A welcome from our Chairperson.
One of the key factors you need to take into account when setting up Data Governance is the IT landscape of the company. Heineken is a multinational FMCG company with 45 ERPs (SAP, JDE, Navision), each surrounded by ~15 satellite systems; Heineken has 80 OpCo’s, SSC, and Global HO. It can be quite challenging to set up Governance across such federated IT landscape, so I have prepared tips and ideas that I have seen and used in my own experience.
I will cover the following topics:
- Why was Data Governance needed (you might suspect it already),
- Data Governance Organization design, R&R,
- What documents and processes were necessary to make it work.
It was definitely an adventurous journey; we keep on learning and searching for improvements as we go. Join me in this session and perhaps you’ll find some inspiration on how to address your own “spaghetti”, as we jokingly say. Every joke has a bit of truth in it though; in fact, it is not that fun at all when there is a lack of Data Governance in your organization. I’m happy to see that there is more of us out there who want to change that, so let’s learn from each other. Sharing is caring, they say!
Advanced Data Analytics give manufacturers insight by identifying patterns, measuring impact and predicting outcomes. The ability to analyse equipment failures, production bottlenecks, supply chain deficiencies and enable better decision-making.
- How are manufacturers using advanced analytics to improve processes?
- What are the best ways of using raw data to create predictive data models?
- Which data analytics tools should I be using to gain insight into my data?
Looking at the complexities of integrating the environmental and financial aspects of a complete supply chain lifecycle, from manufacturing, packaging, warehouse distribution and consumption. How can an organization assess its environmental footprint whilst optimizing the end-to-end operations whilst managing outgoings and profitability?
- Environment impact
- Goal 13 – Climate Action
- Connecting data to deliver climate change
- Delivering outcomes
- Empower your decision making with the right asset intelligence, where do you start?
- Share use cases, goal setting, scope and plan. A solid roadmap is an essential part of any IoT project.
- Hear real-life examples from subject matter experts supporting manufacturers on the ground.
- Data collection and integration, the what, when, how, and why (and how much does it cost)?
- Is a data warehouse still a viable, cost effective approach?
- Data collaboration – overcoming the barriers
- Robust AI-enabled analytics to take advantage of data and optimise operations across the value chain
- Treating data as an asset and building trust as a foundation for a growth
- How should companies go about building an investment case for AI powered analytics?
- What best practice behaviours should be adopted to successfully deploy AI/ML in this context?
- What new business models are now possible because of AI/ML powered product quality and efficiency
- improvements?
- How can companies take advantage of AI/ML to become more efficient?
- What use cases of AI do you see being the most impactful?
- Empower your decision making with the right asset intelligence, where do you start?
- Share use cases, goal setting, scope and plan. A solid roadmap is an essential part of any IoT project.
- Hear real-life examples from subject matter experts supporting manufacturers on the ground.
Looking at the complexities of integrating the environmental and financial aspects of a complete supply chain lifecycle, from manufacturing, packaging, warehouse distribution and consumption. How can an organization assess its environmental footprint whilst optimizing the end-to-end operations whilst managing outgoings and profitability?
- Environment impact
- Goal 13 – Climate Action
- Connecting data to deliver climate change
- Delivering outcomes
- Data collection and integration, the what, when, how, and why (and how much does it cost)?
- Is a data warehouse still a viable, cost effective approach?
- Data collaboration – overcoming the barriers
- Robust AI-enabled analytics to take advantage of data and optimise operations across the value chain
- Treating data as an asset and building trust as a foundation for a growth
The data within organizations is growing faster than ever before, and massive investments are being made to store and manage this data effectively. However, turning data into actionable insights is one of the greatest challenges companies face today. Why? It’s often siloed and largely unstructured, making it difficult for employees to find what they need quickly and easily. Learn how leading organizations are connecting the dots across their information systems to boost productivity, minimize costs, and accelerate innovation.
Andy Stanford-Clark, Chief Technology Officer for IBM UK and Ireland, will describe the technology behind the Mayflower Autonomous Ship (MAS400.com), an un-crewed research ship designed to gather data about the ocean, particularly on the impacts of climate change and our pollution of the ocean on marine wildlife.
Andy’s keynote will cover:
- The AI Captain that controls it, focusing on the technology being used and its importance to the Industrial Sector.
- The scientific experiments that will be on board when MAS sets out imminently on a journey from Plymouth UK to Plymouth Massachusetts, commemorating the 400th anniversary of the original Mayflower crossing.
Join us for 15 minutes that will intrigue and excite you, followed by a five minute Q&A with Andy.
