TUMO Labs

About the Project

Businesses have suffered the most due to events in recent years. Their current state: unstable. Their future: unpredictable. Solutions to the various challenges must be evidence-based instead of being developed with various tools and personal judgement. Plans must be optimized using modern technologies and predictable scenarios.

The “Extended Planning and Analysis” project by TUMO Labs and the world’s leading enterprise software company SAP, consists of four challenges to which you may apply individually or as a team.

Project Start Date: Nov 5, 2021
Duration: 3-4 months
Language: English
Format: Online
Deadline to apply: October 31, 2021
Fee: Tuition-free
Eligibility: Anyone over 18 with the required pre-existing skills, individually or in a team.

Attention: it’s possible to apply to multiple challenges, but you must choose one for your final project.

Registration is closed

Now more than ever, scenario planning is crucial amid global business instability. Modern technology is capable of simulating thousands of scenarios in mere seconds, and recent advancements in AI technologies surpass human pattern recognition abilities.

The aim of this challenge is to review state-of-the-art techniques and best practices in the area of machine-aided scenario creation.

Expected outcome:

  • Collection of scenario identification/creation techniques.
  • Evaluation of strengths and limitations.

Prerequisites:

Students or young experts in the STEM field (Science, Technology, Engineering, Mathematics).

Machine learning and machine reasoning technology promise to supply users with insights that are often out of reach of human pattern recognition abilities and bandwidth. Hence, such results can seem surprising at first. Communicating to the user how a system arrived at a particular conclusion is a key factor in gaining trust, and ultimately acceptance.

Expected outcome:

  • Review of common approaches and best practices for Explainable AI/Machine Reasoning from a user experience standpoint, including their strengths and limitations.
  • Design of novel approaches to convey how machine learning/reasoning implementations arrive at particular results and conclusions.

Prerequisites:

Students or young experts with UX, IXD or related experience may participate in the challenge.

The purpose of this challenge is to survey existing tools and solutions used for
scenario planning, identify key competitive players, and classify solutions based on characteristics such as customer base, end user profile, capabilities, industry, and
so on.
In particular, with machine learning being incorporated into planning approaches,
the analysis should include this as a further dimension for understanding today’s
scenario planning tools.

Expected outcome:

  • Competitor analysis.
  • Product capability analysis.
  • Classification of competitors and products into key dimensions.
  • Evaluation of machine learning incorporation into products (e.g. maturity, benefit provided, data sources).

Prerequisites:

Students or young experts in business or related fields may participate in the challenge.

Steering an enterprise means to navigate an ocean of uncertainties, bearing risks
and opportunities alike. These range from the introduction of new governmental
regulations, over extreme weather, all the way to events such as the current global
pandemic.

Both, machine-predictions and reasoning are often challenged by events that cannot
be easily categorized based on past examples. This challenge aims to
explore ways to predict links between distinct events (e.g. sourced from news feeds)
and key business drivers.

Expected outcome:

  • Students will review state-of-the art techniques, including their strengths and limitations.

Prerequisites:

Students or young experts in the STEM field (Science, Technology, Engineering, Mathematics).