The broad term “data governance” is new hat to some, old hat to others. Either way, businesses must employ the concept of data governance as they move forward into the digital landscape. Every business, from small to large, for-profit to non-profit, collects and utilizes data in some way. Ultimately, the governance of data can be as specific as to how an organization governs data during its life cycle or as broad as the way in which organizations utilize data for multiple purposes, such as forecasting, tracking sales, to comply with the law, and so forth.
When we ask “What is data governance?” we may risk opening a Pandora’s box of definitions that are only partially accurate or not accurate at all. Data is information. Today, much of the data that is collected by organizations is digitized to later be used for various purposes. In most organizations, data can be a framework to help with employee training, to track customer behaviors, for marketing, to ensure legal compliance, and to create accurate financial quarterly reports. Because data can be used for so much, governance procedures should be in place to safeguard data and to ensure accuracy. Governance procedures should also be in place to ensure privacy, as data is often in the form of consumers’ personally identifiable information that must be protected under laws such as FERPA, HIPAA, and FCRA.
Ensuring clean data and compliance are essential for day-to-day business operations, but what’s more important is how governing data can be important to best business practices that lead to more customers and more profits, strengthening the bottom line. When viewed practically, organizations will be able to see how a bad data governance framework can negatively impact them financially while maintaining appropriate, efficient data can be utilized in ways that can affect finances positively.
From purchase to sale, clean and useable data can help streamline the process. Raw materials, supplies, ingredients, consumables, and any items that must be purchased regularly can be ruled by data-driven practices that ensure the purchasing process is efficient and economical. Sales can be better tracked with clean data, leading to an analysis of customer behaviors as well as analysis of cost and profit. Applying capitalist principles to a governance model can help businesses see a bigger picture. Maintaining clean data is extremely important in this process, as bad data can foil the efforts of analysts when attempting to forecast the future health and growth of a company.
There is a lot to a data governance framework. Smaller organizations may only have to deal with a small information technology (IT) component and only a few employees who act as data stewards for incoming data. Larger organizations can have entire IT departments, security staff, and numerous managers and supervisors serving as data stewards. Company growth can complicate the governance process, as an increasing influx of data (consumer information, vendor information, financial information, projections, inventory, sales and marketing reports, and so forth) means more room for error. This is why as a company grows and collects more data, procedures and policies must be in place to make sure that during the life cycle of the data, it is used for the correct purposes and kept clean (meaning that it is free from errors and available to the correct departments). Regardless of how clean the data is, data is useless if it is not used to further the mission of the organization.
The ultimate goal of any business with regards to data should be to streamline the data collection and utilization process to maximize goals, whether for compliance or to increase profits. Ensuring that governance is implemented and that data is collected and maintained correctly, securely, and efficiently will help any organization have clean data that can be purposed for the good of the organization.
