The COVID-19 pandemic has drawn companies’ attention to the focus on Environmental, Social, and Governance (ESG) goals, along with adopting new workplace practices. These goals include business operations to lend a hand to communities to manage the crisis. Social interests are now a top priority for any organization. While some brands have managed to stimulate business growth and hold up customer loyalty and trust by addressing societal problems, many others struggle to do this.
Therefore here we discuss four key principles for building inclusive data for a good strategy that helps organizations attain their ESG goals.
Outline the goals to set in motion data-discovery process: The companies as the primary step have to outline the outcomes they are looking for to achieve along with their performance indicators and then work backward to plot how to attain the identified goals. This will help them to get started with the data-discovery process. Simply it is to identify the data they need and where to obtain it.
Data to build an alliance for change: Organizations on its own cannot prevail over societal challenges. It needs the support of governments, nonprofit organizations, academia, startups, and even competitors which makes an ecosystem. Companies have to spot their capability to put together an ecosystem. These will analyze how it can achieve their desired outcomes in combination with the broader ecosystem and can be used to achieve their social goals also. Interdependencies such as synergies and potential bottlenecks can be recognized with the help of data and will take whichever, an inside-out or an outside-in approach to social innovation.
Data-driven organizational culture: companies need to build new proficiency in data science even if corporations will help overcome their limitations. This takes in the understanding of the changing spatial and of time aspects of data for structure dynamic solutions along with combining different types of data such as voice, vision, and emotion for greater insight. Companies need a mutual and incentive structure to clutch project managers, accountable for achieving ESG goals. Then they will assess the potential impact on the company’s ESG goals of every project and will start to reflect on how to trail relevant data and assess change. A key part of doing good is showcasing what companies have done so far.
Values-oriented approach to data: values-oriented approach ought to be taken to determine how data gets positioned in the social context. Data should not be used to exclude and exploit people. Companies need to put in adequate safeguards such as conscientious software’s that guard against the ability of algorithms to intensify pre-existing unconscious biases.
Finally, companies must ease the risks of sharing data within the ecosystem for social good. Assorted approaches help companies’ moderate data-related risks. Nearly, every company is now a data company. Therefore, a sound data strategy enables companies to overcome the barriers of blending business value with social value.
