Industrial Data Summit has an interactive format that enables in-depth peer-to-peer discussions around your key business challenges, providing real insight and value.
This includes a combination of plenary (keynotes, 5-minute idea, and a panel discussion) and our ‘deep-dive’ roundtable discussion breakout sessions, which are limited to 5 to 8 delegates in each session.
Share your ideas, opinions, and experiences in a collaborative and inclusive environment. Learn from others’ experiences and expertise and gain insights and knowledge from your peers who have faced similar challenges and overcome them.
Plenary
Our Plenary sessions bring together all delegates in a single room – concentrating the event’s focus on to a series of high-profile content sessions. These content sessions include case studies delivered by our keynote speakers as well as expertly moderated panel debates.
Discussion Tables
Select the topics that matter most to you! Over the course of the Summit, three rounds of Discussion Sessions will take place. You will have the opportunity to choose between eight Discussion Tables for a 60-minute interactive Q&A, hosted by a world-class manufacturer and a technology expert. The selection of topics will cover Data Management and Data Insights.
Welcome speech from our Chair.
The manufacturing sector is the latest domain to embrace the digital and data transformation ethos. Whilst there ground to make up, there’s also huge opportunity to accelerate change by learning from successes and failures in other sectors.
- This talk will highlight the investments and change initiatives necessary to grow and thrive in the fourth industrial revolution and beyond using examples from leading change in the public and private sector.
We know it’s the right thing to do, we know how powerful data can be, so why is it so challenging to create a data driven culture? There is a tendency to delve into the technicalities of digital transformations, to focus on the latest technology and how it can be implemented. But without the right foundations and organisational culture no amount of new tech is going to create a data driven culture.
- The challenges
- Laying the foundations
- Creating a digital culture
Accelerating Digital Transformation in Manufacturing with Connected Data
The UK manufacturing industry faces challenges in collecting and integrating data from multiple sources to make informed business decisions amidst Industry 4.0. To streamline operations and drive growth, companies need to optimise the power of data.
This roundtable will discuss the following:
- Strategies to overcome data silos across legacy systems and new technologies to support business organisations and processes.
- How to optimise data use and build a connected data infrastructure with data integration, management, and governance.
- How to create a data culture to support business processes, incentivise data sharing, and enhance employee and customer experience while generating new revenue streams.
A data strategy is not a one-and-done. Data strategies evolve. From an initial focus on getting your data house in order (efficiently storing and effectively protecting data) to a plan enabling its use, a data strategy becomes a roadmap for delivering business value.
Come join Snowflake to discuss the elements of a data strategy, with a focus on effective data governance that facilitates the use of data to deliver differentiation and competitive advantage. As Thomas Edison says, “The value of an idea lies in the use of it.” The same goes for data.
Join Snowflake and your peers to:
- Learn how other companies define and refine their data strategy
- Discuss how data governance allows you to know, protect and unlock the value of data
- Explore how data ecosystems expand data collaboration internally and externally
How data governance is transforming shop floor operations in manufacturing.
Increasing numbers of manufacturers are transitioning their operations to cloud-based platforms to realize benefits including cost savings, convenient access to manufacturing data for enterprise personnel, improved data analysis and insights, and scalability.
However, with the migration of manufacturing data to the cloud, challenges have emerged, including the management of large volumes of data. When transitioning to cloud-based platforms, data governance and security play crucial roles.
- What are the challenges associated to managing all this new information?
- Why is manufacturing data being moved / copied to the cloud?
- How are data governance and security instrumental while moving to cloud?
Legacy infrastructure and applications like Historian servers and SPC (statistical process control) systems hold many back when it comes to modernization and reducing costs. Cloud IOT services have dramatically changed this, but what exactly should be leveraged and how. Join Storm Reply in this session to discuss:
- What should or should not live on Amazon Web Services (AWS) when it comes to machine data
- Are edge analytics with AWS IOT services actually useful
- Is computer vision and digital twin complex and costly
Manufacturers continue to face uncertainty, with huge supply chain disruptions and unpredictable customer demand causing high levels of instability in businesses. At this year’s Industrial Data Summit, join AI experts and manufacturing industry leaders for an intimate roundtable discussion, exploring the role that AI can play in inventory planning. You’ll walk away with key learnings you can take back to your business, gaining a clearer picture of how AI can:
- Mitigate risks associated with uncertainty
- Significantly improve demand forecasting accuracy
- Unify data from across systems to drive great decision making…and much more!
With recent advances in automation and edge technology on the one hand, and data platforms and analytics software on the other, manufacturers have greater potential to harness value from assets and processes than ever before. But to avoid overlapping or competing digitalisation initiatives, it’s key to understand how to bring different roles together with a collaborative approach on infrastructure, tools and applications.
Key questions to consider include:
- How to develop a broad set of goals for usage of data – and from that, develop a plan that ensures you can “re-use, repackage and recycle” data between different stakeholders
- How to define data collection requirements in terms that respect different roles’ need for different levels of granularity vs. aggregation; exploration vs. execution, and so on
- What tools can foster meaningful business collaboration once data is available?
Every day we are bombarded by news stories on the power of Predictive and Advanced Analytics. From Machine Learning through to ChatGPT, there is incredible power in our data. On this table we will explore how to deploy this in an accessible and scalable fashion to industrial processes. Key discussion points will be:
- Big data vs small data
- Creating “citizen data scientists”
- Where to get the skills you need
Data leadership in manufacturing enables organizations to make informed decisions, optimize operations, enhance product quality, reduce costs, and gain a competitive edge in the dynamic manufacturing landscape.
- Building a strong data-driven culture
- Implementing robust data management practices
- Developing a strategic approach to leveraging data to achieve business objectives.
Delegates choose from the same 8 topics for their third and final discussion session:
- Data collection and integration
- Developing a data strategy
- Data Governance
- IoT and Sensors
- AI and Machine Learning
- Data Collaboration
- Predictive & Advanced Analytics
- Data Leadership
A deep dive into the value of data and the importance of it in an organisation.
- Bringing transparency to business data through data quality measurement and analytics enables an organisation to see the impact of poor data on the business result
- A single source of truth provides credible, holistic data insights and removes barriers caused by complex systems landscapes
- Integrating data with collaboration partners can build trust and strengthen relationships through the delivery of a common goal
- How to improve data transparency and organisation?
- What is best practice for standardising processes?
- How to Incentivise data-driven practices?
Delegates choose from the same 8 topics for their third and final discussion session:
- Data collection and integration
- Developing a data strategy
- Data Governance
- IoT and Sensors
- AI and Machine Learning
- Data Collaboration
- Predictive & Advanced Analytics
- Data Leadership
