10 Strategies to Achieve Quality Data in the International Office

strategies-to-achieve-quality-data

Is your international office taking a strategic approach to ensure quality data? Here are the 10 strategies you need to know.  

Wondering which 10 high-level strategies can help your international office to achieve and maintain quality data?  

Higher education institutions and their international office/relations directors must be able to rely on accurate, quality data.  

To achieve this, there are several institutional conditions that international office directors can implement to ensure a data-driven approach. Read on to discover these 10 strategies to achieve quality data in the international office.  

1. Strong executive leadership 

First and foremost, your higher education institution and its international office needs strong executive leadership that understands the importance of data quality.  

These executive leaders need to be advocates for quality data and strong proponents of a data-driven approach to operations and decision making.  

Without this support from the top, your international office will struggle to implement strategies to achieve quality data.  

2. Organize regular internal meetings 

These leaders and other high-level decision makers should organize regular internal meetings to streamline communications and ensure everyone is on the same page.  

These meetings allow all stakeholders involved to stay abreast of the data best practices that the international office is using and how these can be run and managed effectively.  

3. Build relationships and break silos with faculties 

Internal bridges and relationship building are just as important as external partnerships for the international office. 

Without these strong internal relationships, both within the international office and between the international office and other faculties, your international staff cannot collect and analyze data efficiently.  

Breaking down silos and ensuring that all operations and communications are as streamlined as possible can be a critical step to achieving consistent, quality data.  

4. Identify an owner of data systems 

Once these relationships are formed, it’s important to identify an owner of the centralized data system where all international data is stored.  

That way, all parties involved understand who to approach for any data queries, and there’s no confusion around who the data is collected, where it’s stored, or who’s responsible for it.  

5. Identify what kind of information is going to be there 

As part of this process, the international office should also clarify what data and information needs to be collected and why.  

By understanding what kind information is stored in the international office’s central data system, faculties and staff will be more efficient in the collection and delivery of this data.  

6. Decide who needs access 

This data should only be accessed or edited by those with the required permissions, otherwise errors or duplications may occur.  

Those who have access should be trained on how to access the data and what changes or updates they’re allowed to make.  

7. Know how to enter the data 

As part of this training, they should also be taught how to enter data into the centralized system, learning which data sets to input into each field.  

This can help the international office to avoid any common data errors that could lead to inaccurate analysis or misleading insights.  

8. Create an internal user manual and cheat sheet 

To streamline this training process, the international office should develop an internal user manual and cheat sheet. 

This will help staff to quickly learn the above information while minimizing the resourcing burden of extensive training.  

9. Identify who else will manage the data 

If necessary, the international office should also identify other stakeholders who may need to manage the data. 

This could include high-level decision makers who need quick access to international data, or other key stakeholders.  

10. Create structured data 

To ensure that your centralized data system is simple and easy to understand, it’s important to develop structured data. 

This involves setting data rules and requirements within your system, linking data so it’s more intuitive and interconnected, and limiting what data can be added.  

Once these 10 strategies and best practices are incorporated into your international office, quality data can be positioned as a key priority and focus for your team.  

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