The hottest Performance Metrics Substack posts right now

And their main takeaways
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The 2024 True Sack Rate (TSR): Week 7 Update

Trench Warfare • 79 implied HN points • 22 Oct 24
🎾 Sports Football Statistics Player analysis Performance Metrics
  1. The True Sack Rate (TSR) is a system that evaluates sacks by defensive linemen based on how they earned those sacks. It breaks down sacks into categories, helping to better evaluate a player’s skill and performance.
  2. There are four types of sacks in the TSR, ranging from rare high-quality wins over elite blockers to more common 'cleanup' sacks that are less about skill. This helps to highlight which players are truly impactful in games.
  3. Currently, top players in the TSR have recorded impressive sack scores, showcasing their effectiveness this season. Studying their performance can give fans deeper insights into who stands out on the field.

Thinking Like an Owner: Elevating Your Data Team's Impact In 2025

SeattleDataGuy’s Newsletter • 788 implied HN points • 30 Nov 24
💼 Business Data Analysis Team Management Career growth Performance Metrics
  1. Data teams should focus on projects that really matter to the business, not just completing tasks. It's important to pick work that makes a difference.
  2. Understanding how your business works is key to finding valuable projects. Ask questions about the data to see what's impacting your important metrics.
  3. Shift your mindset from being a regular team member to thinking like a business owner. This means taking initiative and seeking out projects that align with overall business goals.

Leading Effective Engineering Teams

Elevate • 1074 implied HN points • 18 Jan 24
💼 Business Team Dynamics Performance Metrics
  1. Google found that psychological safety is crucial for an effective team, along with dependability, structure and clarity, meaningful work, and impact.
  2. Team effectiveness is more about how team members collaborate rather than who is in the team.
  3. Creating a culture of psychological safety where team members feel comfortable taking risks and expressing themselves without fear of repercussion can significantly boost team performance.

Applying the Core 4 framework (Part 2)

Engineering Enablement • 11 implied HN points • 29 Jan 25
🕹 Technology Developer Productivity Software Engineering Business impact Performance Metrics Continuous Improvement
  1. Using Core 4 metrics helps link developer productivity projects to important business outcomes. This way, everyone can understand the impact of these projects.
  2. Investing in improving developer processes can save a lot of time and money. For example, fixing slow review times can free up hours that can be used for more productive work.
  3. Regularly measuring progress helps teams keep improving. It's important to revisit these metrics to find new areas to enhance and continue moving forward.
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AI multi-agents with corporate structures

Alex’s Substack • 66 HN points • 25 Jul 24
🕹 Technology AI agents Corporate culture Software Engineering Performance Metrics
  1. Having multiple teams competing against each other leads to better results for AI agents, just like it does in big companies.
  2. A system that relies on one leader to make decisions tends to perform worse, as it can create weak points if the leader fails.
  3. The way teams are organized influences how well they solve problems, and using effective structures can improve AI performance.

💰 Stock-Based Compensation Explained

How They Make Money • 707 implied HN points • 24 Mar 23
💰 Finance Investing Stocks Compensation Performance Metrics
  1. Stock-Based Compensation (SBC) is a remuneration strategy where companies reward employees with equity interests.
  2. SBC affects investors through ownership dilution, alignment of interests, and impact on company performance.
  3. There are different types of SBC such as stock options, restricted stock units, and performance shares, each with unique characteristics and implications.

Analytics should be an Assembly Line

Data Thoughts • 3 HN points • 10 Sep 24
💼 Business Data Analytics Business Intelligence Performance Metrics Cost efficiency
  1. Analytics should be handled like an assembly line to make it more efficient and accessible. This means creating standard processes to measure and track important business metrics.
  2. Most companies need to focus on basic descriptive analytics, which involves identifying and measuring key metrics. These metrics will help businesses understand what drives their success.
  3. Having well-defined metrics is essential before deeper analysis can happen. Insights from data come from well-measured processes, allowing teams to explore and understand their business better.

Output vs. Outcomes - Problem #4

Fish Food for Thought • 17 implied HN points • 27 Nov 24
💼 Business Management Strategy Product Development Performance Metrics Corporate culture
  1. It's important to focus on outcomes, not just outputs. Companies should ask themselves if their efforts really make a difference for customers.
  2. Measuring success by outputs can lead to short-term wins but might miss real problems. Companies should aim for quality and value instead of just quantity.
  3. Shifting to an outcome-driven approach means redefining success metrics. Businesses should prioritize customer satisfaction and engagement over just the number of tasks completed.

Productivity in Software Engineering: Beyond lines of code, the importance of experience in the development cycle

VTEX’s Tech Blog • 1 HN point • 18 Sep 24
🕹 Technology Software Engineering Productivity Developer Experience Quality Assurance Performance Metrics
  1. Productivity in software engineering is not just about how much code you write. It's more important to focus on code quality and how well the software works.
  2. At VTEX, they listen to developers to improve their work experience. This helps boost productivity by addressing the challenges developers face.
  3. Combining feedback from developers with quantitative data can help understand the impact of changes in tools and processes on productivity.

My biggest mistakes as a data-science team lead

inexactscience • 59 implied HN points • 27 Oct 23
💼 Business Leadership Data science Team Management Performance Metrics
  1. Leadership style should change based on each team member's skills and motivation. It's important to adjust how you lead as people grow and face new challenges.
  2. Focusing only on problems can lead to neglecting high performers. Instead of constantly putting out fires, you should aim to create overall value in the team.
  3. Using data to measure success in a team is crucial. Setting clear metrics helps you understand progress and ensure your efforts are effective.

Defying the Odds With Unconventional Strategies and Smarter Talent Scouting

Workforce Futurist by Andy Spence • 97 implied HN points • 23 Aug 23
🎾 Sports Football Data Analytics Success Strategies Performance Metrics
  1. Talent scouting in football shows the value of unconventional strategies and data-driven decisions.
  2. Underdogs in any industry can succeed by being innovative and leveraging data analysis like Leicester City did in football.
  3. Adopting new approaches like Total Football or Agile methodology can lead to collective success and continuous improvement.

Introducing Etalon: How we choose a LLM with optimal Runtime Performance ?

Machine Learning Diaries • 3 implied HN points • 11 Nov 24
🕹 Technology Machine Learning AI Models Performance Metrics User Experience
  1. Evaluating large language models (LLMs) is important for ensuring a good user experience. Existing metrics like Time to First Token (TTFT) and Time Between Tokens (TBT) don't fully capture how these models perform in real-time applications.
  2. The proposed 'Etalon' framework offers a new way to measure LLMs using a 'fluidity-index' that helps track how well the model meets deadlines. This ensures smoother and more responsive interactions.
  3. Current metrics can hide issues like delays and jitters during token generation. The new approach aims to provide a clearer picture of performance by considering these factors, leading to better user satisfaction.

Issue #9 - Board, Are You Ready for AI Unknowns?

OSS.fund Newsletter • 0 implied HN points • 14 May 25
💼 Business AI Governance Corporate strategy Risk management Performance Metrics
  1. AI governance is becoming a critical focus for boards due to rising data, legal pressures, and new regulations. Companies now need to track their AI progress with scorecards every quarter.
  2. Boards are looking at five key performance indicators (KPIs) to measure AI effectiveness. These include adoption rates, financial performance, and risk management.
  3. There's a growing need for collaboration among different departments in companies. No single team should handle AI oversight alone; a cross-functional approach is key to successful AI governance.

Objectivity and its Discontents

the best of a great lot • 0 implied HN points • 13 Sep 23
💼 Business Decision-making Performance Metrics System Design
  1. Data-driven decisionmaking in businesses aims to be objective by relying on numeric metrics to minimize human biases.
  2. Objectivity can create an illusion of completeness and can be manipulated to support pre-existing beliefs.
  3. Goodhart's Law warns that using measures as targets can lead to negative outcomes as individuals may prioritize meeting the measure over the original goal.

January 2018 Data Update 7: Growth and Value

Musings on Markets • 0 implied HN points • 27 Jan 18
💰 Finance Investing Corporate Finance Market Analysis Data Analysis Performance Metrics
  1. Profitability is measured using various profit margins, which help assess how well a company is doing. It’s important to choose the right measure based on what you're analyzing, like gross margin for efficiency or net margin for overall profitability.
  2. Excess returns show how much a company earns above its cost of capital, and most companies struggle to achieve this. Many firms aren't making enough money to cover their investments, highlighting a risk in company performance.
  3. Regional, sector, and size factors influence company profits. For instance, smaller companies often perform worse than larger ones, and certain industries, like technology, can produce high returns while others, like retail, may struggle.

Is your CEO worth his (her) pay? The Pricing and Valuing of Top Managers!

Musings on Markets • 0 implied HN points • 29 Apr 15
💼 Business Corporate Governance Market Dynamics Performance Metrics
  1. CEO pay has increased significantly over the years, often rising faster than employee wages, and is often tied to stock performance.
  2. Many CEOs are compensated based on market trends rather than their actual performance, which can lead to overpayment.
  3. Good corporate governance is needed to ensure that shareholders can effectively influence CEO compensation decisions.

Hedging hedge funds have higher (h)returns

Klement on Investing • 0 implied HN points • 12 Nov 24
💰 Finance Investing Hedge Funds Risk management Market Analysis Performance Metrics
  1. Hedge funds can actually reduce their risks internally, which helps them perform better. They don't just rely on external factors.
  2. Most hedge funds have realized risks that are lower than expected, known as a negative risk gap. This can boost their overall returns.
  3. Funds that manage their risks well tend to have higher performance, while those that take on more risks often do worse.