The emerging impact of batch analytics

Significant investments by big chemical companies in high-value specialty polymers indicate that specialty chemicals, and therefore batch production, is on the rise. While many organisations don’t yet realise the value data analytics could bring to their market position, forward-thinking companies have moved to digitalise their production.

These pioneers have used trends like self-service analytics to create a digitally-enabled workforce to strengthen their market position and create profitable factories of tomorrow. The reasons for this change are firmly based in financials, such as the return on invested capital (ROIC) performance, which represents their operating profitability.

Profitability and specialty chemicals

In the last four years, the compound annual growth rate in specialty chemicals has rapidly accelerated and has since reached the same TRS (Total Return to Shareholders) level as commodity chemicals. With this shift, a strong specialty chemicals portfolio has become increasingly important for overall company value.

Control over operating costs and enhanced operational flexibility ensures adaptability to challenges such as overproduction and loss of control over market pricing

Digging deeper, the recent ROIC performance of specialty chemicals has indeed strongly increased, outperforming the commodity and diversified chemcials segments. This increase happened as the surge of TRS of the specialty chemical segment is connected to stronger operating profitability.

Driven by unique product innovation, as well as favourable end market choices, specialty chemical companies have a bigger influence over market prices when compared to the commodity sector. This holds great potential for specialty chemical companies: driving down operational costs and increasing operational flexibility. Combined with high market and price control, this can lead to improvement in ROIC performance. Not only that, it can also help to sustain ROIC performance when this is endangered by commoditisation.

Better control over operating costs as well as an enhanced operational flexibility can ensure adaptability to challenges such as overproduction and loss of control over market pricing. Since increased operating efficiency has such a big impact on ROIC performance of a chemical company in any segment, new opportunities for improvement need to be pursued.

Building the digital workforce

In the context of Industry 4.0, new emerging data analytics solutions can have a significant impact on improvements in operating efficiency. Regardless of the industry segment, the potential is estimated to be in the range of 3-5% improvement in return on sales. In general, there are two possible solutions evolving beyond the focus of Advanced Process Control (APC):

• Utilising generic data science tooling in combination with the scarcely available data scientist to solve operating problems
• An emerging domain called self-service analytics, which opens up possibilities to empower the process expert to use advanced analytics themselves to directly solve the bulk of day-to-day operating issues

The upside of the self-service analytics approach is the sheer number of opportunities across the organisation combined with its low cost of implementation when compared to classical APC solutions.

Self-service analytics

Reaping the benefits of process data analytics and self-service solutions leads to increased operating efficiency and a stronger market position. The smaller the batches the higher the need to use data to optimise process performance. Especially within specialty chemicals, a digitally enabled workforce can solve throughput and quality operations challenges, such as:

• Preventing waste on high value batches
• Reducing cycle times in order to meet customers’ demands
• Enabling an increase in flexibility and a more tailored production utilising smaller batch sizes.

In order to fully reap all the benefits hidden in the process data, such a solution has to be robust and easy to use, it should offer a common platform to analyse data from continuous processes upstream and downstream to analyse, monitor, and predict value hidden in the data.

• Artur Beyer is industry principal, chemicals at TrendMiner