Reporting graduate employment can be a matter of compliance with the institution. Establishing standard operating procedures will eliminate errors that occur in the documentation process.
Self Review, Peer Review, Final Review.
Having other eyes on the data will minimize errors when dealing with critical data.
I learned about the different methods of verifying employment and the importance of properly verifying employment.
Having a workflow practice in place allows you to strive for perfection though it is not obtainable. Having a strategy vs. just winging it will help the students and the university in the immediate and long term.
Having partnerships and good communication will reduce errors when documenting data. Showing care and holding students accountable will aid in the process of being successful. It's also important to keep checks and balances in place when it comes to data and record keeping.
Even a good process needs to be evaluated and could perhaps be made even stronger. And P. S. there are always going to be mistakes. Get over it.
Incorporate revisions, proofreading and revise documentation accordingly. Pay close attention to details and ensure document follows a consistent layout.
Communication and establishing expectations.
Learn about employment verification.
Compliance is a big factor! Organizing data & triple checking data is a great way to make sure that everything is ready for verification.
I learned that applying a workflow process can improve the consistency of documentation while reducing errors.
I learned the different ways to efficiently record data and the importance of accuracy when recording. The documentation for verification is a process that must be accurate and following the correct steps or process will lower the possibility of common mistakes. The communication between the students and career services is more beneficial when the expectations are clear and set forth.
The best way to ensure that the documents are completed is doing a internal auditing and a paper doing a checkmark of the documents that are field.
Engaging with students early on in their education so that a dialogue is created with career services. That way verifying employment/ gathering paperwork is an easier process on the student and the Institution. Having a standardized process to collect and process graduate data will minimize verification errors.
I learned the many ways to continuously improve data collection and how to be detailed in record keeping. This benefits not only the integrity of the data but helps with supporting the students and provides accountability after graduation. Communication is key and having an agreed-upon exit interview validates responsibilities on both ends.
I have gained a few more tools to ensure the students understand their own roles and responcibilities when it comes to career services and job placement. Helping to manage expectations and getting buy in is essential.
Having a workflow in place is strategic when collecting data and verifying data collected.
Proper work flow is key to reaching goals/deadlines as well as staying organized. Being able to convey why we are collecting this data and re-verifying information will help us receive more accurate data from individuals ultimately. Also, perfection is unrealistic and does not exist. As individuals part of a larger institutaiton, we should always strive to handle information carefully especially using multiple platforms or ways of communication between different parties.
Another take away is setting clear expectations about job placement and the role the student plays in their success.
Communication is key to elicit buy-in and collaboration from these stakeholders (students, graduates, employers and institution) which is necessary for successful data collection.
Clean, comprehensive data is critical.
Implement workflows and processes to ensure the integrity, maintenance, retrieval and auditing of all collectible data.
Again, accuracy is critical. Perfection is impossible, and we can expect mistakes, but the more diligent we are with ensuring an effective workflow and checking our accuracy can lead to more reliable data.
