Application Prototypes

Practical applicability and knowledge transfer between research and actual software development greatly enhances the value of a research project. This page shows videos of prototypical applications, which we have realized on top of the in-memory data management technology.

Demand Planning on iPad

The flexible analysis of demand planning data is vital for globally acting companies. Our mobile, on-device iPad prototype combines location-based geo data with real customer planning data in an in-memory database. Further, influencing factors such as the temperature, the air pressure, or the level of cloudiness can be overlaid to incorporate them in planning decisions at the speed of thought. Users can intuitively interact with this live data set by zooming in, filter by certain products or customers, browse through time spans, or select different key figures to plan with. This application has the potential to realize manifold scenarios. For example, it is also possible to integrate real-time business web data from other customers or suppliers and enable business operations across company borders at the speed of thought.

This view shows the sales locations in Europe aggregated per country and combined with external weather data.	Users can easily get more detailed information by zooming in on the map. This view shows the actual deliveries in Amsterdam comparing two time periods.
The data can be filtered by the customers’ and product’s hierarchy.	The visualized data per location can either compare two different time frames with the same measure or two different measures (such as planned and actual sales) on the same time frame.

Reschedulable Availability-to-Promise on iPad

As part of our project, Leveraging In-Memory Database Technology for Planning Processes an iPad Demo was created that shows how the ATP check and rescheduling activities can be performed on a smart mobile device. Our ATP check calculates the availability of a product instantly. If there are any conflicts they can be resolved immediately by rescheduling. Our iPad application provides all information necessary to identify product shortages that influence orders of different customers and to resolve them.

The goal of this bachelor project was the identification of new concepts and algorithms for planning processes in the context of supply chain management. The project considered the fundamental paradigm shift that the data needed for a planning process can be entirely kept in memory. In addition, the execution of planning algorithms can be distributed onto several blades and CPU-cores.

Dunning on iPad

With the new in-memory data management for enterprise applications, it is now possible to create lightweight applications that combine simplicity and speed. To show this, we developed an iPad application with one-click access to up-to-date information about your top debtors. In the back-end, we use a real SAP Business ByDesign system that exposes a web service.

Another project using SAP Business Suite showed that we are able to reduce the time to conduct this process from about 20 minutes to less than 1.5 seconds.

iPad Analytics, Production & Financial Planning

In this demo, Hasso Plattner took on the role of a CEO of a footwear and apparel company. He identifies that the sales target for June will not be met. With the iPad application running with a SAP Business ByDesign back-end, he can look at the sales numbers, invoiced orders, open sales orders and opportunities with the target numbers all in one report and real-time, no latency. A root cause analysis concludes that an important order delivery date is confirmed too late. Thus, Hasso Plattner calls his production manager to solve this issue. Furthermore, the controller is called to verify that the target can be met and, in addition, the budgets and targets can be updated in realtime. The navigation in the system is eased using Cestbon, a tool to explore the relationships of transactional business objects developed by our research group.

Interactive Sales Analysis on iPad

Nowadays, executives are limited by reports that have been pre-designed. With this iPad application developed by our research group, we present how easy it is to bring reports to executives. This is inspired by Hasso Plattner's idea showing how a sales analysis could look like by drawing a sketch on a napkin.

Following this, a HPI student was commissioned to develop a sales analysis report. After only two weeks of work, this is what he came back with. A complete custom-built report that uses anonymized data from a real customer. It demonstrates speed & simplicity while browsing high-volume (historical) sales data grouped by region, including drill-down into different locations, comparison with target figures, and rolling periods.

High Performance Discovery Service and Information Services for the EPCglobal Network

RFID-enabled supply chains produce enormous data volumes and network traffic. Many information system implementations for processing RFID-related data fall short regarding performance aspects. In this project, we leverage SAP's new in-memory computing engine (HANA) to design an EPC Discovery Service and an EPC Information Service Repository, focusing primarily on performance aspects. Using the in-memory technology, we are not only able to improve pure transactional performance, but we are also able to implement instant analytics on the stored data. Information sets, comprising of more than a billion records can be searched and aggregated within seconds, providing clients with completely new opportunities regarding the interaction with RFID-related data.

Parallel to the performance focus, the project implements and evaluates a Discovery Service aggregation algorithm. This new algorithm efficiently resolves containment relations between objects, reducing network traffic and processing time for Discovery Service queries.

EPCglobal Secure Tracking Demo

The mobile iPad app can be used to gather detailed information for any individual item equipped with an EPC. It summarizes all events that characterize the product's path through the supply chain. The app can be used in the following two operation modes (by the toggle button in the scanning screen):

• Toggle button deactivated: The application communicates directly with the EPCIS repository via unsecured communication channels. In this mode, exchanged event data can be manipulated, exchanged, or faked without the knowledge of the requester. As a result, counterfeited products are hidden by manipulating the virtual product path.
• Toggle button activated: The application uses the developed security extensions. All data is transparently encrypted by the Access Control Client (ACC) when exchanged between requester and EPCIS repository. In addition, the Access Control Server (ACS) logs the entire inquirer history. When taking an access decision, the history is analyzed and user-specific access rights are derived. Before reading events are exposed to the user of the app, the result are filtered accordingly. Due to the very late access control, it is possible to revoke access rights even after data has been sent to the client site.

The prototype verifies that enabling the security extensions does not significantly affect the processing speed of event data. As a result, the viability aspect of the innovation is demonstrated.

Querying EPCIS directly without Security Extensions

The product's EPC can either be scanned using the integrated iPad camera or entered manually. Then the query is sent via wireless LAN to the EPCIS of the manufacturer.

Traditionally, any user can query all relevant event data from the EPCIS of the manufacturer. In other words, the result set is not filtered in any way.

Activated Real-time Security Extensions

Real-time security extensions are enabled in the prototype by toggling the security button. Instead of sending the query directly to the EPCIS, it is now send to the local ACC of the inquirer. The ACC transparently handles encryption and filtering of exchanged event data.

When having security extensions enabled, the result set is filtered accordingly to the user's querying behavior by analyzing his query history in real-time. Particular information regarding the movements of the queried item is no longer displayed in detail, e.g. to prevent expose of company-internal business steps for the current user.