Automated Data Processing

The trends and opportunities of Automated Data Processing

Maximilian Schneider

When it comes to processing data, one often first thinks of endless Excel spreadsheets into which a clerk manually enters columns of numbers and texts, only to pass them on to the next clerk for further processing. Automated Data Processing is the complete opposite: processing is done by digital applications and platforms instead of manual preparation.

In earlier digitization projects, only the tools for data processing were initially translated from the analog to the digital world [Source: History of digitization]. Building on this, companies are harnessing the true strengths of digital technologies through Automated Data Processing (ADP). This frees internal resources from error-prone processes. It also opens up new business areas for companies and the opportunity to differentiate themselves from the competition in terms of service quality, price and range of services.

What is Automated Data Processing in concrete terms

Automated Data Processing, or ADP for short, is associated with a range of processes and Technologies.This is a method of storing, structuring, organizing, analyzing, or processing digital data that has been read in without significant human intervention. This form of processing should not be confused with the data processing measures for personal data in accordance with the General Data Protection Regulation (GDPR). This regulation explicitly deals with the legally compliant handling of users' personal data on data protection. It should also be noted that the manual processing described at the beginning does not fall within the definition of ADP, since the automated aspect is missing in this case.

A catchy example are regular financial reports, which are commonplace in organizations around the world. A manual process here means that employees first gather the figures from databases and Excel spreadsheets. Then they further process the data into visualizations or summary tables. In contrast, specialized ATP programs automatically generate the annual balance sheet from all known key figures. They take known factors into account and draw charts for the most important key figures predictably in any format. Even the preparation of print-ready materials can often be prepared automatically. An employee can then concentrate on verifying the result and enriching it with creative elements.

What are the advantages of ADP?

The above example already shows some of the benefits of ADP. The reduction of manual steps, especially in the case of often repetitive tasks, reduces the number of working hours required and thus allows employees to concentrate on tasks that promote business.

Efficient employee deployment through automation

Looking at the public sector as another example, it very quickly becomes clear that previous processes need to be fundamentally rethought. Employees are already under high pressure to provide services to citizens in a timely and legally compliant manner. By 2030, the number of available employees will decrease by 20% [Source: Skills shortage in the public sector]. This can only be countered by extensive automation. Instead of manual data processing, the remaining employees can then concentrate on the citizen. They can provide personal assistance, make on-site visits, make decisions based on pre-processed information, and much more.

In the long run, the reduced workload from reduced manual tasks is a boost to employee satisfaction within the organization. Thus, organizations actively prevent official resignations, or more importantly, internal resignations [Source: Dangers of internal dismissal].

Process growing data volumes effectively

Advancing digitization adds a further complication: the sheer number of existing data increasingly prevents processing through manual processes. For example, many website owners want to prepare and analyze data on website visits, user profiles of visitors, or the devices and browsers used. Even medium-sized sites then require a significant number of employees to manually generate daily or even hourly reports. ADP applications are made precisely to process and prepare large amounts of data. At the push of a button, the system creates interactive charts and tables in real time. These help website owners make strategic business decisions to expand their offerings. Potential costs for ADP software are amortized in a very short time due to the reduced manual workload.

Ensure data quality

In addition, the results of processing by digital applications are more reliable. If the input data is correct and the system is implemented correctly, the processing steps are also largely predictable. If, on the other hand, a user has to aggregate, categorize or prepare data for many hours every day, fatigue inevitably sets in. These have a negative impact on the quality of the processing results. Information is assigned to the wrong categories, the wrong numbers are added up, or duplicate data is not recognized. These effects are also already apparent during preparation, when data entry is also performed manually (Manual Data Entry instead of Automated Data Entry).

How Automated Data Entry and Automated Data Processing differ

Within ADP, a variety of technologies for processing data are combined. Procedures for upstream data entry belong instead to Automated Data Entry, also Automated Data Entry. These can be the machine analysis of speech, text or images. In the next step, the Automated Data Processing System ensures the meaningful use of the imported data within the IT solution.

Combining both technologies opens up new possibilities for offering innovative services to customers, even in times of shortage of skilled workers, e.g. in the financial sector, public services or retail. The aim is to use the new systems to empower customers to resolve their concerns themselves at any time, at any place, and with little effort. The digital services adapt to the customer, not the other way around. Automated processing allows customer information from any source to be converted into a consistent format. This format helps the systems in the background to process the tasks without human assistance and the customers to deliver the desired result. No one would assume that if you shout "Alexa, play my favorite song" into the room, an employee will go in search of the right CD to play.

Progress through ADP and Artificial Intelligence

AI Technologies (artificial intelligence) enable a further significant advance in the processing of data. The processing system in conjunction with OCR software (optical character recognition) learns to recognize handwriting better or determine the right information from free-form text. Intelligent applications can identify the right categories from images or even initiate appropriate actions. This area of data processing is called Intelligent Data Processing (IDP) and opens up the next evolutionary stage in data processing. It further reinforces the benefits of ADP by further reducing the exceptional cases where human intervention is required. More complex application fields suddenly become relevant for automated processing.

It is only natural that the results of any data processing software can only be as good as the input data quality and the quality of the programmed processing steps. This is true for ADP applications with and without AI, on-site or in the cloud. However, the development to date shows a clear trend. Only automating the processing of the large volumes of digital data will open up meaningful uses and compensate for the negative consequences of the labor shortage. In the future, however, it will still be up to people to decide which data will be of best use to customers and the organization, and which strategic conclusions can be drawn from the results of data processing.


  1. An overview of the historical development of digitization:
  2. Study by PWC on future personnel development in the public sector:
  3. Contribution to the reasons for and economic consequences of internal employee resignation:

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