Clubhouse

Thanks for coming, Clubhouse mate!

💥 Ask me about cohosting the room about data visualization, innovation, self-development.

Let’s talk on Clubhouse! Contact me to discuss details: Linkedin profile | monika(at)labmp.com

Speakers: Monika Piekarska (LabMP), Nic Prausa, Daniel Althaus

Key takeaways:

  1. Financial literacy is more important than ever. Data storytelling in finance & investing must be emotionless. Machine learning blurs out FUD and FOMO. It is beyond traditional quant. Data-backed interpretation of the current state is a foundation for human decision-making.
  2. Dealing with reporting for multiple stakeholders is a headache. Start with audience personas, system design, and reporting purpose (operational, analytical, executive one).
  3. Dynamic vs static reports. Static reports are satisfactory when you want to convey one message. Interactive reports give more flexibility for data exploration, including dynamic historical trendlines and what-if scenarios.
  4. Don’t show all raw data at once. Show high-level info as a starting point. Then jump to the context and more descriptive details.

 Webinar:

SAP Innovation Awards 2021 selected our predictive planning project as one of the finalists. Join the FP&A Trends webinar to learn more about the project:

Speakers: Monika Piekarska (LabMP), Paulina Davila, Hanieh Nasrollahi

Key takeaways:

  • Successful implementation of data storytelling to business is multi-layered.
  • Understand your data. Start from data governance, data quality and statistical exploration.
  • Be obsessed with delivering a meaningful message to your audience. Work on data culture across all organization levels. Show them the power of visual analytics. Inspire them to act agile way and be 100% stakeholder-centred.
  • Use cognitive psychology to summarize data. Viz responsibly.
  • Self-service analytics is a challenge. Improve data literacy among the audience. Create short and sweet materials.
  • Educate your audience about visual best practices. Show them hard evidence of why it works and why it supports their decision-making process.

Resources:

Color-blindness validators: