Big Data is often defined as high volume, high velocity and high variety of streams of complex data with hidden insights. The retail industry has embraced (aka exploited) the benefits of Big Data by tracking consumer sentiment on social media channels and improving the buyer experience with facial recognition technology. Big Data is often showcased in numerous network crime/murder mysteries by featuring autopsy analysis or investigative biometric statistics – although very Hollywood, the capabilities are real. Many municipalities are now analyzing streams of data to predict with uncanny accuracy crime hot spots, and then deploying police to those locations to reduce criminal activity and improve overall quality of life. But how does a conservative, value-minded industry like chemicals define tangible use cases for Big Data?
The benefits to the industry must encompass reduced risk, improved productivity/profitability and enhanced customer service. According to a recent survey by Accenture, 94% of chemical executives believe that digital technologies will revolutionize the way they are doing business. In order for this digital technology to be effective, companies must have the infrastructure in place to glean insights from the data – merely amassing information will not yield any value.
The chemical industry has always been subject to numerous regulations. The REACh platform, for instance, is now being adopted with various international regional models, each with their own requirements. Compliance with regulations is the cost of doing business; a simple change to a product formulation could result in an infraction. These changes must be reviewed in near-real time, and checking the impact on formulation changes (or even the simple placement of an import/export order) amidst this complex regulatory environment has impeded the speed of business. Certain chemical substances are highly hazardous (or can be easily reformulated to something highly hazardous) and both the shipper and the manufacturer have a responsibility to ensure that the entire product geneology can be traced throughout the complete lifecycle of the product. With an alarmingly retiring workforce, the chemicals industry is faced with many new chemical operators that need to be trained and certified. The tasks they are performing, and even their physical whereabouts, can now be monitored to ensure that a certified operator is performing the task and other unqualified personnel are not physically present.
Leading chemical companies are starting to revolutionize the decision-making process with Big Data by dramatically improving productivity and profitability. Having fully-integrated data models across supply chain, logistics and finance has enabled the ability to run simulations and scenarios in real-time to finally answer the ‘what if’ questions. What if polypropylene prices increase by 4% and I delay my plant shutdown by 2 weeks because customers will likely pre-buy in order to avoid the price increase? Will I have the available capacity/inventory? In this asset-intensive industry, manufacturers are connecting numerous equipment sensors on the shop floor to improve asset utilization through predictive analysis – the ability to predictan equipment failure is now keeping our plants running safely and efficiently. The amount of data that is generated from variable pump speeds, valve vibration analysis, agitator torque tracking, temperatures and pressures with plants that are running 24×7 is staggering. With a new breed of educated talent (yes, the millennials are highly educated) entering the chemicals industry, the core concepts of optimization are not only being applied to the supply chain, but also to product pricing, portfolio planning, logistics and commodities management. All of these changes to supply chain management, asset utilization and advanced optimization algorithms are defining Big Data use cases within the chemicals industry.
Although the chemicals industry is not subject to omni-channels in the same way as the retail industry, the strains of customer service are very similar. Customers expect differentiated service – delivering the right product at the right time to the right location is no longer good enough. Differentiated customer service is now defined by delivering technical data sheets, COA’s, SDS’s, samples, customized labels, pricing documents, call reports, marketing analysis and numerous other reports. The traditional CSR, who is the FIRST interface to the customer, must be able to process nearly any request and the data must be at his/her fingertips. Big Data is enabling superior customer service with Precision Farming, where analysis of weather, soil conditions, seed traits, and historical yields are helping farmers determine what to plant, when to plant, and what types of crop protection chemicals to apply. The example from Precision Farming will eventually be applied to other traditional chemical industries, where information can be used to enhance formulations and applications for truly superior customer service.
The regulatory environment will continue to evolve with greater influence by the end-consumer (ie Walmart Priority Chemicals) as well as sustainable improvements to the oft-neglected Asia-Pacific region. Europe and the US will lead the advancement of nano-technology and green chemistry. As the higher margin specialty chemicals sub-industry slowly transforms to more of a commodity play with global competition, the pressure on margins will force manufacturers to drive improvements and innovations in the extended supply chain in order to remain competitive. Customer service, as we know it today, will evolve from order-taking to information sharing and analysis to address customer intimacy at a new level. These changes will be the primary drivers to the new digital revolution in the chemicals industry and Big Data will be the enabler.