With our business intelligence solution Picavi Cockpit, users take advantage of the process data generated during order picking. Important potentials to optimize logistic processes can be derived directly from the system using the smart data function – Analytics. Our advantage: all important KPIs are available on individual dashboards. Read this blog post to find out what this can look like in practice.
The Analytics feature within the Picavi Cockpit enables a detailed analysis of all pick-by-vision process steps. Among other things, setup times, run times for picking, route and pick times can be recorded. The number of handling units, picks or data on quantity corrections and shortages can also be collected. The data is collected via sensors in the pick-by-vision smart glasses. This makes it possible to collect data at the level of the smallest process steps in the warehouse and, based on this, to carry out a well-founded optimization of warehouse processes.
With the Analytics feature, companies can visualize and evaluate the collected data in a simple process. The visualizations can be configured customer-specifically. Users can derive individual adjustments in the warehouse from the visualizations, as the following examples show:
The tool sets time stamps between the individual steps of a picking run. In this way, the analytics feature shows, among other things, picking, setup, and travel times. Conspicuously long walking or picking times can be identified and reduced. A common example is that items are difficult for the worker to access. This can be easily optimized by adjusting the warehouse infrastructure or the arrangement of the items.
Last Pick Location
The Last Pick Location function creates a live map of the warehouse for the control center, on which the smart glasses are visualized with their location at the last pick saved. This facilitates cooperation between the control station and the warehouse staff – especially when personal contact between the two parties becomes necessary in the event of challenges arising at short notice.
The Analytics feature within the Picavi Cockpit makes it possible to create an ABC analysis based on process data, with which different levels in the warehouse can be viewed individually. For this purpose, each scan is linked to a product and a storage location. The result is a heat map that visualizes which areas in the warehouse are particularly frequented. This also allows ergonomic aspects to be taken into account when allocating items to storage locations. Fast-moving items, for example, are placed in shelves at eye level.
Numerous advantages for logistics
The analytics feature within the Picavi Cockpit allows companies to easily visualize and evaluate the data that is already generated in the logistics process. In this way, action decisions and optimizations can be underpinned on the basis of a valid database. The tool can access additional information that systems that only work on the basis of order data do not even record. In contrast to a warehouse management or ERP system, it can be used, for example, to analyze whether products are regularly located in an unergonomic bending zone for the picker or far up on the shelf. In addition, the analytics function enables historical data storage, which makes monthly as well as annual evaluations from the past visible. The concrete added value for users is versatile: