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The Analyst's Guide Beyond Technical Skills

Updated: Apr 4

To the tireless data warriors, those who breathe life into numbers, navigating the seas of data day in and day out, this one is for you!

Once upon a Tuesday, in the heart of a bustling office in Chennai, India, there was an analyst named Ani. Ani had just cracked a tough nut—a problem that had the whole team scratching their heads for months. When the solution clicked, it wasn't just a win; it was a high-five, fist-bump, office-hero kind of moment. Balloons seemed to materialize, and the humble line chart never looked so festive.

As the confetti settled, Ani sat back, with pride and a satisfying sigh of a puzzle solved. But the celebration was a fleeting pause, a mere comma in the relentless grammar of to-dos. With a reflective smile, Ani opened the backlog in a Google spreadsheet and clicked to reveal the next challenge, the next opportunity, the next enigma waiting for a solution. Why? To replicate the thrill of victory, to relive the rush of being the office hero, the data whisperer whose insights whispered of short-term triumphs. These victories weren't just about personal accolades; they were stepping stones, laying the path toward a promotion.

But wait—does this sound familiar to you? This relentless march from one task to the next, one project to another, without ever stopping to ask: "What's it all for?" Sure, Ani’s work was stellar, but in the grand tapestry of the organization, where did these threads weave into the larger picture? What value did Ani’s work truly contribute? It's easy to become engrossed in the lifecycle of task after task, project after project, but dare to ask yourself: How does your work ripple across the pond of your company's strategy?

If you're always looking down at your feet, you will miss the horizon.

Ever heard the one about data analysts and a journey of a thousand miles? Well, it starts with a single step – or in our case, eight clearly defined ones. Welcome to the bustling metropolis of analytics, where ideas aren't just fleeting thoughts; they're the seeds of revolutions in spreadsheets and dashboards. But let’s face it, not every seed grows into a towering oak. To navigate the twists and turns of this data-driven odyssey, an analyst needs to be a jack-of-all-trades and a master of...well, all eight stages of an analytics project. Why, you ask? stay with me for the next 10 minutes uninterrupted, my amigo. We’re about to unravel the tapestry of an analytics project lifecycle that could very well save your career from the clutches of our friendly neighborhood AI. Having used Gen AI to reproduce some of my best work in the last 14 years, I can promise you that it is going to slowly disrupt everything an analyst does. Check out the Analyst's Guide to take all the steps you can to futureproof your career today.

Spoiler alert: those who cozy up too long in the comfort zone of stages 5, 6, and 7 might just find themselves on the endangered species list.

8 Stages of an Analytics Project

The cover image for 'Stages of Every Analytics Project' by Framework Garage Consulting, which outlines the eight critical stages in any analytics project. It begins with Stage 1, representing the initial idea or request, and culminates in Stage 8, the delivery. Each stage is visually delineated with unique icons and a dotted line, symbolizing the structured progression through research, logic building, development, quality checks, and insight preparation, integral to becoming an effective analyst. It's a framework and lifecycle championed by Anirudh Kuthiala.
8 stages of every analytics project

I shared this 2 editions ago in 3 Must-Have Skills for Analysts to Thrive in the Age of Generative AI. It wasn't just another fancy framework picked from the endless sea of LinkedIn posts or the glossy pages of HBR. This was something born out of the trenches, from the grind of 100s of projects and a 14-year marathon in the analytics arena. It’s real-world, it’s tested, and —it fits any analytics project like a glove.

So, as we dive into these 8 stages, remember, that they're more than steps; they're the breadcrumbs that lead us out of data chaos into realms of structured and strategic thinking. And this isn’t just talk—I've walked this path and can assure you that it’s a practical approach to place analytics as a strategic partner toward business growth.

Stage 1 - Idea or a request

A comprehensive GIF by Framework Garage Consulting illustrating the full journey of an Analytics Project, from Stage 1 to Stage 8. The graphic starts with Stage 1 - Idea or Request, highlighting the initial concept or need for analytics. Each subsequent stage is interconnected, depicting the progression from brainstorming and probing in Stage 2, to the final delivery in Stage 8. The path is marked with distinctive icons and numbers, reflecting the systematic approach to analytics strategy consulting and data analysis consulting championed by Anirudh Kuthiala.
Stage 1

Stage 1 can start with either an idea or a request. When it's an Idea, it's all about proactive thinking (my favorite space of operating). Here, you're not just a participant; you're a trailblazer, identifying areas ripe for improvement or new solutions. It’s your lightbulb moment, where analytics steps into the spotlight of strategy and problem-solving. On the flip side, when it's a Request, you're responding to a specific need or question posed by others. This is where your analytical skills meet the real-world demands, translating someone else's challenge into a data-driven opportunity. Whether it's an internal spark or an external ask, Stage 1 is where the analytics adventure takes its first step.

Skills needed to be effective in stage 1

  • Business Acumen

  • Data Acumen

  • Stakeholder / Client Relationship Management

Stage 2 - Brainstorming or Probing

This informative GIF by Framework Garage Consulting showcases Stage 2 of an Analytics Project, which involves Brainstorming and Probing. A figure in silhouette form stands reflecting, with the iconic superhero outline signifying the strength and strategy behind analytics career coaching. In the thought bubble, a classical statue in deep thought embodies the brainstorming and probing process, essential for laying the groundwork before starting any development in an analytics project.
Stage 2

Here we stand at the crossroads of creativity and inquiry. If it's an idea, this is where brainstorming ignites, where you want to test if your solution has merit. It's the breeding ground for innovation, where your proactive prowess shines, and strategic questions give birth to transformative ideas.

Tip - Rather than brainstorming about the possibility of a solution, you must connect it to a KPI or even better, North Star for your company. This approach is more than just a guiding principle; it's a way to ensure your work directly contributes to the broader mission.

But if it's a request, then probing is the name of the game. It’s a deep dive into the ‘what’ and ‘why’ behind the ask, ensuring that the solution isn't just a band-aid but a blueprint for success. This stage is the forge where raw thoughts are hammered into the beginnings of a solution.

To exit this stage effectively, ensure to have answers to at least these 3 questions.

  1. Which questions can be answered by what you are going to work on?

  2. Once those questions are answered, which decisions will those answers drive?

  3. How do those decisions impact your organization’s business growth?

It’s from my Data Value Trailblazer Framework - something I’ve simplified and honed over the last decade. You should always build your analytics product based on the answers to these 3 questions. Here’s the fun part - if a project doesn’t answer the first two questions, you are empowered to nicely and confidently say no and deprioritize. This isn’t just smart; it’s strategic. It’s your golden ticket to managing your workload like a pro, ensuring every bit of your effort is invested in projects that truly move the needle.

Skills needed to be effective in Stage 2

  • Critical Thinking

  • Strategic Thinking

  • Communication (Probing)

Stage 3 - Research

This engaging GIF from Framework Garage Consulting highlights Stage 3 of an Analytics Project, focusing on Research and Capabilities Assessment. A silhouette stands thoughtfully, looking towards a superhero outline, representing the skills needed to be an effective analyst. A magnifying glass over folders within a thought bubble with the number 3 emphasizes the research phase, where an analyst evaluates their data analysis competencies and resources to achieve the end objective. It's a framework designed by Anirudh Kuthiala
Stage 3

This is the detective work phase, where you don your investigator's hat and your data and business acumen come into play. A lack of acumen would force you to ask for help (which is okay if you are new). It's an introspective journey into your arsenal – do you have the right tools, the right data, the right skills? It’s about understanding the landscape of your resources and sizing up your capacities against the towering task ahead. It's a pivotal point that asks a crucial question: "Do I have what it takes to bring this idea or request to fruition?" This stage sets the stage for a realistic pathway to achieving your project goals.

Tip - In this stage, you should be able to set expectations on timelines and dependencies.

Skill needed to be effective in stage 3

  • Data Acumen

Stage 4 - Logic Building

This GIF, crafted by Framework Garage Consulting, illustrates Stage 4 of an Analytics Project - Logic Building. It shows a thoughtful silhouette figure looking towards a superhero outline, representing the support provided by Framework Garage Consulting in analytics career development. The thought bubble with interlocking puzzle pieces and the number 4 underscores the crucial stage of constructing a robust analytics strategy, a key step in the journey of learning how to be an effective analyst.
Stage 4

Far from a formal process, it's a stage where we each find our rhythm. For some, it's purely a mental process sequencing the ‘how’. Others might pen down their logic in a diary. Then some sketch the journey, crafting flowcharts or mind maps. However it unfolds, each of us is architecting a plan, a unique logic trail that leads us through the 'how' to transform what's needed.

Tip - If your task involves coding, consider writing down your logic in steps and placing your code beneath each step. This not only serves as a useful internal note for you but also defines a clear objective for each code block.

Skills needed to be effective in stage 4

  • Structured Thinking

  • Critical Thinking

  • Strategic Thinking

Stage 5 - Development

An animated GIF by Framework Garage Consulting depicting Stage 5 of an Analytics Project - Logic Building. A contemplative silhouetted figure gazes at an outlined superhero, symbolizing the guidance provided by Anirudh Kuthiala in the realm of analytics career coaching. A brightly colored pyramid in a thought bubble with the number 5 signifies the critical phase of logic building in an analytics project lifecycle, essential for effective data analysis.
Stage 5

This is where the battle is fought with the tools of our trade and won with technical prowess. It's the stage of doing, of transforming plans and logic into tangible results. The theories and strategies laid out previously now meet the hands-on expertise of coding, modeling, and analysis. In this phase, your technical skills are the star of the show – they're what turn the theoretical into the actual. It's a testament to your competency, where your ability to execute is as crucial as your strategy. Here, the abstract becomes concrete as you build the solutions that will drive the project forward.

Skill needed to be effective in stage 5

  • Technical Acumen

Stage 6 - Quality Checks

This is the checkpoint and a safeguard against the slip-ups that can happen when you’re deep in the data trenches. With a blend of Sherlock's insight and a surgeon's precision, we test, debug, and validate, turning 'good enough' into 'flawless'. This is the crucible where technical skill truly becomes artistry, safeguarding the integrity and trust in our data narrative.

Tip - Always bake in time for quality checks in your estimates under stage 3. An analytical product with poor quality not only hits your credibility but also brings in rework a time investment that could have been avoided entirely.

Skill needed to be effective in stage 6

  • Technical Acumen

Stage 7 - Insights Prep

This is where the analytics product is born. Whether it's a detailed Excel spreadsheet, an insightful presentation, a dynamic dashboard, a predictive model, or a concise email, it’s an analytics product in the flesh and you are gearing up to share. It’s where we ensure our analytical product aligns perfectly with the needs outlined in Stage 2.

Skill needed to be effective in stage 7

  • Technical Acumen

Stage 8 - Delivery

An illustrative GIF presented by Framework Garage Consulting, showcasing Stage 8 of an Analytics Project - Delivery. It features a visual metaphor with a silhouetted figure looking up at an outlined superhero, symbolizing the empowerment and achievement in analytics career development. A location pin icon with the number 8 emphasizes the final stage of delivery in the analytics strategy consulting process, indicating the culmination of data analysis consulting and effective analytics implementation.
Stage 8

And here we are, the grand finale - Delivery. It's the moment of truth, where the fruits of our labor, from the spark of an idea or the clarity of a request in Stage 1, are ready for the world to see. Our analytics product makes its debut.

Your product could be delivered to a manager, client, or stakeholder. If this was born from an idea, brace yourself to bask in the glow of your strategic acumen. But if it was a request, it's time to fine-tune the symphony with feedback. Remember, feedback isn't just critique; it's a mirror reflecting the efficacy of our Stage 2 groundwork. Armed with the insights from those crucial questions we answered early on, we stand confident, ready to say, "This is exactly what you were looking for." Because, after all, isn’t that the point of it all? To not just deliver, but to delight.

Skills needed to be effective in stage 8

  • Communication

  • Data Storytelling

  • Strategic Thinking

But hold on…

The journey doesn't end at delivery. It's crucial to circle back and measure the real value of your work. Ask yourself: Can the requestor answer their critical questions with the data provided? Have they made informed decisions based on your analytics? And most importantly, what impact have those decisions had?

These answers not only connect your work to the bigger picture but also help quantify its impact, be it through KPI movement or revenue changes.

Remember, stating that you "Analyzed underperforming user behavior cohorts for conversion, unlocking an incremental $5.5 million increase in revenue" speaks volumes more than merely saying you "Built a comprehensive Tableau dashboard for tracking customer journeys."

It's not just about what you create; it's about the value and transformation your creation brings to the table.

Ever wondered which stages in the analytics lifecycle really demand your technical chops? If you're nose-deep in just honing technical skills, brace yourself – you might be steering towards an ineffective and doomed career as an analyst or leader. The reality is, that mastering all 8 stages is non-negotiable, and it's not just about technical prowess. The top skills that set you apart? Critical and strategic thinking, structured thinking, communication, data acumen, and business acumen. Sure, tech skills are part of the mix, but they're just about 40% of what makes a truly effective analyst!

The Analyst's Guide - Wrap-up

Wrapping up our journey through the 8 stages of an analytics project, it's crystal clear: to be a standout analyst, one must be adept across all these stages. Mastery here isn't just a feather in your cap; it's a vital step toward effectiveness in your career and a beacon for bigger leadership roles.

But here's a twist in the tale: with Generative AI already proving its mettle in stages 5, 6, and 7, those spending over 80% of their time in these zones need to heed the warning bells. If your organization is gearing up to embrace Generative AI applications, your job might just be hanging by a thread. It's time to broaden your horizons, to be effective not just in a slice but across the entire lifecycle.

Remember, an analyst isn’t just a bundle of technical skills. It’s a holistic package – strategy, innovation, execution, and impact assessment all rolled into one. This isn't just about crunching numbers; it's about generating confidence for your leaders to make data-informed decisions toward business growth.

Don’t be just good; redefine what it means to be an exceptional analyst in the age of AI and beyond.


Are you ready to step beyond the numbers and become the data whisperer your leaders can consult for decision-making? I understand that while the internet overflows with resources to sharpen your technical skills, it rarely touches upon the full spectrum of competencies you need to excel as an analyst or step into an analytics leadership role. That's where my Analytics Career Coaching and Training comes in.

With my guidance, you'll do more than just improve your technical acumen; you'll master the essential non-technical skills that make a well-rounded analytics professional. From strategic thinking to effective communication and from data storytelling to business acumen, we'll develop the entire package.

If you are looking to go beyond the comfort zone of technical proficiency. Let's cultivate the skills that aren't just desired but demanded by today's analytics leaders. Take that pivotal step with my coaching and build a solid foundation to have a fulfilling and successful career in analytics.

Schedule time to discuss your challenges or contact me at


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