Challenge

A German medical technology provider has very complex sales processes, as a number of stakeholders such as health insurance companies, patients, doctors, nursing services, etc. are involved in a single order, and completely different factors come into play depending on the situation. The processes are hardly monitored and controlled. Both internal and external factors (organizational/regulatory) make it almost impossible to define homogeneous processes.

Solution

Based on the data analytics tool Qlik, a process mining solution was developed that prepares the purchase-to-pay process of various business units based on different data sources (mainly SAP) and processes it as event data with the customer- and business unit-specific business logics.

Added value

Highlights

Challenge

An international manufacturer of medical equipment wants to automate its reporting to external suppliers with supplier ratings and an overview of the status and urgency of orders. In addition, projects and assemblies are to be prioritized so that the associated subassemblies and individual parts are also prioritized. This is to be done across departments from project management to procurement and production to external production.

Solution

For the cross-departmental solution, all relevant data from the different areas and their prioritizations were combined. In addition, a specially developed user interface has been created that provides overviews for the various departments.

Added value

Highlights

Challenge

The planning and analysis of nationwide inventories and capacities of a leading German automotive manufacturer are very complex. Nevertheless, these processes are important for the profitability of the company. In addition, a planning of upcoming scrapping quantities in combination with a stock requirement planning is to be created.

Solution

A data analytics solution was implemented in combination with our planning extension Write!, including master data management and a release process for plans. This was also integrated into the analyses.

Added value

Highlights

Challenge

A machine manufacturer for drive systems needs transparency towards its customers regarding major projects.

Solution

By linking the project data to production and procurement data from SAP, the data could be clearly prepared.

Added value

Highlights

Challenge

One of Germany's largest engineering companies and automotive suppliers requires an analysis of more than 180 petabytes of sensor data from autonomous driving vehicles (including ABS, radar, camera systems, vibration, GPS signals).

Solution

A Qlik Sense cluster system was used to efficiently analyze the large volumes of data, using a Cloudera system with HBase / Impala.

Added value

Challenge

A European payment service provider has over 1 billion records per year and wants to improve its existing fraud detection. Current PSD-2 rules require enhanced reporting for all industry participants in a high security environment.

Solution

Fraud reporting based on data from the RiskShield fraud detection software was developed. This enables the creation of ad-hoc reports for clients and their customers for PSD2.

Added value

Highlights

Challenge

A globally operating company in the eye diagnostic sector needs a connection of different systems (PPS, BDE, customer service, quality management, personnel, production control) to merge the data from the different systems with the different databases or interfaces.

Solution

The data from the different systems was transformed, cleaned and merged.

Added value

Highlights

Challenge

One of the world's largest banks needs an efficient data analytics platform integrated into its online banking portal to optimize the analysis of stock portfolios and currency rates.

Solution

The data analytics software Qlik Sense was implemented in the online banking portal. For a seamless integration of Qlik Sense, a mashup of Qlik Sense (HTML/CSS and APIs from Qlik) was created via web technology and completely adapted to the bank's corporate design.

Added value

Highlights

Challenge

One of the top food retailers would like to know which goods are sold at which time and on which day by means of a shopping cart analysis. This is not possible through the offline POS systems. Accordingly, the tracking and analysis of the inventory can only be traced based on the stocks and the reorder - but without precise time information.

Solution

Together with the operator of the checkout systems, a solution was developed that now makes it possible to track exactly which goods were purchased when and how much - now also in the stationary stores.

Added value

Highlights

Challenge

Replacement of the SAP CO-PA-based analysis process and introduction of a BI solution that processes data automatically, visualizes it in a comprehensible manner and can be used in a self-service process.

Highlights