After a successful pitch for an existing project in media logistics, we were able to use our experts in the fields of data science and data processing for a more detailed analysis of the potentials after the takeover of the inventory processes. In this way, we were not only able to optimize the project process, but also to achieve extreme resource savings and additionally provide more transparency.
"Digitalization has found its way into many processes. Mostly database solutions are used. Nevertheless, merging data is a core problem and the integration of heterogeneous data often holds untapped potential."
At the beginning, the individual process steps had to be evaluated in terms of resource requirements, benefits and optimization effort in order to be able to plan a sequence of action. Requirements that emerged from several customer interviews also had to be included here. Another challenge for us was that various departments and specialist areas were involved in the overall process, each with their own requirements. It was crucial for all parties involved to have a transparent presentation of their own logistics projects on a daily basis at the push of a button. To achieve this goal and to have a scalable solution for the future, a database was set up that allows live access to structured data. A cloud server was used here, on which the individually developed Phyton scripts for the accumulation and provision of the data run, as well as a data warehouse for the administration of the data. The visualization of the data can be implemented with various tools. In this case, Power BI from Microsoft was used.
Our approach has enabled us to reduce waiting times for inquiries to practically zero. The internal contact persons have significantly less service work and thus more time for operational issues. This creates a significantly higher quality and further approaches to process optimization. We have broken down the overall project into individual modules and analyzed these in turn according to their requirements. These include, above all, recurring doings that are indispensable for the smooth running of the project, e.g. creating invoices for different contact persons; generating performance records that are congruent with the invoice; creating delivery schedules or maintaining product master data. The optimization of process steps is highly relevant for transparent project handling. The traceability within the project process, cleanly maintained product data and a resulting lower correction effort facilitate the work of all process participants. Another focus of ours was on optimizing the most time-intensive tasks. This enabled us to identify further points in the process and make them more efficient. In the implemented media logistics process, products in stock today that are not needed can be quickly recorded and further decisions can be made in a timely manner. By connecting supply partners and customers, orders can be generated automatically in the event of minimum stock levels. Delivery bottlenecks are thus avoided and cost-intensive freight transports can be bypassed.
Our conclusion: This project has once again confirmed that iterative implementation in partnership with our contacts and external partners leads more quickly to the goal. As a result, further possibilities for improving the media logistics process have emerged, which we have implemented in a targeted manner in the current project. Thanks to specifically developed data processes and a sophisticated database architecture, we were able to create a future-proof solution. Heterogeneous data and clean structures help to save resources in the long term. They are the basis for the essential tools of Data Science, such as the development of algorithms through machine learning. We are pleased that we were able to develop a sustainable solution for our customer in the field of media logistics and implement it successfully.
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