Governing your data sources with the appropriate policies and procedures can help stakeholders make timely, actionable decisions. It is paramount to have the right data available to the appropriate people and to help ensure they conduct reliable analysis and reporting, as this assists in achieving organizational objectives. This article will explore three key data aspects that can lead to effective data governance.
Data Quality
Within the overall data structure, data fields are the containers that store specific information (e.g. text, number, date, etc.), and data field gaps may impact effective data analysis and reporting. Filling those gaps can seem like a daunting, overly manual task requiring many hours from employees at all levels. It’s important to have the right policies and procedures in place at the front end to help prevent this from happening. However, fixing gaps on the tail end is entirely possible. There are times when applying systematic logic to a data set can fill those gaps in a more automated and cost-effective way. In addition, applying third-party data sets to fill or replace those fields can save time, energy, and effort in certain circumstances.
Filling gaps for newly-created fields in a tracked, historical data set should not be overlooked. When considering ideal fields to add to a pool of organizational information, those overseeing the data should simultaneously develop procedures for populating past results. This will help accelerate reporting on the new data elements. Waiting for several reporting periods to pass and reaping the rewards of enhanced information does not have to be the case.
Data Usability
Enriching existing organizational data with third-party data sets, both private and public, is a great way to unlock additional potential to help your company to make more effective, analytical decisions. One example could be standardizing the customer addresses format within your systems using a U.S. Postal Service database. This will not only help ensure the cleanliness of your data but also unlock the ability to perform additional analyses based on census data tied to those addresses. Another useful exercise is to assign North American Industry Classification System (NAICS) codes to an organization’s business customers, utilizing various databases available in the market. This allows for an end market analysis that can help increase marketing effectiveness (for where and how you locate additional market share).
If you’ve encountered significant merger and acquisition (M&A) activity, you know the pain of integrating results from those additions into the core data set. One common miscalculation across organizations is simply switching an entity over to a new enterprise resource planning (ERP) system without transforming and incorporating historical data. There are a myriad of reasons why you should and should not expend the effort in doing that transformation. Thus, it is critical to consider all aspects when making that decision.
Syncing the format of data across multiple systems within your organization is a worthwhile effort that can reap significant benefits for the answers you need. There are various ways to go about this, and they are dependent on the types of systems and the specific fields you want to enhance. Often, organizations have the same customer within multiple systems with slightly different variations of the customer’s naming conventions. Without an associated primary key, such as a customer ID or number in each system, it can be a daunting task to link the information together. Controlling the field format at the input of data is encouraged, as this early step can save a lot of headaches in the future.
All organizations can benefit from linking their various systems together to help improve their data points’ usability. The more disparate systems an organization has, the more important this exercise becomes. Whether an organization seeks to have queries work across systems or needs to pull all data into a centralized data lake, the benefits of these workstreams can significantly increase the effectiveness of a company’s decision-making process.
Data Availability
System access is another piece of the puzzle to effective data governance. Occasionally, companies can overlook the considerations concerning who can access other systems within an organization. Imagine the potential unruliness of a company’s customer relationship management (CRM) data if anyone can input prospects or leads without regard to formatting, data duplication, etc. Determining that the right people are tapped to assist with managing risk and overseeing data availability is of the utmost importance for organizations.
Conclusion
With data quality, usability, and availability at the forefront, organizations can set themselves up for success with a strategic data governance framework. For more information on data governance policies and procedures, along with its effectiveness for your organization, please reach out to one of our Analytics professionals from Forvis Mazars.