Using Data Analytics in Consulting

Many amazing presenters fall into the trap of believing their data will speak for itself. But it never does… Our brains aren't spreadsheets, they're story processors. You may understand the importance of your data, but don't assume others do too. The truth is, data alone doesn't persuade…but the impact it has on your audience's lives does. Your job is to tell that story in your presentation. Here are a few steps to help transform your data into a story: 1. Formulate your Data Point of View. Your "DataPOV" is the big idea that all your data supports. It's not a finding; it's a clear recommendation based on what the data is telling you. Instead of "Our turnover rate increased 15% this quarter," your DataPOV might be "We need to invest $200K in management training because exit interviews show poor leadership is causing $1.2M in turnover costs." This becomes the north star for every slide, chart, and talking point. 2. Turn your DataPOV into a narrative arc. Build a complete story structure that moves from "what is" to "what could be." Open with current reality (supported by your data), build tension by showing what's at stake if nothing changes, then resolve with your recommended action. Every data point should advance this narrative, not just exist as isolated information. 3. Know your audience's decision-making role. Tailor your story based on whether your audience is a decision-maker, influencer, or implementer. Executives want clear implications and next steps. Match your storytelling pattern to their role and what you need from them. 4. Humanize your data. Behind every data point is a person with hopes, challenges, and aspirations. Instead of saying "60% of users requested this feature," share how specific individuals are struggling without it. The difference between being heard and being remembered comes down to this simple shift from stats to stories. Next time you're preparing to present data, ask yourself: "Is this just a data dump, or am I guiding my audience toward a new way of thinking?" #DataStorytelling #LeadershipCommunication #CommunicationSkills

Master the art of Financial Storytelling 🧑🏫 Your numbers tell a story, but are you telling it right? 👇 Numbers without context are just digits on a page. The real power comes from transforming those numbers into insights that drive action. ➡️ COMMON MISTAKES IN FINANCIAL REPORTING Let's start with what NOT to do when presenting financials: 1️⃣ Dropping raw numbers without context Raw data overwhelms your audience. When you say "Revenue grew to $100K," what does that mean for the business? 2️⃣ Reading slide content word-for-word Your presentation should add value beyond what's written. Share insights that aren't visible in the numbers. 3️⃣ Rushing through without pausing for questions Financial data needs time to digest. Create moments for discussion and clarification. ➡️ BUILDING A COMPELLING FINANCIAL STORY Here's how to transform your financial presentations: 1️⃣ Start with the fundamentals Always begin by establishing context. What's normal? What's exceptional? What benchmarks matter? 2️⃣ Connect data points to strategy Show how financial results link to business decisions. If working capital improved, explain which specific actions drove that improvement. 3️⃣ Use comparisons effectively - Period over period changes - Budget vs actuals - Year over year trends - Industry benchmarks 4️⃣ Structure your narrative - What happened? - Why did it happen? - What does it mean for the future? - What actions should we take? ➡️ COMPONENTS OF GREAT FINANCIAL STORYTELLING 1️⃣ Clear Dashboards Start with a clean, focused view of KPIs that matter most. Don't overwhelm with data. 2️⃣ Strategic Context Show how financial results connect to company goals and market conditions. 3️⃣ Forward-Looking Analysis Use current data to paint a picture of future opportunities and challenges. 4️⃣ Action Items End every presentation with clear next steps and decision points. ➡️ PRACTICAL TIPS FOR IMPLEMENTATION 1️⃣ Know your audience CFO needs different details than the marketing team. Adjust your depth accordingly. 2️⃣ Use visual aids Graphs and charts can illustrate trends better than tables of numbers. 3️⃣ Practice active listening Watch for confusion or disengagement. Adjust your presentation based on real-time feedback. 4️⃣ Create discussion points Plan specific moments to pause and engage with your audience. === Remember: Financial storytelling isn't about making numbers sound good. It's about helping stakeholders make informed decisions. What techniques do you use to make financial data more engaging? Share your thoughts in the comments below 👇

There's nothing more painful than watching a data scientist stumble through a presentation without a framework. They dump data, show too many charts, forget to make a recommendation - and wonder why nothing happens. What they're missing is a proven structure that actually persuades. Here's the battle-tested structure that data scientist Russell E. Walker, PhD taught me from his experiences in competitive debate, that transforms technical presentations into persuasive business cases: 1. 𝗛𝗔𝗥𝗠 - 𝗪𝗵𝗮𝘁'𝘀 𝘁𝗵𝗲 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗽𝗿𝗼𝗯𝗹𝗲𝗺? ✴️ Don't just state facts - frame the problem in terms your audience cares about For example: ✴️ For a medical audience: "Patient hospitalizations increased 20%"   ✴️ For a finance audience: "Hospitalization costs increased 20%" Same data, different framing 2. 𝗦𝗜𝗚𝗡𝗜𝗙𝗜𝗖𝗔𝗡𝗖𝗘 - 𝗛𝗼𝘄 𝗯𝗶𝗴 𝗶𝘀 𝘁𝗵𝗲 𝗶𝗺𝗽𝗮𝗰𝘁? ✴️ Quantify the harm in dollars, time, or other metrics that matter  ✴️ Put it in context (e.g. "This represents 15% of our annual profit") ✴️ Make it material to business goals 3. 𝗜𝗡𝗛𝗘𝗥𝗘𝗡𝗖𝗬 - 𝗪𝗵𝘆 𝘄𝗼𝗻'𝘁 𝘁𝗵𝗶𝘀 𝗳𝗶𝘅 𝗶𝘁𝘀𝗲𝗹𝗳? ✴️ Identify the root cause  ✴️ Show the problem is systemic, not temporary   ✴️ Prove intervention is necessary (e.g. "This trend has continued for 18 months despite normal business cycles"). 4. 𝗦𝗢𝗟𝗩𝗘𝗡𝗖𝗬 - 𝗛𝗼𝘄 𝗱𝗼𝗲𝘀 𝘆𝗼𝘂𝗿 𝗿𝗲𝗰𝗼𝗺𝗺𝗲𝗻𝗱𝗮𝘁𝗶𝗼𝗻 𝘀𝗼𝗹𝘃𝗲 𝗶𝘁? ✴️ Present your plan or recommendation  ✴️ Connect the dots: show exactly how your solution addresses the root cause  ✴️ Loop back to the original harm (e.g. "This will reduce hospitalizations by X%, saving $Y annually") This works because you're taking your audience on a logical journey from problem to solution - each step builds on the previous one. And it works for any data science presentation - whether you're presenting a model, recommending process changes, or requesting resources. Try this structure in your next presentation. Start with the business problem your audience cares about, not with your methodology. Stop watching your brilliant insights get ignored because of poor presentation structure. How do you currently structure your data science presentations? #datascience #business #career --- 👋 If you enjoyed this, you'll enjoy my newsletter. Twice weekly, I share insights to help data scientists get noticed, promoted and valued. Click "Visit my website" under my name to join.

I watched a junior analyst present a finding that could have saved her company $2M a year. The room went silent. Everyone nodded. The CEO said, "Great work." Then they moved to the next agenda item. Six months later, nothing had changed. She never presented data again without a recommendation. Here's what she learned. You know this routine: You run the numbers. You build the dashboard. You present the report. And then… you wait. You wait for "decision-makers" to decide. That's where your role ends, right? Except you've probably watched it happen: You uncover a critical trend. Everyone nods. They call it "important" and "insightful." Then the meeting ends. The Slack thread goes quiet. The dashboard gets bookmarked and forgotten. No action. No change. No impact. Your best work, dead on arrival. Here's why: Data doesn't move the world. People do. And the person best equipped to guide the decision? Often, it's you. But somewhere along the way, we convinced ourselves that our job is to inform, not to influence. The next time you're in that room, try changing the script. Instead of stopping at: ✔ "Here's what the data shows" Go three steps further: ✅ "Here's what it means for our strategy" ✅ "Here's what I recommend we do next" ✅ "Here's the risk if we don't act" Watch what happens. The room shifts. Questions get sharper. The energy changes. You're no longer just reporting findings—you're guiding decisions. Leaders respect clarity. Teams value direction. And your insight finally has a fighting chance to become impact. Your role isn't to drop numbers on the table and disappear. You're not a human calculator. You're not a chart factory. You are: A strategist who sees patterns others miss A problem-solver who connects dots across departments. A driver of action who turns "interesting" into "essential" Your voice might be the single difference between another forgotten dashboard and a real-world change that actually matters. So the next time you're tempted to hold back because "my job is just to present the data"— Stop. Your work doesn't end at insight. It ends at impact. And impact requires you to speak up, lean in, and guide the room toward what the data is screaming at them to do. Have you ever held back a recommendation because you thought it wasn't your place to say it? What happened? Did someone else eventually make the call, or did the insight just... disappear? I'd love to hear your story.

In a sea of possible insights, how do you know which are worth reporting? As a data analyst, there are two types of insights you will report: 1) Ones that are directly aligned to a business question or priority 2) Ones that nobody is asking for… but should be 90% of the time, you should be focusing on the first one. But when done right, the second can be very powerful. So… how do you find those hidden insights? How do you know which ones truly matter? ➤ Explore high-level trends Scan dashboards, reports, or raw data for unexpected patterns. Look for sudden spikes, dips, or emerging trends that don’t have an obvious explanation. ➤ Slice the data by different dimensions Break data down by different categories (customer segments, time periods, product lines, etc.). Where are things changing the most? Which groups are behaving unlike the others? ➤  Identify outliers Look at the extremes. What’s happening with your best customers? Worst-performing regions? Most productive employees? Outliers often reveal inefficiencies or hidden opportunities. ➤ Tie insights to business impact Before reporting, ask: Would knowing this change a decision? If it doesn’t, it’s probably not worth surfacing. ➤ Pressure-test with stakeholders Run your findings by a manager or friendly stakeholder. Ask them if the finding resonates with other trends they've seen, whether they see potential value, and whether it could influence strategy. In other words: - Start broad - Dig deep - Sense-check —-— 👋🏼 I’m Morgan. I share my favorite data viz and data storytelling tips to help other analysts (and academics) better communicate their work.

Data alone won’t get you approved. (Let’s fix it with 5 secret Storytelling ingredients) I spent 2 years on an EV fast-charging project. Published 2 papers & filed 2 patents. A success, right? BUT… when I presented to sponsors... there was pin-drop silence in Zoom room. I lost them to their smartphones. Another opportunity wasted. MISSING PIECE? I was presenting data, not stories. Steal this 5-step process to turn boring data into stories: 1/ SETTING (Time & Context) ↳ When and where your story unfolds ↳ Creates immediate relevance BUSINESS EXAMPLE: ❌ "We had system downtime" ✅ "At 2 PM on Black Friday, our checkout system crashed while 50,000 customers were trying to buy" DAILY USE: → Status meetings: "During yesterday's client call..." → Problem reports: "Right before the quarterly review..." → Strategy presentations: "In the current economic climate..." TAKEAWAY: Context turns facts into urgency. 2/ CHARACTERS (Your Stakeholders) ↳ WHO gets impacted by your message ↳ Makes abstract problems personal BUSINESS EXAMPLE: ❌ "Customer satisfaction declined 15%" ✅ "Jennifer, our top enterprise client who renewed for 4 years straight, called to cancel her contract" DAILY USE: → Executive updates: Name the affected teams/customers → Budget requests: Show WHO benefits from approval → Change proposals: Identify WHO struggles with current state TAKEAWAY: People fund people, not percentages. 3/ NORMAL STATE (Baseline) ↳ How things operated before the problem ↳ Establishes what "good" looks like BUSINESS EXAMPLE: "For 18 months, our support team handled 200 tickets daily with 4-hour response time" 4/ DISRUPTION (The Change) ↳ What broke the normal pattern ↳ Creates tension that demands action BUSINESS EXAMPLE: "Then the product launch tripled our user base overnight, and response time hit 48 hours" TAKEAWAY: Story is about contrast: “before” vs. “what went wrong.” 5/ RESOLUTION (New Normal) ↳ What happened AFTER addressing the disruption ↳ Shows outcome and path forward BUSINESS EXAMPLE: "We hired 3 specialists, automated tier-1 responses, and cut response time to 90 minutes while handling 600 daily tickets" DAILY USE: → Project wrap-ups: Show the measurable improvement → Lessons learned: Share what changed permanently → Success stories: Provide the roadmap others can follow TAKEAWAY: Your resolution becomes their next action plan. IMPLEMENTATION FRAMEWORK: Before your next presentation, answer these: 1️⃣ WHEN/WHERE does this matter most? 2️⃣ WHO gets affected if nothing changes? 3️⃣ HOW were things working before? 4️⃣ WHAT specifically broke or changed? 5️⃣ WHERE does this lead us next? 5 questions. 5 elements. Every presentation. ♻️ REPOST if your presentations need more impact ➕ Follow Waqas, P. for communication skills 💾 SAVE for future use 📌 How often you see presenters losing audiences to smartphones?

Imagine you've performed an in-depth analysis and uncovered an incredible insight. You’re now excited to share your findings with an influential group of stakeholders. You’ve been meticulous, eliminating biases, double-checking your logic, and ensuring your conclusions are sound. But even with all this diligence, there’s one common pitfall that could diminish the impact of your insights: information overload. In our excitement, we sometimes flood stakeholders with excessive details, dense reports, cluttered dashboards, and long presentations filled with too much information. The result is confusion, disengagement, and inaction. Insights are not our children, we don’t have to love them equally. To truly drive action, we must isolate and emphasize the insights that matter most—those that directly address the problem statement and have the highest impact. Here’s how to present insights effectively to ensure clarity, engagement, and action: ✅ Start with the Problem – Frame your insights around the problem statement. If stakeholders don’t see the relevance, they won’t care about the data. ✅ Prioritize Key Insights – Not all insights are created equal. Share only the most impactful findings that directly influence decision-making. ✅ Tell a Story, Not Just Show Data– Structure your presentation as a narrative: What was the challenge? What did the data reveal? What should be done next? A well-crafted story is more memorable than a raw data dump. ✅ Use Clean, Intuitive Visuals – Data-heavy slides and cluttered dashboards overwhelm stakeholders. Use simple, insightful charts that highlight key takeaways at a glance. ✅ Make Your Recommendations Clear– Insights without action are meaningless. End with specific, actionable recommendations to guide decision-making. ✅ Encourage Dialogue, Not Just Presentation – Effective communication is a two-way street. Invite questions and discussions to ensure buy-in from stakeholders. ✅ Less is More– Sometimes, one well-presented insight can be more powerful than ten slides of analysis. Keep it concise, impactful, and decision-focused. Before presenting, ask yourself: Am I providing clarity or creating confusion? The best insights don’t just inform—they inspire action. What strategies do you use to make your insights more actionable? Let’s discuss! P.S: I've shared a dashboard I reviewed recently, and thought it was overloaded and not actionably created

If your HR data lives on dashboards, you owe it to your dashboard users to turn those numbers into stories that spark action. Here’s the key: Context, Clarity, and Connection I'm a founder of natural language AI for HR data insights, I talk to a lot of HR executives. Not every company is ready to hook AI up to their HRIS or dashboards for full cycle automation of custom reports. So here's how you can take action now: 🟩 Context: Don’t just say, “Our turnover rate is 15%.” Show why it matters: “Turnover has jumped from 10% to 15% since we cut back on flexible work policies. That’s costing us an extra $250K in rehiring and training.” 👉 By adding context—historic trends, external comparisons, or qualitative insights from exit interviews—you transform an isolated number into a relevant piece of intelligence. 🟩 Clarity: Skip buzzwords. Instead of burying leaders in pivot tables, highlight the core insight: “Our data shows that when managers engage in weekly check-ins, their teams stay 12% longer and report 20% higher job satisfaction.” 👉 Simplicity is crucial. Data can be daunting, so distill it into its most straightforward form. Describe what’s happening in plain language, highlight the key takeaway, and avoid excessive buzzwords. 🟩 Connection: Make the data human. Share a brief story about an employee’s journey—how they left due to inflexible hours, or how a new mentorship program increased retention. 👉 This personal angle sticks in leaders’ minds and moves them to act. When data is told as a story, it becomes memorable, persuasive, and actionable. That’s how you move from presenting numbers to driving real change. Storytelling is GREAT ⭐ 👍 Visualization: By combining that number with a narrative—like highlighting how three top performers left due to inflexible work policies—suddenly, you have context and emotion. Decision-makers can visualize the impact on projects, productivity, and team morale. 👍 It Captures Attention Leaders face a tidal wave of emails, reports, and dashboards every day. A compelling story cuts through the clutter. Instead of reading yet another data dump, they encounter a narrative that clearly connects metrics to outcomes (such as cost savings, product quality, or customer satisfaction). 👍 It Accelerates Buy-In Numbers can be debated or ignored, but when they’re woven into a story that resonates—especially one that ties to real pain points—leaders are far more likely to take action. A powerful story engages emotion and logic, making it easier for people to rally behind a solution. What's your Data storytelling tip? What works with your leaders ? #peopleanalytics #hrdata #peopledata #hr #dashboards #hrdashboards

Your clients don't need data providers. They want strategic advisors. So share your perspectives on key takeaways. Highlight risks, challenges, and chances to improve. Translate data into insights that tie back to client goals and priorities. Make data-driven recommendations. Ask hard questions to extract the story behind the data. Turn conversations with clients into strategic discussions, not just reports. Data alone isn't valuable. Real impact comes from advisory that blends analytics with critical thinking.

As analysts, uncovering valuable insights is just the first step. The real magic happens when those insights drive action and results. Here’s how I approach turning analytics into decisions that matter: 1️⃣ Start with the End in Mind Always tie your analysis to a business objective. Whether it's increasing user retention, reducing churn, or improving operational efficiency, knowing the "why" behind your data ensures your insights are actionable. 2️⃣ Frame the Narrative Insights are only as powerful as the story behind them. Craft a narrative that’s: Clear - Avoid technical jargon; explain what’s happening and why. Concise - Highlight the key takeaways in a few bullet points or visuals. Compelling - Use data visualizations or analogies to make your insights memorable. 3️⃣ Collaborate Early and Often Actionable insights often require buy-in from multiple stakeholders. Engage key decision-makers, product managers, and engineers early in the process to align on priorities and understand constraints. 4️⃣ Provide Recommendations Data alone doesn’t drive action—recommendations do. Pair every insight with a clear next step, such as: A/B test this feature for higher engagement. Adjust pricing strategy to improve conversion rates. Focus marketing efforts on underpenetrated customer segments. 5️⃣ Quantify Impact Leverage forecasts or historical comparisons to show the potential upside of acting on your recommendations. For example, “Implementing X could increase revenue by 10% over the next quarter.” 6️⃣ Follow Through Action doesn’t end with delivering insights. Stay involved: Monitor implementation progress. Measure outcomes against your forecasts. Share success stories or lessons learned. 7️⃣ Build a Culture of Action Encourage data-driven decision-making across your organization. Host workshops, create dashboards, or share case studies of how analytics has driven impact. Insights are powerful, but actionable insights are transformative. What steps do you take to ensure your analytics drive real-world change? #data #dataanalytics #datainaction