In any business, you’ll have a lot of data accumulating. Much of it will be important, some sensitive, and some of it useless or redundant. It may also be scattered among multiple data sources, from the cloud to desktop databases. Keeping data organized and secure is a challenge, but the main goal is getting your money’s worth from you data applications. To provide a return on investment, your information should not only provide a record of your activities, but a source of insights for making improvements and increasing productivity or efficiency. For HR managers, this extends to every part of the company. Here are some cost-effective ways to manage your data.
1. Establish Access Rules
With sensitive data such as social security numbers or salaries, access should be restricted so that only those with a need to know can read it. Otherwise you increase the risks of it being exposed and leading to problems. But with non-sensitive data, providing simplified access for your entire team is a better choice. Shared data can provide better value to the company because everyone can be working with the same information. This leads to greater consistency in reporting and analysis, verifiable results, and more opportunities to discuss, understand, and apply the information you’re accumulating every day.
2. Scrub Your Data
Poor data quality leads to gaps, redundancies, and incorrect statistical results, which will negatively affect business decisions. You could have information that’s the wrong data type, in the wrong format, linked to the wrong people, departments, or locations, or incorrectly dated. It can be hard to detect these mistakes in large or even moderate files being loaded from disparate sources. It’s important to have validation techniques in place that check every record before it’s loaded. By establishing data integrity, you provide greater accuracy to your results, and more value to the company.
3. Share Metadata
Metadata is information within a system or application that describes the actual data. This is important to data cleansing as mentioned above, but also to sharing data between different systems and domains. The data’s purpose can depend on what it’s used for, from simple statistics for weekly reporting to complex data models for predictive analysis. It’s also important to the software platform where the data is used. You want systems that are able to correctly share and interpret these data definitions for greater accuracy, flexibility, and transparency across the enterprise.
4. Data Technologies
In most companies the data is loaded into a central, structured framework such as a data warehouse where it can be accessed from these different applications. With HR, this often means specialized solutions, namely human resource information systems, or HRIS systems. These are engineered to provide streamlined servers to your team for managing regular tasks such as payroll, benefits, employee reviews, and more. They typically also include reporting and search features. Use-specific tools such as this also maximize the value of your data systems.
5. Support Analysis
While statistical reporting and analysis is important, many companies will want to utilize more sophisticated methods for purposes such as identifying various kinds of patterns, or data modeling to explore certain scenarios. You company’s data management tools should be capable of providing optimal use for your data scientists to solve problems and anticipate markets. In HR, you may want to test and improve your processes for recruiting, hiring, or training. The capacity for in-depth data analysis can be a major factor in business growth.
Your technical tools should go well beyond efficient storage and prompt data discovery. They should provide a clear benefit to both your present operational needs and future business value. The quality of your data technology affects your company’s ability to make the right decisions when you need them.