The unstoppable rise of data science is already having a major impact when it comes to product and process development. Professor Jeroen de Mast shares his vision on how project managers and industrial engineers can continue to use their expertise in a data-driven future.
“At Holland Innovative you will find a lot of expertise when it comes to six sigma, reliability engineering and project management. But we see how the rapid rise of data science is affecting almost all disciplines. It is therefore essential that professionals look at how their expertise in the field of Design for Six Sigma and reliability relates to data science in the new reality! ” according to Jeroen de Mast
From data sets to data streams
“Looking at Six Sigma, so far it has mainly been based on 'classic' statistics. A huge new range of analytics, including AI and machine learning, has been added in the last decade. These tools offer unprecedented new possibilities for the successful development of new products. But the changes go even further: based on Design for Six Sigma, industrial engineers are used to working with data sets. These days you see that such data sets are rapidly being replaced by data streams. ” “So no more the use of a 'little excel file', but a continuous stream of information - numbers, audio files, pictures, reviews, Twitter messages and much more. That is all valuable data.”
Until now, data science has been the playing field of ICT. Yet it is precisely the engineers who - with their knowledge and insights - know how to concretize innovative processes and projects. "We see that organizations where program managers and engineers are able to make the translation to integrate data science into their product and process developments, are creating important innovations in existing products."
By bringing together the knowledge of six sigma, reliability and data science, professionals can use their product, process and project knowledge as a flywheel in formulating future-proof business models.”
New business models
“But it is to be expected that data and analytics will increasingly become a source of completely new innovative products. Just look at the automotive industry. It is assumed that within nine years, half of the turnover will no longer be realized through the sale of hardware – aka cars – but from the sale of data and data-related services. ”
"We are already seeing these shifts arise in business models in other industries. Recently, for example, we made a forecasting model for a large food supplier. This allows them to predict the demand for newly introduced products. Another example is a reliability system that we implemented on behalf of one of our customers active in consumer electronics. This early warning system detects and signals when there are issues in the field with sold products. Such data-driven innovations increasingly form the basis for new promising innovation-driven strategies.”
Ready for the future
“It is great to see how knowledge in the field of Six Sigma and Reliability and the insights obtained by applying AI, machine learning and more can complement each other so well. In the training courses that we offer at Holland Innovative - Project Management & Leadership for Data Scientists, Data Science for Six Sigma Green Belts & Black Belts and Life Data Analysis & Reliability Testing – we show how data scientists can successfully roll out a project and how engineers and project managers can use data science to optimize product quality.”
“The use of data undeniably has an enormous impact on product development and the development of an innovation strategy. But it is precisely by bringing together the knowledge of six sigma, reliability and data science that professionals can use their product, process and project knowledge as a flywheel in formulating future-proof business models.”
Curious about how new insights from the world of big data and machine learning can make your innovation strategy future-proof? Don’t hesitate to call or email us still today.
* Scientific Director at Holland Innovative, Academic Director at Jheronimus
Academy of Data Science and Professor at the University of Waterloo in Canada