Automatic capture of performance record for transparent & accurate working time processing
The year is 2021, and if the capturing of performance records takes place on paper and the subsequent processing in Excel, then that is hardly 2021-worthy. And yet in many places, digitization or not, this is still exactly how things are done. Particularly in industries where craftsmen are on construction sites, cleaners in facility management, or nursing staff in care, performance recording is often a task that is performed several times a day, once a week, and once a month, and thus involves considerable effort. In order to minimize administrative costs, at least in the processing of performance records, something other than tedious manual work processes is needed.
In order to be able to invoice the customer or show the employer the work performed, these services must be documented. Logically, nothing works without this documentation. So far, so good. Efficient processing of proof of performance is therefore indispensable. How else can a decent workflow take place? How else is the customer to be invoiced in due course for the services rendered? In this article, you will learn how these pain points can be solved intelligently with the use of AI-based OCR (Optical Character Recognition).
One of the big problems is the lack of transparency, which is bad for everyone involved
Performance records and the specific data
As an essential supplement to the contract and as certification that the previously agreed services have been performed, the performance record with the recording of working hours takes up an important part of the entire work process. Specific data must be extracted from the performance records, which in turn are then used for the next processes, such as invoicing. The data to be extracted includes the following:
- Date and start/end of work (with a scan of the barcode, as appropriate)
- Services/activities performed
- Possible travel times
- Any extra pay (e.g., overtime, night and weekend work, etc.)
If performance records are in paper form, then chaos is not only pre-programmed but also a practical fact quickly
Tackling paper-based proof of performance with intelligent, AI-based OCR
As mentioned at the beginning, even with the possibilities of digitization, many companies are still lagging behind. Part of this certainly has to do with the industry itself. In construction, not only is the interaction harsher than in many places but also the capturing of performance records is often the responsibility of the foreman for his entire team. Finally, the performance records received in the office department have to be checked carefully and without exception for completeness and signatures, which is a massive effort. However, the problem associated with manual processing is not only a headache for companies in the construction industry, but is also not unknown in other sectors, often where many part-time employees are on the road. To ensure that all factors, regardless of the industry or whether part- or full-time, do not play a role, competent and capable (and automated) solutions are needed. That competence and capability come in the form of intelligent, AI-based OCR (Optical Character Recognition). It cares precious little about a wide variety of circumstances. All that matters to intelligent, AI-based OCR is the accurate and rapid identification, extraction, and transparent processing of all relevant data from proofs of performance.
Increasing transparency and minimizing administrative effort – not a dream, but a reality with intelligent, AI-based OCR
The automated data extraction from the performance records
The intelligent, AI-based OCR takes care of the processes around the performance records in an automated manner and as follows:
- The proofs of performance are filled out and received in the office, where they are automatically recognized
- Quality improvement and, if necessary, page separation follow
- The statements of work are classified and checked for completeness (fully automated)
- All relevant data from the performance records are automatically extracted and output as structured data that can be directly processed by systems
- Based on the structured data, the next process steps are initiated automatically
Thanks to intelligent, AI-based OCR, added value can be achieved at various levels – not just in the actual processing of the proof of performance
Added value with intelligent, AI-based OCR
The extracted data from the performance records can of course not only be used for the actual processing and invoicing but additionally, for example, for the entire payroll processing and coupled with future planning. Other significant benefits with intelligent, AI-based OCR include:
- Transparent and accurate processing of services rendered: Trust is good, control is better – a plus for all involved
- In case of queries from the customer: With the automatically extracted data from the proof of performance, simple and quick verification is possible
- Faster recording: Invoices can be issued in a timely manner
- Conclusions on project profitability: Data can be used to evaluate work/projects
- Easy scalability: from a few to several hundreds (and thousands) of activity reports per day.
The numerous added values in intelligent proof-of-work processing, simple integration, and rapid ROI make intelligent AI-based OCR a “winner takes it all” rather than a “winner gives it all” for businesses.