The chemical industry & big data
22 Jan 2019
By Mike Snape, Partner at Oliver Wight EAME
Without question, big data is set to transform the way the chemical industry operates – for the better. Big data is nothing new – organizations have collected information for decades, but the crucial difference is that we now have the technological capability to do something useful with it. Used properly, it gives an organization the edge over its competitor, and in an ever more competitive and volatile environment, can mean the difference between thriving, or surviving, (or not).
Given the scope of its various market sectors and customers, the chemical industry is not naturally suited to the 21st century, which rewards agility and flexibility. Modern markets are changing more rapidly than ever before, with chemical companies having to contend with catering to new customer segments, globalization, fluctuating raw material costs, increasing competition, and developments in technology.
What’s so great about big data?
Historically, the chemical industry has been fairly predictable, with innovation and analysis of markets a biannual, or even annual event. In a 21st century framework, this is detrimental – companies that do this are missing valuable opportunities. By harnessing big data in the right way, organizations can reduce costs, increase margins and streamline processes, as well as allocating resources in line with the strategic goals and future objectives.
Greater forecast accuracy is one of the many benefits, as predictive analysis is refined using big data. By using corresponding tools, such as modelling, and sophisticated IT systems to identify hidden patterns and interpret early signals, an organization can make adjustments and realign its strategy early enough to avoid fire-fighting in the future. It promotes a proactive approach, rather than a reactive culture.
Analytics also enables companies to anticipate future customer behaviors to inform their forward business plan with true knowledge. By understanding what the customer wants and is likely to want in the future, chemical organizations can stay a step ahead in terms of meeting customer demand, with faster response times and shorter lead times. A better understanding of markets will also ensure that there is focus on the right ones and will create shorter-term results to please shareholders, whilst optimizing profitable and sustainable growth in the long term.
Practically speaking, data and analytics can have hugely beneficial effects in the chemical industry.
In process-based industries, one of the proven benefits of advanced analytics is increased yield, whether through improved production or reducing waste. Similarly, superior quality is a by-product of advanced analysis, as insights emerge as to exactly which parameters influence yield variation. By carefully pinpointing which processes are underperforming and using data to assess the effect of the varying factors on production, organizations can decide on a course of action as to how to best tackle issues that are negatively affecting yield.
Preventative maintenance & asset management
There are now predictive maintenance systems for equipment used in chemical manufacturing, such as turbines and compressors. These are fitted with sensors that collect continuous data, which is then subsequently analyzed to identify patterns and prompt intervention before breakage, or to source parts in preparation for breakage occurs to reduce the amount of time that the equipment is out of action. By avoiding unanticipated machine shut-downs, chemical organizations can optimize performance and productivity.
Big data also has a role in optimizing a lean supply chain, especially in transportation logistics, which is crucial for the delivery of raw material for production, and for shipping out products. Advanced analytics give organizations the ability to analyze weather patterns and forecasts, highlighting events that might cause delays in supply chain such as tornadoes, earthquakes, and other natural disasters. Based on these statistics, companies can then form contingency plans – identifying backup suppliers, for example – to enable them to continue to meet operational targets.
Data-sharing can also encourage transparency; linking internal and external data sources and sharing information can strengthen end-to-end planning along the multiple segments of the supply chain.
Pricing & purchasing
There are several factors that impact chemical pricing; market demand, raw material & energy pricing, exchange rates, competitor strategy, weather, etc., making chemical pricing strategy complex. Traditionally, it’s largely been based on experience, ‘gut feeling’ and outdated data - methods which are clearly unreliable and prone to inaccuracy By using big data, manufacturers can leverage information from multiple sources to track prices, identify when to make key purchases, and explore cost-reduction strategies. Not only does this promote increased profitability, but it can also provide competitive pricing solutions to customers.