The Importance of KPIs for Decision-Making

“If we track everything, we’ll finally feel in control.” That’s what a founder told me before launching a 60+ KPI dashboard. It was real-time. Color-coded. Mounted on TVs across the office like a Formula 1 pit wall. And it completely backfired. Here’s what actually happened: - The founder checked it every hour… and panicked when a number dipped. - Meetings turned into 45-minute metric marathons. - The team checked out, not because they didn’t care, but because they didn’t understand what mattered. The truth? Startups don’t fail because they lack data. They fail because they track everything, and act on nothing. More metrics = more noise. More dashboards ≠ more clarity. So… how do you choose the right KPIs? Start here: 1. Anchor to a core objective. What does success look like right now? (Retention? Burn runway? Gross margin?) 2. Define decision-making needs. If a metric doesn’t inform a clear decision, cut it. 3. Limit by team, not by dashboard. Give each leader 2–3 metrics they own, understand, and drive. 4. Make it human. A KPI is only useful if your team understands it. Talk about it. Teach it. Use it to drive action, not anxiety. It’s about shifting the conversation inside the company: → From reporting to decision-making → From panic to progress → From reactive leadership to aligned execution If you’re scaling and your dashboard looks impressive but feels like noise, it’s probably time for a reset. PS: Be honest, how many KPIs are you currently tracking?

Many businesses struggle with financial reports because they track: • The wrong things • Not enough things • Too many different things The result? Confusion instead of clarity. Ask yourself: Why are you tracking that metric? If the answer is: “Because that’s what I was taught in school.” “The trade association said so.” “It’s what we’ve always done.” Then you are tracking data, not facilitating decisions. Instead, use Connected KPIs—a framework where each KPI links back to a strategic goal. 1. Start with your desired outcome (e.g., revenue growth, profitability). 2. Work backwards to identify the key drivers. 3. Focus on the lead domino (the metric that starts the chain reaction) What are the lead dominoes in your financial reporting?

Day 6 of whatever it takes, Continuing our discussion on the optimization of Fraud Model & thereby reducing the False positives to improve the Customer Satisfaction & Reduce the revenue loss. Below were the KPIs we talked about: 1. Business Impact: False Positive Rate (FPR), Revenue Loss Due to False Positives, Customer Churn Rate Post-False Positive, Business Impact Score (BIS) & finally, Returns on Investment (ROI). 2. Customer Experience: Customer Complaint Volume (Related to Fraud Flagging), Average Resolution Time for False Positives, Customer Satisfaction Index (CSI), Revenue Reinstatement Rate Post-Resolution, Net Promoter Score (NPS) Post-Incident, Customer Account Blocking Rate, Repeat Incidence Rate of False Positives. 3. Model Drift: Population Stability Index (PSI), Feature Importance Drift, - Concept Drift Metrics (Sudden and Gradual Drift Detection): By monitoring for both sudden shifts and gradual pattern changes, these metrics help capture new fraud tactics quickly. - Model Performance Degradation Over Time: Observing declines in core metrics like precision and recall provides a direct indication of how well the model is coping with drift. - Retraining Frequency and Adaptation Impact: Tracking retraining frequency shows how adaptable the model is to changing patterns and can indicate areas where the data environment is volatile - Drift Detection Using Adversarial Validation: By creating a classifier to detect differences between past and current data, this KPI provides a nuanced look at subtle shifts that may otherwise go unnoticed - Error Rate Increase Across Data Segments: Monitoring error rates for specific customer groups helps to localize drift impacts, ensuring that segments like small businesses are not disproportionately affected. - Time to Detection of Drift-Triggered Performance Drop: This KPI ensures that any significant performance drop is quickly flagged and corrected, minimizing the risk of ongoing misclassifications. The revenue part of the business which also gets impacted due to High Number of False positives are also important to interpret: - Revenue Impact of False Positives: Total revenue of legitimate transactions blocked or delayed due to incorrect fraud flags. - Average Revenue per Blocked Transaction: Total Revenue Impact of False Positives/Total number of such transactions - Lifetime Value (LTV) Loss from False Positives:  Sum of LTV for customers who churned due to false positives. - Average Revenue Delay Due to False Positives: Average time delay multiplied by revenue for transactions wrongly flagged as fraud. - False Negative Revenue Impact (Missed Fraud): Estimated revenue lost to undetected fraud cases. These KPIs across Business Impact, Customer Experience, Model Drift and Revenue Loss will help us in understanding the technical details of the optimization. #FraudOptimization #ML #Data #Analytics #DataDrivenDecisionMaking #Intelligence #consistency

What happens when the board asks about metrics that aren't on those reports? How's the cash conversion cycle looking? What’s the return on equity? You pause. You’re great at the details, but the bigger picture? It feels... overwhelming. And here’s the thing—today’s accountants are expected to go beyond just the numbers. You're not just closing books anymore; you're expected to guide the business, spot risks, and predict opportunities. But how can you do that if you're only focused on what’s already happened? Without the right KPIs, you're flying blind. You might nail every journal entry, yet miss the warning signs in liquidity. Your reports could look polished, but they might not tell the story leadership needs. It’s frustrating, right? Knowing there’s more you should deliver, but not being equipped to do so. The reality is clear: the numbers on the surface are no longer enough. To really deliver value, you need to understand the core drivers behind them. That’s where knowing the right KPIs makes all the difference. _________ Follow Amit Kumar for more insights around accounting and finance. #financekpis  #businessandaccounting  #finance

$5,000,000 revenue. 100 employees. Zero real metrics. Here's the dead-simple system that fixes it this week: Last week, I was talking to a founder who built a high-touch SaaS platform for medical practices. Great margins, solid team, but he was hitting the leadership ceiling hard. When I dug into his operation, I found the problem immediately. No cascading KPIs. No clear metrics. No visibility into who was actually performing. He was running a $5M business like a corner store. Making decisions based on gut feel. Hoping people would figure it out. Delegating without any way to measure results. That's not leadership. That's expensive guesswork. Here's the exact framework we used to fix it: The 3-Level KPI Stack Level 1: Company KPIs (3-5 maximum) Monthly recurring revenue growth Customer acquisition cost Net revenue retention Gross margin percentage Level 2: Department KPIs (tied directly to company goals) Sales: Lead conversion rate, average deal size, sales cycle length Product: Feature adoption rate, bug resolution time, user engagement Support: Response time, resolution rate, customer satisfaction Level 3: Individual KPIs (tied directly to department goals) Sales rep: Calls per day, demos booked, deals closed Developer: Features shipped, code review completion, sprint goals hit Support agent: Tickets resolved, first-call resolution, satisfaction score The Weekly Execution Process: Monday: Everyone submits their numbers in a shared Google Doc Wednesday: Department heads review and flag issues Friday: Company-wide brief on what's working and what's not No fancy software. No complex dashboards. Just 5 minutes a day to get brutal clarity. The moment you install this system, weak performers can't hide and strong performers get the recognition they deserve. Every decision based on feelings costs you money. Every decision based on data makes you money. Ready to stop running your million-dollar business on vibes? I'm sharing the complete KPI framework that turns chaos into clarity in my upcoming workshop: https://buff.ly/BRpKAKr