Hall: 1, Stand-Nr.: A19 - The consultants and interim managers at logisticconsultant.net have stood for operational excellence in logistics, SCM, purchasing, transportation and shipping for over 25 years. And just as companies, their processes and needs change over time, the consulting and analysis methods adapt to the requirements.
It is still undisputed that performance data, such as data from ERP systems, is an indispensable data source for analyzing and deriving measures in the respective customer projects. New data sources such as GPS real-time data have been added in recent years. This has resulted in new requirements for data processing, which must become more dynamic and flexible due to better availability in terms of quantity and timeliness. Here, an organization in temporal and spatial data series makes sense. Particularly in purchasing, logistics and supply chain management processes, attributes such as location, time, quantity, quality and other details form the basis for any further analysis. This can be done by organizing data in clusters in order to gain a better understanding of the spatial and temporal data and identify patterns. These patterns help to recognize correlations in real time and to derive trends with regard to spatial, quantitative and qualitative aspects.
By interpreting trends correctly, the right decisions can be made more quickly and with greater focus. Forecasts become more accurate, potentials become more visible earlier and processes, e.g. in intralogistics, can be optimized in a more targeted manner. This can result in effective and measurable successes for companies more quickly than before, making the use of logistics consultants and interim managers an even more worthwhile investment.
The solution approach is an AI logistics and SCM strategy that enables the creation of reliable real-time planning data and key figures for live analysis.
It is still undisputed that performance data, such as data from ERP systems, is an indispensable data source for analyzing and deriving measures in the respective customer projects. New data sources such as GPS real-time data have been added in recent years. This has resulted in new requirements for data processing, which must become more dynamic and flexible due to better availability in terms of quantity and timeliness. Here, an organization in temporal and spatial data series makes sense. Particularly in purchasing, logistics and supply chain management processes, attributes such as location, time, quantity, quality and other details form the basis for any further analysis. This can be done by organizing data in clusters in order to gain a better understanding of the spatial and temporal data and identify patterns. These patterns help to recognize correlations in real time and to derive trends with regard to spatial, quantitative and qualitative aspects.
By interpreting trends correctly, the right decisions can be made more quickly and with greater focus. Forecasts become more accurate, potentials become more visible earlier and processes, e.g. in intralogistics, can be optimized in a more targeted manner. This can result in effective and measurable successes for companies more quickly than before, making the use of logistics consultants and interim managers an even more worthwhile investment.
The solution approach is an AI logistics and SCM strategy that enables the creation of reliable real-time planning data and key figures for live analysis.
