Work in progress report use case „Integrated data analytics and collaboration in order management” at ERCO (UC3)
Target of the third use case is, to implement predictive analytics supporting collaboration and optimal allocation of resources between companies business departments. An additional aim is, to establish new competencies in the organization reaching a higher maturity level in data science projects.
Introduction to the ERCO use case
As so called application partner and medium-sized company ERCO fetches competencies in education, development and qualification of employees into the AKKORD research project. Additionally ERCO provides a highly integrated data network and the basic ability to apply analytic methods to manage the steering of a Supply Chain. ERCO wants to enrich information’s coming from quotations and orders, together with data from customer relationship module (SAP CRM), to establish a prognosis based on algorithms. This forecast shall be completed with data’s from social media and “erco.com” content. The upraised data provides the basics for planning of companies resources. Within the intercompany collaboration with sales organizations, production and assembly as well as supplier integration, the prognosis is a driving element of the supply chain. At this point, Rapid Miner AI software comes into the focus.
A further key aspect represents the building-up of personal competencies of employees. In the field of data science, new data driven procedures shall be created and established.
Approach to establish an integrated demand prognosis based on market information
Order prognosis at ERCO is based on two pillars of data structures stored in the project opportunity, in SAP Customer Relationship System and the quotation data stored in the SAP ERP.
ERCO Opportunities are created in combination with a milestone “projected order entry”. This date can change over the time, during the project development and will be maintained regularly. In combination with quotation data in SAP ERP, (product and quantity), we are able to determine the projected demand for a period of 4 month.
The projection of order entry is used to size the capacitive parameters of the ERCO production and as demand planning key figure, to align the supply chain in case of changes of market needs. The coordinating instance is the so called project & order center. Steering of supply chain is performed in close collaboration with external suppliers, purchase, preproduction, assembly as well as regional sales organizations.
The expected results out of the research project AKKORD consists the extension of existing skills of analytics in the project & order center. The technical data enrichment with information and data out of social media or the erco.com page shall create a better validity of the prognosis and data.
In conclusion, our target is to increase validity of planning and an improved availability of critical components and resources as well as customer orientated shorter lead times.
Conduction of a survey to relevant requirements of competencies
Together with the chair of teaching methodology of the university of Kaiserslautern / Hamburg and an interdisziplinary team of ERCO we have conducted an interview to determine the relevant requirements of skills. Expected result of the interview was to identify the relevant gaps and to anchor it within the ERCO use case. In the case of data science ERCO’s competence level is comparable low, although we need a substantial support for the following learning modules:
- Data Mining
- Machine Learning
- Artificial Intelligence
- Neural Network
- Recognition of patterns
- Data modelling and visualization
- General statistics
Based on this modules the concept specification and implementation is planned into AKKORD Work & Learn platform.
Collaboration in AKKORD Work & Learn Platform
Within AKKORD project and in the first stage of working package 4 we have discussed with Neocosmo a concept to link two learning management systems. The LMS of “ERCO Learning Campus” consists of learning modules covering the megatrend “Digitalization”. Learning modules can be done as classroom trainings, e-learning-courses as well as webinars. At the moment there are no existing modules dedicated to Data Science. Here we are planning an active interchange between both systems.
Verification of a data science maturity model
mosaiic developed a model of data science maturity and ERCO employees verified it, to identify the development level of an organization in terms of ability to adapt itself, within the data science environment. The results of the conducted interview were reflected into the business unit. Fields of development and recommended actions have been identified and established. ERCO plans to repeat the interview in a larger scale, again.
Summary and preview on research targets
Preparation and Implementation of analytical and presentation modules, as well as the utilization at ERCO and in addition, a generic approach within the AKKORD project frame, are key targets of the research. Moreover we want to establish a business-information-organization as key aspect in the project. The focused upgrowth of the ability to develop and extend data driven analytics are completing the target of the research project. All named aspects and the positive development status are fortifying the importance of the project in relation to the competitiveness of a medium-sized company.
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