While technology has opened a new world of automation, information, communication, and management for businesses, it has also created an increasingly more complicated data environment. Where businesses used to be able to utilize paperwork files or spreadsheets, the newer complexity of data has led to a wider swath of data management problems.
In this article, we discuss some of the most common data management problems companies face—and how to solve them.
6 Common Data Management Problems & Solutions
Many of the most common challenges surrounding data management have to do with inputting and organizing data correctly—and having processes in place for utilizing this data.
1. Keeping Systems Synced
One of the first problems companies may face regarding data management is keeping different systems synced. Business intelligence is only as good as the data going into it, which means it’s important for data to be entered into the system in a consistent, timely, and predictable way. After all, if you want to pull a report on the first of the month, but only half the data has propagated at that time, your report will most likely be incorrect.
Solution: Real-Time Data Streaming
One of the most common ways to solve this problem is to institute real-time data streaming. That means instead of data pulling into your business intelligence system at intervals, such as once a day or once a week, the data pulls immediately. For most data management systems, this is a standard and automated process.
2. Comparing Apples to Oranges
Another common data management problem is having disparate data that may not come together easily into a collective report. This is especially common with companies that do business in other countries or currencies, have multiple arms of the business that may not operate interconnectedly, or utilize tools that don’t present information in an immediately compatible way.
Solution: Data Organization & Translation
This comparison problem is solved by having a system to organize and translate data into something that can interact more collaboratively for reporting and analytics. Data organization and translation are at the heart of data management. The right tools and expertise can create protocols for organizing and translating data automatically without the need for manual interpretation.
3. Duplicate Data Entry & Queries
Depending on the complexity of your organization, you may face problems related to data duplication and queries. For instance, a home services company may have one homeowner submit information for a quote and enter the CRM under their contact information. Later, the second homeowner may complete the purchase and payment. This may result in two contact CRM entries with only one converting to an actual sale. This can skew close rates, acquisition costs, and more.
Solution: Recognize Potential Variations & Trigger Corrective Action
Depending on the structure of your data, there is likely a pattern of variations that can be identified. The right data management platform will be able to recognize these variations and automatically trigger corrective actions. This helps keep your data as clean and accurate as possible.
4. Underutilizing Data
Even the best data management systems won’t do a company any good unless stakeholders are able to access and use the information in a productive way. Your company may have robust data analysis tools, but without a clean and clear dashboard that answers the right questions and provides the right insights to the right people, the data will almost certainly be underutilized.
Solution: Data Visualization, Platform Support, & Training
There are several solutions to this data management problem. The first is to ensure you have proper, easy-to-use dashboard tools in place. These are tools that provide visual reports to those people who will utilize the information and allow queries and analysis in a user-friendly space.
In addition to comprehensive and easy-to-use reporting tools, you should also plan on providing training and support for your data management platform. Individuals who will be participating in the business intelligence process should be trained on the platform and have easy, reliable access to support to ask questions and help troubleshoot as needed.
5. Incorrect Data
Another problem often faced in data management is incorrect data. As mentioned at the beginning of this article, data analyses are only as good as the data that go into them. However, in many cases, much of this data may be provided manually. This means the data is susceptible to user error.
Solution: Better Processes
The easiest solution to this issue is to implement better data processes. This means defining roles and expectations, naming conventions or taxonomies, timeframes, etc. With more specific processes in place, it can be easier to prevent data issues as well as to identify and resolve them more quickly.
6. Security Challenges
Finally, you may also face security challenges with your data management depending on how the data is hosted and processed. Security challenges may include having data stolen or misused, liability challenges regarding how your data is stored, or even having data erased or deleted.
Solution: Know the Regulations & Implement Processes
Depending on the type of data you are managing, there may be regulations in place that dictate how your data should be managed. Examples include financial, personal, or medical information. You should keep apprised of these regulations and ensure your data management techniques help to protect this information—and protect you from liability. In addition, you should implement processes such as data governance that put controls in place for who can access the data and where. Finally, you should have a backup and disaster recovery plan in place that ensures that if data is compromised, it can be identified and resolved quickly.
Final Thoughts
Data management, when done properly, can propel your business with actionable insights that drive company value. However, getting your data to the point of being able to power informed decisions can often be a complicated and time-consuming process. Data Meaning is here to help. Request a free, no-obligation strategy consultation today to speak with a data management expert about your company’s specific needs.