Role of Agile in Navigating Successful AI Integration

Introduction Agile and AI together are a powerful combination that’s shaping the future of how we work. Agile gives us flexibility, quick feedback, and collaboration—important aspects for dealing with the complexity of AI projects. AI, on the other hand, brings speed, efficiency, and (large) data-driven insights that boost Agile practices. When you mix Agile’s adaptable approach with AI’s capabilities, you get faster decision-making, smarter processes, and more value delivered to customers. Agile helps AI teams test, refine, and stay on track, while AI supports Agile teams with automation and real-time insights. This partnership allows teams to work smarter, adjust quickly to changes, and continuously improve—key ingredients in today’s fast-moving market. How does combining Agile and AI benefit us? Agile and AI complement each other in meaningful ways. Agile’s iterative cycles are ideal for AI development, where changes and surprises are common. Agile helps develop the AI models in Sprints and each sprint allows for testing and refinement, making it easier to adapt and improve. AI speeds up many repetitive tasks—like data processing, testing, and bug fixing—freeing up the team to focus on creative and high-value work. This helps deliver faster releases, reduces errors, and leads to higher-quality products. AI also helps with making smart decisions by providing real-time insights from large data sets. This helps with better work prioritization, effective risk management and well-informed decisions to meet customer needs. When Agile’s flexibility meets AI’s power, the results are smarter work processes, rapid adaptation, and better overall outcomes. How Agile Helps AI Development? As said above, Agile makes AI development smoother and more adaptable. AI projects often involve uncertainty and frequent changes—Agile’s flexibility is perfect for handling these. Iterative cycles let teams test AI models in smaller, manageable steps, gather feedback, and improve continuously. This makes AI projects more reliable and easier to manage. Agile also encourages strong collaboration among different roles—data scientists, engineers, stakeholders—keeping everyone aligned on goals and requirements. Prioritization helps teams focus on the most critical tasks first, reducing wasted efforts and delivering early value. You may be interested in reading: https://agilonomics.com/data-science-mastery-agile-strategies-for-high-performance-teams-in-evolving-industries/ The continuous feedback loops in Agile ensure that any issues are addressed quickly, and the project adapts as new information comes in. So, Agile brings structure and stability to AI projects that are inherently unpredictable. Leadership’s Role in Integrating AI with Agile Leaders have a key role to play in bringing AI and Agile together. First, they need to set a clear vision, showing teams how AI adds value and connects with Agile goals. This will help everyone stay aligned and focused. Leaders should encourage teamwork, bringing data scientists, developers, and business experts together to solve problems. By breaking down silos, they make sure everyone communicates and collaborates effectively. Servant Leadership is crucial for true success here. Promote a culture of continuous learning and keep the focus on ethical standards. Guide your teams on responsible data use and fairness, making sure AI solutions uphold your organization’s values. Real-World Wins: How AI and Agile Are Transforming Industries Integrating AI with Agile methodologies has led to major successes across industries: Financial Sector – Fraud Detection at JPMorgan Chase: The bank uses AI to analyze transaction patterns, helping Agile teams iteratively refine fraud detection models. This approach has improved response times and detection accuracy.Ref: https://www.americanbanker.com/news/jpmorgan-chase-using-chatgpt-like-large-language-models-to-detect-fraud Healthcare – Patient Care Optimization at Cleveland Clinic: By applying AI-driven insights in Agile workflows, the clinic has been able to adjust patient schedules in real-time, reducing wait times and boosting patient satisfaction.Ref: https://consultqd.clevelandclinic.org/how-ai-assists-with-staffing-scheduling-and-once-tedious-tasks Automotive Industry – Predictive Maintenance at BMW: BMW’s AI models analyze machine data for predictive maintenance, allowing Agile teams to adjust production schedules, reducing downtime and increasing efficiency.Ref: https://effectiv.ai/resources/fraud-detection-using-ai-in-banking/ E-commerce – Personalization at Amazon: Amazon employs AI to personalize product recommendations in real time, iterating Agile feature development based on customer preferences and feedback. This Agile integration has led to increased user engagement and improved revenue per session. Retail – Supply Chain Optimization at Walmart – Walmart uses AI for demand forecasting and integrates these insights into Agile sprints, leading to better inventory management and optimized supply chains.Ref: https://www.jpmorgan.com/insights/payments/payments-optimization/ai-payments-efficiency-fraud-reduction Conclusion Combining AI with Agile methodologies is shaping a new future for project management. By bringing together the power of AI to analyze data and the adaptability of Agile, teams can innovate faster, solve complex problems, and create meaningful products.  By encouraging teamwork, guiding with empathy, and supporting a culture of curiosity, leaders can help their teams succeed. The future of Agile and AI is bright, but it will shine even brighter with the right mix of smart tech, motivated people, and meaningful leadership.

Why SAFe Training and Certification are Important?

Why SAFe Training and Certification are Important?

SAFe training and certification are quite popular today. They are important for anyone who is seeking to work in an environment implementing Agile at Scale. The SAFe concepts will not only come in handy at a large number of companies that have embraced SAFe implementation but will also be beneficial if deeper understanding of these concepts (e.g. SAFe LPM) can be applied in a practical manner to places that want to scale their homegrown organic Agile implementation. Additional reasons why SAFe training and certification can contribute to your success Scaling Agile in a Structured way: SAFe is a structured framework that helps large sized organizations become effective in applying Agile across many teams. The structured setup, processes and practices aligns everyone and guides them to move in the same direction with common goals. Better Career Opportunities: As demand for SAFe (especially in large organizations) is high, the need for SAFe certified personnel is also high in demand. SAFe certification can therefore boost your career prospects. It can help you stand out in a competitive job space and open up opportunities like SAFe Scrum Master, SAFe Product Owner, SAFe Product Manager, SAFe Release Train Engineer, SAFe Developer, and more. Deeper Understanding of Lean-Agile Principles: SAFe training will help you under the deeper aspects of Lean Agile Principles and their effective application in practical real world scenarios. This will empower you to drive outcomes impacting productivity, quality, speed-to-market and organic cost-reduction. High Performing, Collaborative Teams: Alignment, Transparency and Collaboration are encouraged and emphasized in SAFe. Proper training from people who breathe, live, love and work(daily) hands on at enterprises helping implement Agile and SAFe effectively will ensure all Agile team members from developers to executives will be on the same page. This will result in improved team performance and satisfaction. Practical learning from Industry Experts: Training and certifying with coaches who have worked hard over the years to succeed with Agile, will help you receive practical, hands-on learning from experts. Such a real-world experience is priceless and will help you apply your understanding to effectively implement SAFe in your organization. Continuous Learning, Inspection and Adaptation: The modern work landscape is continuously evolving. SAFe training encourages continuous learning and adaptation and enables you to stay up-to-date with the latest trends and practices that work. Don’t embark on a SAFe training and certification to get a stamp, but to enhance your skills, improve your career prospects through deeper understanding of principles and their application and drive meaningful change in your organization. Invest in SAFe training and certification from people who don’t train and certify to just make a living but do so to also share their passion and success in implementing Agile and SAFe over many years. Learn from their experiences – both success and failures – and grow into an effective and impactful Agile professional.

Why SAFe Training with Agilonomics

Why SAFe Training with Agilonomics?

SAFe(Scaled Agile Framework) is more than just a framework. Many consider it heavy-weight. We feel it is a comprehensive approach for guiding Agile practices to scale across an organization. The demand for SAFe expertise continues to rise. It is important, therefore, to invest in high quality training and coaching to empower yourself on how to navigate the complexities of implementing SAFe effectively. Here is why choosing Agilonomics for your SAFe journey will make all the difference. All Round, Hands-on Expertise:SAFe is well known to be heavy and complex. Theoretical knowledge alone isn’t enough to navigate through its intricacies. When you learn with Agilonomics, you get much more than just a certification. You’re investing in gaining insights from seasoned practitioners who have helped many clients (Fortune 100 – Startups) to succeed with SAFe and Agile. Our trainers bring a collective experience spanning well over 1000s of hours – coaching and training – to ensure you receive practical insights to current and real-world challenges Advance In Your Career:Many take certification for getting a badge. It only helps you go so far. In today’s competitive world, investing in training from a trusted provider who understands the game inside out, will not only get you the certification but also help in your career advancement. Choosing Agilonomics will equip you with the skills, insights and confidence to drive successful SAFe transformations. You will gain the ability to grow into a sought after Agile and SAFe transformation leader. Hands-On Learning:Only way to succeed with SAFe is to move beyond theory to deeply understand how to apply its principles in fast paced, complex environments. Engaging with Agilonomics, you will be exposed to hands-on experience with practical real-world challenges and gain the ability to develop powerful solutions and strategies. Our training underscores the importance of collaboration, one-team-attitude, problem-solving and adaptability to ensure you’re well equipped to tackle the complexities of Scaling Agile. Sharing Client Success Stories:We, at Agilonomics, measure our success by the success of our clients. Our coaches and trainers have helped organizations like Sony PlayStation, Blue Shield of CA, At&T, among others, to achieve remarkable results with implementing SAFe through our training and coaching programs. Agilonomics’ Commitment to Excellence:Our purpose is to create greatness in the corporate world, one person, one company at a time. So, we’re committed to excellence in everything we do. This shows up in the quality of our training and the expertise of our trainers. We strive to uphold the highest standards to ensure your learning experience is exceptional. With us, you’re not just investing in training but investing in a partnership that is committed to help you succeed Your choice of SAFe training with Agilonomics is more than just a decision. It’s a strategic investment that will help you grow professionally, and succeed in your career. Our comprehensive knowledge, hands-on experience in many industries, and commitment to excellence will empower you on your SAFe journey every step of the way. Ready to move forward in your journey? Take the next step! Book your seat for a free SAFe webinar today

Agile and AI Development: Bridging Complexity with Flexibility

Why Agile with AI is Important Today? The world of technology is changing as always. Many feel threatened today with the impact of Artificial Intelligence (AI) on their jobs and career. Agile is not spared either. However, building AI products is complex and integrating Agile ways of working with AI development is crucial for organizations to stay competitive. Agile mindset of flexibility and iterative development matches up perfectly for handling complexities and uncertainties inherent to AI development. AI projects often involve a lot of experiments, ongoing learning, frequent changes or adjustments based on emerging data and insights. Agile methodologies promote adaptability, collaboration, and continuous improvement. They provide a lightweight structured framework and are well suited to accommodate these dynamic requirements.By adopting Agile principles and truly understanding their application, organizations can effectively manage the iterative cycles of AI product development. This will help with timely delivery of innovative and valuable AI solutions while staying adaptable to new information and changing markets. This teaming up of Agile and AI will boost the success of AI projects by driving innovation, efficiency, time-to-market and ultimately impacting business value. Why AI Development is Challenging? Developing AI products brings unique challenges to the table; challenges that set them apart from traditional software projects. Here are some common challenges that I see often with AI Despite the above challenges, AI projects have immense potential for success and will bring in high return on investment. They already are, and will continue to shape the future of technological innovation and human evolution.Organizations that effectively tackle these challenges will harness the transformative power of AI to create solutions that will drive innovation, speed-up decision making, and offer competitive advantages. However, to achieve success will need a flexible, adaptive and collaborative mindset that translates to behaviors and practices that can effectively manage the complexities and uncertainties inherent to AI product development. This is where Agile comes into play with its empiricism, inspect and adapt, customer focus, systems thinking on one hand and servant leadership, collaboration, swarming, attention to results, commitment, team ownership (accountability), healthy conflict and foundation of trust on the other (hand). These two sides of Agile can provide a structured, adaptable and safe ground for making AI projects thrive! How Can We Help You? Hernan Tocuyo, my peer Coach and I, worked for a year at a client where we were onboarded with bringing their DATA ART (Agile Release Train) to become effective and high performing. Multiple teams in that ART are engaged in high complexity work, including AI, Machine Language, Data Science, Data Engineering etc. They develop algorithms, test hypotheses, and build models. Their work includes enablers, spikes, and needs cross coordination between domain experts and across ARTs. They use all industry standard data management tools such as Teradata, Apache, Databricks, Hadoop, Informatica, Tableau etc. Using Agile values and Agile and SAFe principles we brought all teams to a high level of effectiveness in a very short time. They figured out better ways to write stories, have conversations, refine work, collaborate and make their PI planning effective. Some data scientists paired with us and brought out an effective way to write their Data Science stories and created and continuously polished templates that everyone could use. Inspired by our work with them and the collaboration between Agile Coaches and Data Scientists, we wrote a blog on this Conclusion: Agile done wisely and sensibly does work and works well enough. The teams from this above client have members across 4 time zones with very little overlapping hours. Despite this and other challenges, they have developed into effective, highly collaborative, high performing teams. The current AI wave is creating a lot of fear about “Agile is dead” and all the noise of Scrum Master jobs being taken away. I would call out to all the passionate Scrum Masters that AI will never be able to replace the need of human beings who inspire greatness in others, create safe environments to work and are true Servant Leaders serving their teams and organizations. Strive to be a powerful Servant Leader Scrum Master; truly imbibe the universal values and principles of Agile and Scrum and you will never find yourself out of job. There will always be a need for humans who can bring positive behaviors out in others through their caring attitude and inspire change for the betterment of an organization. We have done successful end-end organic Agile Transformations for multiple clients using two of the most popular scaling frameworks, Scaled Agile (SAFe) and Scrum@Scale. Contact us to learn how we did it for them. Due to huge success with onsite and client training, we started to offer both SAFe training and certifications and will be starting with Scrum Alliance training and certifications soon. In addition, Agilonomics’ own training workshops with certification are also available. Each of these is taught by an expert coach with many 100s of hours of training and hands-on coaching. Check them all out https://agilonomics.com/safe-training-and-certification/

Strategies for Successful Agile Transformation

Strategies for Successful Agile Transformation

Introduction: What is Agile Transformation? Agile Transformation in simple words means creating effectiveness in teamwork through Agile Mindset that impacts behaviors and culture and organizes people into effective teams (as opposed to working groups)  to deliver high value to users and customers.  A wise Agile implementation will have these 3 characteristics: This is in contrast to bitwise, piecemeal or superficial transformations where teams and employees are expected to follow Agile but leadership behavior is unintentionally disruptive to the new ways of working. As a result, the larger unresolved cultural or environmental issues eventually contaminate or pollute the new Agile Teams. As a result people will be happier, healthier and wiser in their day-day work and interactions. Agile transformation is a continuous journey of cultural shift, where individuals, teams, and organizations evolve to become more adaptive, collaborative, and responsive. Why are Agile Transformations important? Enabling teams and individuals to operate at their best potential while delivering high value to the business is a desired goal of any organization. Agile principles in action help teams improve their responsiveness to customer needs, negotiate market shifts better, and expedite the delivery of high-quality products and services.  Wise Agile transformations cultivate safety, trust, and sustained growth among team members, while also promoting continuous improvement, empowerment for iterative processes, and a culture of learning and evolution.  The modern business landscape is complex and dynamic. Organizations must adopt Agile mindset and behaviors to remain competitive, flexible, innovative, and achieve faster time-to-market. Why do many Agile Transformations fail? Successful and effective Agile Transformation involves: As you can see, an effective Agile Transformation involves the whole village – individuals, teams, managers, leaders and executives. Everyone needs to show up and do their part to positively impact the mindsets, behaviors, culture and results! With this approach the Agile Transformation will not only be effective, but also long lasting and reflect in end-end behaviors (bottom-up and top-down). While all of the above is desirable and may seem easy on paper, it is very hard to achieve. The change agent Agile Coaches often lack necessary skills and fail to grapple with the demands of a holistic end-end Agile transformation. This highlights the importance of selecting Agile coaches who are solid in their foundations and exemplify strong purpose and core values. My Agile Journey: From Frustration to Discovery In my journey as the CEO and Co-Founder of Agilonomics, I’ve experienced the transformative power of Agile time and again. My journey started with a sense of frustration at a large enterprise where I found myself leading a group of people focused on waterfall practices. I vividly remember the days when we met as a team, usually once a week but hardly anyone spoke. Our manager would facilitate, share a few artifacts, ask for status updates and that was it. This was a routine mandatory gathering rather than a meaningful team collaboration session. Something was missing. I realized that we are just a working group and not a cohesive ‘team’. This realization made me research better ways of working. I had an open and honest conversation with my boss, where I expressed my concerns about the team lacking engagement and happiness. His initial response was surprising as he thought salary, bonuses and stocks alone made employees happy!? It took me a few sessions of hard but respectful conversations to help him realize that happiness for humans stems from meaningful connections and shared happiness. The result was permission to attend an Agile Developers Conference and bringing in Agile and Scrum to my team as an experiment to see if it helps boost collaboration, engagement, customer value and team happiness. My Experiment with Scrum I failed miserably at the beginning as team members grappled with new processes and practices. Interference from management dictating how to do Scrum was not helping either. I had to coach my boss to step aside and trust me to work with the team in establishing the process. He then partnered with me supporting and championing our team.  Building a Successful Agile Team Through perseverance, commitment and dedication, we transformed into a high-performing Agile team. The team behaviors reflected Agile values and principles. There was camaraderie, bonding, enthusiasm, warmth and collaboration among team members. The focus shifted from creating outputs to customer value. We committed to Sprint goals as “one team”, took accountability for all work and continuously improved our process through feedback and retrospection. Lessons Learned with Insights Organic Agile transformation begins with a focus on people. Engaging leaders, encouraging transparency and leading by example are important ingredients of a successful transformation. Embracing Agile values and principles, patience and striving for continuous improvement are some factors that contribute to successful transformation. Authenticity and purpose are foundational to effective Agile Leadership. Staying true to core values, striving to grow employees and genuinely caring for people can drive meaningful change. Establishing an Agile Practice Group and supporting a culture of continuous improvement are key to sustaining Agile transformation. By promoting human values and prioritizing transparency, accountability, and learning, organizations can navigate change with confidence and resilience. A final note on what kind of coaching is effective for Agile Transformations When selecting Agile Coaches, look out for the ones that standout with strong core values and purpose. An effective Agile Coach will go beyond just fixing processes to serve as a role model, bringing up greatness in individuals and teams. Coaches must remember that true transformations come from within and cannot be imposed from outside. Effective coaching includes leaders to be part of the transformation. No transformation can be complete by excluding leaders and managers who serve the teams undergoing Agile transformation.At Agilonomics, we offer a proven “Agile Transformation Blueprint” refined over two decades, facilitating impactful transformations across various organizations led by renowned servant leader coaches.

Agile For Data Science Mastery - Agilonomics

Data Science Mastery: Agile Strategies for High-Performance Teams in Evolving Industries

This is an informative, educational article and is being written in two parts. Part 1, below is an introduction about Data Science Teams, the challenges they face. Part 2, that comes later,  will cover detailed strategies on how to make Data Science project development effective using Agile ways of working Introduction: Exploring the Intersection of Data Science and Agile for Teams In today’s fast-paced, emerging and evolving digital world, data science and engineering teams play a central role in driving innovation and competitive advantage for organizations. However, the complexity of their work, along with with the dynamic nature of the industry, presents unique challenges that traditional project management approaches struggle to address effectively. As an Enterprise Agile Coach working closely with development teams, I often see the challenges data scientists face in managing the complexity of their projects. From dealing with massive datasets to harnessing the power of AI and machine learning, these teams encounter obstacles that demand a fresh perspective and Agile solutions. In this blog, we’ll look into the complexities of data science work and explore how Agile thinking can offer a pathway to success. Drawing from personal experiences and industry insights, we’ll uncover the importance of embracing Agile principles and practices to overcome the challenges inherent in data-driven projects.  Understanding Challenges: Obstacles Faced by Data Science and Engineering Teams Data science and engineering teams encounter various obstacles that can slow their progress and impact the success of their projects. To gain a better understanding of these challenges, let’s explore the historical evolution of data science methodologies and frameworks. Exploring Data Science Methodologies: A Historical Perspective As data science continues to evolve, so do the methodologies and frameworks that guide its practice. One such approach is the circular model, which forms the foundation for various methodologies employed in the industry. Below is a brief text on the evolution of this approach followed by some of the key methodologies that have emerged over time. Simple Circular Approach to Data Science Evolution of the Circular Approach The circular approach, also known as Agile-ish development within the data science realm, has undergone significant evolution to meet the changing demands of the field. Initially, the focus was on creating a flexible and adaptable framework that could accommodate the iterative nature of data science projects. Over time, this approach has matured, leading to the development of structured methodologies that provide clear guidelines for practitioners. Key Methodologies in Data Science Among the methodologies that have emerged, IBM’s CRISP-DM (Cross-Industry Standard Process for Data Mining) stands out as one of the most widely adopted frameworks. CRISP-DM offers a structured approach to data mining projects, with well-defined stages that guide practitioners through the entire process. The CRISP-DM model defines six crucial phases in the data science life cycle, demanding meticulous attention and expertise at each stage. These six stages are: Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment. There is well-defined logic for jumping between different (back and forth or from one to another) stages of this model. For example, you could go from “Business Understanding” to “Data Understanding” and back a number of times until data clarity is achieved.  CRISP-DM Diagram In addition to CRISP-DM, several other popular methodologies have emerged to guide data science projects. These include the OSEMN (Obtain, Scrub, Explore, Model, Interpret) model, which emphasizes a systematic approach to data analysis.  The KDD (Knowledge Discovery in Databases) process is another widely used framework that focuses on extracting useful knowledge from large datasets.  Additionally, SEMMA (Sample, Explore, Modify, Model, Assess) offers a structured approach to data analysis, while TDSP (Team Data Science Process) emphasizes collaboration and teamwork throughout the project lifecycle.  Furthermore, KDNuggets CRISP-DM, a modified version of the original CRISP-DM model by KDnuggets, and LIFT (Lightweight Iterative Framework for Text Mining) provide specialized approaches tailored to specific data science tasks and domains.  Each of these methodologies brings its own set of principles and practices to the table, catering to the diverse needs of organizations in the field of data science. Looking Ahead As data science continues to evolve, so too will the methodologies and frameworks used to guide its practice. By understanding the evolution of the circular approach and exploring the key methodologies employed in the industry, data science and engineering teams can gain valuable insights into how best to approach their work and overcome the challenges they may face. Common Challenges faced by Data Science Teams We will primarily focus on the CRISP-DM model to help understand the common challenges faced in Data Science projects.  Splitting Work to Provide Incremental Value: Integrating the six phases of the CRISP-DM model into user stories presents a significant challenge for data science teams. How do we fit all phases into a single 2-week Sprint? How do we show and deliver value when the work is split to fit in the Sprint?  Dealing with Massive Datasets: Data science projects often involve working with massive datasets, requiring teams to develop efficient strategies for data collection, storage, and analysis. Managing and processing such large volumes of data can strain people, resources and infrastructure, posing a significant challenge to teams. Harnessing the Power of AI and Machine Learning: With the increasing adoption of AI and machine learning technologies, data science teams must stay abreast of the latest developments and best practices in these areas. Incorporating AI and machine learning into projects requires specialized knowledge and skills, presenting a challenge for teams that may lack expertise in these domains. Ensuring Data Quality and Integrity: Maintaining data quality and integrity is critical in data science projects, as the accuracy of insights and decisions hinges on the reliability of the underlying data. However, ensuring data quality can be challenging, particularly when dealing with diverse data sources and incomplete or inconsistent data. Managing Project Timelines and Deadlines: Data science projects often operate under tight timelines and deadlines, requiring teams to deliver results within specified timeframes. However, the iterative nature of data science work, coupled with the unpredictability of data-related

Is Demand for collocated teams – A Dead Reality?

Is Demand for collocated teams – A Dead Reality? Are collocated teams a relic of the past? Perhaps not entirely. Yet, in my experience as a consultant working with various companies, remote team members have become increasingly common. As businesses expand their global presence, the need for collaboration across multiple sites has intensified. Additionally, consulting firms take advantage of opportunities to serve clients, often deploying consultants across continents for fulfilling roles and skills needed for projects. These dynamics add layers of complexity, sparking debates over which approach (collocation vs. Remote) yields superior ROI. While many leaders lean towards staffing from multiple remote sites for its perceived ease of access to diverse skill sets and cost efficiency, passionate Agile enthusiasts think otherwise. They argue that collocated teams are possible and manageable but demand a broader vision and a deeper understanding of their inherent value. Contrary to common assumptions, collocated teams can yield long-term cost savings, although not much data is available to drive home this point.   Some Interesting Facts about Distributed Teams The word “remote” is so open to interpretation that it is not surprising to see how the definition of “remote teams” has changed over the years as outlined below: One local team and one remote site: Initially, a company might have its main team in one location and a smaller remote team in another. One local team and multiple remote sites: As the company grows, it might establish remote teams in various locations to tap into diverse talent pools. All remote sites in the 2nd time zone: For example, a company based in San Francisco might have all its remote teams located in different cities in India, such as Bangalore, Delhi, Hyderabad, and Mumbai. Multiple remote sites in multiple time zones: As operations expand globally, remote teams might be spread across different countries, each in its own time zone, such as India, Romania, and Argentina. Remote sites from contracting companies: Sometimes, companies partner with external firms to fulfill specific project needs, leading to remote teams with different corporate backgrounds and work practices. However, aligning their ways of working with Agile principles can be challenging.  Example, while Coaching a team for cross functionality, I introduce planning poker for anonymous estimations to have open conversations on every team member’s work. Everyone participates whole heartedly and learns  from one another and eventually begin to swarm and co-own each other’s work. But, a recent team reported that its remote team members were from separate consulting firms and their SOWs did not allow them to share their expertise with members from other consulting firms. This created an impediment to increasing cross functionality. These different setups showcase the diverse ways in which companies adapt to distributed workforces, each presenting its own set of advantages and complexities. Pros and Cons of Collocation and Remote Teams Summarizing the table in words below Collocated teams offer several advantages. Face-to-face communication is easier, fostering better bonding among team members and enabling activities like swarming and pairing. Additionally, managing such teams is often more straightforward, although it may inadvertently encourage a command-and-control management style. However, hiring individuals with all the necessary functional skills for a collocated team can be challenging. On the other hand, remote teams present their own set of challenges and benefits. While face-to-face communication is more challenging, technology can bridge this gap to some extent. Building trust and safety within remote teams can be more difficult, but it’s not impossible with deliberate efforts. Managing remote teams requires more attention to coordination and communication. Interestingly, the remote setup often promotes a more decentralized, empowering leadership style. Hiring diverse talent for remote teams is generally easier, and remote setups can potentially offer cost savings, although the actual return on investment (ROI) varies based on factors like team structure and management approach, safety and trust established among the team members. Watch Out: Unrealistic Expectations Can Lead to Disappointment! It’s surprising how some individuals refuse to be with reality. Take, for instance, a recent conversation I had with a newly appointed Agile Coach at a company undergoing Agile Transformation.  Frustrated, he blamed the leadership’s failure to grasp the significance of collocated teams. He firmly believed that a comparative analysis of funding and ROI between teams with multiple remote members and those comprising solely collocated members would reveal the value and superiority of collocated teams. And he’s not wrong. The seamless workflow, face2face communication, and efficient delivery, among other advantages associated with collocated teams far outweigh the perceived cost savings of hiring remote contractors.  However, what he fails to recognize is the transitional nature of leadership’s understanding. Merely expressing dissatisfaction and complaining won’t get their buy-in. Instead, I advised him to build connections with leaders, demonstrate his value through a few tangible transformations in select teams, find a champion leader to buy into his idea and support him to stand one collocated model team to prove the difference. Convincing leadership demands compassion, intelligence, and above all, patience and servant leadership skills. It’s a journey that requires time and perseverance. Tips for Minimizing Overhead with Remote Teams Here are some key strategies to reduce the challenges associated with remote teams: Maximize Overlapping Hours: Encourage team members to adjust their schedules to ensure there’s significant overlap in working hours. This might mean starting early or working late to accommodate different time zones. Embrace Video Communication: Encourage a culture where team members commit to being on video during meetings and discussions. Seeing each other’s faces adds a personal touch to remote interactions, making them feel more like face-to-face conversations which helps with bonding, swarming and building safety and trust Step Out of Comfort Zones: It’s essential for the Scrum Master to take initiative in facilitating regular meetings with individuals and small groups. These interactions provide opportunities for team members to share updates, address concerns, and build rapport despite the physical distance. Empower Scrum Masters: Allow Scrum Masters to communicate and collaborate with remote member managers to align on new ways of working. This

Success Mantras for Startups: Agile Wisdom in Action

“The startup life is a wild ride; survival demands more than a map—it requires a compass, and that compass is Agile.” In the unpredictable world of startups, where 9 out of 10 face the stormy seas of failure, Agile emerges as a guiding light. From insufficient market understanding to struggles of cash burn, startups wrestle with an array of challenges.  There’s a lot of uncertainty and a wrong step could mean the end. Yet, chances of failure can be minimized; or in fact it can even be an opportunity or stepping stone —  to learn, adapt, and rise stronger. It’s here that Agile mindset and putting it into practice can make a difference. Here is an attempt to unveil the practical application of Agile principles and address some top reasons startups fail.  Top 15 reasons startups fail:  In the relentless journey of startups, failure often looks at you from a close distance. Understanding the terrain of challenges is crucial to move through this uncertain path successfully.  We highlight key reasons that often challenge startups and show how Agile principles can help address each. Although, it is important to know writing is easier than following and executing and a lot of it has to do with culture, environment and management behavior. 1. Lack of Market Demand:  Starting a business involves understanding what your target customers need. This requires a keen understanding of market needs. Agile, with its focus on collaborating with customers and making adjustments through iterations, helps to foresee and fulfill market demands.  Example: Let’s take the example of a hypothetical startup called TechGear Innovations(TGI). TGI is developing a cutting-edge fitness tracker and assumes an initial set of features for its MVP launch. They work closely with potential Customers and users to get feedback, validate their assumptions and identify some holes in their thinking. They go back and modify their requirements. Their MVP, as a result, fares much better than it would otherwise. 2. Go-to-Market Strategy Woes:  Launching your product successfully demands a well-thought-out strategy. Agile’s approach, with its adaptive planning and early delivery, ensures your strategy is not just thorough but also flexible to market shifts. The initial releases and reviews should answer the question, “Are we building the right product?”. Once that is in place, the subsequent releases and reviews should answer the question, “Are we building the product right?” Example: Let’s say TGI’s initial strategy was to focus solely on online sales. Working with an Agile coach, they shifted to adaptive planning. This prompted them to move away from sticking to a fixed, rigid go-to-market strategy. They decided to release the initial version of the product locally before a broader launch. This was a result of  insights gained through the development process and studying the changing landscape through customer collaboration. 3. Poor Product Development:  A flawed product can be a death knell for startups. Agile’s iterative development, collaboration, focus on technical excellence and systems thinking (keeping the big picture in mind approach) ensures continuous improvement. It aligns development with changing requirements and enhances the product as it evolves. Example: Let’s say TGI faced issues with performance when their fitness tracker was released locally. They collaborated with customers, refined technical aspects and ensured the performance improved with iterations and regular firmware deployment ensured customer happiness. Building something great means constant refinement – each iteration is a step towards excellence 4. Bad Business Model:  Agile thrives on adaptability. It encourages constant reassessment and adjustment, providing startups the agility to refine their business models based on real-time feedback and market shifts. Example: TGI’s initial revenue model relied heavily on direct sales. Adaptive mindset encouraged them to experiment with subscription based models and partnerships based on real time feedback. As a result, they were able to positively impact the sales and loyalty for their fitness tracker. 5. Pricing and Cost Issues:  Striking the right balance between pricing and cost (without compromising quality) is important for any company, and more so for startups. Agile’s emphasis on sustainable development and continuous attention to technical excellence can provide startups with ability and insights in making cost-effective decisions without compromising quality. Example: Let’s say TGI was struggling to balance pricing and cost. They worked with a lean approach to identify and eliminate unnecessary waste in their manufacturing process, thereby cutting costs without compromising quality. They also focused on technical excellence and improvised features that truly added value. 6. Not the Right Team:  The success of a startup rests on the shoulders of its team. Agile’s people-centric approach fosters collaboration, transparency, and adaptability, ensuring that the right team dynamics are cultivated for success. Example: TGI’s teams faced communication gaps. There were lapses in accountability and results were impacted. Safety and trust issues came up often. TGI invested in strong Servant Leaders coaching and guiding their teams. The leaders encouraged collaboration and swarming and acknowledged and rewarded people who showed such behaviors. This resulted in transparency, collaboration, and skill development, ensuring the team dynamics were conducive to success. 7. Being Unprepared for Market Changes:  Startups are at the mercy of market fluctuations. Agile, with its responsiveness to change and regular reflection, equips startups to not only weather market changes but also leverage them for growth. Example: TechGear anticipated the volatile nature of the fitness tech market. They utilized Agile principles to remain adaptable, monitored, reviewed and retrospect market trends, and quickly adjusted their product roadmap based on emerging changes.  8. Failure to Learn and Adjust:  Learning from mistakes is a cornerstone of Agile philosophy. It cautions us about the missteps and guides us with adapting and improving. Agile reviews and retrospectives provide a structured way for startups to learn, adjust, and iterate.  TGI instituted regular retrospective rituals where the teams openly discussed failures and successes. This allowed them to learn from mistakes, adapt their strategies, and continuously improve their development and business processes and people behaviors. There is no such thing as failure …. Only Feedback 9. Inability to Raise Capital:  Agile principles encourage delivering value continuously.

Maintaining a balance between predictability and adaptability in Agile methodologies

Exploring the challenge of maintaining a balance between predictability and adaptability in Agile methodologies.

In the Agile world, there’s a constant struggle to find the right mix between sticking to plans and being open to change. This is like walking a tightrope where, on one side, you have the safety of knowing what lies ahead (predictability), and on the other, the thrill of being flexible and responsive (adaptability). Striking this balance is an ongoing challenge for Agile practitioners, and, from my own experience, getting this balance right has been more of a journey, rather than a goal. Predictability brings a sense of security, allowing teams to plan and commit to goals like following a roadmap. But too much focus on predictability can stifle innovation and make it tough to adapt. Adaptability is at the core of Agile. Welcoming change, adapting swiftly, and responding to evolving needs are the behaviors that support this mindset.     However, while, the excitement of adaptability fuels innovation and quick responses, too much adaptability without a solid foundation of predictability can lead to confusion and missed targets. I’ve found that effective communication is the key to maintaining this balance. It involves open discussions about expectations, setting clear goals, and fostering a culture of openness. Creating an environment where predictability and adaptability complement each other, allowing plans to adjust while providing a sense of direction is the way to go! Remember, growing in Agile isn’t just about mastering agile methodologies; it’s about mastering this balance. It’s about becoming a guide through change, knowing when to lean on predictability or adaptability. It’s not about choosing one side but seamlessly integrating both, using predictability and adaptability to drive projects forward in an ever-changing environment. Have you grappled with this balance in your Agile journey? How do you keep it in check in your projects? Please share your thoughts to enlighten others. Do Check Our LinkedIn post.

Navigating the Rough Waters of Agile Offshore Teams: A Coach’s Playbook

Intro: The Uncharted Waters of Agile Transformation Agile is no longer the new kid on the block. Over the past two decades, it’s been around the block, through the maze, and even found its way into traditional, non-tech sectors. But despite its widespread application, one thing that’s rarely talked about is how Agile fits with offshore remote teams. Businesses are heading toward this model in droves, and yet we’re still stuck on Agile playbooks that advocate for co-location. So, let’s cut to the chase: How do we make Agile work in this complex offshore maze?   A Story Worth Telling: The Offshore Abyss Let’s walk through a common war story.  You’re working with a client in the Midwest, running a Scrum team that’s a cocktail of cultures and time zones. You have folks in India, Argentina, and Romania. Right off the bat, your Scrum Master is struggling. The offshore team members are shying away from the camera, creating a virtual barrier that’s hard to break down. These ‘invisible’ members find themselves swimming in their private ponds, disconnected from the team’s collective objectives. The Scrum Master looks like a helpless spectator, attempting to conduct Scrum events but never really achieving the cohesion Agile demands.   The Elephant in the Room: When Time Zones Attack But what about another beast? The time zones. Forget the cultural barriers and organizational eccentricities for a second. The sheer lack of overlapping working hours between Romania and Argentina, and India and US for example, is a challenge of herculean proportions. Your daily standups turn into an uncomfortable juggle between the early mornings and late nights, and you struggle for more team time but know it can’t come without making someone less happy.   More Than Just Cultural Gaps: The Silent Struggles And, then there are cultural nuances. Imagine having a Product Owner who’s a Westerner—outspoken, assertive, and always open for dialogue. Now pair this person with team members from India or Romania, where the culture might promote more subdued, less confrontational communication styles. You have a fertile ground for misunderstanding and missed opportunities.   The Devil’s in the Details: Misaligned Metrics And let’s not forget, your offshore team members aren’t just juggling multiple tasks, they’re juggling multiple performance metrics. They have their managers and KPIs to answer to, which often don’t align with Agile methodologies. It’s not their fault, but it’s a hurdle, nonetheless.   The Way Out: Strategies that Actually Work So, how did we overcome these challenges in our war story? First, I pulled everyone back to the basics—to the ‘Why’ of Agile. With regular training sessions, we rehashed the essence and importance of every Agile ceremony. When team members understand why they are doing what they’re doing, the ‘how’ becomes easier. It adds a layer of respect and purpose to daily stand-ups and retrospectives. For the Scrum Masters in the room, it’s time to embrace the essence of Servant Leadership fully. No longer can they afford to be mere facilitators; they must be leaders who command respect and are capable of guiding their troops through the Agile labyrinth. This starts with equipping them to have tough conversations, even with the vendor managers of their offshore team members. The key is intimacy. I advised Scrum Masters to conduct more targeted one-on-ones with their team members. If you want to break down barriers, start by building bridges. Forging individual relationships can provide team members the safety to voice out their challenges and concerns, be it time zones or vendor metrics.   Avoiding the Pitfalls: Lessons from the Trenches If you’re a leader navigating these waters, remember that Agile doesn’t just ask for co-located teams; it demands small and stable teams. Offshore or not, team members are humans, not resources. Moving them around like chess pieces can severely destabilize your Agile practices. Another pitfall is stretching your Scrum Master too thin. Serving two teams filled with offshore members from multiple time zones is a recipe for burnout and inefficiency. Take this off their plate. Make it an organizational concern.   Conclusion: Doing Agile Right—Anywhere, Everywhere To be clear, there’s nothing inherently wrong with having offshore team members in Agile teams. It’s the lack of aligned practices and the underestimation of the complexities involved that trip us up. We’re writing the rulebook as we go along, but one thing is crystal clear: Agile can be successfully implemented in remote, offshore settings. It takes a village of committed leaders, empowered Scrum Masters, and engaged team members. Guidelines and working agreements must be in place with clear expectations that all parties agree and adhere to. Otherwise, the complexity of it all will weigh too heavy for Agile to start rolling smoothly

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