SpatzAI Empowering Bold Idea Sharing, Spat by Spat

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SpatzAI Empowering Bold Idea Sharing, Spat by Spat. SpatzAI - Real-time objection app & peer review network to create a psychologically safe environment for innovative teams. Empowering members to resolve their spats before they escalate or are ignored, encouraging more innovative, yet objective teamwork.

Leadership & Management

THE PROBLEM
Innovators in teams hesitate
to share their radical ideas
due to the lack of protection
from being browbeaten.
“Erk!! That’ll never work!!”

THE PRODUCT - TOOLKIT
We’re Building a spat resolution toolkit, while using the
SpatzAI real-world LLM data for predicting team success or failure.
Intervention
Charter
Agreement
3-Step
Objection
Application
Data Collection
for SpatzAI
Machine Learning
Democratic
Peer-Review
Network

OUR UNIQUE PSYCHOLOGY
OUR (SPECIAL SAUCE) UNDERSTANDING OF…
1. Objecting vs. Disagreeing or Complaining.
2. Effects of Unresolved Spats (micro-conflicts) on teams.
(Research-Based Insights)
3. Upside of Uncertainty vs. Dogmatic Language.
4. Inclusion of the Least Powerful Voices.
5. Accountability for Misbehavior.

FINDING & CONVERTING LEADS
• Promote research pilot results.
• Create plugins for team Atlassian, Slack & Scrum
• Product demos, free trials, and personalized outreach.
• Using online channels like LinkedIn
• Also leveraging offline HR networking and referrals.

MARKET SIZE (TAM)
• 500,000 tech companies in the USA alone
• 5 million tech employees.
• TAM at $2 per team member user per month
• $120 million per year.

WHY I AM BACKABLE
• 20 years developing, aiming to be commercial
within 2 years.
• Self-published 2012 book, 760 blog posts, 50 journals.
• Trained product designer – industrial designer.
• Tech expertise in creating a successful insurance startup,
Tripcover, reaching $1M in annual sales in AU and NZ

HOW MUCH MONEY
• $30,000 to 50,000
WHAT WE WILL DO WITH IT
• Run a pilot of some 100 participants for 1 month.
With 50 SpatzAI users and 50 control group.
• Contracting AI data specialist and psych researcher.
• Fully develop the App and network plugin.

Contact: Desmond Sherlock
Website: Spatz.ai
Email: des@spatz.ai
Blog: Object123.com
Linkedin: linkedin.com/in/tripcover
Disclaimer: The information contained in this pitch
is speculative and needs to be tested and should only
be used in agreement with all team members.
Thanks for watching
our presentation.

This document proposes a toolkit called Spatz AI that aims to protect team members from minor conflicts ("spats") when sharing bold new ideas, in order to promote psychological safety. The toolkit uses machine learning on real-world data to predict team success/failure and provides tools like an intervention charter and democratic peer review process. An MVP has been created and the founder is seeking funding to pilot the toolkit with 100 participants over 1 month to collect data and further develop the app and plugins. The goal is to help innovative teams and ultimately reach the $120 million annual market in the tech industry.

SpatzAI Powering Bold Idea Sharing in Teams Spat by Spat

Desmond Sherlock

SpatzAI Powering Bold Idea Sharing Spat by Spat

Desmond Sherlock

This document proposes a toolkit called Spatz AI that aims to protect team members from minor conflicts ("spats") that discourage bold idea sharing. The toolkit uses machine learning on real-world data to predict team success/failure and provides tools like an intervention charter and democratic peer review. The goal is to commercialize the research by 2024 by developing apps/plugins for team tools and conducting a pilot program. Funding of $50-100k is requested to run the pilot program and further develop the products.

SpatzAI - Powering Bold Idea-sharing in Teams Spat by Spat

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This document proposes an AI-powered tool called Spatz AI to help resolve conflicts or "spats" within innovative teams. It aims to objectively assess unfair challenges to ideas to prevent team members from avoiding challenging ideas. The solution would create an app and network plugins to acknowledge issues, accept apologies, and provide consistent accountability. With $50-100k, the founders plan to complete an MVP, run a pilot test with 100 participants, and further develop the app and network integration. The goal is to help the 500,000+ tech companies and 5 million tech employees better manage conflicts within teams.

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The document proposes a solution called SpatzAI Referee Toolkit to help resolve disputes and conflicts within innovative teams. The toolkit uses a team charter, 3-step procedure app, and SpatzAI data analysis to determine unfair behavior. It compares data from a pilot group of 100 members where 2659 potential disputes were resolved. The market opportunity is estimated at $120 million per year serving 500,000 tech companies. Funding of $50-100K is requested to complete an MVP and pilot with 100 participants.

SpatzAI - Powering Bold Idea-sharing in Teams Spat by Spat

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The document proposes an AI referee toolkit called Spatz to help resolve unfair behavior, disputes, conflicts and "spats" in innovative teams. The solution includes a team charter, 3-step procedure app, AI analysis of team dynamics, and assisted review platform. It provides examples of how the toolkit could resolve various issues like disputes, conflicts and spats based on comparative pilot data. The potential market size is estimated at $120 million per year given the number of tech companies and employees. Funding of $50-100k is requested to complete an MVP and pilot with 100 participants.

SpatzAI - Powering Bold Idea-sharing in Teams Spat by Spat

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The document proposes an AI referee toolkit called Spatz to help resolve disputes and conflicts within innovative teams. The toolkit would use a team charter, 3-step procedure, and app to analyze team dynamics and assist in reviewing incidents. An MVP has been created including branding, algorithms, and manual testing. The potential market is large at $120 million per year serving 500,000 tech companies. Funding of $50-100K is requested to complete the MVP, run a pilot test, and further develop the app and network plugins.

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This document proposes a platform called SpatzAI that uses machine learning to help innovative tech teams share radical ideas without fear of unfair criticism. It would analyze team interactions and predict success/failure. The toolkit includes tools like an objection app and Slack plugin to facilitate democratic discussions. With $50,000, the founder plans to pilot the tools with 100 people on 10 teams for a month to test the SpatzAI algorithm and further develop the product. The goal is to help innovative teams feel comfortable sharing new ideas to increase creativity and success.

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This document describes a proposed SpatzAI Referee Toolkit that aims to address unfair criticism and uncertainty in innovative teams. The toolkit would include a team charter agreement, an AI assistant to analyze team data and assist in dispute resolution, and a team review platform. It would help resolve disputes, conflicts and criticisms in a constructive manner. The proposed toolkit has potential in the large market of tech companies and employees, and $50k-$100k of funding would allow developing an MVP and pilot program to test the toolkit's effectiveness.

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This document presents a toolkit called the SpatzAI Referee Toolkit that aims to address unfair criticism and uncertainty in innovative teams. It uses a three-step process including a team charter agreement, team data analysis using an AI agent, and a team-assisted review platform. The toolkit is meant to help resolve disputes, conflicts, and criticisms in a healthy manner for technology and design companies. It has been researched for 20 years and the founder has experience in founding two successful startups. With $50-100k funding, the founder plans to complete an MVP, run a pilot program, and further develop the app and network plugins.

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This document describes a referee toolkit called SpatzAI that aims to address unfair challenges to ideas in teams and help resolve minor disputes. It works by having teams agree to a charter and using a 3-step app procedure along with AI data analysis of team dynamics. The toolkit would provide official cautions, objections, and stops to discourage unfair challenges and assist in resolving disputes. It has the potential to help the many tech companies and their employees avoid issues caused by the loudest voices always winning. Initial testing of an MVP has shown promise in resolving conflicts. Funding of $50-100k is requested to further develop the app and network plugin and conduct a larger pilot test.

SpatzAI Empowering innovative team members to safely address browbeating and ...

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This document summarizes a proposal to develop a platform called SpatzAI that uses machine learning to help innovative teams share ideas without fear of criticism. It will collect data on team discussions and interactions to predict future success or failure. The proposal requests $50,000 to pilot the tool with 10 teams, fully develop the app and plugin, and hire additional support. The founder cites their experience developing a similar insurance startup and research on resolving conflicts to demonstrate their qualifications to lead this project.

SpatzAI - A referee toolkit to protect bold ideas

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This document describes a referee toolkit called SpatzAI that aims to address unfair play and reduce uncertainty for innovative teams. It uses a three-step process including a team charter agreement, team data analysis, and a team-assisted review platform. The toolkit standardizes disputes and conflicts using a large language model and provides feedback categorized from caution to objections. It has the potential to help the 500,000 tech companies in the US by resolving issues for teams in a fair and data-driven manner. The creator is seeking $50,000-$100,000 to further develop an MVP and pilot the toolkit.

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This document presents a referee toolkit called SpatzAI that aims to address unfair idea challenges and minor disputes within innovative teams. The toolkit employs a team charter, 3-step procedure app, and AI data analysis to analyze team dynamics and assist in resolving conflicts. It also provides a comparative data example from a pilot test showing how the toolkit helped resolve various disputes, conflicts, and minor spats within a hypothetical 100-person team over one week. The proposed solution aims to serve the 500,000 tech companies in the US with 5 million tech employees, representing a total addressable market of $120 million per year.

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This document proposes a referee toolkit to help address unfairness and resolve disputes when challenging ideas in innovative teams. The toolkit would include a team charter, procedures app, and AI data analysis to analyze team dynamics. It would provide guidelines for acceptable challenges and apologies. An MVP has been created including branding and principles. Funding of $50k-$100k is requested to pilot the toolkit with 100 participants and further develop the app and network plugin.

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SpatzAI Empowering innovative team members to address browbeating and unfair ...

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SpatzAI - Real-time objection app & peer review network to cultivate a psychologically safe environment for innovative teams. Empowering members to resolve their spats before they escalate or are ignored encouraging more innovative yet objective teamwork. The SpatzAI is a toolkit that can be implemented and agreed to within teams to protect each other from overly dogmatic and absolute naysaying during difficult discussion. The toolkit consists of the Spatz charter agreement, the Spatz 3-step objecting app, the Spatz peer review network and the Spatz AI LLM for machine learning for predicting the success or failure of teams. The objective of SpatzAI is to create a more objective environment by objecting in real-time to any minor browbeating from misbehaving naysayers. By providing teams with a simple yet effective intervention for resolving their minor spats team members will feel more confident to share their most radically innovative thoughts and ideas freely.

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The document describes a proposed referee toolkit called SpatzAI that uses artificial intelligence to help resolve disputes and conflicts within teams in a fair manner. It analyzes team data and interactions to identify potential issues. When issues arise, it facilitates a review process with the team to achieve resolution. The goal is to create a psychologically safe environment where team members feel comfortable collaborating without fear. It also provides market sizing information, details on how the solution works, and a request for funding to further develop the minimum viable product.

SpatzAI - A referee toolkit to address unfair play in teams

Desmond Sherlock

The document proposes a referee toolkit called SpatzAI to address unfair play in teams. It consists of a team charter agreement, a 3-step app with an AI agent for team data analysis, and a team review platform. The toolkit aims to create psychological safety for teams by acknowledging and resolving disputes, conflicts and issues in a protected way without fear of repercussions. It provides examples of how the toolkit could work and analyze team data, as well as the potential market size and need for such a solution given the number of technology companies and employees. Funding of $50-100k is requested to complete an MVP and pilot the solution with test groups to gather feedback.

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The Ready-Made Garments (RMG) industry in Bangladesh is a cornerstone of the economy, but increasing costs and stagnant productivity pose significant challenges to profitability. This study explores the implementation of Lean Management in the Sampling Section of RMG factories to enhance productivity. Drawing from a comprehensive literature review, theoretical framework, and action research methodology, the study identifies key areas for improvement and proposes solutions. Through the DMAIC approach (Define, Measure, Analyze, Improve, Control), the research identifies low productivity as the primary problem in the Sampling Section, with a PPH (Productivity per head) of only 4.0. Using Lean Management techniques such as 5S, Standardized work, PDCA/Kaizen, KANBAN, and Quick Changeover, the study addresses issues such as pre and post Quick Changeover (QCO) time, improper line balancing, and sudden plan changes. The research employs regression analysis to test hypotheses, revealing a significant correlation between reducing QCO time and increasing productivity. With a regression equation of Y = -0.000501X + 6.72 and an R-squared value of 0.98, the study demonstrates a strong relationship between the independent variables (QCO downtime and improper line balancing downtime) and the dependent variable (productivity per head). The findings suggest that by implementing Lean Management practices and addressing key productivity inhibitors, RMG factories can achieve substantial improvements in efficiency and profitability. The study provides valuable insights for practitioners, policymakers, and researchers seeking to enhance productivity in the RMG industry and similar manufacturing sectors.

Impact of Effective Performance Appraisal Systems on Employee Motivation and ...

Dr. Nazrul Islam

Healthy economic development requires properly managing the banking industry of any country. Along with state-owned banks, private banks play a critical role in the country's economy. Managers in all types of banks now confront the same challenge: how to get the utmost output from their employees. Therefore, Performance appraisal appears to be inevitable since it set the standard for comparing actual performance to established objectives and recommending practical solutions that help the organization achieve sustainable growth. Therefore, the purpose of this research is to determine the effect of performance appraisal on employee motivation and retention.

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Samirsinh Parmar

Disaster management; Cyclone Disaster Management;; Biparjoy Cyclone Case Study; Meteorological Observations; Best practices in Disaster Management; Synchronization of Agencies; GSDMA in Cyclone disaster Management; History of Cyclone in Arabian ocean; Intensity of Cyclone in Gujarat; Cyclone preparedness; Miscellaneous observations - Biparjoy cyclone; Role of social Media in Disaster Management; Unique features of Biparjoy cyclone; Role of IMD in Biparjoy Prediction; Lessons Learned; Disaster Preparedness; published paper; Case study; for disaster management agencies; for guideline to manage cyclone disaster; cyclone management; cyclone risks; rescue and rehabilitation for cyclone; timely evacuation during cyclone; port closure; tourism closure etc.

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SpatzAI Empowering Bold Idea Sharing, Spat by Spat

1. Empowering Bold Idea Sharing, Spat by Spat.

2. Managers, and HR of tech companies with innovative teams. IDEAL CLIENT PROFILE (B2B)

3. THE PROBLEM Innovators in teams hesitate to share their radical ideas due to the lack of protection from being browbeaten. “Erk!! That’ll never work!!”

4. THE PRODUCT - TOOLKIT We’re Building a spat resolution toolkit, while using the SpatzAI real-world LLM data for predicting team success or failure. Intervention Charter Agreement 3-Step Objection Application Data Collection for SpatzAI Machine Learning Democratic Peer-Review Network

5. OUR UNIQUE PSYCHOLOGY OUR (SPECIAL SAUCE) UNDERSTANDING OF… 1. Objecting vs. Disagreeing or Complaining. 2. Effects of Unresolved Spats (micro-conflicts) on teams. (Research-Based Insights) 3. Upside of Uncertainty vs. Dogmatic Language. 4. Inclusion of the Least Powerful Voices. 5. Accountability for Misbehavior.

6. FINDING & CONVERTING LEADS • Promote research pilot results. • Create plugins for team Atlassian, Slack & Scrum • Product demos, free trials, and personalized outreach. • Using online channels like LinkedIn • Also leveraging offline HR networking and referrals.

7. MARKET SIZE (TAM) • 500,000 tech companies in the USA alone • 5 million tech employees. • TAM at $2 per team member user per month • $120 million per year.

8. WHY I AM BACKABLE • 20 years developing, aiming to be commercial within 2 years. • Self-published 2012 book, 760 blog posts, 50 journals. • Trained product designer – industrial designer. • Tech expertise in creating a successful insurance startup, Tripcover, reaching $1M in annual sales in AU and NZ

9. TRACTION & RESULTS • MVP consisting of a 3-page messaging app. • The SpatzAI Slack network, website and brand • The SpatzAI charter agreement, LLM algorithm. • Five guiding principles (see Our Unique Psychology). • The SpatzAI manual and anecdotal testing and feedback.

10. HOW MUCH MONEY • $30,000 to 50,000 WHAT WE WILL DO WITH IT • Run a pilot of some 100 participants for 1 month. With 50 SpatzAI users and 50 control group. • Contracting AI data specialist and psych researcher. • Fully develop the App and network plugin.

11. Contact: Desmond Sherlock Website: Spatz.ai Email: des@spatz.ai Blog: Object123.com Linkedin: linkedin.com/in/tripcover Disclaimer: The information contained in this pitch is speculative and needs to be tested and should only be used in agreement with all team members. Thanks for watching our presentation.

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