4#5 - Olga Sergeeva - Data and AI in Modern FMCG Supply Chains (Eng)

MetaDAMA - Data Management in the Nordics

«We made a transition from being a company that produces a lot of data, to a company which has control over the data we are producing.»
Unlock the secrets of optimizing supply chains with data and AI through the lens of TINE, Norway's largest milk producer. Our guest, Olga Sergeeva, head of the analytics department at Tine, takes us on her journey from a passion for mathematics to spearheading digital transformation in the fast-moving consumer goods industry.
Ever wondered how organizations can successfully integrate AI tools into their business processes? This episode dives into the uneven digital maturity across departments and the strategies used to overcome these challenges. We discuss how data visualization tools act as a gateway to AI, making advanced algorithms accessible without needing to grasp the technical nitty-gritty. Olga shares how TINE’s data department empowers users by providing crucial expertise while ensuring they understand the probabilistic nature of AI-generated data.
Finally, discover how teamwork and a systematic approach can drive data adoption to new heights. From improving milk quality with predictive algorithms to optimizing logistics and production planning, we explore practical AI use cases within Tine's supply chain.
Here are my takeaways:

• Mathematics is a combination of beauty, art and structure.
• Find your way in data and digitalization before jumping on the AI-train.
• Ensure that people can excel at what they are best at - this is what Tine tries to do for the farmers.
• Data only has a value, when it can be used - find ways to use data from analytics to prediction to more advanced algorithms.
• Create a baseline through a maturity assessment to see how you can tailor your work to the different business units.
• Follow up and monitor the usage of your data tools in the different areas of your business
• Create a gateway into data for your business users: Once that gateway is established it is also easier to introduce new tools.
• Data Literacy has a limit - not everyone in the business needs to be a data expert.
• Yet you need someone you can trust to enable and provide guidance - the Data team.
• Business users need to understand the difference between concrete answers and probability.

• How do you transform a complex organization without breaking the culture?
• Your data/digital/AI transformation team is key in ensuring good transformative action without breaking culture.
• Ensure you have good ambassadors for your data work in the Business Units, that what to transfer their knowledge in their respective units.
• Create a network of data-interested people, that help to drive adoption.
• Engage people by showing an initial value.
• Offer courses and classes for people to learn and understand more, but also to spread the word about your focus points.
• Inhouse courses provided by your own staff can increase the confidence in your data team.

• AI can mean different things to different people. It is important to define AI in your setting.
• Don’t replace existing work process with AI-driven solutions, just for the sake of it. Find ways to focus on where improvement actually provides business value.
• When you think of a new AI project, you have several options:

1. Develop in house
2. Buy off the shelf
3. Do nothing

• Option two should be your preferred solution
• AI strategy is part of a larger ecosystem, with conditions to adhere to.
• Data and algorithms should become interconnected, also visually represented.
• «Always remember your core business.»

Kapitler

1. Data Management in the Nordics (00:00:00)

2. Enabling Data Adoption in Organizations (00:11:48)

3. Driving Data Adoption Through Teamwork (00:20:18)

4. Data-Driven Strategy for Supply Chain (00:25:49)

5. Digital Twin for Supply Chain Optimization (00:36:51)