Automation in Enterprise Data Management: Making the Best Out of The Strongest Business Currency

Automation in Enterprise Data Management: Making the Best Out of The Strongest Business Currency

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Data is considered as the strongest currency nowadays. Mostly it is due to its increasing value to the business world: it is the driver for changes, a basis for re-invented strategies, and well-thought tactics. 

If you find yourself struggling with the dilemma of efficient corporate data collection, integration, and analysis, then you have obviously heard of automation management solutions for corporate data. 

One of such solutions is Robotic Process Automation. 

In this article, we will consider the areas where RPA can help businesses in their data management processes and provide you with the use cases of RPA in various industries.


How RPA can help in data management 

Benefits from implementing RPA

RPA in data management: 3 use cases


How RPA can help in data management 

According to Experian Global Data Report, around 30% of American entrepreneurs consider their data management operations as not very accurate. 

In this regard, RPA is growing in demand since more companies recognize its benefit for data management automation, especially in big data. 

RPA refers to bots imitating data-related processes that are typically executed by humans manually. The scripts create robotic actions that automatically perform rule-based and repetitive tasks. In a nutshell, they are software robots.

Applying RPA in data management processes makes tasks such as data entrycapture, and creation or update much more efficient. All of these assignments are highly repetitive and tend to be unique, as each data processing scenario demands special consideration. Here when an excellent opportunity for applying RPA appears. 

It should be noted, that RPA can be combined with other techniques to create complex data managing solutions. Robots can be used to automate operations management, such as extracting information from scanned documents using Optical Character Recognition (OCR) to create metadata and reduce content to a usable format for big data or machine learning (ML) processes.

Benefits from implementing RPA

RPA provides exceptional solutions for improving outcomes in all data management areas. 

Augmented by machine learning and AI, RPA can streamline data input (such as initial processing of images and documents) and improve processes by reducing the time consumed. It can reduce headcounts for manual and highly repetitive processes and enhance the quality of data. 

Below are some Robotic Process Automation benefits and capabilities that impact in boosting data management processes:

  • Replacement of tedious manual data entry by automated, programmed bots
  • Capability to connect to any external source for data processing
  • No limits on the volume of processed data
  • Acceleration of data management processes – repetition rate of data update requests reduced to 0.1 second
  • Presets for MS Excel and Google SpreadSheets
  • Optical character recognition of data from PDF and scans
  • Programming capabilities within scheduling and building timetables
  • Capability to be installed either on the server or the cloud 
  • Capability to connect to FTP, SQL, MongoDB, and other databases, as well as various applications
  • Compatability with wide-spread ETL infrastructures (Amazon Redshift, BigQuery, Snowflake)

RPA in Data Management: 3 use cases

As proof of the theory provided above, here are 3 examples of RPA used in various data management projects.

Use case 1: Accounting

Challenge: 

It takes around 40 minutes daily for an accounting specialist to manually capture invoices’ data via Optical Character Recognition software and input it into the accounting system.

Solution:

A bot is programmed to automate the data capture process. Once the invoices data is processed, the bot inputs the information into the accounting system and reconciles it.

Outcomes:

  • Increased invoice processing accuracy management
  • 160+ FTE hours saved per year

Below you could see how Electroneek bots handle with data extraction with the use of OCR:

Use Case 2: Insurance

Problem: A large insurance company processes more than 600 claims during the week. Each page of the documents should be verified manually by ID. The process takes from 7 to 10 hours per week

Solution: The bot is programmed to automate the ID verification process, providing the insurer with the opportunity to spend more time on value-added tasks.

Outcomes:

  • Enhanced employee morale
  • 900s of FTE hours saved per year

Use Case 3. Marketing

Challenge: 

A marketing department specialist usually spends 2 to 4 hours to gather data on consumers’ acquisition channels from various sources. Then he manually forms a report in comparison diagrams and charts

Solution:

A bot is programmed to automate data collection and report preparation processes. Apart from it, once the report is created, it is forwarded to the stakeholders.

Outcomes:

  • Enhanced customers satisfaction 
  • More than 140 FTE hours saved yearly

RPA: Making the best out of your data

We have considered the benefits of RPA as an integral part of the data management ecosystem and demonstrated the practical use cases in several industries. 

The robust data management strategy is one of the critical components of operational excellence and competitive advantage.  

With the help of RPA, you can simplify the complex data management workflows and cast aside the dilemmas related to it. 

Reach out to our automation experts to learn how ElectroNeek can take the burden of manual data management processes and maximize your profit numbers!