• about reply
Syskoplan Reply Logo
Menu
  • Customer Expertise
  • Ultimate Technologies
  • Newsroom
  • Contacts
Choose language:
  • about Reply
Syskoplan Reply Logo

Search

Focus On

Best Practice

Using relevant information from large quantities of data in a profitable way

FOCUS ON: Ultimate Technologies,

Data is the new oil. This metaphor clearly shows the value of data, but also highlights the difficulties when it comes to using it.

Data can be very valuable. An example: measured using stock market value, Google has managed to topple top dogs, such as the oil company Exxon Mobile, from their leading positions as the most expensive companies in the world. However, the value of its data only became apparent once it had been tapped into and refined. In order to generally identify the importance of data for a company, we don’t need to think about giants like Google. The range of companies that can benefit is extensive, and includes global IT Groups and retailers as well as regional producers. This can be seen in the manufacturing industry: For example, machine downtime can be optimised using predictive maintenance, and sales volume forecasts can help to keep a hold on over- and under-production. According to the PAC study “Predictive Analytics in Manufacturing Industries”, forecasting delivery dates is one of the most difficult activities in one in three companies. The number of available applications is large, and the analysts from PAC have also come to the conclusion that predictive analyses play a key role when it comes to making companies more efficient and innovative.

The industrialisation of findings

Syskoplan Reply industrialisation of findingsIndependent processes are needed to extract systematic findings from data. First of all, the required data is extracted from a specific use case, which is then merged and analysed together with information from other data sources. The insight gained with this is then integrated into existing business processes, in order to, for example, reduce costs, save time or increase the efficiency of manufacturing processes. On the road towards implementing such a process, companies need to ask questions from various different areas and also outside of the box. Legal aspects, such as which data may be collected and processed and in which form, then play a role. Infrastructural topics, like the choice of platform or tools used, are also obvious aspects, but employee skills or the integration into existing processes are also important.

Identify relationships and structures

Syskoplan Reply relations and structure of dataWhich sensor data is needed in order to predict a machine stoppage? What form and granularity is needed for this data? What’s more, how is it possible to identify whether a machine is “healthy”? Questions like these are usually the starting point for deriving an appropriate model, which is to be utilised for predictive maintenance, for example.

The analysis itself is the step that can be compared with the refining of crude oil. Usable products in the form of findings are derived from the raw material, which is in this case the collected data. The crux of the matter here is being able to identify relationships and structures in the data, which are based on a causal relationship, and thus enable a forecast. For example, you could imagine a vibration sensor, which reports that a mounting is defective in advance. The preferred tools here are statistical and mathematical methods and models, combined with solid programming knowledge.

This combination is both a blessing and a curse for many companies: One the one hand, these tools enable the required level of abstraction, in order to expose the information that is hidden in the enormous quantities of data so that it can be seen with the human eye. On the other hand, this interdisciplinary playing field contains precisely those hurdles that need surmounting, as it is rare that all of these key skills are possessed by just one person.

RELATED CONTENTS

Sap Hybris

Case Study

OMNICHANNEL INTERACTION
AND SELF-CHECKOUT AT POS

How do I motivate my customers to identify themselves at the point of sale, even if they "just look" and inform themselves? Many retailers face this challenge when they try to get one step closer to the Omnichannel vision. Omnichannel often fails because of the link between online and offline shops.

OMNICHANNEL INTERACTION 
AND SELF-CHECKOUT AT POS 0

Reply Voice Commerce

Best Practice

Conversational Commerce Extension for SAP Customer Experience

Customers are looking for new, interactive buying experiences and offers geared to their needs. At the same time they want to make the replenishment process as efficient as possible, especially when it comes to every day products. With Reply Voice Commerce, Syskoplan Reply has developed an extension for SAP Customer Experience that precisely addresses this need for simplification, and with which language can be used as a natural communication medium.

Conversational Commerce Extension for SAP Customer Experience  0
Marketing Automation and Personalization 0

Marketing Engagement

Best Practice

Marketing Automation and Personalization

Forward-looking marketing is characterized by complexity, creativity, technology and analysis: customers research and purchase in their own time and at their own speed. They want further information when they required it, and this to the currently relevant topic.

Reply ©​​ 2023​ - Company Information -
 PrivacyCookie Settings​
  • About Reply​​
  • Inves​tors​​
  • Newsroom
  • Follow us on
  • ​
​
  • Privacy & Cookies Policy
  • Information (Client)
  • Information (Supplier)
​ Reply Enterprise Social Network​