Planning data and scenarios

Big Data & Flexible Data Management

Product master data, movement data, sales orders, stocks - the information density of business data in logistics is huge compared to other divisions. This results in enormous amounts of data. The order items of one year alone often reach two to three-digit million lines in medium corporations. The structured analysis of big data and flexible management of this mass data are therefore the key to optimizing processes and structures in an agile manner, recognizing long-term trends and weighing up alternatives.

Whether data for planning tasks are first prepared in Excel and uploaded as .csv files or the data of the ERP, TM or WMS system should be made available automatically each day – W2MO offers a variety of configurable interfaces for each use case.

W2MO always offers a direct .csv template for data upload of product data, orders, transporters, bin status reports and bills of materials. The following example of order headers and positions shows how easily and comfortably the data preparation and upload can be managed by W2MO.

For the operational use, W2MO offers configurable standard interfaces for standardized data import and export with one click or automatically. For example, data from SAP EWM can be imported as a direct copy into the W2MO model and can then be transferred to the model configuration by filters and logic rules. In this way, both data collection and data processing can be directly controlled and validated. An overview report with the results of the data collection will be created and sent per mail automatically each time the connector is importing data. Consequently, the model is being constantly updated with the latest data.

Extrapolation and Data Adaptation

Planning and optimization of warehouses and logistics networks always serves the purpose of testing growing structures and mastering future challenges.

In addition, the available data basis does not usually correspond to the desired state for logistics and supply chain projects in terms of scope, level of detail and quality.

However, these data gaps can be easily generated and integrated based on planned figures and assumptions with W2MO. This creates a solid data basis for future planning and growth scenarios. Forecasted developments of business figures and order data provide an essential support for planning, simulation and optimization. With help of the extrapolation functionalities of W2MO, this data can be generated and manipulated in a detailed and structured manner. The expected database is created on a comparable historic time period with growth planning figures, expert knowledge and qualified assumptions.

However, forecasting is generally a complex task. In addition, a purely quantity-based extrapolation is not sufficient for most considerations. Changes in the range of articles and order structures can have much more serious impacts in today's supply chains than changes in quantity. In order to cope with the diverse changes in the supply chain we developed sophisticated statistical methods and implemented them in W2MO to provide the extrapolation of amounts, articles and structures.

Based on structural parameters, changes of amounts, number of articles and order structures can be calculated. These generated future scenarios can be taken as a basis for the long-term and sustainable optimization of supply chain and warehouse logistics. Through the detailed extrapolation, the entire dynamic of the distribution process is extrapolated as well, including the effects on e.g., inventory.

The extrapolation approach generates new articles, orders and orderlines based on existing data. This enables the comparison of logistics services based on the latest data.

Data Generation, Verification & Validation

Data of sufficient quality and quantity are not always available. With W2MO you can quickly adapt your database to your project and close gaps by automatic generation based on templates and structures. Simple statistical parameters are sufficient to generate orders and products exactly.

Master data quality and data validation become continuously more important due to the growing amount of available data. Being integrated into W2MO, data can be easily checked for consistency, adjusted and corrected using table references, filters and mass updates directly in the database.

All data and results of the models and simulations can be easily downloaded in the .csv format for further processing. Using the database connector, it is also possible to directly return the optimization results back to the WMS or ERP system and thus benefit continuously and operationally from the powerful algorithms.

The automatic verification and correction functionalities in W2MO allow an automated validation of the simulation data. Model errors, data gaps and contradictions are thus avoided or directly corrected.

Scenario Comparison

Growth scenarios, market entries, segmentation, and developments in the product portfolio – with the extrapolation functionalities you always create a realistic and structurally accurate data basis for your scenarios. The simulation in W2MO then enables you to evaluate planning scenarios on the basis of real costs and capacity requirements.

Layout scenarios, various storage techniques, picking strategies and even product assignment strategies can be generated quickly and easily. The evaluation of the scenarios on the basis of the simulation allows dynamic comparisons of the resulting logistics parameters and performance indicators.

Each order is individually channelled through its own processes and their linking logic, processed and then evaluated. This approach shows synergies, combinatorial effects, bottlenecks and peaks and thus real potentials. This could not be adequately evaluated by a pure average analysis without simulation which would lead to wrong safety levels.