Measuring Business Performance

In automotive, everyone stares at the same KPIs. Units. Gross. CSI. Nothing wrong with that, but KPIs only tell you where you landed. They don’t tell you how much you left on the table. Jay Abraham calls them OPIs.  Overlooked Performance Indicators. The tiny leverage points inside a dealership that almost no one pays attention to. And he’s right. Because when we started examining our own operation through that lens, here’s what we saw: Most of the biggest opportunities weren’t new initiatives. They were already happening… just not maximised. Things like: - How many service customers get an equity scan, every single day. - How quickly calls are returned. - How many unsold showroom ups get re-engaged the same day. - How many customers are actually aware they can leave service in a new car with a lower payment. - How many of yesterday’s RO customers got a follow-up. These aren’t budget items. They’re behaviour items. And when you improve several of these by just 10%? It’s not 10% growth. It compounds. Jay calls it multiplicative, and he’s not exaggerating. We saw it firsthand. No new building. No new staff. No miracle inventory. Just a team willing to question everything, tighten every gap, and squeeze every ounce of value out of the opportunities we already had. The result? One of the best months we’ve ever had. Because we got better at the invisible work that drives the visible numbers. That’s the real lesson here: The dealership doesn’t transform because of a single big move. It transforms because the team stops walking past the small ones. If you’re running a dealership, here’s a question worth asking: What are the OPIs in your business and who’s watching them?

Most L&D professionals learned the Kirkpatrick Model early on. Fewer have seen it applied beyond Level 1. Here's what each level can actually look like when you put it into practice, not just the textbook definition. ✨ Level 1: Reaction 🔹 Textbook version: Did learners find the training engaging and worth their time? ✅ In practice: Instead of "Did you enjoy this session?", ask "Was this relevant to the work you do?" and "Could you apply this right away?" ✅ Metric to track: Relevance and applicability ratings, not just satisfaction scores. ✨ Level 2: Learning 🔹 Textbook version: Did learners gain the intended knowledge or skills? ✅ In practice: Replace recall-based quizzes with scenario-based checks. Can the learner apply the concept to a situation they'd actually face? ✅ Metric to track: Pre/post assessment scores on scenario-based questions, not just "did you pass the quiz." ✨ Level 3: Behavior 🔹 Textbook version: Are learners applying what they learned on the job? ✅ In practice: 30/60/90-day check-ins, manager observations, or peer feedback on whether the new behavior is showing up in real work. ✅ Metric to track: % of participants demonstrating the target behavior, based on manager or peer input, not self-reported confidence. ✨ Level 4: Results 🔹 Textbook version: Did the training impact business outcomes? ✅ In practice: Pick one business metric the program was meant to influence, before you build it, not after, and track the change. ✅ Metric to track: Movement in that specific KPI (error rates, time-to-productivity, conversion rates, retention) compared to a baseline. Most programs are measured thoroughly at Level 1 and barely at all beyond it. But Levels 3 and 4 are where the "did this actually matter" conversation happens, and they are also where L&D earns a seat at the table. Which level does your organisation measure consistently, and which one do you wish you could measure better? #LearningAndDevelopment #LnD #KirkpatrickModel #TrainingEvaluation #InstructionalDesign #LearningMeasurement #TrainingAndDevelopment #LnDStrategy

𝗜𝗱𝗲𝗮 #𝟭𝟲: 𝗠𝗲𝘁𝗿𝗶𝗰𝘀 𝘁𝗵𝗮𝘁 𝗺𝗮𝘁𝘁𝗲𝗿: 𝘁𝗵𝗲 𝗯𝗲𝗮𝘂𝘁𝘆 𝗼𝗳 𝘀𝗽𝗶𝗹𝗹 𝗮𝗻𝗱 𝘀𝗽𝗼𝗶𝗹 I worked with a hotel chain that was focused on two high-level KPIs: 𝗮𝘃𝗲𝗿𝗮𝗴𝗲 𝗿𝗼𝗼𝗺 𝗿𝗮𝘁𝗲 (𝗔𝗥𝗥) and 𝗼𝗰𝗰𝘂𝗽𝗮𝗻𝗰𝘆 (%).  Occupancy was around 80% and had increased year on year but this aggregate average was hiding significant opportunities. When we de-averaged the overall occupancy by hotel and night, we discovered that very few hotels were 80% full: most were either completely full or only half full.  We reframed performance using two “failure metrics” (see illustration): • 𝗦𝗽𝗼𝗶𝗹: measured empty rooms (by hotel, by night). • 𝗦𝗽𝗶𝗹𝗹: measured “lost trading days” when a hotel reached full occupancy too early. By analysing 𝘀𝗽𝗶𝗹𝗹 𝗮𝗻𝗱 𝘀𝗽𝗼𝗶𝗹 𝗮𝘁 𝗮 𝘀𝗶𝘁𝗲-𝗻𝗶𝗴𝗵𝘁 𝗹𝗲𝘃𝗲𝗹, we uncovered significant value: • Spoil caused by pricing too high or insufficient marketing.   • Spill caused by pricing too low or overmarketing.   𝗦𝗽𝗼𝗶𝗹 𝗶𝘀 𝗮 𝗳𝗮𝗰𝘁. 𝗦𝗽𝗶𝗹𝗹 𝗶𝘀 𝗮 𝗺𝗼𝗱𝗲𝗹. One measures what you wasted; the other estimates what you missed.   The principle applies to almost any decision made under uncertainty: where there’s finite capacity and variable demand, there’s always a 𝘀𝗽𝗶𝗹𝗹-𝘀𝗽𝗼𝗶𝗹 𝘁𝗿𝗮𝗱𝗲-𝗼𝗳𝗳.  I’ve applied this framework across a diverse range of businesses: • 𝗖𝗮𝗹𝗹 𝗰𝗲𝗻𝘁𝗿𝗲𝘀: spill = calls with no agents (missed sales); spoil = agents with no calls (wasted labour). • 𝗥𝗲𝘀𝘁𝗮𝘂𝗿𝗮𝗻𝘁𝘀: spill = understaffed hours (poor service); spoil = overstaffed hours (low productivity). • 𝗦𝘂𝗽𝗲𝗿𝗺𝗮𝗿𝗸𝗲𝘁𝘀: spill = missed sales (poor availability); spoil = waste (over-stocking). Every business wrestles with these two-sided costs – the 𝗰𝗼𝘀𝘁 𝗼𝗳 𝗲𝘅𝗰𝗲𝘀𝘀 and the 𝗰𝗼𝘀𝘁 𝗼𝗳 𝗺𝗶𝘀𝘀𝗲𝗱 𝗼𝗽𝗽𝗼𝗿𝘁𝘂𝗻𝗶𝘁𝘆.  Once you measure both, you can manage the balance intelligently.  The best metrics don’t just describe performance – they expose 𝘧𝘢𝘪𝘭𝘶𝘳𝘦 𝘮𝘰𝘥𝘦𝘴 that can actually be fixed. Key takeaways: • Analyse at the most atomic level that could be actionable (hour, site-night, SKU-store, agent, keyword etc.) • Define the acceptable 𝗴𝘂𝗮𝗿𝗱𝗿𝗮𝗶𝗹𝘀 for that atomic outcome.  • Systematically analyse the distribution of performance outside guardrails. • Recognise that averages hide opportunities where good and bad performance offset each other There’s a fascinating 140-year history of optimising these decisions which are commonly referred to as Newsvendor problems – but that story deserves its own post.

Want to know what CEOs were actually talking about in Q2 2026? Check out the latest from IoT Analytics. 😃 𝐊𝐞𝐲 𝐅𝐢𝐧𝐝𝐢𝐧𝐠𝐬: • 𝐀𝐈 𝐈𝐬 𝐒𝐭𝐢𝐥𝐥 𝐨𝐧 𝐓𝐨𝐩: AI appeared in 53% of earnings calls, even though mentions slipped 4% from Q1. The AI conversation is not fading. It is just being crowded by more immediate operational risks. • 𝐆𝐞𝐨𝐩𝐨𝐥𝐢𝐭𝐢𝐜𝐬 𝐅𝐨𝐫𝐜𝐞𝐝 𝐈𝐭𝐬 𝐖𝐚𝐲 𝐈𝐧: Iran mentions jumped 196% QoQ to 14.2% of calls. Strait of Hormuz mentions rose 200% to 5.1%, and geopolitics reached 28.9%. This is no longer “watch the news” territory. • 𝐄𝐧𝐞𝐫𝐠𝐲 𝐚𝐧𝐝 𝐈𝐧𝐟𝐥𝐚𝐭𝐢𝐨𝐧 𝐀𝐫𝐞 𝐁𝐚𝐜𝐤: Energy showed up in nearly 40% of calls, inflation in 32.6%, and uncertainty in 30.8%. CEOs are clearly bracing for higher input costs, pricing pressure, and more tactical operating decisions in the second half of the year. • 𝐅𝐫𝐨𝐧𝐭𝐢𝐞𝐫 𝐀𝐈 𝐆𝐨𝐭 𝐒𝐩𝐞𝐜𝐢𝐟𝐢𝐜: Anthropic’s Mythos appeared in 1.3% of calls, while Claude passed ChatGPT for the first time, reaching 4% versus ChatGPT at 3.7%. • 𝐀𝐈 𝐁𝐮𝐛𝐛𝐥𝐞 𝐚𝐧𝐝 𝐒𝐮𝐬𝐭𝐚𝐢𝐧𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐓𝐚𝐥𝐤 𝐅𝐞𝐥𝐥: AI bubble mentions dropped 22% to 1.3% of calls. Sustainability also continued its decline, with sustainability, emissions, and climate averaging 10% of calls. 𝐌𝐲 𝐓𝐚𝐤𝐞: What I see in this quarter is a CEO agenda getting pulled in two directions at once. On one side, leaders still have to invest in AI because the competitive pressure is real. On the other side, they are getting dragged back into very physical problems: oil, energy, freight, raw materials, interest rates, and supply chain exposure. That matters because AI does not get deployed in a vacuum. If your costs are moving, your suppliers are unstable, your energy exposure is rising, and your teams are firefighting, then “AI strategy” quickly becomes an execution problem. To me, Q2 was the quarter where AI ambition collided with geopolitical reality. 𝟑 𝐏𝐢𝐞𝐜𝐞𝐬 𝐨𝐟 𝐀𝐝𝐯𝐢𝐜𝐞: • 𝟑 𝐏𝐫𝐞𝐬𝐬𝐮𝐫𝐞-𝐓𝐞𝐬𝐭 𝐐𝟑 𝐀𝐬𝐬𝐮𝐦𝐩𝐭𝐢𝐨𝐧𝐬: Recheck forecasts against higher fuel, freight, raw material, and energy costs. Do not wait for Q4 to admit the model changed. • 𝐑𝐞𝐯𝐢𝐞𝐰 𝐇𝐨𝐫𝐦𝐮𝐳 𝐚𝐧𝐝 𝐌𝐢𝐝𝐝𝐥𝐞 𝐄𝐚𝐬𝐭 𝐄𝐱𝐩𝐨𝐬𝐮𝐫𝐞 𝐍𝐨𝐰: Map suppliers, shipping routes, energy dependencies, and customer commitments tied to the region. Even indirect exposure matters. • 𝐍𝐚𝐫𝐫𝐨𝐰 𝐭𝐡𝐞 𝐀𝐈 𝐀𝐠𝐞𝐧𝐝𝐚: For the next 90 days, prioritize AI use cases tied to cost control, supply chain visibility, pricing speed, cybersecurity, and productivity. This is not the quarter for science projects. 𝐑𝐞𝐚𝐝 𝐟𝐮𝐥𝐥 𝐚𝐫𝐭𝐢𝐜𝐥𝐞: https://lnkd.in/ekX4c_Bf ******************************************* • Visit www.jeffwinterinsights.com for access to all my content and to stay current on Industry 4.0 and other cool tech trends • Ring the 🔔 for notifications!

Are you measuring what matters in your organization? A comprehensive measure of organizational effectiveness includes much more than profit margins and growth rates. The market and media often celebrate companies that show rapid financial growth or high profitability, leading to a cultural bias towards these metrics as signs of success BUT the tide is slowly turning- more businesses are recognizing the long-term value of a holistic approach to effectiveness and success. Many more businesses are embracing the concept of the "Triple Bottom Line," which measures success not just by financial profit ("Profit"), but also by the company's impact on people ("People") and the planet ("Planet"). HOWEVER 🚨 There is more work to be done! The prioritization of non-financial elements of organizational success can get pushed aside when financial pressures hit or quick results are valued. You have probably heard the phrase "What gets measured gets managed". This is generally true. Quantifying and measuring non-financial aspects of effectiveness, such as employee well-being, social impact, and workplace culture, is hugely important but remains challenging. 💡 Here's some straightforward steps to move you towards a more holistic approach to measuring success: 𝐒𝐭𝐚𝐫𝐭 𝐰𝐢𝐭𝐡 𝐜𝐥𝐞𝐚𝐫 𝐠𝐨𝐚𝐥𝐬: Define what holistic success means for your organization. This could include specific targets related to employee well-being, social impact, and environmental sustainability. 𝐄𝐧𝐠𝐚𝐠𝐞 𝐬𝐭𝐚𝐤𝐞𝐡𝐨𝐥𝐝𝐞𝐫𝐬: Talk to employees, customers, and community members to understand what aspects of your business matter most to them. Their insights can help shape your holistic success framework. 𝐂𝐡𝐨𝐨𝐬𝐞 𝐫𝐞𝐥𝐞𝐯𝐚𝐧𝐭 𝐦𝐞𝐭𝐫𝐢𝐜𝐬: Based on your goals and stakeholder feedback, pick metrics that are meaningful and manageable. For example, employee satisfaction can be measured through regular surveys, while environmental impact can be tracked through energy consumption or waste reduction metrics. 𝐔𝐬𝐞 𝐞𝐱𝐢𝐬𝐭𝐢𝐧𝐠 𝐟𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤𝐬: Look into established frameworks (like GRI or B Corp standards for sustainability; Gallups Q12 Engagement Survey for employee engagement or the Denison Organizational Culture Model to measure workplace culture). There are existing frameworks for most known elements of organizational effectiveness so it's just a matter of looking into them. 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐞 𝐢𝐧𝐭𝐨 𝐝𝐞𝐜𝐢𝐬𝐢𝐨𝐧-𝐦𝐚𝐤𝐢𝐧𝐠: Ensure that these holistic metrics are part of regular business reviews and decision-making processes, not just side projects. 𝐑𝐞𝐩𝐨𝐫𝐭 𝐭𝐫𝐚𝐧𝐬𝐩𝐚𝐫𝐞𝐧𝐭𝐥𝐲: Share your progress openly, including both successes and areas for improvement. Transparency builds trust and credibility. 𝐂𝐨𝐧𝐭𝐢𝐧𝐮𝐨𝐮𝐬 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠: Be prepared to adapt and refine your approach as you learn what works and what doesn't. This is a journey, not a one-time task. #organizationaleffectiveness #measurewhatmatters #leaders

For half a decade, I thought I was tracking the right metrics I was wrong Revenue. Growth rate. ROAS. Conversion rate. New customers. Repeat revenue All important But they could tell me the business was growing without telling me whether that growth was making the company more valuable You can buy more traffic, discount more aggressively, and acquire less-profitable customers while the top line keeps going up The business gets bigger That doesn’t automatically mean its equity value does A stronger Brand should make future revenue easier to earn, more profitable, and less dependent on buying every sale Here are the 11 metrics I wish I’d started tracking sooner, framed as questions: 1. Are branded organic searches growing faster than revenue? 2. Are contribution dollars and contribution margin going up? Contribution Dollars = Revenue - variable costs like COGS, marketing, and shipping 3. Is direct and branded search revenue growing faster than overall revenue? 4. Is the gap between gross and net sales shrinking? This signals less reliance on discounts and fewer returns 5. Are 30, 60, and 90-day incremental LTV going up, excluding the first purchase? 6. Is reach growing as fast as—or faster than—revenue? 7. Have your worst days gotten better? One way to measure this: is the average of your 30 lowest-revenue days trending up? 8. For organic search, is revenue per session rising while sessions are growing or stable? 9. Is your share of branded organic searches growing versus your competitive set—at both the Brand and category level? 10. Is Baseline Revenue growing, both in dollars and as a percentage of total revenue? I define Baseline Revenue as revenue from direct traffic, organic search, and organic social referrals It’s imperfect. But if it’s rising in dollars AND as a percentage of revenue, good things are generally happening 11. Is Baseline Revenue per branded organic search going up? Branded searches are an imperfect proxy for the Brand you’re building. Baseline Revenue per search shows whether you’re monetizing it better If searches are soaring but Baseline Revenue per search isn’t, that’s something to audit — A few caveats: None of these metrics are perfect. You can game any of them They’re also mostly leading indicators—not the ultimate company scorecard The ultimate outcome is more operating profit and net cash over time The right metrics also change with the company’s stage, economics, and strategy. A five-month-old company shouldn’t use the same scorecard as a 100-year-old company But if you can honestly answer “yes” to most of these questions, there’s a good chance the quality of your growth is improving And that gives you a better chance of building a more valuable company—not just a bigger one Question for the people of the internet: What else do you track to understand whether growth is increasing the quality and equity value of the business?

I once blanked during a $200K pitch meeting. → Not stage fright. → Sleep deprivation. After 14 days of 4-hour nights, I couldn't recall our core offering that I'd personally designed. The prospect's expression said it all: "If he can't remember his own product..." Sleep isn't a performance hack for founders. It's your primary strategic asset. The research most founders ignore: 1. Decision quality erodes before energy   • Your frontal cortex (judgment center) deteriorates first   • You make increasingly poor calls while feeling "fine" 2. Recovery follows a 3:1 ratio   • After my sleep collapse, it took 21 days to rebuild my strategic capacity   • Each week of deficit demands three weeks of repair 3. Leadership patterns create company culture   • When I implemented mandatory offline hours, error rate dropped 26%   • Your sleep discipline shapes organizational performance 4. The blind spot effect   • Sleep-deprived brains can't self-diagnose their impairment   • The biggest decisions deserve your clearest thinking The ultimate competitive edge isn't working harder. It's having clarity when your competitors are operating in a cognitive fog. Which is more important: your 11PM emails or your 9AM strategic decisions? ps: you might like this: https://lnkd.in/g7i6WdCq

Reserve Replacement Ratio (RRR) is not just a technical metric. It is a strategic signal, and ultimately a signal of value. It measures how much reserves are added for every barrel of reserve produced. Courtsey of ENERGY ANALYTICS, we have the graphic below showing the 3-year rolling RRR for six majors, and it tells a revealing story: ✅ TotalEnergies: 138% ✅ ExxonMobil: 131% ✅ Petrobras: 126% ✅ Equinor: 100% ✅ Chevron: 80% ✅ Shell: 55% Let's connect some dots here. RRR Above 100% = Strategic Continuity ✅ When RRR sustainably exceeds 100%, a company is replacing more reserves than it produces. ✅ This reflects deliberate upstream capital allocation: deepwater, LNG, high-IRR projects. ✅ The companies above 120% are not retreating from hydrocarbons. They are high-grading and replenishing. RRR at or Below 100% = Strategic Inflection ✅ A sustained sub-100% RRR implies reserve attrition, shorter production runway, and reduced long-duration cash flow visibility. ✅ That may reflect: Portfolio rationalization, Capital discipline, Divestments ✅ Or a deliberate pivot toward lower-carbon businesses For valuation, this metric matters. Here's how: ✅ In upstream valuation, reserves are inventory. ✅ Production converts that inventory into cash flow. In prior analysis of Canadian upstream firms, I found market capitalization to be strongly correlated with oil production and oil reserves (correlation coefficients ~0.97). Reduce production, and valuation sensitivity becomes material. Deplete reserves without replacement, and long-duration cash flow visibility declines. RRR therefore feeds directly into: ✅ Reserve life (R/P ratio) ✅ NAV modeling assumptions ✅ Terminal value expectations ✅ Investor perception of sustainability Strategy vs Behavior In a recent strategic scan of 16 global majors (link in comments), I grouped companies into five archetypes. When you overlay the RRR with the strategic archetypes, you find: ✅ The highest RRR companies are still materially leaning into hydrocarbons - even while investing selectively in transition technologies. ✅ RRR trends often align closely with capital behavior Follow the CapEx. Follow the reserve additions. Follow the replacement discipline. That is where long-term corporate intent becomes visible. The bottom line is that reserve replacement discipline still shapes enterprise value. Link to the full strategy analysis in the comments. #EnergyAnalytics #OilandGas

Your sales managers are drowning in data—but starving for clarity. I was on a call last week with a VP of Sales who showed me his dashboard. 47 different metrics. I asked him : "Which number, if it moved 20% this month, would change everything?" Silence. Here's what I see happening: Leaders know *something* is off. Pipeline isn't converting. Reps are busy but not productive. Deals are slipping. But they can't pinpoint the actual behavior or skill gap that's causing it. Here's how to actually diagnose what's broken (and fix it fast): —— Step 1: Pick ONE North-Star Metric Not 10. Not 5. One. What's the single number that, if improved, would cascade into revenue growth this quarter? Could be: → Connect rate → Discovery-to-demo conversion → Demo-to-proposal rate → Close rate Pick the constraint. Ignore the rest for now. —— Step 2: Work Backward to the Behaviors Metrics don't move themselves. Behaviors move metrics. Ask: What are the 3–5 specific actions that directly influence this number? Example—if your North-Star is close rate: • Multi-threading (are reps building champion + EB relationships?) • Next-step clarity (is every call ending with a concrete commitment?) • Objection handling (are reps folding on pricing or timeline pushback?) Now you have a target. You know exactly what behaviors to inspect and improve. —— Step 3: Inspect the Work, Not Just the Outcome Most managers live in lagging indicators. They see the deal lost, the pipeline gap, the missed forecast—after it's too late. Top leaders inspect leading behaviors weekly: → Listen to 2–3 discovery calls per rep. Score them on your behavior checklist. → Review pipeline hygiene: Are next steps clear? Are close dates realistic? → Check activity quality: Are reps reaching the right people, or just burning through volume? You'll spot the gap in week one. You can course-correct in week two. —— Step 4: Use BIPSY to Diagnose the Root Cause When a behavior isn't happening, most managers assume it's a skill problem and throw training at it. But the issue might be: B – Behavior: They don't know they should be doing it. I – Issue Diagnosis: We don't know the CAUSE of the problem. P – Process: There's no clear standard or it's not reinforced. S – Skill: They know what to do but can't execute it well. Y – You (Impact): YOU as the leader aren't doing the right things. Diagnose correctly, and your fix is 10x faster. Don't guess. Diagnose. —— Step 5: Coach the Behavior Until It Sticks One conversation won't change anything. Great managers build a weekly rhythm: Monday: Inspect the work (calls, pipeline, activity). Tuesday–Thursday: Coach the gap in 1:1s with real examples. Friday: Measure early proof (did the behavior improve?). Rinse and repeat. This is system force, not brute force. The Bottom Line: Your team doesn't need more dashboards, more meetings, or more motivation. They need clarity and specific actions.

Power BI for Sales Performance Analysis Boosting Sales with Power BI: A Real-Life Success Story   Scenario: Challenge: Our sales team struggled with tracking performance metrics across different regions and product lines. The data was scattered across various sources, making it difficult to get a unified view.   Solution: We implemented Power BI to consolidate sales data from CRM, ERP, and other systems into a single, interactive dashboard.   Steps: 1. Data Integration:    Used Power BI's built-in connectors to pull data from multiple sources.   Example Query:     let         SalesData = Sql.Database("ServerName", "DatabaseName", [Query="SELECT * FROM Sales"])     in         SalesData     2. Data Modeling:   Created relationships between tables to allow for comprehensive analysis.   Example: Linked sales data with regional data to analyze performance by region.   3. Interactive Dashboards:   Designed dashboards to track key metrics like total sales, sales growth, and regional performance.   Features: Drill-down capabilities, slicers for filtering by date, product, and region.   Impact: Improved Visibility: Sales managers now have a clear, real-time view of performance metrics. Faster Decisions: Quick access to data enabled faster decision-making and strategy adjustments. Increased Sales: Identified high-performing regions and focused efforts on underperforming areas, resulting in a 15% sales increase.     Include screenshots of the Power BI dashboard, before-and-after performance metrics, and user testimonials. Have you used Power BI to transform your sales performance? Share your story in the comments!   #PowerBI #Sales #DataVisualization #BusinessIntelligence #TechInnovation #DataDriven