Crowdsourced information governance is enabled by empowering a company’s hundreds or thousands of business users to collectively improve the value of overall corporate data.
Many companies are embarking on critical business transformations to increase their competitive advantage and profitability — these initiatives also require a data transformation to match their new business model, including establishing proper information governance to be successful. While the latest cloud, AI and BI tools can certainly help businesses get the upper hand on competition, operate more effectively and generate predictive analytics, they are mostly useless if bad data is being fed into them – rendering invalid results that are then used to make misinformed business decisions.
To establish a baseline of consistent data quality, many companies use a Center of Excellence model for information governance with a small group of stakeholders; however new technologies allow for more modern approaches by leveraging machine learning and AI capabilities. The result? The rise of crowdsourced information governance — empowering a company’s hundreds or thousands of business users to collectively improve the value of overall corporate data — and using it as key driver for business transformation.
Leverage Organization-Wide Tribal Knowledge
As large organizations have thousands of possible business data contributors throughout their various departments worldwide, the potential for capturing the value of individuals’ tribal knowledge is immense. By first establishing a centralized information governance initiative with standardized processes, data processes, definitions and rules, companies are streamlining the way all members of their organizations interact with and curate data across various systems and departments.
Once all business users are speaking the same data language, savvy organizations can take this foundation of information governance to the next level by applying machine learning. The result is a “synthetic consultant” – an algorithm that synthesizes and curates business users’ collective knowledge and data best practices to help an organization establish and benefit from repeatable processes that build on its resources’ ever-evolving knowledge bases. Applying crowdsourced automation also allows organizations to improve their ability to scale data management best practices and ensure corporate data is reliable and up to date across all departments. This generates a reliable and validated body of corporate data that can be trusted to inform better business decisions and outcomes.
Create World-Class Crowdsourced Information Governance
Establishing a world-class crowdsourced information governance initiative requires a dedicated effort and targeted business processes across an organization. This includes establishing a baseline community of interest within the organization that aligns with business goals and setting proper information governance policies and enforcement to drive intended results across the organization. It also means setting up processes for identifying data errors, assigning ownership to relevant business data owners, and establishing effective and rapid remediation procedures.
Once the internal community of interest is established, organizations may wish to expand their crowdsourced efforts by incorporating the deep guidance realized from other companies in similar industries. For example, if an organization specializes in the finance and banking industry, it will be required to adhere to numerous IFRS and GAAP regulations. With a crowdsourced information governance initiative that connects into aggregate data libraries from similar organizations and perhaps even third-party industry experts, companies can more effectively stay in the loop on the latest industry challenges and regulations by loading specific industry policies, benchmarks and rules into their machine learning environment.
Ultimately companies that take a crowdsourced approach to information governance are able to utilize the collective knowledge of their business data contributors to elevate the impact of their organizations’ business transformations. Rather than approaching business transformation from a siloed, department-specific view, these organizations are successfully employing automation to plug business users into the transformation effort and give them a real stake in its long-term success.
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