The next step in information governance - Crowdsourcing
Many organizations looking to implement and information governance programs rely on a "center of excellence” model, where a handful of high-level managers set enterprise-wide data policies and a group of assigned data stewards enforce those policies. While this approach certainly serves as a clearinghouse for all things data, it may not be the most efficient way to meet the rapidly changing needs of today's organizations.
Data – coming from a vast array of complex sources – has now evolved to include a multitude of structured and unstructured forms, new data classifications to meet regulatory requirements and increasingly, employees outside of IT tasked with data governance tasks.
The next natural step in unlocking the full potential of effective information governance lies in the concept of crowdsourcing. Used by organizations seeking to leverage a broader range of data stakeholders, crowdsourcing can create a more dynamic and collaborative process throughout the organization – connecting executives, managers and data stewards alike.
A crowdsourced information governance approach engages an organization’s full breadth of data stakeholders and applies techniques such as natural language processing and machine learning to guide less experienced data contributors. This allows organizations to react in real time to rapidly changing business requirements.
Shifting Into a Crowdsourcing Mentality
A major force driving information governance and data management initiatives is the need to treat data as an asset. Looking at data as an asset means focusing on increasing the “value” of that asset through active management of data policies and the enforcement of those policies. Handling all of these complex tasks through a small CoE with particular individuals taking ownership over different elements of ERP data sorted by vendor, customer, material and other master data objects simply won’t scale, and key employees often suffer from “CoE burnout” as a result.
This siloed approach was designed to minimize human errors, with requests for corrections going directly to the CoE with occasional outreach to other data stakeholders. IT was also involved in fulfilling requests from business users who needed specific analytics data or an Excel document to be exported for fed into a data warehouse.
As new dimensions of data have arisen and hybrid IT landscapes with best-of-breed applications have become the norm, CoEs (regardless of size) and IT teams are now becoming overwhelmed with a barrage of new requests that compete with their ability to fulfill their primary job responsibilities. To meet the needs of the business while remaining agile, responsive and dynamic, organizations need to shift toward sharing the load among a larger group of enterprise data stakeholders.
Applying Crowdsourcing to Information Governance
Crowdsourcing has been widely recognized as an effective method for driving social change, raising awareness and funds for charitable causes, and affecting change in government policies. Similarly, by using technology to bring together business experts in an enterprise forum where their data-focused input can be harnessed and guided in real time, corporations can effectively improve the value of their data as an asset through crowdsourced information governance.
Using the power of machine learning and algorithms tailored to specific data processes, users can respond to automated prompts around various business rules – enabling those rules to evolve in real time based on the latest parameters, geographic requirements, industry regulations and brand standards.
For example, a new accounting rule needs to be established around vendor payment terms based on geographic elements and the particular types of products they deliver. The enterprise can then use artificial intelligence-driven crowdsourcing to prompt questions around establishing terms in an overall system glossary as well as ask the user whether the term “payment term” should be classified as a standardized term for future use. This approach allows for a more collaborative effort to establish information governance and offers transparency into process improvements that benefit the entire organization.
Getting Business Value from Crowdsourced Data
Applying crowdsourcing to business data helps enterprises automate the process of curating, synthesizing and governing data and can dramatically improve their ability to elevate the value of strategies and actions they take as a company. It also offers a high level of accountability throughout the business and ties information governance initiatives to real monetary value and tangible effectiveness. Having the ability to direct and enforce its cross-departmental data policies through engagement with a large corporate constituency is an invaluable benefit of a crowdsourced information governance model.
There is also a common dynamic among businesses where enterprise IT system catalogs are largely out of date, often due to business users using preferred cloud or native apps outside the purview of IT. In this case, it is difficult to establish governance and clear ownership around these tools, not to mention their relationships to overall terms, policies, and rules that the organization seeks to enforce. With a crowdsourced approach, both business and IT users are involved in the global view of how enterprise systems affect company-wide policies and results.
An additional way to maximize the value of crowdsourcing information governance is to embed algorithms so users can curate data assets independently based on their particular requests. To accomplish this, enterprises can utilize automation and “train” their systems to become smarter by incorporating the collective knowledge of the crowdsourced group.
Crowdsourcing also applies across company boundaries by accessing “opt-in” capabilities for comparing an organization’s governance programs to actions taken by others within the same industry, department or even by compliance initiative. With access to this kind of information, enterprises can consistently increase the value of data as an asset as well as cope more quickly with their ever-evolving data and enterprise system environments.
On the whole, enterprises that choose to augment their policy CoE model to crowdsourcing for information governance will be better prepared to transform their data into a valuable asset that can serve as an impetus for overall innovation and business success.