Today, organizations that embrace diversity are leading the pack when it comes to innovation. A diverse workforce results in a winning mix of ideas, opinions, and solutions. Across the board, companies know that the topics of diversity and inclusion (D&I) are essential to the success of their business.
In its 2017 Global Human Capital Trends study, Deloitte found that over two-thirds (69%) of executives rate diversity and inclusion as an important issue. Studies have also shown that highly inclusive organizations generate 2.3 times more cash flow per employee, 1.4 times more revenue, and rate themselves 170% better at innovation.
To be truly inclusive, businesses need to consider diversity as more than just a reporting goal. It needs to be fully embedded within the organization.
Diversity and Inclusion as a Business Imperative
These measurable statistics illustrate the business imperative. Recognizing the importance of a diverse and inclusive culture is, however, just one piece of the puzzle.
As mentioned, businesses need to consider diversity as more than just a reporting goal. It must be embedded into their company culture, systems, and talent processes. And by doing so, they establish HR and D&I as the heart of an intelligent enterprise.
At SAP, for instance, we recognize that talent is ubiquitous, but opportunity is not. To address this, we drive access to opportunity primarily through our four pillars of D&I:
- Gender Intelligence
- Generational Intelligence
- Culture & Identity
It is key to remember that what shapes a business, dictates the business outcomes.
But diversity is not just a topic for leaders—it must be lived and breathed at every level of the company. For that reason, we are also working with colleagues who serve as D&I ambassadors to help drive awareness, amplify impact, and execute D&I activities.
The Impact of Intelligent Technology
As intelligent enterprises, organizations can “leverage emerging technologies such as artificial intelligence (AI), machine learning (ML), the Internet of Things (IoT), and analytics to enable the workforce to focus on higher value outcomes.”
Workforces of the future also need to be just as agile and make data-driven decisions quickly. In an intelligent enterprise, data—be it structured or unstructured, in the cloud, or on-premise—must become an accessible asset across an organization that enables all users to make confident decisions. Embedded intelligence offers numerous ways to support businesses in their efforts to become more diverse and inclusive.
Having an analytics tool that can proactively eradicate bias when analyzing data is crucial. Powerful but simple-to-use analytics capabilities built directly into HCM solutions allow HR professionals—and not just data analysts—access to insights across their business.
Solutions that combine the full spectrum of analytics domains—business intelligence, planning, and predictive—can analyze and foresee trends that can be immediately considered in workforce planning.
Natural language processing allows us to explore our data by asking questions just as we would with a search engine, while embedded models allow us to automate decisions and certain analytics tasks so that both the HR and the data specialist users can spend their time on higher value tasks.
At SAP, for instance, we are using such smart technologies to fight even unconscious bias with, for example, our job analyzer functionality that leverages the power of machine learning to predict and flag language that reflects gender bias during the recruitment process.
We also measure our progress in these areas to ensure we are constantly improving our D&I efforts. We also look to analyze the impact and ROI from taking part in, for example, recruiting events by comparing aspects such as the number of jobs placed on job boards against the number of candidates hired per hiring manager or the level of branding exposure versus cost.
Preventing Bias in Our Behavior and Our Technology
Artificial intelligence also helps us with one of our most human traits – bias.
On the one hand, machine learning algorithms can help us avoid gender-biased language in job descriptions. On the other, it also helps us further upstream in the process in the analysis of our data.
Even with the most extensive and accurate data at our fingertips, we can only find what we are looking for. As humans, we tend to look for patterns that confirm our existing beliefs.
Intelligent analytics tools help to correct this by uncovering and making us aware of previously unrecognized patterns and insights. By doing so, the software can help us embrace diversity at the level of solving business problems. This enables us to combine our creativity and empathy with technology.
But technology can also be susceptible to bias.
The quality of the machine learning algorithms depends entirely on the quality of the data used to train them. Their “understanding” of the world is based on the information we feed them. And, if the data they have consumed leads them to incorrect conclusions, their behavior will reflect that. This is why it is also so important to focus on and invest in the quality of the data set.
For example, at SAP, we leverage advanced analytics capabilities to:
- Measure, monitor, and drive activities to ensure accountability
- Accelerate excitement around current D&I initiatives
- Learn and improve what we’re doing and how we are doing it
This helps us to deliver on our vision of an ever more diverse and inclusive culture.
Learn More About An Intelligent and Diverse Enterprise
Intelligent enterprises embed D&I into the DNA of their business. In the age of the data-driven business, diversity, creativity, and empathy are more important than ever. The future is about creating new ideas, not incrementally improving on the old ones.
The creativity inevitably generated by a diverse mix of people with a diverse mix of ideas doesn't follow any fixed path. By combining, supporting, and fostering this with technology and AI, we are bringing together the best of both worlds—connecting people, ideas, and data.
This article originally appeared on the SAP Newsroom and has been republished with permission.