One of the main stumbling blocks to business people relating to the importance of data management initiatives is the lack of cohesion between business and IT. It's a topic constantly addressed and spoken about but difficult to quantify and address in terms of the unique challenges within any given organization.
On the business side, profits and strategy drive business initiatives. The importance of the backend data that provides visibility into what is happening within the organization acts as a supporting role instead of a primary one. IT departments, on the other hand, maintain the infrastructure of the business by developing and maintaining solutions that use data to drive business decisions. They do not always understand the business value the supported data gives operations. Consequently, each side sees the other as lacking, when in reality, without an understanding of how the other side conducts business and the benefits data provides, it becomes impossible to see the value inherent in how either side operates. Therefore, implementing a strong data management initiative requires both business units and IT.
What this means is that instead of creating a strong IT infrastructure and data management structure in a bubble, it becomes important to define data elements in terms of how they relate to the business and subsequently who interacts with and gains benefit from these entities. This is the promise of data governance.
This article looks at the role of data governance within organizations and the importance of business-driven data management initiatives. To fully realize the potential of data governance and overall data management projects, moving away from IT focus and driven initiatives are essential. Because of the complementary role of business units and IT in relation to maintaining a successful enterprise, both groups should be involved in driving data management projects and the ongoing maintenance of those initiatives.
The purpose of data governance
Data governance aims to integrate business processes and the data surrounding it through the management of that data by various business units. Through first defining what data means, organizations can start to identify how information relates to business performance. A common example is defining a customer, which differs by department. For instance, within an IT helpdesk a customer refers to internal employees that work outside of IT; for customer service representatives, customers will refer to people outside of the company calling in for support, and the list goes on. Some people in the organization may see channel partners or suppliers as customers even though they call them something different.
In essence, people across the organization will consider a customer something unique to their job function. Because of this, the ability for IT to act alone and to create a data model for the whole enterprise that identifies process flows and outlines the way the business works will be meaningless unless there is an equal understanding of what the data tied to all of these processes means.
Knowing where the data comes from is only half the battle. Understanding the value of information requires the marriage of business and IT. Therefore, the role of data governance enables the management of data by business through the creation of a framework that identifies the importance of various data entities to the business. Data governance enables organizations to integrate the technological aspects of data and how it flows within the company with the business benefits associated with that flow.
Data governance and its relevance to business - benefits from integrating data management into their daily business processes
The relevance of data governance to business is threefold: it provides better visibility into business performance, it enables collaboration across the organization, and it creates an environment focused on continuous improvement.
Business performance visibility
Data is power when used properly. What many businesses want more than anything is the ability to look at information across the organization in a holistic way. Not only does this mean the analysis of data, but the transition from being a reactive company towards a proactive one. The only way to do this is to understand how data is captured and used within the organization to gain broader insights into how to drive better performance.
Data governance does not live in a box. Although organizations may start data management initiatives by taking one entity such as customer or product into consideration, it is still essential to define what customer or product means to different business units and how these data elements interrelate within the organization as a whole. Consequently, even if only one entity is being considered, interaction and collaboration will still be required from many different people within the organization. This in turn can promote collaboration on more levels and for additional projects moving forward.
Once people start to see the benefits of managing their information assets and in improving business processes and aligning them to overall performance and increased data visibility, continuous improvement becomes possible. The ability to welcome change and to facilitate improvements driven by this change is empowering. Unfortunately, in many cases change is met with resistance. However, once new strategies and initiatives lead to improvement, business units and change agents start to look at what other areas can be improved upon. In addition, the data management initiative becomes iterative and not a one-time event so that data stewards and the like look at how to improve upon the current data infrastructure and surrounding data governance practices.
Data governance takeaways
Add to this the ability to solve issues surrounding better decision-making, identifying gaps in performance, reducing costs associated with customer management and general inefficiencies, and starting a data governance initiative begins to make sense. Unfortunately, many people without technical savvy shy away from the concept of data management because they feel it resides in the realm of IT. In reality, by managing business operations, by analyzing information, and by resolving issues, people are interacting with their data. In essence, knowledge workers deal with information to help solve issues and to do their jobs. The addition of data governance only enhances their ability to become more effective in their role within the enterprise.
About the Author
Lyndsay Wise is an industry analyst for business intelligence. For over seven years, she has assisted clients in business systems analysis, software selection and implementation of enterprise applications. Lyndsay is the channel expert for BI for the Mid-Market at B-eye-Network and conducts research of leading technologies, products and vendors in business intelligence, marketing performance management, master data management, and unstructured data. She can be reached at firstname.lastname@example.org. And please visit Lyndsay's blog at myblog.wiseanalytics.com.
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