According to Experian 2020 report on data management, 85% of organizations see data as one of the most valued assets to their business; however, most companies cannot manage it. Data plays a key role in digital transformation and planning company growth strategy for any organization. Modernizing data management skills to keep up with the growing technological advancement and securing scattered data is becoming essential.
Protecting and maintaining company data is not as hard as it may appear to you. You need to know your data management process and ensure that you organize your data daily. So that your managers are empowered with real-time data streaming as and when required.
Here are some effective data management practices for every organization:
It is not just about managing data and keeping it safe, but it also needs to be effective. To do so, it may require a reliable tool or strategy to access, integrate, cleanse, govern, store, prepare, and manage data. But, again, applying simple data management practices can make it easier and faster.
1. Must-Know Tips for Effective Data Management
Every organization must consider making a data management strategy to ensure that it is readily available when required. Here are some of the must-know practical data management tips.
1.1 Outline your data management objectives
Having a clear objective helps you determine your process and the necessary tools before beginning with data management. Your action plan will include clarity regarding valuable data insights and the kind of data you should collect and focus on.
As you begin, you'll find that most data is of no use or unused for a very long-time, but takes up a large amount of space in your storage system, also known as 'dark data.' This dark data needs to be carefully reviewed, and all the extra/unwanted data should be eliminated from the system.
It is advisable first to mark your company objectives before you begin with data management.
1.2 Build a flexible data management process
Now that your objectives are clear, it's time to get into the details of building a relevant and lasting data management process in your organization. The process includes three steps, namely collecting, storing, and analyzing.
1.3 Select your data management technology wisely
The next step after developing a process is finding the right data management technology. This is also one of the most important steps because it is nearly impossible to do it manually with so much data to sort. Artificial Intelligence (AI) and Machine Learning (ML) powered data management process enables digital transformation. It enables organizations to process more data and at a faster pace. Furthermore, applying automation in the process eliminates the time and amount spent on labor-intensive tasks. As a result, people management software is trending.
1.4 Comply with all the regulation and governance
Applying appropriate regulation will help you avoid falling victim to any incident exposing your confidential or protected data/information. Indeed, the last thing your customers would expect from you, that their personal information is safeguarded. Therefore, complying with regulations will ensure the privacy of your leads and other vital data.
Similarly, having governance standards in place for data management will help you determine what action needs to be taken, by whom and when for better customer success operations.
This will help you integrate processes and streamline data collection ensuring everybody is following the same formula.
2. Final thoughts
Other important things to remember -
Ensure that your management data empowers your team with real-time data streams and automated prescriptive guidance.
Applying the right people intelligent technology or other operational management technology for data management will help you redefine the way leaders manage, optimize and plan company growth. This will help you with scalable growth.
Unlike traditional business practices where business decisions were based on gut feelings and experience, today, the world requires a new approach with real-time data and facts to go ahead confidently.
In this guide, you will find:
- OKR principles
- Formulas & scores
- OKR methodology
- Step-by-step guide
- Free OKR templates
- Common mistakes
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