Learning needs for master data management


In the recently published "Market Study 2015 - Multidomain Master Data Management Systems" by the Fraunhofer Institute for Industrial Engineering IAO, it is clear that, among the benefits of using master data software, respondents value the harmonization of company-wide master data more than the regulation of clear responsibilities in master data management or the implementation of standards in MDM processes.
Harmonization alone is not enough
"This is not our view, because harmonization alone is not enough"
comments Monika Pürsing, CEO of ZetVisions.
"Rules and standards for handling master data are just as imperative as the definition of clear responsibilities. Without effective data governance, it simply won't work if you don't want to start from scratch every time."
The study also confirms the findings of the "Master Data Quality Trend Study 2013" conducted by Heilbronn University, according to which 70 percent of companies see the very high manual maintenance effort as the greatest challenge to ensuring master data quality.
Susceptibility to errors
After all, the fulfillment of compliance requirements is in fourth place when it comes to the question of which current corporate IT requirements are essentially supported by the use of master data software.
First and foremost, however, companies attach importance to promoting sales growth. In second and third place are improving the evaluation and use of information and improving interaction with the company's customers and partners.
"The evaluation and use of data - data on which information is then based - is becoming an ever greater challenge in the age of big data. The decisive factor is that the data quality must be right. There can be no 'good' information from 'bad' data"
says Pürsing.
Only professional master data management provides the basis for generating "good" information from "good" data and then using effective analytics to generate reliable knowledge, which in turn enables well-founded business decisions.
Industry 4.0 drivers
In its market study, the Fraunhofer IAO also investigated which general IT trends the manufacturers of MDM software consider to be particularly relevant for the further development of master data software.
According to the survey, the five most important IT trends for master data software are Rich Internet Applications/HTML5, Partner Collaboration, Data Shareconomy, Analysis of unstructured data and Predictive Intelligence. Big data only follows in ninth place, with the much-discussed Industry 4.0 in 18th place.
"That's quite amazing"
wonders Monika Pürsing.
According to PwC, the degree of digitalization of value chains will increase rapidly in the future. The degree of digitalization of the horizontal value chain alone, i.e. the networking between customer, company and supplier, is set to increase from 24% (2014) to 86% in five years. The most important component of this digitalization is data.
"And the quality of this data is by no means at its best. Back in 2013, the IAO's 'Production Work of the Future' study on Industry 4.0 found that in 51% of the companies surveyed, the poor quality of production data made short-term interventions in production control necessary to a great or very great extent; Another important reason for this is the lack of up-to-date production data (44 percent strongly/very strongly). Manufacturing companies must recognize this: Industry 4.0 belongs right at the top of the relevant drivers for master data software."