„More than 50% of the companies are not willing to invest in Big Data Applications. These companies will go bankrupt over the next 10 years“. A provoking statement made by Thomas Froese from atlan-tec, a software developing company specializing on process optimization and data mining. And yet, there are many who share his view: Huub Rutten,Sopheon, points in the same direction when he says that „companies that think Big Data Analytics is something for their marketing department, and not relevant to all other functions, will not have a long life anymore.“
The awareness in the process industry is there: According to Accenture’s Digitals Chemicals Survey in 2014, 79% of chemical industry executive expected digital to make the greatest impact over the next five years through improved productivity. On the other hand, only 58% were embracing digital to gain a competitive advantage over industry peers. Taking the expert statements on competitiveness into account, there seems to exist a potentially dangerous gap – big data is introduced, but it might in some cases be too little, too late.
Predictive Big Data Analytics and Machine Learning will transform most industries by supporting better informed and more customized decisions by both, humans and machines, increasing agility and efficiency, lowering costs, enabling better and more customized products and services, forecasting risks and opportunities, and increasing automation. Early adopters will gain significant competitive advantages, while others are likely to be left behind.
Ralf Klinkenberg, RapidMiner
Big Data analytics has become more and more important to the process industries. Sure, the process industry has always collected data to supervise production processes, to identify disturbances, and to ensure product quality, and this will continue.
The application of data analytics will improve efficiency in the chemical industry!
Matthias Hartman, ThyssenKrupp System Engineering
But with the tremendous increase in data storage and processing capacities, new algorithms have become accessible. They open up new market opportunities, enabling process advantages and cost reductions within the production, decreasing time to market and, ultimately, making new customized and individualized products accessible. The application areas in which data analytics can be used profitably are diverse and in process industries nowhere near exhausted.
In the process industry, digital technology provides actionable solutions to challenges and groundbreaking opportunities for innovation.
Matthias Feuerstein, Microsoft
Provided the data is collected, analyzed and used intelligently and efficiently, as Benjamin Klöpper, ABB Research Center, points out:„The major challenge for Big Data Analytics in Process Industries are not scalable architectures or clever algorithms, but remains to have the right data in the right quality to address relevant and pressing issues. Today’s information system infrastructure often prevent us often from obtaining this right data in an efficient data.“ Adds Nico Zobel, Fraunhofer IFF: „One of the major challenges will be to generate use cases of the analysis of data from heterogeneous sources.” And the sources in the chemical industry are nearly endless.
Chemical space is big. Very big. Published and unpublished data only cover only an exceedingly small part of possible small molecule space. Machine learning and algorithmic prediction tools can help fill in the explored parts of chemical space. What kinds of data sources and prediction tools will come next?
David Flanagan, Wiley ChemPlanner
Jens Kamionka, T-Systems Multimedia Solutions, widens the scope by taking security issues into account – a major challenge in times of increasing cyberattacks: „Many companies still fail to address security, infrastructure or data quality issues.” Concepts that allow one the one hand the company-wide or even inter-company integration of data streams along value chains, at the same time preventing data leaks and cyberattacks, are the intensely sought after.
And once these questions are solved – are we looking at a future with fully automized, smart plants that anticipate customers’ wishes before they are even aware of them? No, according to the experts. Human intelligence will always have its place. „Big Data opens up many opportunities in different areas of a chemical company. Besides toolsets and technology, mind-set and communication skills are additional success factors for these novel approaches”, says Sindy Thomas, Clarian. And Drazen Nikolic from Ernst & Young sums it up:““If you do not understand the problem, you are not able to frame the right question. “
Meet these and other experts and discuss what Big Data analytics might mean for your business at the DECHEMA-PRAXISforum “Big Data Analytics in Process Industry”, 1-2 February 2017, Frankfurt. For the full program and registration, click here DECHEMA-PRAXISforum Big Data Analytics in Process Industry