How to Measure Inclusion in Your Organization
- Whilst inclusion is fundamental to business performance, it is historically hard to objectively define because it relates to emotions, thoughts, feelings and attitudes of the workforce.
- Workforce analytics must find ways it can accurately measure inclusion in conjunction with diversity statistics.
- Using organizational science, we explore how these difficulties can be overcome.
There is an age-old saying; ‘The act of weighing a pig doesn’t make it heavier’. This jibe serves as a warning to those who see measurement as the most important thing to improve performance.
Clearly, the act of weighing the pig does not make it heavier. However, the data gathered can be used to better inform future action e.g., changing the pig’s diet. Therefore, the initial act of measurement is not futile, rather it should be regarded as the first step towards improvement. As workforce analytics becomes more sophisticated, so does our ability to measure variables and create metrics. Organizational and data sciences have enabled us to capture, quantify and track key business metrics, but the advancement of such tools also creates two big problems:
- Extrapolating these techniques incorrectly and thus providing inappropriate metrics.
- The inability to interpret and action the insight derived from the data.
Essentially, we have to be really clear about what impact we are trying to make through measurement. Critically, measurement should always precede analysis, inform insight and ultimately determine action.
Measuring Inclusion
Inclusion poses a difficult challenge for business leaders because it is very difficult to systematically calculate that which is invisible. The feeling of not being included can often be the result of our unconscious biases. These are often yet subtly displayed through our behaviours and interactions (e.g. being less expressive, body language, joking/laughing less).
We generally have good intentions, but our biases can sometimes be interpreted as malicious or detrimental to others. The dilemma is that these biases are often unconscious, and our lack of awareness contributes to an environment where these negative influences guide our behaviours and interactions.
Becoming conscious of the unconscious
If inclusion is an outcome, employee feeling, bias and sentiment are all inputs that we must measure to assess the level and depth of inclusion within organizations. We must become conscious of the unconscious in order to help make an environment which is inclusive for all employees.
To measure these inputs, we need to find superior ways of asking employees and colleagues how they feel. Language is crucial to the effective communication of feelings and expressing complex thoughts. Until recently it has not been possible to systematically transform vast quantities of language into something quantifiable, without bias or limitation.
Quantifying the intangible requires a transformed approach to analysis that has been made possible through the application of technology. Qlearsite’s Natural Language Processing software solves this problem. Too often we confine employees to continuums or checkboxes. Instead, ask people open-ended questions in employee surveys to describe their working lives.
We collect what employees say and feel, group them into themes and evaluate their relative strength and sentiment. This process transforms complex experiences into a simple measure of inclusion that can be compared from one business to another.
Organizational barriers to measuring Inclusion
Part of the problem with improving inclusion in organizations is that much of management thinking has been borne out of a manufacturing environment where the interdependencies are far clearer. For instance, in a factory making complex products each worker is dependent upon the people upstream and downstream. Defects in one process clearly result in substandard, rejected products i.e., the mistakes are far more visible and non-compliance with standards is obvious to all involved.
Conversely, in a service-based environment, people are working with a multitude of tasks that are not obviously interrelated. There are no obvious consequences of action or inaction which means problems go unnoticed for a long period of time. It is only when a crisis emerges does the issue become apparent.
Indeed, a lack of understanding of these inter-dependencies has led to inclusion being overshadowed in the Diversity & Inclusion (D&I) conversation. Diversity is the dominant issue in the debate as it is something that is easily measured. It is a headcount along one dimension; a visible manifestation of different groups of people in an organization. Inclusion however, is the invisible evidence behind how an organization operates, and how people develop dependencies.
Understandably, many organizations struggle to analyse and compare to the same deeper level of understanding. The point is they are trying to measure diversity and inclusion in the same way, which is wrong.
Qlearsite 'Include'
This week is Global-LGBTI-Business week; a clear recognition that companies and organizations have the opportunity to make meaningful progress in this area and so contribute to the never-ending quest to improve productivity. Qlearsite’s ‘Include’ offering is the most sophisticated metric to understand Inclusion. We have built a benchmark out of the words spoken by employees to describe their real working lives. This enables us to accurately measure inclusion and track an organization’s performance over time. Our unique way of measuring inclusion has the potential to improve commercial performance and change the way business is run altogether.
For more information about our Include offering, please click on the Learn More button.
Include
Define your cultural strategy using technology designed to measure, track and identify actions to improve corporate culture and diversity&inclusion in your organization.
Key Features
Culture and D&I Reporting
Quantify Culture and Inclusion
Data Driven Decision Making
– Written by Fred Gulliford from Qlearsite a Prompta partner.