Publications, Events, and Changes at mayato

Price Sensitivity Forecasts for a Porcelain Manufacturer
14. Feb 2019

Survey-Based Customer Analytics

Our customer, a heritage-rich porcelain manufacturer, developed a completely new laser engraving method for use on porcelain products after production with the fundamental intension to launch a specific product design in the form of engraved plate sets.

A data collection process using online and offline surveys as well as interviews was designed to identify the market potential and to forecast price sensitivity and expected sales figures using advanced analytics methods.

Read more about the forecasting results and the challenges to overcome in our new case study.

download case study

porcellain manufacturer (image ©siculodoc

#AdvancedAnalytics #PriceSensitivityForecasts #Retail #HoReCa

Digital Transformation in Renewable Energy
20. Nov 2018

A central data management platform for analyzing aggregate sensor data

Collecting, processing and analytically evaluating its own historical data, sensor data and energy data centrally – with this goal in mind, a global energy group planned the development of a digital platform. All facilities for renewable energy were to be monitored and controlled in real time. The use of data science tools to analyze the vast quantity of data should enable predictive maintenance on a large scale.

But the first step was to bridge the gap between business users and IT: the energy group engaged Positive Thinking Company with this qualified change management. Our case study explains which hurdles had to be overcome and how the gap between business users and IT was closed.

Download  case study

Recommender System for an Online Sales Platform
30. Oct 2018

For an online retailer, mayato created a customer and product segmentation using historical sales data. Based on buying behavior, mayato experts detected preferences to differentiate customers from each other and structured the product offering accordingly.

Read our case study ‘Recommender System for an Online Sales Platform‘ to find out how even less complex, cluster-based approaches bring great added value and why this model was successful.

download Case Study

Coaxing a 20th-century factory into the new millennium
23. Aug 2018

Retrofitting legacy machinery with IoT-ready control units

Once the plant of an established manufacturer of metal-mesh personal safety equipment was highly innovative. Built in the 1960s and upgraded with the most modern electronic controllers available in the 1980s – is starting to show the weaknesses of its age: although the machinery still works smoothly, the electronic components are woefully out-of-date: replacement parts are no longer easily obtainable, so malfunctions can result in stoppages of unforeseeable duration. In addition, manual processes make process flows more difficult: Starting up a production batch involves flashing a memory card with the process instructions and walking it over to a controller box mounted onto the equipment, where it is slotted in by hand. The procedure has been repeated for each new run, several times a day – for the last 30 years.

Aufbruch in Industrie 4.0 (more…)

Predictive Technical Diagnoses
17. Aug 2018

Development of a predictive service and maintenance solution for laboratory systems from Siemens Healthineers with SAS

Atellica Solution für fortschrittliche Labordiagnostik
Atellica Solution for advanced laboratory diagnostic (image rights Ⓒ Siemens Healthineers)

Siemens Healthineers is among the world’s leading companies in diagnostic medical technology. For the new clinical laboratory diagnostics system Atellica Solution, the company incorporated the integration of a predictive service and maintenance solution and chose mayato for its conceptual design and implementation.

Reporting malfunctions to customer service should be the exception rather than the rule for users of the laboratory diagnostics system Atellica® Solution. As early as the development phase, the engineers from Siemens Healthineers defined which machine data of the future diagnostic laboratory system could be relevant.