The Analyst's Guide Beyond Technical Skills

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?

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.

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

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

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

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