(269e) Value-Driven Digitalization Initiatives at Dow

Largely, the process industry has matured beyond the initial frenzy around automated reports, dashboards, and the embedding of statistics in software products, and has firmly moved toward building out infrastructure and decision-support systems to improve safety and maximize value.

Industry megatrends around M&A for narrowed domain focus, commoditization, low capital intensity, geo-political uncertainty, and emphasis on sustainability and customer experience require nimble and responsive supply chains, systems analysis for understanding trade-offs, and maximization of value from asset footprints. Further, with the emergence of AI platforms, the time has never been more ripe for practitioners to help an allegedly sluggish and slow-to-adopt industry to embed digital tools as a core part of their strategy.

A lot of emphasis has rightly been on external visibility of product portfolios to customers, as well as on internal decisions around what, when, and where to produce product---consequently involving IT, customer service/marketing, and supply chain functions. Although there continues to be significant opportunity in this space, AI technology and analytics has become increasingly relevant to R&D groups in the development of new products and innovative processes; and to maintenance and operations organizations in predicting and responding to process events.

Further, most digitalization projects fall in one of three areas of increasing implementation complexity: (1) technology that enables improved decision-making in a local environment that can be then cloned in different environments with small tweaks; (2) technology that is specific to a particular domain, business, class of products, or process; or (3) technology that spans across multiple assets and allows consolidated decision-making at scale. These three categories differ in the effort needed to standardize, scale, and get buy-in from stakeholders. These pose slightly different challenges, and the way organizations structure support organizations, empower employees, and manage programs is critical to the successful deployment of these systems and in effecting culture change.

Here, we provide specific examples where Manufacturing 4.0-related projects have enabled product, process, maintenance, and supply chain innovation at Dow, including recent success stories of deploying process intensification at scale. We also cover what Dow has done to intensify its organizations through three key capabilities---the Digital Marketplace, the Digital Operations Center, and the Digital Fulfillment Center, where domain experts and engineers sit alongside software architects, UX designers, and database experts to deliver solutions effectively. Further, we discuss how communities of practice around analytics have helped us align analytics professionals across different functions to develop a coherent strategy for the company around, for example, deployment best practices, building data pipelines, and digital twins. External partnerships with universities, consultants, and vendors do play a key role in technology transfer and adoption, and balancing the development of in-house talent with the right external support is important as well.

Through these stories, we hope to illustrate how an organization can plan a steady and firm climb out of the trough of disillusionment with digital technologies into the plateau of productivity.