion in the workplace is a must, with many looking to implement it as a core corporate objective.
A people data warehouse that can collate people data from different parts of an employee life cycle is becoming an invaluable source of insight for D&I initiatives. We have demonstrated this in projects where we identify any areas of an organisation affected by potential unconscious bias. The objectives are twofold:
- Identify any hidden issues that could hamper the organisation in achieving its ambitious D&I targets over the course of the next five-years
- Address any unconscious biases that have been found as this can improve employee engagement (x3), reduce employee flight risk (x3) and drive innovation (x2.5).
- We have developed a hypothesis which covers four key topics: Descriptive analysis of representation across the organisation
- Applications and hiring
- Turnover and leavers
- Career progression.
Some of the data used in the analysis includes:
- Job applications
- Job descriptions
- Job requisitions
- Job histories
- Career progression
- Performance and potential
- Learning and development
Analysis of the data clearly demonstrates how representation has been changing over time (hopefully, improving). In addition, problem areas are quantified at a macro-level (affecting the entire organisation) as well as at a micro-level within a very specific area of the business. For example, the analysis can uncover potential hiring bias against women in specific grades within a specific function and geography. This is inferred using benchmark analysis of hiring rates and application success rates across the entire organisation.
Beyond a static report – the drivers of representation metric
An analysis report with findings provides you with actionable insight. However, we also realise that a breakdown of the contributing factors and drivers to changes over a period of time is also essential, so as to gain insight into the trajectory on which an organisation is likely to be heading. It would also allow organisations to determine specific areas of concern, and address them with targeted initiatives on an on-going basis. This was the driving force behind the development of the Drivers of Representation (DoR) metric, designed to measure the following:
- Is an organisation on track to meeting a D&I target over time?
- Which are the key drivers for helping the organisation meet / miss the targets?
- How equitable have internal policies been on the representation of the subgroups?
The DoR metric is based around the view that an employee population is a closed ‘stock and flow’ system. Once an employee population is defined, all possible channels (or flows) in and out of this population can be identified and the metric is calculated for each.
Broadly speaking, within an employee population, inflow is made up of hiring, promotions and lateral movement. Outflows on the other hand are made up of; employees leaving the business via promotions or lateral movement. The DoR metric for each flow is a proxy for how it contributes to a D&I target. The sum of all components is referred to as the “total deviation” from target.
All inflows are tied to the strategic corporate target for representation (For example, 50% female representation). In doing so, we have set the expectation that any inflow, such as hires, should have at least the target representation, as this should be the ideal case in an equilibrium. The outflows, however, were benchmarked not against the corporate target, but against the existing representation at the start of the period. The assumption in this case is that outflows such as leavers, promotions and/or transfers out of the population should be evenly spread across the population. Any deviation from the existing proportion indicates an unequal impact between the groups.
The DoR metrics help evaluate whether the organisation (or a part of it) is heading towards achieving its corporate D&I target. It also helps uncover the underlying contribution of each inward and outward employee flow.
Let’s use a theoretical example of a function within an organisation over a two-year period where female representation dropped from 29% to 26%. The number of females hired and moving into the function are compared to a target of 50%, while the target number of females leaving and moving out of the function should be no more than 29% to be representative of the gender representation at the start of the period.
The total deviation (or sum of DoR contributions) is -12%; but if all targets were met, the female representation in the function would have been at 38% at the end of the two-year period. The current representation is 26%, which is approximately -12% away from 38%. From the contribution DoR metrics we can see that the major cause of the problem is that hiring is way off target while other inflows and outflows are less of a concern.
Ultimately, we believe that the DoR metrics, that can be filtered and benchmarked across different business dimensions, to provide organisational leaders a valuable instrument to track progress towards D&I targets, whilst being able to identify problem areas and surgically address them when the need arises.
Data is in Darshan’s DNA – both literally and figuratively. Data story-telling is his passion. He obtained a DPhil. (Ph.D.) in “Molecular Cell Biology of Health and Disease” at the University of Oxford prior to joining Concentra's Analytical Consulting Team - now TrueCue Services. As Analytics Lead and Consulting Manager, he manages the delivery of analytics projects, develops solutions and oversees the Analytics Consulting Team.