End-to-end digital transformation of chemical manufacturer

Digital technology subverts the old way of working, but it also reveals opportunities for improvement. Chemical manufacturer can obtain value by digitizing the whole value chain.

Three major trends are reshaping the operation mode of chemical manufacturers: great progress in technology and innovation, rapid changes in customer demand, and rising costs and productivity. Of course, these trends overturn the old way of working, but also lead to changes in strategy and tactics, making the complete, end-to-end (E2E) digital transformation picture of their plans cloud.

Because of this uncertainty and the subsequent inability to maintain the end-to-end perspective of digital transformation, many chemical manufacturers find it difficult to deploy their efforts on a large scale – the key to success. This perspective allows companies to see where the biggest opportunities are and capture the greatest value. In fact, making decisions at the overall level, optimizing the interface between functions and levels, and using all available data sources without knowing what the connection is, can increase the average earnings before interest, tax, depreciation and amortization (EBITDA) by 8.5 to 16.0 percentage points (see Figure).

Each digital support domain must work together to maximize value within and across functional silos. In addition, the two enabling features (the overall operational model and it / OT infrastructure) must be consistent with the transformation objectives to capture all data in a single source. The exhibition also shows the effects of segmentation across all functions. Although the 7.5 to 14.0 percentage point improvement in EBITDA comes from the digital conversion of each functional domain, from the overall E2E perspective, an additional 1.0 to 2.0 percentage point improvement in EBITDA can be achieved.

From the perspective of end-to-end technology, chemical manufacturer can quickly adapt to the changing market environment and maximize profits. For example, in the case of rapid growth, numbers and analytics can help release capacity while reducing costs by increasing production and throughput. At the same time, the seamless integration of supply chain and business functions ensures that this new capacity is allocated to the most profitable customers and products, providing the best profit. Considering trade-offs, production and supply plans are updated in real time at every step of the value chain.

Similarly, in the case of low demand, numbers and analysis can help inform sales decisions in advance through algorithms, so as to “push” low margin products into the market, fill capacity and digest fixed costs. The algorithm can also inform the demand redistribution between factories, and suggest that the whole line be closed temporarily. Most importantly, the increased level of digital assistance can guide workshop operators, allow easier redeployment of employees across departments, and recommend the use of contractors’ best time (e.g., during peak activities).

All in all, these digital insights support more efficient and flexible use of resources.