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Future of Data Entry – Automation and Manual Data Entry to Coexist

Published On April 21, 2020 -   by

Automation is spawning a whole new generation of data entry and causing major technological disruption in this domain. According to Garner, the AI-derived business value would likely to reach 3.9 trillion dollars by 2022. Artificial Intelligence (AI) and Machine Learning (ML) are the catalysts behind this industry-wide shift towards automated technologies and creating new opportunities in the realm of manual data entry. With traditional data entry services being transformed by automation, information is input and processed much more quickly and accurately than ever before.

However, data entry specialists will not become obsolete; instead, their skill sets and job requirements will shift as they manually support these new automated systems with regularly updated databases and digitization of paper-based documents.

Emergence of Automation

AI and ML have paved the way for the emergence of numerous applications of automation that are currently being used across diverse systems and databases, both complex and simple.

  • CRM Data Entry From partnerships within the same domain to expanding customers across industries, CRM data entry processes in eCommerce and B2B industries are redefined by automation, for improved customer segmentation, personalized marketing, and sales forecasting. 
  • Forms Processing Data Entry Automation has altered forms processing data entry beyond simplistic capture across payroll processing, online order fulfillment, insurance claims, applications, shipping forms, and account and legal forms in industries like banking, logistics, and healthcare. 
  • Annotation and Tagging AI technologies like Computer Vision have brought automation to annotation and tagging. Image annotation and tagging, for example, automatically labels, classifies, and tags image data in cases like 3D Bounding Boxes. Companies can then quickly interpret information to make predictions or train robotics in industrial scenarios.

Manual Data Entry and the Human Touch to Meet Custom Needs

In a world of complex data and data entry automation, manual data entry service providers are still needed to meet the modern demands and customized needs of clients across industries and use cases. 

  • More Cost-Efficient System Expenses: Manual data entry is more cost-efficient than introducing various specialized machine systems and software programs. Manual processing systems enable businesses to access the benefits of data entry without investing substantial capital.
  • More Control: Using manual data entry means that a company has greater control over categories, fields, characters, numbers, and other data that needs to be entered into business systems according to unique needs, like using the data to monitor certain sales trends.
  • Better Accuracy in Data Validation: Accuracy is one of the most important parts of data entry, and this can be achieved with specialized human expertise. Automated systems require specific data to operate, and poor quality data can impede processes, create biases in decision making, and can cause redundant data collection and storage. 
  • Support During Transitional Periods: As organizations adapt to new business demands and grow their company, needs began to change, and transitional periods where new processes and systems are introduced can become difficult to manage. Manual data entry technicians are valuable in both performance and consultation capacities to assist in migrating or maintaining data records to new programs and systems.
  • Superior Data Oversight: Companies that generate volumes of data that are not easily categorized by machines and software programs, such as unstructured properties or attributes, require the superior data oversight provided by human data entry specialists.

Why Manual Data Entry Will Coexist with Automation 

AI and ML are the backbones of automation for data entry. But these technologies are not going to replace human data entry specialists, only augment their capabilities and help them to improve their own workflows and processes:

  • AI Database Support: Even with AI, the AI database needs to be developed, supported, and maintained with manual modes of data entry. It also requires manual intervention with specified criteria and inputs labeled correctly for the automated system to function. 
  • Monitoring CRM and ERP Systems: Manual data entry operators are still a necessary component of creating, organizing, and monitoring CRM and ERP data entry systems. Additionally, they ensure quality control and check for ongoing accuracy during the data entry, indexing, and document management processes.
  • Specialized Data Criteria: Manual data entry specialists are a definitive component in defining and monitoring all industry-specific data criteria related to medical, retail, transportation, hospitality, media and entertainment, eCommerce, insurance, and banking and finance. This ensures automated systems have relevant, industry-specific labels and data parameters. 
  • System Quality Control: During the final stages of AI system automation, a quality control check for system accuracy must be manually performed to ensure that all automated processes are controlled and deliver the best outcomes. 
  • Centralized Governance Data Groundwork: Companies that are transitioning to use more automation usually make a shift to centralized governance. Transitioning to a centralized governance framework will require manual data entry specialists to lay the groundwork for data identifier standards and cross-referencing for constituent databases. 
  • Human-Facilitated Image Annotation: Human-enabled Image Annotation is a necessary component of Computer Vision, and this task requires a human specialist to determine the correct, relevant information used for training AI models and defining image labels for uses like 2D and 3D Bounding Boxes. 
  • Legacy System Support: Businesses who have been operating for years still have old, outdated systems and documented forms that require the support and operational assistance of a human data entry specialist that can help to bridge the gap between automated and legacy systems. 
  • Acquisition of Offline Data: Acquiring offline data remains a challenging activity for paper-intensive companies like medical institutions, banks, and logistics businesses with records, proof of identity, and other archival data stored offline. Manual technicians work alongside OCR and update siloed data.

Manual Data Entry Would Still Play a Crucial Role 

It’s quite obvious that legacy techniques and technologies get obsolete with the advancement of new technologies. However, manual data entry still has an important role to play in shaping up AI-enabled systems. Closely monitoring automation with AI and ML Data Entry Outsourced (DEO) has been continuously and aggressively adopting the need for backend databases and digitization of information documents to fill the gap. With an in-house team of experienced data entry specialists and advanced techniques, DEO is evolving alongside the rapid pace of technological disruption and providing the support that modern-day systems require. Along with CRM data entry, ERP data entry, annotation and tagging, and many more, contact DEO for all your data entry requirements.

– Data Entry Outsourced

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