Our story behind data success | Stefan Kreihsler | TEDxTUWien

TL;DR

Only three out of every 100 data projects deliver value to the business, but by following the principles of knowledge, goals, and actions, companies can improve their success rate.

Transcript

Transcriber: Elisabeth Buffard Reviewer: Walaa Mohammed 2023 will be remembered as the year in which AI became mainstream. And yet we observe how difficult it is for companies to successfully implement data projects. Did you know that, shockingly, only three out of every 100 data projects managed to deliver value to the business? Today, I want to s... Read More

Key Insights

• 📽️ Knowledge of the domain is essential for successful data projects.
• 😫 Setting clear goals and objectives helps avoid chaos and inefficiency.
• 🥡 Taking action, even in uncomfortable situations, is necessary for progress.
• 😨 Vienna's public transport system design affects car usage patterns.
• 😤 The team at Upstream Mobility successfully implemented 40 data projects.
• 🥅 The speaker emphasizes the importance of the three principles: knowledge, goals, and actions.
• 🖤 Lack of clear objectives can hinder progress in data projects.

Questions & Answers

Q: How many data projects successfully deliver value to the business?

Shockingly, only three out of every 100 data projects manage to deliver value to the business. This low success rate emphasizes the need for improvement in implementing data projects.

Q: What is the significance of acquiring knowledge in data science projects?

Acquiring knowledge about the domain you are working in, such as data science and the mobility sector, is crucial. This understanding helps in unraveling insights and making better decisions, such as understanding why people in Vienna prefer cars over public transport.

Q: Why is it important to set clear goals in data projects?

Lack of clear objectives often leads to chaos and inefficiency in data projects. Even if the team is working towards the same goal, losing sight of that goal or getting stuck in details can hinder progress. Setting clear goals ensures everyone is aligned and focused on the desired outcomes.

Q: Why is taking action often difficult in data projects?

Taking action can be challenging because it involves stepping out of comfort zones. In some cases, it may be uncomfortable to have conversations or make decisions that can lead to improvements. Fear of failure, risk aversion, or lacking the necessary tools can also make taking action difficult.

Summary & Key Takeaways

• The speaker, Stefan, shares three key principles for successful data projects: knowledge, goals, and actions.

• Acquiring domain knowledge is crucial for understanding the field you're working in, such as data science and the mobility sector.

• Setting clear objectives and ensuring everyone is working towards the same goals is essential to avoid chaos and inefficiency.

• Taking action is often difficult but necessary, as it can lead to improved outcomes even in uncomfortable situations.