Data Governance Sets the Foundation for Business Innovation

Conal Thompson, CTO and VP, Information Technology, CAS
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Conal Thompson, CTO and VP, Information Technology, CAS

Big data can be both a blessing and a curse. Organizations have access to more information—in more forms and from more sources—than ever. With that information comes the challenge of making sense of it and, more importantly, leveraging it to extract insights that will ultimately lead to innovation and business success. A well implemented data governance structure adds tremendous value in influencing sound business decisions that drive innovation.

What is Data Governance?

A common definition in the technology world defines Data Governance as encompassing the people, processes, and technology required to create consistent and proper handling of data and understanding of information across an organization, ignoring the boundaries created by organizational structures. It is the overarching strategy for managing an organization’s data, regardless of the source or the consumer, with the goal of providing accurate, relevant information to stakeholders throughout the organization. It provides the framework for the intersection of technology and an organization’s needs for information working together to establish confidence and credibility in the enterprise's data. Data governance goes beyond data projects, employing standards for managing data. Data governance sets the standards for how data is gathered, maintained, updated, integrated, and analyzed based on the information needs of the organization. It also provides guidance on best practices for implementing new technologies and builds the foundation for how data is managed.

Leveraging Technology to Fulfill Business Needs

In any organization, consumers of information bring unique perspectives and have different needs. While manufacturing and planning wants to improve efficiencies, Business Development is looking for opportunities to fill gaps in the portfolio or bolster competitive advantages. Marketing needs data for competitive analyses, brand management and product planning, and the C-suite is interested in business performance compared to the competition and current projections as well as areas of opportunity for new growth. Data governance considers all of these needs and applies process technology to design and establish a strategy that makes it possible for an organization to leverage its data to the fullest extent.

While information technology teams are typically charged with the implementation, it is the business needs that drive data governance. The relationship between IT and business leadership is symbiotic: leaders use the information and insights extracted from the data to make decisions; IT uses the information needs that drive the business to determine the most effective and efficient ways to manage and analyze the data. As needs and technologies evolve, open, ongoing communications between IT and other business leaders is essential. Ideally, a data governance team is established with members from across the organization to ensure all parties’ needs are met.

Data Architecture

Data governance is comprised of various data management principles: data planning, data development, data architecture, data security, data quality, data stewardship… the list goes on. Several governance structures are possible, depending on the industry, markets, internal business drivers and strategic direction.

Data architecture is one of many facets of data governance. Based on the requirements established by data governance, data architecture determines what data is collected, where it is stored and how it is accessed throughout an organization. Data architects support data governance by designing a data management structure, workflows and technologies that ensure data quality, security and other business requirements necessary for innovation. Data inventory and flow diagrams provide the framework within which the data governance function can make decisions about policies, identify potential impacts on the business and set appropriate expectations among stakeholders throughout the organization.

According to Gartner, “Businesses are facing three critical big data challenges: overflowing data warehouses, rapidly expanding data sources, and growing infrastructure expenditures. In order to combat these mounting pressures, businesses are turning to enterprise data hubs as a way to optimize their enterprise architectures.”

While there are multiple standard approaches to data architecture, many organizations have found a hub-and-spoke structure valuable because it makes it easier and more efficient to find relationships between different pieces of information and then link that data together. Given that data sources can be internal or external, a data hub also provides tools for customization and data enrichment that give data consumers throughout an organization the flexibility to extract precisely the data that is germane to their business decisions.

As noted in a recent article from SAS Canada, most organizations fall into the 80/20 rule, spending about 80 percent of their resources “crunching” data and only 20 percent on analytics. A sound, well integrated data architecture can shift that ratio and make more in-depth analytics possible, consequently, generating more valuable information and insight.

Data Governance and Innovation

The variety and volume of information available makes it possible for organizations to generate a holistic view of the business landscape. But decisions are only as good as the information on which they are based. Sound data governance gives leaders confidence that the decisions they are making are well-founded. Clearly defined business goals and information needs, along with a well-planned technology infrastructure set the stage for leaders to use the data to drive innovation.

Innovation can encompass everything from new product development, gaining new insights from data, or even process improvements. From an internal perspective, organizations can now accurately track everything from attendance to detailed sales information. A more detailed and comprehensive view of internal systems could expose inconsistencies and inefficiencies, which present opportunities for process and performance improvements. Data governance enables business leaders to pull together all of this information from multiple sources. Customer information is now available at a level of detail that allows markets to be segmented with increased precision. This deeper understanding of the customer makes it possible to tailor products to more precisely meet customer needs. Adding market analyses and competitive intelligence to customer information could provide a better view of the broader business landscape and potentially identify new market opportunities or enhancements to existing offerings that will better meet customer needs. Add to this market trends and expectations, and plans for the next generation of products and services can begin to take shape.

Leadership can use data to derive a wealth of information, including insight into customers, product growth, market growth and new business opportunities. Leveraging information effectively can lead to the development of innovative products and services. With strong, effective data governance and communication, an organization will be positioned to capitalize on the information extracted from data. With that information, insightful leaders can set a course for business success.

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