Leading and Managing Teams on a Global Scale: Insights from Etsy Engineering
Introduction:
Introduction: Managing globally distributed teams has become a common practice in today’s business landscape. Initially driven by cost-cutting measures, companies now establish offices in multiple geographies to gain diverse perspectives and make better decisions. As someone who has led globally distributed teams for 14 years, I have witnessed significant improvements in products and services through this approach. However, it required continuous learning and adaptation. In this article, I will share my biggest learnings, divided into tips for managing and leading. Management involves establishing clear processes, documentation, and ensuring access to the same information. Leadership, on the other hand, focuses on human connection, visiting remote offices, inviting team members to visit, establishing local leaders, and understanding cultural differences within teams.
Full Article: Leading and Managing Teams on a Global Scale: Insights from Etsy Engineering
Managing globally distributed teams has become commonplace in today’s business world, with companies establishing offices in multiple geographies to seek out different perspectives and build better products. Having managed such teams for over 14 years, I have learned valuable lessons that have enhanced the productivity and effectiveness of my teams. In this article, I will share my biggest learnings in managing and leading globally distributed teams.
Tips for Managing Globally Distributed Teams
1. Documentation: One mistake I made when managing my first remote team was assuming that minimal documentation, favored in the tech industry at the time, would work for them as well. However, without the luxury of face-to-face interactions, my remote team struggled with information gaps, leading to confusion and frustration. To avoid this, it is crucial to ensure that all teams have access to the same information and resources.
2. Clear Processes: Another assumption I made was that my remote team had their own established processes that made them most effective. This led to inconsistent practices and a lack of definition, causing delays and misalignment between my local and remote teams. It is important to establish clear processes and ensure they are followed by all team members, regardless of their location.
3. Conveying the “Why”: While documenting tasks and expectations is important, it is equally crucial to convey the purpose and customer problem behind the project. Remote teams often face moments of uncertainty where they need to make decisions, and having a clear understanding of the project’s purpose helps them move forward and make better decisions. It also boosts morale and inspires a more cohesive and inspired product.
Tips for Leading Globally Distributed Teams
1. Visit Remote Offices: Visiting remote offices in person is invaluable for gaining a deeper understanding of your team’s work environment, priorities, and challenges. By experiencing their daily commute or addressing issues like lack of proper infrastructure, you build empathy and develop a better perspective on their needs.
2. Invite People to Visit You: Offering your remote team members the opportunity to visit your local office allows them to meet face-to-face with colleagues, understand local office culture, and gain a broader perspective. This experience fosters stronger connections and facilitates better collaboration between local and remote teams.
3. Establish Local Leaders: Building relationships with influential individuals in remote offices, whether they hold formal leadership positions or are informal leaders, is essential for navigating change and cultural nuances. These leaders can greatly influence team dynamics and help bridge any gaps that may arise.
4. Pay Attention to Culture: When managing teams from different countries, dedicating time to understand and appreciate their respective cultures is vital. Cultural differences can impact communication styles, decision-making processes, and work preferences. By being culturally aware, you can foster a more inclusive and harmonious work environment.
Conclusion
Successfully managing and leading globally distributed teams requires a combination of effective management practices and strong leadership skills. By prioritizing clear communication, understanding and respecting different cultures, and establishing strong relationships with team members, leaders can build cohesive and high-performing teams, regardless of geographical boundaries.
Summary: Leading and Managing Teams on a Global Scale: Insights from Etsy Engineering
Managing globally distributed teams has become commonplace in today’s business landscape. Companies now establish offices in multiple geographies to seek out different perspectives, make better decisions, and build better products. In this article, the author shares their biggest learnings from leading globally distributed teams. They emphasize the importance of clear documentation, consistent processes, and conveying the “why” behind projects. Additionally, the author highlights the significance of human connection in leading remote teams, including visiting remote offices, inviting team members to visit, establishing local leaders, and paying attention to cultural differences. Overall, effective management and leadership are essential for success in globally distributed teams.
Frequently Asked Questions:
Q1: What is Machine Learning?
A1: Machine Learning is a branch of artificial intelligence that focuses on the development of algorithms and statistical models that enable computer systems to learn and improve from data without explicit programming. It allows computers to analyze and interpret large volumes of data to make predictions or take autonomous actions.
Q2: What are the main types of Machine Learning algorithms?
A2: The main types of Machine Learning algorithms are supervised learning, unsupervised learning, and reinforcement learning. Supervised learning uses labeled data with known input-output pairs to make predictions or classify new data. Unsupervised learning deals with unlabeled data, aiming to find hidden patterns or structures within the data. Reinforcement learning involves training an agent to make decisions in an environment and learn from feedback through a reward-based system.
Q3: In which industries is Machine Learning commonly used?
A3: Machine Learning has found applications in various industries, including healthcare, finance, retail, manufacturing, transportation, and entertainment. In healthcare, it can assist in diagnosing diseases or predicting patient outcomes. In finance, it helps analyze market trends and detects anomalies for fraud prevention. In retail, it is used for recommendation systems and demand forecasting. These are just a few examples of the vast potential of Machine Learning across industries.
Q4: How does Machine Learning differ from traditional programming?
A4: Traditional programming involves explicit instructions given to a computer to carry out specific tasks. In contrast, Machine Learning algorithms learn patterns and behaviors from data, enabling the computer to make predictions or decisions without being explicitly programmed. Traditional programming focuses on rules, while Machine Learning focuses on learning from data.
Q5: What is the role of data in Machine Learning?
A5: Data is essential in Machine Learning as it forms the foundation for training and developing models. The quality, quantity, and relevance of data greatly impact the performance of Machine Learning algorithms. Properly labeled and diverse datasets are crucial for supervised learning, while unlabeled datasets are used for unsupervised learning. Data preprocessing, including cleaning and feature engineering, is also vital to ensure the accuracy and efficiency of the models.
