Eliminating Paper Records and Automating Data Entry to Improve Data Integrity

Eliminating Paper Records and Automating Data Entry to Improve Data Integrity

04/28/2020, 10:30 AM - 11:15 AM

Stage 2, Booth 1577, Exhibit Hall
Language:
English
The transition from paper to electronic records is a challenge for many Pharmaceutical manufacturers looking to improve data accuracy while also putting their data to work using the ever-expanding set of industry leading data processing tools. This presentation will demonstrate how a SCADA upgrade project bridges that connection for an older legacy system while also improving recipe management tracking, response time to disaster recovery, and mean time to resolution using electronic audit trails. Automated data entry not only increases accuracy while reducing the time needed to ensure compliance, it also frees individuals to focus on tasks requiring their expertise. Attendees will have the opportunity to learn the application of data integrity principles through the lens of a SCADA upgrade case study.

Contributors

  • Tony Zhang

    Speaker

    Systems Engineer

    Grantek

    Tony Zhang is a Systems Engineer with Grantek. He has 5 years of on-site experience across many industries. For 40 years, top manufacturers in Food...

Objective

  1. Objective 1. This presentation will demonstrate how a SCADA upgrade project bridges the connection between data accuracy and data value for an older legacy system while also improving recipe management tracking. 2. This presentation will outline how Pharmaceutical manufacturers who are looking to improve data accuracy can use electronic records to improve response time to disaster recovery. 3. This presentation will provide a roadmap for Pharmaceutical manufacturers who want to use electronic audit trails to improve the mean time to resolution, while also allowing their data to guide other decisions using the ever-expanding set of industry leading data processing tools.

Type of Session

  1. Type of Session
    Session

Categories

  1. Track
    Data/Information Management

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