DoorDash’s Post

Interesting thoughts from the VP of Analytics at DoorDash in favor of a centralized analytics team vs decentralized analysts embedded within siloed departments. Pros and cons to either, depending on the org and culture, in my opinion- regardless, I do fully appreciate the benefits Jessica brings up in this video! Thoughts? Have you experienced pros or cons of either model?

A good watch to everyone who respect #data and wish to create good #impact to the business! Few topics which Lenny Rachitsky curated are below: - Centralized vs. embedded analytics teams. - Balancing proactive and reactive work. - Advice on how to push back or question effectively to get more clarity. - Hiring for curiosity and problem solving. - Encouraging cross-functional roles. - Defining effective metrics & Simplifying metrics for better outcomes. - Focusing on edge cases and fail states. - Managing a global data organization. - Leveraging AI for productivity. - Building diverse and skilled data teams.

There's rarely a one-size-fits-all... Amazon Web Services (AWS) presents the concept of "The Modern Data Community," advocating for a shift from monolithic data organisations to a decoupled model. In this approach, central Data teams focus on providing technology that enables distributed consumers and producers to self-serve in discovering, using, and publishing data across the organisation. This model aims to increase autonomy, ownership, and speed in data operations. AWS does also note that "the level of decentralisation depends on maturity of skills, complexity of business, domain knowledge required, and pace of tech change".

Solid work Jessica Lachs! The part about working on edge-cases that are most problematic is golden! I highly recommend searching them out and solving them. It may not put a dent in overall volume of complaints but they most often than not greatly improve experience and compound in value over time. I know this first hand because when we did this, the comments section on our customer support channels went from outright bodily harm to our executives (no, not a joke) to customers asking to sign on as ambassadors and asking how to work for the bank. #products #metrics #data #analytics #growth #retention

I really enjoyed this podcast with Jessica Lachs , the Global Head of Analytics & Data Science at Doordash. She believes in centralizing data teams and giving them ownership not just to create dashboards, reports, and models to explain the what and the why, but also to determine the so what and design strategies to generate revenue from the insights derived from data. I'm tired of seeing data scientists in companies with zero alignment between their analyses and the business, which means they don't truly understand the data they work with and aren't motivated to go beyond to demonstrate that a company that takes data seriously can achieve the highest ROI. To achieve this, she structures the data team into its own divisions with ownership in marketing, sales, customer success, etc., instead of embedding data scientists in those teams. Another interesting point she mentions is that composite metrics like the customer health score ultimately become meaningless because they are confusing to interpret. It's better to have 3 or 4 more specific metrics that can be linked to concrete actions. And then go deeper into other proxy metrics one by one.

"🍕 Basic But Exciting Data Analysis Project! 📊🔍 I dove into the sales data of a pizza company, uncovering trends, identifying top-performing products, and visualizing key insights . 📈💡 Pizza lovers, you won't believe what the numbers reveal! 🤓🍕 #DataAnalysis #PizzaSales #ExcelMagic" #dataanalytics #dataanalyst #dataanalyticsjourney #datacleaning #datavisualization

"🚀 Unleash your inner data ninja! 🥷📊 When business meets stats, magic happens! 💼✨ Example: A pizza shop owner used regression analysis to predict topping demand. Result? 50% less waste, 30% more profit! 🍕📈💰 Are you ready to crunch numbers and dominate your market? Let's get statistical! 🤓💪 #DataDrivenSuccess #BusinessStats"

“Making the data talk is what I love the most in my job” 🔥 Words from Kevin Robert, Head of Data at Le Wagon. Don't just follow the #data; be the one who interprets its story. Join us for a deep dive into the 3 essential roles played by the data team in strengthening our data-driven #strategy.

Excited to share my recent project where I dove deep into Walmart's data! From data cleaning to insightful data visualizations and analysis, I uncovered valuable insights that can help businesses make data-driven decisions. 📊💡 #DataAnalysis #DataVisualization #WalmartAnalysis #DataInsights

Day 13 of 100 Days of Data Analytics! 🚀 Excited to announce the completion of my coffee sales dashboard! 📈 It provides valuable insights into location trends , weekly patterns, monthly reports, and more. Below are screenshots and videos showcasing its functionalities. Grateful for the hands-on experience and looking forward to applying these insights in future projects! ☕️ #DataAnalytics #DashboardDesign #CoffeeSales #100DaysOfDataAnalytics