In the Digital Age, organizations acquire and manage more data than ever before. In fact, reports show that we generate roughly 1.145 trillion megabytes of new data every day!
While this information can help drive a business forward, it’s important to handle it the right way. Without a dedicated data management strategy, you could miss valuable insights. You could even put the security and performance of your teams at risk.
Today, we’re sharing eight of the most common mistakes in data management. We’ll also share how you can avoid them and leverage business intelligence to optimize operations.
1. Failing to Assign a Governing Body
If possible, there should be a dedicated data management team within your organization. This group will focus on establishing and maintaining a data governance framework. In short, these employees are tasked with analyzing the data that comes in, managing its transmission, and ensuring that everyone has access to the insights they need.
If your company has an online data management system in place, then it’s easy to assume that the software will take care of everything for you. While this may be true to an extent, there should still be human eyes on this system, as well as its related processes.
2. Executing on Data Alone
Yes, data should inform and help influence a majority of your business strategies. Yet, in your quest to optimize this strategy, don’t forget to allow room for creativity, too. Your team members have ideas and innovations that they can contribute to your organizational mission, and making decisions based on data alone could stifle this ingenuity.
Prioritize data management to an extent that allows you to generate value and progress within your workforce. Then, make sure employees know that they can brainstorm and share opinions, too.
3. Tackling Large Amounts of Unstructured Data
If your company handles a large amount of data, then it can be tempting to jump into it before you have a clear strategy in place. While you might feel like this approach will give you a head start, the opposite could hold true.
Raw data can frustrate and overwhelm even the most seasoned employees. Before you attempt to glean insights from it, take the time to assemble the right team and put the right strategy into motion.
4. Overlooking Data Quality
Every insight is a good insight, right? Not quite. When you’re dealing with business data, it’s important to make sure that the information you’re transmitting is high-quality, useful, and actionable.
Otherwise, you’re just cluttering up your files and frustrating your employees. Modern data management software will include safeguards to help ensure that data is clean and correct before it enters your system. Especially if you’re basing mission-critical decisions on these insights, you need to make sure they’re not duplicated, outdated, or otherwise unusable.
5. Not Investing in Visualization Tools
In its raw and unfiltered state, data can be overwhelming to the extent that it’s unuseful. This is where robust data visualization tools can help. These programs take business insights and translate them into graphs, charts, and reports that are easy to conceptualize and understand.
Without such techniques in place, it’s likely that your data will be too unorganized to deliver any true business value. While these types of software can be expensive at the onset, the investment is worth it. With data visualization, business leaders can explain key concepts to stakeholders and C-suite executives, who can use that information to make decisions, set forecasts, and plan for the future.
6. Underemphasizing Data Security
Data is only helpful to the degree that it’s secured. While modern digitization has opened new doors for businesses around the world, it’s also left them vulnerable to common cyber threats.
Data security is the process of putting specific controls, policies, and procedures in place that can keep your data safe from a range of issues. A few of these include:
- Unauthorized user access
- Intentional data destruction
- Accidental data loss
There isn’t a one-size-fits-all approach to data security. Rather, it usually involves a mix of sophisticated software and employee-driven strategies. A company like KHA can help you create a safety data sheet library that keeps your policies and procedures accessible and secure.
Not only does an emphasis in this area keep your confidential information secure, but it also conserves money, saves time, and protects your brand reputation.
7. Not Tying Data to Business Objectives
Unless employees clearly understand how business data can benefit their roles and improve operations, then it can be difficult to motivate their involvement in this effort. This is why it’s critical to align or map data to specific business capabilities and overarching value streams.
Moving forward without these discussions can leave many team members assuming that data governance is largely an IT-specific task. It can help to break complex topics into small discussions so everyone understands how the process works, and why it’s important.
While you do need IT leaders and executives to buy into your data strategy, collective action is key to scaling your strategy and ensuring its long-term success. A data program driven solely by the C-suite could derail without team-based support.
8. Relying on an Outdated Data Management Strategy
Data management tactics that worked years ago are likely unable to keep pace with today’s onslaught of new data demands. Even if your strategy is relatively new, ongoing assessments and reviews are necessary to keep it fresh and accurate.
If you have a data team in place, then this task will largely fall on their shoulders. They can review the current data management program and measure how well it’s working.
Is it improving productivity? Are you seeing real business value from the steps in place? Or, are your team members becoming overwhelmed by the massive amounts of unused data sitting on machines?
By scheduling routine reviews, you can make sure that the plan you employ is working for your organization, and not against it. Data is a fluid and living business mechanism and should be treated as such.
Avoid These Mistakes in Data Management
Business data can open new doors and insights for your team. However, it’s important to make sure you’re managing it the right way. These mistakes in data management could derail your efforts, but they’re all avoidable.
Now that you know what not to do, you can initiate this effort with a clear strategy. By focusing on the right people and processes, you’re one step closer to leveraging these insights for business success.
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