Digital transformation strategies for applied science domains

• Published in: Research Ideas and Outcomes Vol. 9; pp. 29 - 21
• Main Authors: Bentum, Samuel, Wild, David
• Format: Journal Article
• Language: English
• Published: Sofia Pensoft Publishers 09.08.2023
• Subjects: app; digital transformation; digitisation strategy; R&D; Research & development
• ISSN: 2367-7163; 2367-7163
• DOI: 10.3897/rio.9.e105197

The key hallmark of a digitally minded organisation today is seen in their rapid advancement, globalisation, innovation and resilience to change. Companies that wish to thrive must be prepared to adapt to the new digital reality. Being digitally minded does not mean implementing new technology, investing in tools and upgrading current systems. These stages are critical, but they are not the entire picture. If a company wants to remain competitive, it must not just be able to adapt to changes, but also anticipate and drive innovation. Companies must plan ahead and be proactive architects of their future in order to achieve this vision. This is where a digital transformation strategy is crucial. A digital transformation strategy assists organisational leadership in addressing challenges about their business, such as the present level of digitisation and a digital maturity roadmap. Although diverse data capturing technologies and data-generating assets exist, material/chemical science domains, such as R&D and Manufacturing groups, struggle to harness the full power of their data. A typical industry will have significant data sources generating large amounts of data stored in siloed databases with minimal to non-existent cross-talk. This in part creates scenarios for researchers to be able to perform a deep dive in one set of data, but unable to co-populate and harness the interdependences or relationships amongst the different datasets. This paper seeks to define, distinguish, aggregate and propose an integrative approach to utilising the various types of disparate data sources commonly encountered by researchers in the field of their material science research. The main focus here is defining strategies to harness insights across integrative data to aid in efficient research in R&D organisations as these industries seek to embrace the power of digital transformation. Although the principles described here relate to industries in the applied science domain, the general strategies proposed can be applied to other industries on a case-by-case basis.