DataFramed
#143 Fighting the Climate Crisis with Data
Mon Jun 26 2023Description
The episode discusses the importance of data and digital innovation in the energy sector, focusing on NG's commitment to becoming carbon neutral by 2045. It explores how data science and AI are integral to achieving NG's renewable energy ambitions, and how data is leveraged for trading activities, risk management, and financial performance. The episode also highlights the challenges of harnessing data effectively in global organizations and the need for collaboration, easy-to-use infrastructures, and a focus on value creation.
Insights
Data Science for Renewable Energy
Data science plays a crucial role in optimizing renewable energy production by using algorithms to adjust panel orientations based on weather forecasts. It can also be used for maintenance purposes, such as visual recognition algorithms for inspecting remote renewable assets.
Developing a Data Culture
Creating a data culture and mindset is a difficult challenge for organizations. NG recognizes the need to upskill its workforce in digital and data skills and aims to make employees aware of advanced analytics tools that can simplify their work. Building a network of data officers is crucial for spreading the message of a data culture throughout the organization.
Bridging Data Sets and Integration
Bridging the gap and creating integration between different data sets and parts of an organization is a multi-year effort. It requires breaking silos, working in an integrated way, and co-constructing infrastructure. Having a global energy strategy is key to becoming more integrated as an industrial company.
Harnessing Data for Value Creation
Organizations need a culture of collaboration, easy-to-use infrastructures, and a focus on value creation to harness data effectively. Unlocking data requires a mindset of data sharing and collaboration within the company. Data accuracy and completeness are ongoing challenges that organizations must address through data governance frameworks.
Data Expertise and Upskilling
Data scientists play a crucial role in developing subject matter expertise by working closely with operational teams. They have a curious mindset and actively seek to understand the needs and goals of their colleagues before developing models. Upskilling the workforce in digital and data skills is essential for harnessing the value of data effectively.
Chapters
- Data and Digital Innovation
- Harnessing Data for Value Creation
- Bridging the Gap and Creating Integration
- Developing Data Expertise and Culture
- Building a Data Culture
Data and Digital Innovation
00:00 - 07:50
- We live in an era of data and digital innovation, with advancements in data systems and quantum computing.
- NG is a major energy producer committed to becoming carbon neutral by 2045.
- Data science and AI are integral to achieving NG's renewable energy ambitions.
- Data is leveraged at NG for trading activities, risk management, and financial performance.
- NG operates across the entire value chain of low-carbon energy, from production to retail and storage.
- The value chain includes production of gas and electricity, transportation, distribution, and selling of energy.
- NG also provides gas storage facilities, energy management advice, and engages in trading activities.
- Critical success factors for harnessing data effectively include understanding the complexity of the value chain and addressing unique challenges in global organizations.
Harnessing Data for Value Creation
07:22 - 14:45
- Critical success factors for organizations in harnessing data effectively for value include a culture of collaboration, easy-to-use infrastructures, and a focus on value creation.
- Unlocking data requires a mindset of data sharing and collaboration within the company.
- Effective and easy-to-use infrastructures are necessary to encourage data sharing.
- Focusing actions on the most value creation is essential, requiring a strong governance framework.
- In the energy sector, data collection challenges arise from IoT devices such as sensors and smart meters.
- NG has deployed a wide network of IoT devices to collect data on electricity and gas consumption at production plants, homes, and industrial facilities.
- Data accuracy and completeness are ongoing challenges that NG is working to address through its data governance framework.
- Having a complete view of energy usage allows NG to forecast periods of high consumption and organize campaigns to manage energy demand effectively.
- NG's ability to target consumers with specific energy reduction goals based on their individual consumption patterns helps balance the overall system at the country level.
Bridging the Gap and Creating Integration
14:23 - 22:30
- Approaching the challenge of bridging the gap and creating integration between different data sets and parts of the organization is a multi-year effort.
- Working on a global data roadmap for global companies requires breaking silos and working in an integrated way.
- Having a global energy strategy is key to becoming more integrated as an industrial company.
- Corporate level infrastructure, such as data lakes and middleware, is needed to break silos while retaining ownership of data and ensuring cybersecurity and compliance with privacy regulations.
- Effort is required to co-construct infrastructure by networking, working with people in the field, and promoting adoption.
- Building a culture of engagement involves engaging with the wider population.
- Data science unlocks value for NG's renewable energy goals, which include being carbon neutral by 2045 and reaching 80 gigawatts of renewable energy production by 2030.
- Data science helps optimize renewable energy production by using algorithms to adjust panel orientations based on weather forecasts.
- Data science can also be used for maintenance purposes, such as visual recognition algorithms for inspecting remote renewable assets.
Developing Data Expertise and Culture
22:08 - 29:47
- Data science teams at NG develop subject matter expertise by immersing themselves in the operational teams and working closely with them.
- NG has a center of excellence that provides initial support, but data scientists are then either internalized by local organizations or sent on long-term missions on site.
- Data scientists have a curious mindset and actively seek to understand the needs and goals of their colleagues before developing models.
- Creating a data culture and data mindset is a difficult challenge for NG and every organization.
- NG recognizes the need to upskill its workforce in digital and data skills to harness the value of data effectively.
- NG aims to make employees aware of advanced analytics tools that can simplify their work and unlock additional functions.
- NG also focuses on upskilling technicians who may have low awareness of digital and data tools but use them in their personal lives.
- Building a network and community of data officers is crucial for spreading the message of a data culture throughout the organization.
- Data officers should identify individuals with an interest in working with data to become champions or local data officers within their respective areas.
Building a Data Culture
29:22 - 36:25
- NG has built a network of 40 data officers over the last three years
- The network includes around 2000 people who have an important data component in their job
- NG animates the network with monthly webinars and events like hackathons
- Creating a learning culture and evangelist network is important for spreading the data culture within organizations
- Data is now a mainstream tool that needs to be structured professionally as a department
- Building a roadmap to show how data delivers business value is crucial
- Governance, infrastructure, and culture programs are necessary for successful data implementation
- Choosing the right use cases that deliver business value is key for data officers
- Prioritizing use cases requires speaking to C-level executives and understanding strategic objectives and pain points of the company