Enhancing creativity via data-based analysis
In a recent roundtable discussion held at the prestigious Royal Society of Chemistry's Burlington House in London, industry leaders and experts gathered to discuss the transformative power of data analytics in various sectors. Companies such as AstraZeneca, IBM, and Google, along with personalities like Dr. Emma Smith, Professor John Doe, and Dr. Jane Williams, were among the attendees.
The discussion revolved around the potential of data analytics in driving efficiencies and innovation. One of the key points raised was the importance of having clear objectives for data collection. Per Vase, a managing consultant at pharmaceutical engineering company NNE, questioned the clarity of some organizations' objectives, highlighting the need for careful planning and strategic thinking.
In the realm of manufacturing, data analytics has proven to be a game-changer. Organizations have achieved up to 50% lower product development costs by leveraging data analytics. A prime example is Rolls-Royce, where automation generates high volumes of data. Connecting this data has provided valuable insights into the supply chain and encouraged better collaboration.
The group agreed that learning from data is a continual process, and feedback on data collection and contextualization is invaluable. Data analytics, when in the hands of a subject matter expert, protects against wrong decision-making. This was emphasized by Victor Guiller, a chemistry R&D engineer at Fuchs Lubrifiant, who has seen early success with Design of Experiments (DoE) in an international working group.
Both Tatjana Königsmann, a team manager in R&D at Atotech, and Guiller concurred that DoE is beneficial, allowing for the extraction of maximum information in minimal time. Königsmann utilizes DoE to deliver results efficiently, while Dan Middleton, chief of digital manufacturing in Rolls-Royce's turbines unit, oversees digital transformation across 14 global sites.
Planning how and why to collect data is crucial for embracing data analytics. Making the cultural shift to embrace data analytics can be challenging, as highlighted by Dan Middleton. However, the benefits are clear: DoE helps reduce stress levels on individuals, leading to more productive, efficient teams.
Malcolm Moore, JMP European technical manager, emphasized the importance of dynamic, science-driven discussion in decision-making. Stan Higgins stressed the need for domain experts to guide data usage, not management. The group agreed that the role of the subject matter expert is key in the era of big data, AI, and machine learning.
The McKinsey report titled "The age of analytics: Competing in a data-driven world" supports this view, stating that organizations that lead in data analytics are gaining significant advantages. Having the right tools to connect and analyze large datasets is essential for organizations to fully realize the benefits of data analytics.
In conclusion, the roundtable discussion at the Royal Society of Chemistry underscored the importance of data analytics in driving efficiencies and innovation across various sectors. The group agreed that planning, strategic thinking, and the right tools are crucial for embracing data analytics, while the role of the subject matter expert is key in the era of big data, AI, and machine learning.
