To Make Lasting Progress on DEI, Measure Outcomes - HBR.org Daily

Organizations that seek to achieve diversity, equity, and inclusion as measurable outcomes know the importance of metrics and Key Performance Indicators (KPIs) in their efforts. DEI metrics allow organizations to better understand and operationalize their challenges, hold their leaders and other stakeholders responsible for making progress, and experiment with targeted interventions to reduce inequity. However, even in organizations that already recognize the importance of DEI metrics, leaders can struggle to measure the right ones. It’s both hard to know where to start and challenging to draw out the most important metrics from the noise.

Leaders looking to effectively measure their DEI progress must first realize that there are many categories of outcomes valuable to stakeholders deserving measurement, and that only measuring demographic representation is insufficient. For each that you choose to measure, develop a theory of change — a set of connected hypotheses that will collectively create positive outcomes — to identify tailored proxy metrics. Finally, to ensure that the hard-earned findings from your data-driven DEI efforts don’t simply gather dust on a shelf, create a plan in advance for using that data to take action, hold leaders accountable, and communicate the purpose of your organization’s DEI efforts. Taking these actions allows you to clearly prove your progress to stakeholders, form a case for scaling initiatives that are working, and effectively and responsibly deploy cutting-edge DEI interventions.

Recognize the importance of outcomes beyond demographics.

As of late 2021, over half of all Russell 1000 companies publicly share the race/ethnicity, gender, and job category information they send to the government with their other stakeholders. Many of the leaders I talk to, thinking of these disclosures, link “DEI metrics” to “disclosure of demographic information.” “Our DEI metrics are great,” one told me, “Our company is 52% women.”

While publicly sharing these metrics is an important step, on their own these metrics aren’t enough to meet rapidly changing stakeholder expectations. If your organization cares about DEI, recognize that in practice this means caring about a much larger set of outcomes, including:

• Accountability infrastructure: the system of incentives and responsibilities by which an organization holds its leaders accountable for achieving DEI goals. Some high-profile examples include the appointment of Chief DEI Officers or decisions to tie executive pay to the achievement of corporate DEI and Environment, Social, and Governance (ESG) goals. An example of an outcome metric related to this category is the percentage of VP-level and above leaders who have DEI-related responsibilities embedded in their evaluation, promotion, or pay.
• DEI infrastructure: the formal and informal groups through which an organization does DEI work and achieves DEI goals, which often includes Employee Resource Groups (ERGs), DEI Councils, Committees, and Advisory Boards, Working Groups, and DEI full-time employees and consultants. An example of an outcome metric related to this category is the funding and/or headcount available to the entit(ies) tasked with doing DEI work, relative to its size and the size of the organization.
• Progression: the processes and structures related to employee career progression. This includes the processes for promotion, recognition, and learning and development, as well as formal and informal programs like sponsorship and mentorship. An example of an outcome metric related to this category is the average period of time for an employee to be promoted.
• Misconduct and conflict resolution: the formal and informal processes by which an organization resolves incidents of misconduct, like discrimination. These processes include reporting processes and conflict resolution practices. An example of an outcome metric related to this category is the percentage of formal and informal employee reports resolved in a satisfactory way for the reporter.
• Wellbeing: the resources and systems that enable employee and stakeholder wellbeing on and off the job, including an organization’s healthcare benefits, flexible and remote working policies, pay and salary, accessibility, and sick pay and leave policies. An example of an outcome metric related to this category is the percentage of the workforce that works when sick.
• Personnel: the demographics and other qualities of an organization’s workforce, including not only employees, but others working in an organization’s ecosystem, including part-time workers, seasonal workers, contractors, partners, and vendors. An example of an outcome metric related to this category is the proportion of female employees at each job level.
• Social impact: the impact of an organization’s operations on the people and communities around it, including its contributions to democratic norms and safe and civil society. An example of an outcome metric related to this category is monetary losses from legal proceedings associated with unethical behavior like fraud, insider trading, anti-trust behavior, or malpractice.
• Environmental impact: the often-unaccounted-for impact of an organization’s operations and supply chains on the environment, life within it, and climate change. An example of an outcome metric related to this category is the percentage of waste recovered and revalued through reuse.

Stakeholders are no longer only interested in representational data; they increasingly want to know if an organization is funding effective DEI work, eliminating discrimination and resolving incidents fairly, and ensuring that its operations don’t disproportionately impact marginalized communities. Collecting metrics on a variety of outcome types and disaggregating each of them by demographics allows your organization to gauge progress on DEI in a similarly holistic and multifaceted way as your stakeholders do, and improve the likelihood that when you report success, your stakeholders agree.

Create a theory of change.

For each category you seek to measure, develop a working theory of change: a set of connected hypotheses for actions that will collectively move your organization from your current Point A to your intended (in this case, more diverse, equitable, and inclusive) Point B.

For example, if your organization is seeking to increase its representation of Black, Latine, Indigenous, and Southeast Asian people, women, disabled people, and LGBTQ+ people at every job level, a sample theory of change might involve:

A theory of change is essentially an informed guess operationalized into hypotheses. While there is no such thing as a correct or incorrect theory of change, developing one collaboratively with a diverse group of stakeholders increases the likelihood that these informed guesses are accurate to your organization.

The primary value of an accurate theory of change, however, is in its ability to directly inform specific proxy metrics: metrics that do not directly measure the desired outcome, but rather important additional factors related to its achievement.

If your theory of change involves lowering the turnover rate by creating a more inclusive culture and implementing pay transparency policies, then it follows that the proxy metrics you’d collect beyond the outcome metric of turnover rate would be assessments of inclusion and level of pay transparency. Applying this same process to each aspect of your theory of change will give you the set of outcome metrics and proxy metrics best related to your DEI efforts.

Use your data and findings to follow up.

Your DEI measurement efforts don’t end at “picking the right metrics.” Metrics bring the most value to DEI work when they’re directly used to align leaders on what challenges need addressing, and to get from metrics to useful findings, you’ll need to disaggregate these metrics by demographic and organizational factors.

Demographic factors refer to social information collected about people’s identities, traits, communities, and beliefs. Common dimensions include race, gender, age, and disability status, though depending on the region, organization, and research question, additional dimensions may be assessed like sexuality, religion, political orientation, class status, parental status, pregnancy status, transgender status, and veteran status.

Organizational factors refer to information collected about people’s experiences and positions within organizations. Common dimensions include tenure, job level, department, role, management vs. independent contributor status, office location, pay, and remote vs. hybrid status.

Analyzing your data by these factors might, for example, reveal a gender disparity in turnover rate primarily related to experiences of junior-level employees with their managers. Exploring this data further and collecting additional qualitative data through focus groups, interviews, qualitative surveys, and exit interview data might illuminate managerial bias, the lack of resources for managers to lead effectively, or aspects of the company-wide culture that punish junior-level employees who speak up.

Even before you arrive at your findings, ensure you create a plan to follow up on what the data reveals and know how to effectively safeguard, use, and communicate about the data itself. In other words, treat DEI metrics and DEI data with the same rigor and accountability you would treat any serious data-driven initiative, and rely on it to add the same degree of rigor and accountability to your organization’s DEI initiatives.

While DEI measurement may feel like a relatively “new” space, informed leaders don’t have to be intimidated by the prospect of leading these efforts in their own organizations. There may not be an easy list of “best practice” metrics; that’s true. But if you’re able to recognize the outcomes your stakeholders value in your organization, create a theory of change to guide the metrics you use, and follow up on your data and findings, you’ll be able to make measurable, accountable progress toward achieving Diversity, Equity, and Inclusion as tangible outcomes.

Adblock test (Why?)

"lasting" - Google News
January 27, 2023 at 08:10PM
https://ift.tt/Nrnq0hb

To Make Lasting Progress on DEI, Measure Outcomes - HBR.org Daily
"lasting" - Google News
https://ift.tt/wVXhfMr
Shoes Man Tutorial
Pos News Update
Meme Update
Korean Entertainment News
Japan News Update

Bagikan Berita Ini