Automated Data Processing: How to get 3 more hours of productivity per day?

Productivity can be difficult to measure and difficult to optimize. When it comes to data processing, the story is different.

On average, employees can spend over 3 hours a day on daily entry tasks. The average employee loses 60 hours per month to tasks that can easily be automated. The costs associated with manual data entry extend beyond the mere loss of time for employees. This practice can result in heightened errors, decreased productivity, and missed prospects for growth.

Given the ineffectiveness of manual data entry, it becomes imperative to explore alternatives for facilitating corporate functionality. The solution lies in automation, which not only enables cost and time savings but also improves the overall efficiency of business operations.

But what exactly are the effects of automating data on business operations? Read on for further elucidation.

Table of Contents

Why automate data processing?

‘Why would you want to automate a task when you have someone to do it for you?’ We asked this question to multiple B2B SaaS leaders and their answers were all the same. 

Leaders in the B2B SaaS industry who did not automate their tasks experienced several setbacks, such as decreased productivity, lower efficiency, and increased errors in the data processing.

While the leaders who automated these tasks not only overcome these issues but with automation, their teams were relieved of time-consuming manual tasks that mostly lead to burnout and decreased morale.

Our conclusion: Inefficient workflows can result in missed deadlines and poor customer experience, leading to decreased revenue and business growth.

The Top 5 Benefits of Using Automated Data Processing in Your Business Operations:

  1. Converts cluttered numbers in structured statistics:

    Automated Data Processing uses software and algorithms to organize and analyze data, which results in easier identification of patterns, trends, and anomalies in the information. By converting the humongous pile of cluttered numbers into structured statistics, data becomes more accessible and easier to interpret. Once readable it enables businesses to gain valuable insights into their operations and make informed decisions.

  2. Collated data at your fingertips:

    Automated data processing uses a comprehensive approach to managing data, from collecting data from various sources to formatting it for analysis, validating, cleansing, and contextualizing the data. By automating these processes, businesses have access to collated data from one centralized location, without having to search through multiple sources. This provides valuable insights into the data that can be used to achieve business objectives.

  3. Transforms your data and gives greater insights:

    Dataset formats, also called data transformations, are the gatekeepers of ensuring compliance with your set standards. With automated data processing, you can be confident that the dataset format is correctly set up in the destination repository before proceeding with downstream processes. By eliminating duplicates, your data is accessible in a standardized format for easy manipulation, analysis, and transformation. This speeds up downstream processes, enabling faster decision-making and providing greater insight into your data to help you achieve your business objectives.

  4. Greatly reduces human errors:

    Humans, by default, are more susceptible to errors compared to data automation software. And in the SaaS industry, human errors can have significant consequences. Automated data processing eliminates the need for manual data entry, enabling the collection, manipulation, uploading, and analysis of large volumes of data with exceptional precision and accuracy. By minimizing the risk of errors, automated data processing provides assurance that your data is reliable and trustworthy. This is crucial for making data-driven decisions that impact your business's productivity, KPIs, customer experience, and overall efficiency. 

  5. Streamlined operations reduce costs:

    Automating data processing is a proven money-saving technique that streamlines operations, boosts efficiency and reduces costs. By automating data processing, businesses can free up valuable time and resources that would otherwise be spent on manual processing, allowing employees to focus on higher-level tasks that can drive growth and revenue. All in all, it helps businesses save money, time, and resources, all while improving their bottom line.

Prescient is the prime choice for automated data processes for edge and operational time-series data.

AI isn’t going to wipe out your competitors but businesses that use AI will most definitely evolve faster than the ones that don't.

Prescient offers a comprehensive approach to automating and processing data operations, especially when it comes to distributed data sources. 

While there are many cloud solutions available, Prescient shines when you need to combine various disparate and distributed data sources located at different sites and output raw, noisy data. Our data engine collects, combines, and processes all of these different data sources securely and directly at the edge, and gives you the option to perform more advanced data transformation and analytics in the cloud. 

Prescient focuses on streamlining and automating your data processes to improve your visibility into on-site operations, and to provide the data insights you need to make better business decisions. Reach out to us or book a live demo with us to learn more about how we can help your specific business needs.

Previous
Previous

How a Distributed Data Engines Enables Massive Operational Data Analytics

Next
Next

Launch Real-Time Insights for Analytical Instruments - Prescient Devices