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Clean Data for a Smooth Supply Chain

Reading Time: 5 Minutes 13.09.2022 Currents & Trends

How companies strengthen their resilience and resistance

If you want to improve your resilience, you need to master the most important basics of your working routine. Besides transparency across all areas and efficient business processes, this also includes smooth processes along the supply chain. Incomplete or incorrect data, duplicates or even missing information quickly become big obstacles that take companies a lot of time to overcome. In order for processes to be free of errors and efficient, and sometimes also to be based on AI, they need the right basis: high-quality data.

Used in an intelligent way, digitalization can ensure smooth processes along the supply chain. You should keep an eye on the quality and quantity of your master data and transaction data, though. After all, they have an effect on the way processes work, including AI-based ones. To optimize the quality of your data and to prepare it for the use with AI processes in your ERP system, you should observe the following steps.

  1. Identify processes that are critical to your success
  2. Define quality standards
  3. Check existing data pools
  4. Remove duplicates
  5. Create unambiguous data
  6. Update and check your data continuously

Only then will you be able to improve information quality on the long term and create a single point of truth where every piece of information is contained only once and accessible anytime. This requires you to have regular automated quality checks, plausibility checks, workflows, data cleansing, and defined rules for newly entered data. To this end, proALPHA provides you with an extensive check list and further information.


Data management on the basis of all relevant information

Once the data have been cleaned, you should move on to intelligent data management to get the most out of your ERP system. The proALPHA ERP+ system and its AI-based advanced analytics solution NEMO form an innovation platform that deeply integrates all solutions of the proALPHA Group. For instance, a modular software solution for performance management offered by Corporate Planning, can be used to import the information necessary for accurate planning on the basis of simulations or variance analyses from the upstream ERP system.

APIs provide all relevant information and assemble it in a structure suitable for simulations, planning and analyses. As value changes in the connected systems are automatically taken into account, up-to-date information is ensured at all times.

Optimize maintenance and repair with AI-based service information

The ERP system serves as a digital AI-aided process and data hub where all information is collected. The profitable use of AI requires all production data to be recorded in real time, all deviations from the schedule to be determined and all data to be visualized as the result. Transparency and information are essential to the smooth interplay of technology and people in the company.

Prof. Marco Huber, Fraunhofer IPA and Stuttgart University, says: "How much the acceptance of AI depends on its transparency and explainability can be easily seen on the example of predictive plant maintenance: if such an AI system gives an alert, the users should be able to understand why there was an alarm. This can also be applied to other AI services.".

The merger with Empolis allows proALPHA to put this theory to practice and enables people working on the service team to exploit the required know-how quickly and easily in the specific contexts. With the Empolis Service Express solution integrated into the proALPHA ERP+ system, you can access important service information around the clock. AI-based and learning, the system uses decision trees to develop the best solutions, thereby speeding up processes in repair and maintenance work.

Recurring routine tasks ‒ a job for RPA

Robotic process automation, or short RPA, can be used to process tasks on the basis of a defined workflow and is extremely useful when it comes to processing the information from service calls. These processes imitate human users who run an application and initiate digital processes. This ultimately reduces the employees' workload regarding routine tasks and almost eliminates the risk of errors in data processing while at the same time drastically cutting the costs.

In general, RPA can be used for all structured processes that follow clear instructions and recurring rules. Typical tasks include:

  • Moving and transferring files and folders
  • Copying, pasting and comparing data
  • Filling out forms
  • Extracting structured and semi-structured data from documents

In an increasing number of companies, the order process has become a standardized procedure that is improved by RPA to make it more efficient and cost-effective. During this process, the RPA system retrieves information about the purchase order from the ERP system and compares it to the data entered in the stock receipt. If these checks are positive, the RPA system releases the invoice for payment in the ERP system. The bot automatically completes all related tasks such as sending the order confirmation, printing the shipping document and issuing the invoice to the delight of the employees who used to have to do all this manually.

RPA differs from other automation technologies because it doesn't need an intricately programmed application interface nor modifications to existing systems or the corporate IT infrastructure. The scalable software is closely connected to the ERP system, is usually hosted on virtual machines and available around the clock. The implementation of RPA is particularly beneficial for areas with a high number of recurring processes.

In order for RPA systems to be able to also handle highly complex processes in the future, cognitive software robots are currently being developed and will be capable of continuous improvement thanks to AI. This opens up whole new fields of applications that are still unthinkable today.