Jenny is an accomplished Technical Director in Project Strategy and Australia Digital Delivery Practice Lead at Mott MacDonald, boasting an impressive career spanning over two decades. Her expertise encompasses design and construction development, digital transformation advisory, asset management, and data & information management, making her a global contributor to various industries.

In a recent conversation with The Global Woman Leader Team, Jenny talks about balancing digital transformations with operational resilience. She also emphasises on building talent strategies for the digital age and unlocking the potential of data-driven processes & model design principles. Jenny also highlights the basics of digital twin technologies and asset management. Read the conversation to know more.

In today’s rapidly evolving digital landscape, how are organizations balancing the push for digital transformation with the need to maintain operational resilience, especially in light of recent economic uncertainties?

The current digital landscape presents key trends where we aim to balance digital transformation with operational resilience. We are investing in modern IT infrastructures and enhancing cyber resilience to strengthen security from both data and information perspectives, with greater emphasis on privacy and data sovereignty. We are also adopting agile methodologies to connect systems and exploring the potential of artificial intelligence to drive industry advancements.

Key areas of focus include upskilling our people to handle new technologies and leveraging data analytics for better decision-making. Given the economic uncertainties, our priority is to support clients in their innovation journeys, helping them retain growth and enhance their strategies. This approach enables them to remain flexible, secure, and competitive, while adapting to changes and continuing their digital evolution.

As digital transformation increasingly shifts from technology-centric to people-centric, how are organizations rethinking talent strategies to align with new digital initiatives? What role do digital skills and culture play in ensuring the success of these transformations?

We need to rethink our talent strategies to better align our employees with new digital initiatives. With resource shortages, it’s unrealistic to expect to find all the “unicorns” with every skill required. Instead, we should aim to create a learning environment that fosters skill development through targeted training programs. For example, the partnership between organizations like the Transport for New South Wales state government and universities such as UTS to co-develop micro-credentials in emerging technologies, data analytics, carbon measurement, and cybersecurity.

The goal is to support professionals with existing technical expertise in pivoting and reskilling for the next phase of their careers. Key digital skills coupled with soft skills are critical for transformation projects, including effective communication, simplifying complex language, adaptability to change, and fostering collaboration across disciplines. This approach enables us to nurture the next generation of digital leaders with a growth mindset.

With data becoming a critical asset for decision-making, how can organizations shift from simply collecting data to fully leveraging it for predictive insights and strategic decision-making? How do you see the role of Data Integration evolving to unlock untapped potential in business operations?

We are entering a digital era where everything we do is founded on data-driven processes and model design principles. To move beyond merely collecting data, we must leverage advanced data analysis techniques, machine learning, and AI functionalities to create our own language models within organizations. This helps establish consistent language that can be traced and tracked.

A key part of this approach is having a clear problem statement and being purposeful in transforming raw data into actionable insights through predictive modeling and data visualization. This involves knowing what we are tracking and who is responsible for it. Data integration plays a crucial role by combining different sources into a unified view, eliminating silos, and ensuring data consistency. This holistic approach enables real-time decision-making, strategic planning, and unlocking untapped potential.

However, many overlook the importance of data cleansing and restructuring, which are foundational layers for ensuring the success of data transformation efforts. If not addressed properly, these foundational issues can lead to future failures.

Digital twins are often touted as the next frontier in digital transformation. How do you see the application of digital twin technology reshaping industries, and what challenges do organizations face in effectively implementing these models to create value beyond mere simulation?

Digital twin technologies are reshaping our industry by enabling real-time monitoring to collect and built data, provide insights to inform predictive maintenance decisions and optimize operations for various assets. This involves creating a 3D representation of real-world objects and transforming digital twins into smart, intelligent systems.

In manufacturing, digital twins enhance production efficiency and reduce downtime. In healthcare, they aid in personalizing treatments, improving surgical planning, and supporting remote work environments. From a transportation perspective, digital twins aim to improve safety, customer experiences, and reduce the carbon footprint while optimizing infrastructure operations.

Current challenges include data integration, ensuring high data quality, and overcoming high implementation costs. Additionally, there is a need for specialized technical expertise to effectively use digital twin technologies. To address these issues, organizations must explore the full potential of digital twins to unlock new value beyond simulations, connecting multiple data sets for deeper insights.

As organizations move towards model-based design and engineering frameworks, what are the critical success factors that ensure these frameworks are not only implemented but also embedded within the organizational culture? How can businesses measure the real impact of these frameworks on their bottom line?

Key success factors for embedding a motivated design and engineering frameworks include strong leadership support, with leaders actively participating in the core design process and clearly understanding the value outcomes and use cases. Continuous training is crucial to ensure that the focus is not merely on chasing technology, but on developing the next future state of technology. Promoting a culture of innovation and collaboration is equally important, which involves not only creating new solutions but also optimizing the efficiency of current processes. Ensuring interoperability between systems is essential to facilitate seamless data integration while maintaining the highest data integrity standards.

To measure real impact, businesses must track performance indicators (KPIs) such as reduced development time, cost savings, and benefits analysis. This approach helps to improve product quality without being constrained by system administration complexities. Additionally, assessing the implementation's maturity level and conducting regular performance reviews are critical for quantifying the benefits and evaluating the return on investment of these frameworks.

With asset management increasingly integrating with digital technologies, how can organizations ensure that they are not just digitizing existing processes but fundamentally transforming them to enhance efficiency, reduce risk, and drive innovation?

To fundamentally transform asset management, organizations must adopt a strategic approach that integrates digital technology to support and uplift existing systems. This involves rethinking workflows and enhancing data input and output. People are critical to this transformation. We need to shift their mindset from legacy systems to a more adaptive learning environment. Leveraging advanced real-time data analysis enables us to better understand asset performance and reduces the risks associated with inaction. Small changes can lead to improved asset performance and drive innovation.

Continuous learning and training in change management are essential. Effective communication is vital to ensure that all stakeholders are on board and understand the milestones, value, and use cases being implemented. Measuring impact through KPIs helps track progress and demonstrates value achieved. This continuous cycle is critical; digital technology is an evolving ecosystem. Change is inevitable, but with structured workflows and an understanding of skill sets, we can effectively measure and monitor change.

Message For Readers

I hope we can work together as an industry to foster collaboration and adaptability to change, which is inevitable. By preparing as a cohesive group, we can drive significant progress and shift to a better growth mindset. While we face constraints in resources, timeframes, and costs, collaboration among software vendors and supply chains will enhance our understanding of maturity and the next steps in our digital landscape.

Our technology is advancing exponentially, so we must focus on processes and people to leverage systems and data effectively. I envision a future with greater collaboration, innovation, and diversity, which will propel us into the next phase of our digital evolution.