The chemical industry and big data

big data, chemical industry
© Vladimir Zapletin

Without a shadow of a doubt, big data is set to transform the way the chemical industry operates – for the better

Big data is nothing new – organisations have collected information for decades, but the crucial difference is that at last we now have the technological capability to do something useful with it. Used properly, it gives an organisation the edge over its competitors and in an increasingly more competitive and volatile environment, this 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, globalisation, 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 which do this are missing out on valuable opportunities. By harnessing big data in the right way, organisations can reduce costs, increase margins and streamline processes, as well as allocating resources in line with the strategic goals and future objectives.

Greater demand plan 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 organisation 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 behaviours to inform their forward business plan with true knowledge. By understanding what the customer wants and is likely to want in the future, chemical organisations 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 a focus on the right ones and will create shorter-term results to keep shareholders happy, whilst optimising 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, organisations can decide on a course of action as to how to best tackle issues which 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 which collect continuous data, which is then subsequently analysed to identify patterns and prompt intervention before breakage, or to source parts in preparation for when breakage occurs to reduce the amount of time that the equipment is out of action. By avoiding unanticipated machine shut-downs, chemical organisations can optimise performance and productivity.

Supply chain

Big data also has a role in optimising a lean supply chain, especially in transportation logistics, which is crucial for the delivery of raw material for production, and for shipping out products. Advance analytics give organisations the ability to analyse weather patterns and forecasts, highlighting events that might cause a delay in the supply chain, such as tornadoes, earthquakes and other natural disasters. Based on these statistics, companies can then form contingency plans – identifying back-up suppliers, for example – to enable them to continue to meet operational targets.

Data-sharing can also encourage transparency; by linking internal and external data sources and sharing information, this can strengthen end-to-end planning along the multiple segments of the supply chain.

Pricing & purchasing

There are several factors which 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.


Mike Snape

Associate Oliver Wight EAME LLP

Tel: +44 (0)1452 397 200


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