Intended Audiences:

• Data Scientists who want to successfully drive machine learning in their organization and want to make their way to the Head of Data & AI or Chief Data & AI Officer.
• Business Professionals & Managers who want to transform their company into a data-driven & AI-powered business and innovate data & AI products.
• Product & Project Managers who are responsible for data & AI solutions and want to accelerate design, development, and delivery.

Goals:

1. Understand the key success factors behind an effective Data & AI strategy—and what it takes to build a truly data-driven, AI-powered business.
2. Gain the skills to design a tailored Data & AI strategy for your organization
3. Learn how to facilitate impactful workshops that inspire collaboration and buy-in from your key stakeholders.

Content:

Most (~80%) data & AI projects fail. And they fail right from the start – because they are implemented for the wrong reasons: because of FOMO, because of the AI hype, because of misbelief in technology. They fail due to a lack of user acceptance, a lack of data (quality) and a lack of business value.

The antidote is data & AI strategy. A data & AI strategy guides your data science team through the data swamps and AI jungles and leads your data & AI projects towards the high value, low risk applications. It aligns your data & AI initiatives with the business initiatives, integrates data & AI into the business model and connects data & AI experts with the business domain experts. It ensures mutual understanding and acceptance and thus accelerates your team and your company. It helps you do less, better.

However, most companies are doing it wrong: a data & AI strategy is neither a superficial PowerPoint presentation nor a detailed plan for the next five years that will take you months to develop. What you need is a Lean Data & AI Strategy. A Lean Data & AI Strategy defines the goals, localises your current position and outlines the best roadmap to the results. That way, everyone knows what needs to be done, how it needs to be done and why it needs to be done.

In this workshop, you will learn how to develop a Lean Data & AI strategy in one day using concrete practical examples and interactive group exercises. We will use the free and freely available Miroverse Lean Data & AI Strategy template. You will get to know numerous useful visual collaboration tools such as the Analytics & AI Maturity and Data Monetization Canvas. And you’ll learn what makes a good Lean Data & AI Strategy and how it helps your Data & AI team collaborate better with the business and achieve more in less time.

Agenda:

8:30 am Registration
9:00 am Presentation of agenda and introduction of participants
9:15 am Lecture: The Why, What & How of a Lean Data & AI Strategy
10:30 am Coffee break
11:00 pm Practice I: How to ideate & prioritize analytics & AI use cases.
12:30 pm Lunch break
1:30 pm Practice II: How to assess the analytics & AI maturity and plan a roadmap.
3:00 pm Coffee break
3:30 pm Practice III: How to design Data & AI Products, the Data & AI Architecture and the Data & AI Organization.
4:45 pm Open feedback and Q&A session
5:00 pm End of workshop

Trainer:

With his strategy consultancy Datentreiber, Martin Szugat supports companies in their transformation to data & AI business models and processes with strategy workshops, hands-on consulting and interactive trainings. His clients include companies such as Roche, Nestlé, Kühne+Nagel, Axel Springer and Schaeffler. Since 2014, he has served as program director for the Machine Learning Week Europe conferences in Europe. He is lecturing on Data & AI Strategy, Business and Transformation at the Hochschule für Wirtschaft in Zurich, Steinbeis University, Steinbeis Augsburg Business School and the International Space University.

Testimonials

“Participating in the Datentreiber’s Data Thinking certification was a successful investment in my professional skills as a Data Scientist. With the help of the training, I can align my daily work more closely with the business model, objectives, the users, and the data landscape at Axel Springer. Furthermore, I have learned the tools to identify new analytical use cases from a user perspective and examine them for their business viability.”
– Justin Neumann, Data Scientist, Axel Springer SE

“I really enjoyed the Data Business seminar. Martin is very friendly and also very competent. I especially liked the good mix of content and application examples. It met my expectations, that’s why I find the seminar recommendable.”
– Irmen Rebai, Senior Manager Digital Transformation, EnBW Energie Baden-Württemberg AG

“As a keynote speaker on the topic of Data Science, Martin Szugat was able to bring strong impulses into the organisation within the framework of “Data Thinking” and has thus brought the topic of data strongly to the fore within the framework of the digital transformation at Roche. Furthermore, Martin successfully supports us in the development of an overarching data strategy in Roche Diagnostics GmbH through the moderation of workshops, which exhibits the company in a future-oriented way. Martin will continue to accompany us on this path.”
– Nadja Schaefer, Digital Transformation Manager at Roche Diagnostics GmbH

For more reviews and customer testimonials check Google and YouTube.

Datentreiber Client Thomas Knauer – Datentreiber Acknowledgement