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How to increase data quality for a competitive edge in procurement
Any company can increase its data quality in purchasing through the automation of document processing. AI and Big Data are undoubtedly game-changers for establishing new digitised business models. Although good data quality is crucial for successful operational processes, purchasing departments struggle with poor data quality. The Netfira Platform can solve this problem by automating the manual processes where data originates.
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What is data quality?
Data quality is the key to the digitisation of processes and workflows in companies. In this context, data quality is the evaluation of data stocks concerning their suitability for fulfilling a specific purpose. The criteria to evaluate data quality include: correctness, relevance, reliability and its suitability for various systems.
The role of data quality in purchasing
Good data quality is crucial for successful operational processes. The increase in productivity of purchasing teams thanks to good data quality has become a decisive competitive factor. Moreover, clean data helps to make informed decisions and increases the accuracy of forecasting.
Reasons for poor data quality
Too often procurement teams are held back by poor data quality. In many cases, suppliers identify product data quality as an unnecessary cost factor and afford it a low priority. On the other hand, the manual input and comparison of data in operational procurement leads to slow and error-prone processes.
Obstacles to benefitting from Big Data
Procurement departments collect vast amounts of data every day. However, having Big Data at their disposal does not necessarily mean that they are able to use it profitably. Benefits of Big Data include gaining deep insights and a basis for decision-making and process automation. That is why it is necessary to start where data originates.
The Netfira Platform increases data quality in purchasing
The stream of data can be made controllable and usable by replacing the laborious and error-prone manual interface at the data creation process with an automated one. The Netfira Platform can capture, correlate, validate and process the typically unstructured data from suppliers with almost one hundred per cent accuracy and turn it into structured data.The automation of manual document processing with the cloud-hosted Netfira Platform also leads to a cleansing of master data. For purchasing, this means a high level of accuracy, a considerable increase in speed, and thus more time for value-creating activities. These are all prerequisites for purchasing to position itself for the future within the framework of Industry 4.0.
Conclusion
Data quality is a vital competitive factor. The structuring of data is crucial to overcome poor data quality issues in purchasing and benefit from the vast amount of data collected every day. The Netfira Platform remedies the problem of unstructured data as automating document processing goes hand in hand with cleaning data. The automation of operational processes, which leads to drastically reduced manual, time-consuming and error-prone work, has to be a priority. With this, data quality will automatically increase and only then can Big Data be used profitably.
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