Digital
Transformation

General description
The production processes and value chains in modern companies are known to be multi-layered and very complex. Various IT systems are used (e.g. ERP, CRM, SCM, MDM) and many automated and manual business processes are carried out simultaniously. Sooner or later, errors occur in the execution of these work processes and they can lead to loss of revenue. An automated error-cause analysis and quality monitoring, which gets to the bottom of these complex issues, alleviates the decline in sales.
In this context the following questions can arise for a company leadership team:

• Why were certain products not sold as planned?
• Where are the disturbances or errors in the production process? How can we rectify them?

Solution overview
Our data-based automated "quality monitoring" solution is a targeted response to the increasing complexity of processes. It delivers reliable and fact-based results and provides the appropriate answers to the above questions as well as many more.
We collect the data ("digital trails") from various IT systems, link them and show exactly where the anomalies are to be found. In doing so, we discover outliers, trends and systematic errors. In addition, we show the relevance of problems and the effect on sales. We use modern Big Data & Cloud technologies and can therefore process and analyse any amount of data.

Your benefits
The use of our quality monitoring solution leads to a considerable yield assurance and increase as well as comprehensive data set- and process improvements. We always have the quality of your processes in mind. Understanding, maintaining and improving, that’s the ADEAL way!

General description
Nowadays, many companies intend to provide a variety of products while remaining competitive. The markets are volatile and changes occur quickly: e.g. contingents are used up, competitors make better offers or suppliers raise prices. Companies are very often no longer able to manually monitor and control market prices, internal production chains and product quantities. In the long run, a mature automated approach is essential.
In this context the following questions can arise for a company leadership team:

• Which price ranges increase the sale of my products?
• How can I optimise my stock levels and thus avoid bottlenecks in the delivery of goods?

Solution overview
With an automated dynamic pricing our "Revenue Management" solution offers a targeted response to these challenges. "Markups" as well as purchasing and marketing recommendations will be generated and presented to the decision makers or automatically implemented.
We collect the data in pursuing the following focal points: Market demand and prices, product supply and margins, search queries and bookings, external inventory, policies and strategic goals of the company. Based on historical data, we make predictions regarding market behavior (e.g. "demand forecasting"). The data collection and forecasts are then used to calculate intelligent recommendations on prices, stock/contingents, marketing campaigns and procurement. Finally, the recommendations are evaluated and implemented by the decision makers.

Your benefits
As a result, the use of our revenue management solution leads to a significant increase in sales, improved workflows and greater transparency of business objectives at all levels of the company. We always keep an eye on the market and the products. Understanding, predicting and recommending, that's the work of ADEAL!

General description
In modern industrial companies Inventory and Asset Management are usually multi-layered and complex. Power plants, water, oil and gas facilities, but transportation vehicles (cars, airplanes and trains) are equipped with many components and subsystems whose run simultaneously and also communicate smoothly with each other. A failure of even the smallest parts can cause damage in millions and, in extreme cases, even pose a danger to passengers. A major focus of affected companies is therefore automated monitoring, real-time analysis of errors and proactive maintenance of machines and equipment.
Production processes and supply chains are multi-layered and at the same time demanding, their operating facilities can correspondingly be prone to errors. More and more work steps are being automated and carried out by robotics and programmable control devices. In this automated environment, the price of an issue is essential, as it can cause damage to several products simultaneously. Therefore, monitoring and quality analysis of production processes are dominating key to success.

Solution overview
Due to the rapid development of Industry 4.0 in the manufacturing industry, it is now possible to quickly and inexpensively install sensors in production facilities and link them to the IoT (Internet of Things) network. The sensor data is collected and evaluated. This forms the basis for the described monitoring and analysis of production processes.
Our "Operational Analytics" solution is based on a proven reference cloud architecture and a combination of data streaming, stream processing, real-time monitoring, visualization and self-service analysis technologies. In production operations, our approach allows horizontal scaling, uses the elasticity in the cloud and is dynamically billed based on resource consumption.

Your benefits
As a result, our solution delivers real-time visualization, KPI reporting and AI capabilities as services to end users. It is scalable and can significantly increase productivity and process quality in the manufacturing industry. We make Cloud IoT accessible to users and always keep an eye on your assets and processes. We connect you with the future!

General description
Modern companies try to acquire new customers and to maintain existing ones by providing better products and services at the right moment for the best price. Especially in the digital age better customer communication and personalization through digital channels becomes crucial. It is a commonly known fact that personalization significantly reduces acquisition costs and increases the efficiency of marketing. Thus, the companies struggle for providing personalized customer experience throughout the whole customer journey.
Today, the quality of marketing and sales processes increases and the new technologies from the area of data analytics facilitate this development significantly. Enterprises extend their existing systems through analytical CRM and start dealing with predictive personalization, personal recommendations and highly effective digital marketing campaigns.
However, customer experience management is a complex data-driven analytical process. Building up a structured automated and intelligent customer monitoring, segmentation and targeting continues to be a big challenge. Exactly in this context, we provide our “Customer Segmentation” self-service analytical solution, which embraces all the essential analytical approaches and steps for effectively managing the customer journeys in the company.

Solution overview
The solution is based on structured customer lifecycle management, continuous client state and transition monitoring as well as intelligent targeting recommendations. Our main focus lies on business indicators like customer cohort, sleeping/active client, churn/retention rate, loyalty level and favourite product category. To achieve that, we operate with typical KPIs like average order value, purchase rate and pace, CLV, ABC and RFM. Such essential tasks as 3600 customer profile creation, multivariate customer segmentation, continuous KPIs monitoring, response and churn rates estimation as well as best personal offer recommendations are automatically executed within our solution.
The input data requirements are straightforward. The transactional data (derived from ERP) and customer profile data (derived from CRM) are sufficient. The whole solution is easily extendable through machine learning and data mining components for better client scoring, microsegmentation, uplift modeling, response prediction, cross and up-selling recommendations.

Your benefits
As a result the company gets a structured customer base, lifecycle transition rates, up-to-date customer segmentation, automatic detection of customer churn and retention. Since the solution is based on continuous monitoring of business KPIs, it avoids biased conclusions and provides comprehensible recommendations. These include recommendations for marketing campaigns, personal targeting and price markups; moreover automated campaign management and evaluation is continuously executed. Therefore, the use of our solution leads to a significant increase in sales and customer loyalty, reduction of customer churn and better positioning of the brand. Use the ADEAL approach and care for your customers better!

General description
Both, plant control and operation in modern industrial companies are usually very complex. Many work steps are automated and performed by robots. In this automated environment, the price of an error is very high, as it can lead to damage to several products at the same time and expensive production interruptions. Incalculable reactive maintenance of their equipment can be difficult for companies to afford. Maintenance intervals are cost-intensive, but without maintenance the probability of failure increases significantly. However, machine parts with high wear and tear can be detected and quickly replaced or repaired.
In this context, modern companies demand not only real-time monitoring and analysis of problems, but also a direct answer to the question "When and where will the next undesirable event or irregularity occur and how can we remedy it?" It's all about nothing less than future-proof predictive operation of machines and systems while reducing downtime and maintenance costs.

Solution overview
Compared to Operational Analytics, which deals with monitoring and alerting, Predictive Maintenance analyzes historical data with the aim of making forecasts of critical operational events. Thus, our "Predictive Maintenance" solution is an intelligent, future-oriented extension to "Operational Analytics".
Using modern data mining and machine learning methods, the data is prepared, correlated and classified. Predictive models are trained and validated. The tested and validated models are then published accordingly as cloud services and made available to end users and IT systems. At the end of this chain, each company receives a model-based forecast of errors and failures, predictions of useful life and operating and maintenance times. In addition, concrete advice is given on the most critical wear parts.
We regard our Predictive Maintenance solution as an integral part of the production cycle of companies. It monitors material conditions and makes recommendations for maintenance and repair work on industrial plants and their components.

Your benefits
Our solution significantly increases the efficiency of production processes in companies. Downtimes and production stops are minimized and the availability of production facilities is maximized. This increases the quality of work and saves maintenance costs. We make your plants smarter and more durable, ready for the future!