9MANUFACTURING TECHNOLOGY INSIGHTSJUNE - 2023· BUSINESS OUTCOMES: Digitalizing an innovation workflow of any scale and complexity is a MAJOR investment. Definition of what the system will enable through measurable value creation is fundamental to both the justification and design of that system. For example, with PI we are enabling a radical increase in speed of response to our customers so that our project capacity is increased, and our customers go to market faster.· DATA COLLECTION AND MANAGEMENT: At risk of stating the obvious, its ALL about the data and this is where the major component of investment come in. Typically, large datasets are required for predictive modeling of complex systems. Data acquisition needs to automated in labs that are often distributed around the world and sometimes using different equipment. And finally, the data needs to be curated to make it `modeling ready' and minimize rework.· FUTURE PROOFING: The digitalization journey often starts with ardent technical professionals launching grassroots efforts that gain momentum and grow into big ideas. When the digital tools are intended to be key capabilities for the business, the organizational capabilities to sustain and extend them must be put in place. Without that, they will die a death of accidental attrition as key early contributors move on.· COLLABORATIVE CULTURE: Functional siloes are massive decelerators of success. Successful predictive capabilities (meaning those that fulfill their business value) are a multidisciplinary team effort ­ probably more so than most initiatives that most of us will engage in during our careers. The diverse skills of teams compromising experts from IT, AI, chemistry and materials, marketing, communications, and sales all need to be aligned in service to the objectives of the program, requiring the establishment of an intensely collaborative culture that enables collective, enterprise-based work. · CHANGE MANAGEMENT. I believe that this last topic is often an overlooked element that determines the ultimate success of the digital investment. Because the journey is long and complex and because the culture change is massive, deliberate change management is critical. In addition to all of the technical dimensions, we are ultimately asking people to change the way that they work. The ultimate measure of success is adoption ­ both by employees and customers. People need to be supported to understand how to navigate and embrace new ways of working based on the impact on THEM as individuals and work groups.Reflecting on the journey of Predictive Intelligence at Dow ­ we have learned and applied all of these lessons. I expect as we extend our scope to support our customers' manufacturing operations, we will keep learning more. The most important lesson I have learnt in my digitalization journey is that it is never over, we need to be flexible and agile and keep looking for new solutions and new ways to create the future of our industry. The need of the hour is to harness the power of empirical data and fundamental modeling to predict product performance properties and innovate a new and more efficient era for manufacturing
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