How much time do you think you waste each week searching for data or replicating data that already exists. If you were to search through your most used tools (EHRs, CRMs, spreadsheets, etc.), how many unnecessary duplicate entries would you find?
The Data Warehousing Institute estimates that U.S. businesses lose a cumulative 600 billion dollars a year due to problems with data quality.
Managing data gets more difficult every day as the frequency, volume, and speed of incoming data continues to increase. But without a strong data management plan in place, it's likely that your organization is disconnected or under-utilizing important data.
What is data management?
Data management is the process of acquiring, validating, storing, protecting, and using data in an accessible, reliable, and meaningful way. No matter the industry, you’re organization houses a lot of important data. But without good data management, you may be missing out on insights that could help your organization make better decisions or increase profits.
Why take the time to manage your data?
Taking the time to institute a data management plan may seem like a daunting prospect with low return. You may feel that your team already functions well without a data management plan in place.
However, without a long-term plan and scheduled audits, you risk your overall efficiency by opening your team up to overlooked data errors, under- or over-utilization of tools, and security blindspots. Additionally, it’s likely that many of your team’s most common problems could be solved by applying a few data management best practices.
Today, we’re going to look at some of the most common data problems facing businesses today and show how applying a few data management tips could solve or prevent them.
Problem #1: Data is difficult to find and often goes missing.
Solution: In order to ensure quick and easy data access, your information assets must be well-managed. If your teams are having trouble finding data, it's likely that your information assets are being housed in insulated, disparate systems where access is restricted—otherwise known as data silos.
Data silos can spring up under many circumstances, but they typically occur as a result of three main factors.
- Company Culture: When departments, teams, or individual employees work in competition, or under animosity, staff may tend to keep their data to themselves rather than work together.
- Management Hierarchies: In large organizations, staff are often separated into many layers of management and specialized staff. In these situations, information tends to remain amongst small groups and doesn’t trickle down to employees who need it for their daily work.
- Technological Barriers: In situations where different departments operate using different software, applications are often unable to share information or be cross-referenced. We frequently see this problem in hospital systems where different facilities use a variety of electronic health records and are unable to easily share patient data to ensure quality care.
Data silos present a very large, overarching problem that will likely require some significant cultural shifts, but there are some initial steps you can take to start tackling this problem.
First, identify what processes and systems are currently housed in silos. This will help you to collect information about your primary systems and who uses them. What data sets does your staff deem the “source of truth?” If you have many data sets housed across many systems, find ways to combine information.
Pro Tip: Institute a quarterly or biannual data management health audit. Auditing your data will help you continue to measure the security, lifecycle, quality, and flow of your data.
Problem #2: Data is difficult to share.
Solution: If you can’t share your data in a meaningful way, it’s not much use to you. Across your organization, much of your staff may require access to multiple databases in order to get the data they need for their work. Data sharing is an important part of your team’s success, and shareable data must be stored in a standardized format, under a single schema.
Take the time to institute a sharing procedure as a part of your data management plan. Sit down with your team and ask a few high-level questions to understand what data you may need to share across departments or project leads.
- What data are we generating?
- Who needs access to this data?
- How will data be shared or accessed?
- Does the data contain private or confidential information?
- How will access be restricted or managed?
If you address these questions and find that the data you need to share is housed in disparate systems, you may need to find a way to integrate your tools and streamline data into one database.
Problem #3: Data is low quality, and duplicate entries are often found.
Solution: Low quality data can exacerbate an organization’s data silo problem. If employees don’t feel they can trust the data in their primary system, they commonly turn to personal tools or spreadsheets to maintain their own trustworthy data set.
In a sales team, for example, missing or incorrect client contact information may equate to failure to close on an opportunity. It’s even more frustrating to think your accounting team probably has accurate information used to bill current clients. But this information is held in a different system that’s inaccessible to your sales team. How do you avoid this problem?
Problem #4: Data security and compliance are a frequent concern
Solution: For organizations working in European markets, handling patient information, or dealing with financial data, compliance is an important factor in your work.
You won’t be able to institute these methods of data management overnight. But once you do, you can start using your information assets to inform business decisions and improve efficiency.
Learn more about how Formstack Products can improve data management across your organization and tame data chaos for good.