Best practices: data collection for disclosures

Best practices: data collection for disclosures
October 14, 2014

Request, manage, aggregate, and repeat.

According to Data's Credibility Problem, knowledge workers waste up to 50% of their time hunting for data, identifying and correcting errors, and seeking confirmatory sources for data they do not trust.

But the data collection process doesn't have to be so tedious.

The first step to making it manageable is to put a plan in place. Here are a few best practices to follow when creating your data collection roadmap:

Automate the request
The back-and-forth during a collection process is painful. Automate the process, and eliminate some non-value added tasks from your to-do list. Your time is too valuable to be babysitting the data collection process.

Take the guess work out of aggregating
Copying and pasting collected information from multiple spreadsheets is a challenge, especially when there are version control issues. Ensure that your process allows data to be locked down from editing by data providers, so it only flows to the master aggregating template when it's approved.

Set up a realistic timeline, and strengthen communication
Communication is key. Make sure to set deadlines for your collectors and approvers, so they have adequate time to complete their templates. They'll feel better about the process, and you'll have more time for analysis.

Don't question the accuracy of your data. To see more about how the data collection process can be simplified, check out this infographic.

Mike Sellberg

About the author

Mike Sellberg is Executive Vice President and Chief Product Officer at Workiva. He is the former EVP and CTO at iMed Studios and the former Divisional General Manager at Engineering Animation, Inc.