According to Plowmann, the task of logistics is to ensure the availability of the right goods, in the right quantity, in the right condition, at the right place, at the right time, for the right customer and at the right cost. The planning tasks become complex because each individual process (delivery times, handling times, etc.) in the global supply chains is again associated with its own uncertainties: an important delivery arrives later than expected, in the next month only 100 (or 1,000) items could be sold instead of the 500 announced, etc.). And the next delivery may not arrive next week, as announced, but in five weeks. These uncertainties need to be understood in the best possible way: The better the future can be predicted, the more efficiently the logistics can be planned.
Get the support of logarithmo today: With the help of interdisciplinary teams of mathematicians, statisticians and computer scientists as well as domain experts from the fields of logistics and supply chain management, we solve your individual planning problem: For example, you are an online retailer and would like to benchmark different forecasting procedures based on your sales history to improve the status quo? For this we can offer you a complete web application. You would also like to take individual special features into account? With the help of our standardized toolboxes, in which the majority of logistical planning problems have already been modelled, we can create your individual solution within a few days. The result is a web application that you can use easily and intuitively via your browser - we take care of the mathematics behind it.
Better forecasts give you a head start
Better forecasts increase the ability to plan your processes and give you a competitive advantage.
Get early information about process deviations by monitoring relevant influencing variables.
Checking future scenarios
Vary your assumptions and planning hypotheses to review future developments.
Use-case - online retailer
An online retailer finds that on average far more capital is tied up in his warehouse than he expects. He loads his sales history into a logarithmo web application and discovers that his product range consists of far more seasonal articles than expected. Improved forecasts can save an average of 15% of storage costs for these items. In order to further optimize his processes, he discusses with logarithmo further applications that best support him in his situation.
Review your strategic sales planning assumptions by regularly benchmarking planning results against historical forecasting methods. logarithmo uses a forecast toolbox to calculate the article-specific forecasts that are suitable for you based on the information available.
Improvements for future production program planning can be derived from past production data.
Procurement and production planning
Which machines formed the bottleneck in the past? What measures can be derived to improve the current situation? We are happy to support you in answering these and similar questions.
You derive the material requirements for future production on the basis of sales planning and BOMs. We support you, for example, in analyzing which articles (for what reason) have most frequently failed in the past.
Which distribution structure is suitable for your products and customer requirements? Where is there still potential in the existing structures?
Which additional functionalities (e.g. live tracking, limitation of delivery windows to one hour) can you already offer your customers based on the current processes?
By benchmarking various forecasting methods, we can provide you with well-founded suggestions for your current situation.