Understanding Cost Analysis

I used to think charging less would get me more clients. After my trip to the US I realised it just made them trust me less. when i was cheap, clients questioned everything. "why this approach?" "can we try something else?" "i'm not sure about this." so when i raised my rates, they trusted my decisions completely. same work. different psychology. so here's what i've basically realized about pricing: when someone sees a low price, their brain doesn't think "great deal." it thinks "what's the catch?" they start looking for problems. inexperience. desperation. corners being cut. low prices trigger fear of loss, not excitement about savings. but when they see premium pricing, something else happens. "if they can charge this much, they must deliver results." "other people are paying this, so the value must be there." "the risk of not solving this problem costs way more than the investment." premium pricing signals confidence in your work. think about it. rolex doesn't make better watches from a functionality standpoint. but the price tells you everything about what owning one means. same thing with services. a premium project isn't necessarily 10x better in execution. but the price signals experience, systems, proven results. and here's the shift that changed everything for me: i stopped anchoring clients to the price and started anchoring them to the outcome. not "this costs X" but "this will generate Y for your business, and the investment is X." when they're thinking about ROI, the price becomes secondary. your pricing isn't just a number. it's a signal to the market about who you are and what you deliver.

She started invoicing her company for data requests. $200 per PowerPoint. $500 per dashboard. What happened next: It began as a joke during her performance review. "You say I'm not strategic enough," she told her manager. "But I spend 60% of my time on executive data requests." "That's part of the job," he replied. That night, she built a simple system. Every data request generated an internal invoice: - Time required - Hourly rate - Opportunity cost - Total "charge" She didn't send them. Just tracked them. Month 1 total: $18,400 Month 2 total: $22,100 Month 3 total: $19,750 During her next one-on-one, she presented the receipts. "I've generated $60,250 in data services this quarter. My actual job contributed $0. Which one should I prioritize?" Her manager went pale. She continued: "If we outsourced this to a data analyst at $50/hour, it would cost the company 75% less. And I could do my actual job." Word spread. Other employees started tracking their "invoices." The numbers were staggering: Engineering: $147,000/month in data services Product: $89,000/month in reporting Design: $34,000/month in presentations Someone built a company-wide dashboard: "Internal Data Services Inc." Running total: $4.2M annually The CFO called an emergency meeting. "This is ridiculous. You don't actually invoice internally." Someone responded: "Why not? Every external agency does. We're just the agency that also tries to do our real jobs." That's when it clicked. They were running two companies: 1. The actual business 2. An internal data agency with no billing department The CFO did what CFOs do. Ran an ROI analysis. Option A: Keep status quo ($4.2M hidden cost) Option B: Hire 3 dedicated analysts ($350K) Option C: Buy proper tools and train execs ($100K) The decision took five minutes. Within 30 days: - Executives learned self-service dashboards - Three analysts hired for complex requests - "Invoice system" retired The woman who started it all? Got promoted to Chief of Staff. First initiative: "Time is Money" visibility program. Now every team tracks the true cost of interruptions. Not to invoice. To inform. Because when you make invisible costs visible, behavior changes instantly. The company motto became: "Would you pay $500 for that PowerPoint? Then don't ask someone else to." Revenue grew 40% the next year. Not from new features. From people actually building them. Try it at your company. Track the invoice you'll never send. Watch how fast things change. Because nothing shifts behavior like a price tag.

Capex investments shape cash flow and impact operating efficiency. Here's an example you might borrow. There are 3 separate forecasts for 3 different capital expenditures for a food company: • Buildout of a commercial kitchen • Acquisition of a tempering machine • Acquisition of an automatic filler There are a few areas to demystify: 𝟭) 𝗧𝗶𝗺𝗶𝗻𝗴 𝗮𝗻𝗱 𝗖𝗮𝘀𝗵 𝗙𝗹𝗼𝘄𝘀 Major projects are rarely paid all at once. The timing of the schedule matters for cash flows and financing. The move to the commercial kitchen is estimated to cost $800,000. 10% of this amount ($80,000) will be due first to the general contractor. There is a drop-down, using data validation, that allows the modeler to select which month the deposit is set to be paid. The remaining drop-downs allow the modeler to forecast the 1st phase and 2nd phase payments. 𝟮) 𝗧𝗶𝗺𝗶𝗻𝗴 𝗮𝗻𝗱 𝗗𝗲𝗽𝗿𝗲𝗰𝗶𝗮𝘁𝗶𝗼𝗻 While depreciation doesn't matter much for direct cash flow modeling, it's important for depreciation expense on the P&L, accumulated depreciation for balance sheet forecasts, and tax planning. Here you can see that I'm assuming 15-year, 5-year, and 7-year depreciation respectively across the investments. This assumption determines the monthly depreciation expense. Below the assumption for useful life, an automated formula determines the first full month of the asset deployment. The month prior, uses an automated mid-month convention for conservatism. 𝟯) 𝗧𝗵𝗲 𝗖𝗮𝗽𝗲𝘅 𝗢𝗻/𝗢𝗳𝗳 𝗧𝗼𝗴𝗴𝗹𝗲 Excel nerds unite. I use the check box functionality at the top to include or exclude these capex forecasts from the integrated model. Why not just zero out the forecasts instead? Because that's manual and permanent. The CFO will hate that and you'll waste time. The toggles let you maintain the assumptions while running, or not running, scenarios on the forecast. 𝗛𝗲𝗿𝗲'𝘀 𝗮 𝗿𝗲𝗰𝗮𝗽: • Each project is broken down into phases (initial deposits, final payments). • Depreciation is tied to the month the fixed asset enters service, not just when cash goes out. • Check boxes allow the CFO to keep the capex forecast assumptions in place, but turn on/off the impact to financial forecast models. • Everything in blue font is an assumption, while everything in black font is formulaic. The forecast can be updated in minutes and toggled in seconds.    This is benefit of building a highly-reliable templated approach for one capex forecast. You can copy it and apply similar flexible methodology to the others.

🌍 New paper out in Nature Climate Change on a critical question for climate policy: How does policy sequencing impact energy decarbonization? Led by Huilin Luo and Wei Peng, with Allen Fawcett, Jessica Green, Gokul Iyer, Jonas Nahm and David G. Victor Our team used advanced energy modeling to examine "carrots" (subsidies like those in the Inflation Reduction Act) vs. "sticks" (carbon pricing) - and crucially, the ORDER in which they're deployed. Key findings: ✅ Carrots alone don't achieve deep decarbonization – sticks are needed ✅ Near-term impacts of carrots vary widely by sector and consistency ✅ Timing is critical: delaying carbon pricing by 20 years (vs. 10) increases the eventual price needed by 40% ✅ Carrots boost green industries but don't significantly phase out fossil fuels - sticks are essential for that ✅ With rapid innovation, carrots followed quickly by sticks can be nearly as cost-effective as leading with carbon pricing The research bridges political science and energy modeling to analyze real-world policy tradeoffs. While carbon taxes are economically "first-best," political reality often requires starting with industrial policy - making the transition strategy crucial. Check out Mark Purdon’s great commentary on the paper: Green Industrial Policy Is Not Enough for Deep Decarbonization https://lnkd.in/gURqCbUE Read the full paper: https://lnkd.in/gW52_bcC #ClimatePolicy #EnergyTransition #ClimateScience #InflationReductionAct #Decarbonization

An unacknowledged loop costs more than any front-facing glitch. 𝐇𝐢𝐝𝐝𝐞𝐧 𝐟𝐚𝐜𝐭𝐨𝐫𝐢𝐞𝐬: They’re the invisible vampires of your organization, quietly draining time, resources, and budgets while you’re focused on the shiny, visible processes. On paper, everything looks great—clear plans, detailed KPIs, and a confident team. Yet deadlines slip, and costs balloon. Why? Because beneath the surface, there’s an uncharted underworld of rework, ad-hoc fixes, and undocumented processes keeping the ship afloat. This “hidden factory” might be a production operator manually fixing defects or a marketing coordinator managing spreadsheets because the CRM can’t handle reality. It’s work that doesn’t show up in reports but shows up in your margins. 𝐖𝐡𝐲 𝐝𝐨𝐞𝐬 𝐭𝐡𝐢𝐬 𝐦𝐚𝐭𝐭𝐞𝐫? Armand Feigenbaum, the OG of Total Quality Control, nailed it: You can’t fix what you don’t measure. Hidden factories consume 𝟐𝟎-𝟒𝟎% 𝐨𝐟 𝐚𝐧 𝐨𝐫𝐠𝐚𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧’𝐬 𝐜𝐚𝐩𝐚𝐜𝐢𝐭𝐲 and can be the difference between thriving and surviving. 𝟓 𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐚𝐥 𝐒𝐮𝐠𝐠𝐞𝐬𝐭𝐢𝐨𝐧𝐬 𝐭𝐨 𝐄𝐱𝐩𝐨𝐬𝐞 𝐚𝐧𝐝 𝐑𝐞𝐝𝐮𝐜𝐞 𝐚 𝐇𝐢𝐝𝐝𝐞𝐧 𝐅𝐚𝐜𝐭𝐨𝐫𝐲: 𝟏) 𝐔𝐬𝐞 𝐒𝐦𝐚𝐫𝐭 𝐌𝐞𝐭𝐫𝐢𝐜𝐬: Track hidden work with tools like MES and advanced KPIs (e.g., DPMO). 𝟐) 𝐋𝐢𝐬𝐭𝐞𝐧 𝐭𝐨 𝐄𝐦𝐩𝐥𝐨𝐲𝐞𝐞𝐬: Create systems to capture frontline feedback and reward solutions. 𝟑) 𝐒𝐭𝐫𝐞𝐚𝐦𝐥𝐢𝐧𝐞 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐞𝐬:  Map workflows, eliminate waste, and simplify handoffs. 𝟒) 𝐁𝐞 𝐏𝐫𝐨𝐚𝐜𝐭𝐢𝐯𝐞:  Use predictive tools and preventative maintenance to avoid surprises. 𝟓) 𝐓𝐫𝐚𝐢𝐧 𝐂𝐨𝐧𝐭𝐢𝐧𝐮𝐨𝐮𝐬𝐥𝐲: Teach Lean and Six Sigma to empower a culture of improvement. 𝐅𝐨𝐫 𝐚 𝐝𝐞𝐞𝐩𝐞𝐫 𝐝𝐢𝐯𝐞: https://lnkd.in/ehy-XhAr ******************************************* • 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!

What happens to an EV battery after 305,000 miles? Two weeks ago, a customer set a new record. 305,221 miles, almost 500,000 kilometers, on the clock.  Of a 2022 Tesla Model Y Long Range. That's the battery health report with the highest mileage we've ever seen so far. Of course, when I saw it come in, I rushed to take a look at the results. By the way, the car was fast-charged 43% of the time. And it showed a 74% state of health. Is it a good or bad result? Being that this car is equipped with a 77.8 kWh NMC (Nickel-Manganese-Cobalt) battery pack, this is a result I was expecting to see. Recently, several Model Ys around 200k miles showed a state of health in the high 70% area or even slightly beyond 80%. But what's the most important consideration we can extract from this result? I can already hear the comment: "My gas car still drives the same after 3 years." Let's run the math and see where this car stands, looking at what it represented for its owner. This car was fast-charged 43% of the time, likely at around $0.35/kWh. Assuming avg consumption 3.5 miles/kWh • 131,245 miles fast charging @ $0.35/kWh = $13,125 • 173,976 miles home charging @ $0.14/kWh = $6,959 • Total: $20,084 ($12,209 if 100% home charging) For a comparable gas vehicle Assuming avg consumption 25 MPG • 305,221 miles with avg fuel price $3/gallon • Total: $36,626 Even with heavy fast charging use, we're looking at $16,542 in fuel savings alone. If this driver had charged at home 100% of the time, they would have saved $24,417 in fuel costs instead. Add in no oil changes, no transmission services, no timing belts, and the total savings in maintenance easily add up to around $6,000. Yes, EVs wear tires faster due to instant torque and heavier weight. Let's calculate that. At roughly $1,000 per set. Replacement needed every 18,000 miles for EV instead of 25,000 for gas. • EV: ~17 sets × $1,000 = $17,000 • Gas: ~12 sets × $1,000 = $12,000 • Additional tire cost for EV: $5,000 Even accounting for faster tire wear, the driver still saved about: • $17,500 with 43% fast charging use  • $25,400 with primarily home charging. This perfectly overcomes most fear-mongering claims that still make people think EVs need a new battery every 50k miles.   This battery, after more than 300k miles, doesn't need to be replaced at all. With a perfectly balanced battery pack, this car still delivers more than 200 miles of range on a full charge. And the cool thing is that even if you replaced the battery pack with a new one, you'd still have money in your pocket compared to an equivalent gas version. There are many EVs like this that have proven durability at scale. With running costs that are a fraction of ICE equivalents. And still plenty of life left. What's the mileage range you'd be comfortable with when considering a used EV?

What factors affect the CAC(Customer Acquisition Cost) and should be incorporated in its calculation? Many digital-only brands include just their media spends in the CAC computation. However, CAC varies a lot based on the following factors. 1. Discounts New user discounts play an important role in the first-time user conversion rate. So, media CAC goes down whenever we introduce a new user discount. Hence, adding the new user discount to the CAC(Customer Acquisition Cost) calculation is crucial to measure channel efficiency correctly. 2. Seasonality Seasonality increases the demand and also improves the conversion rate. So, the campaign tends to perform better during the high season weeks. And it goes up right after the event as the demand drops. Averaging the CAC over this period is essential for channel sanity. Tip: Never claim the credits for the CAC reduction leading the seasonal event. You will be in trouble. 3. Brand campaign boost Brand campaigns almost always improve the performance of campaigns CAC. It could be due to more brand-aware people coming to your audience pool or additional exposure to the audience closer to the purchase. It always does. Give credit where it is due. After a successful brand campaign, there will also be a baseline shift in the CAC. Make sure you are inculcating it in your scale-up plan. Of course, when there is genuine improvement in the CAC due to campaign optimization and creative, take the credit. These days, you get them less often when you are operating at scale.

Many founders treat pricing as a revenue optimization problem. Figure out the product first, scale usage, then monetize. That's backwards. Pricing isn't about extracting money. It's about discovering whether you built something people actually value. At Gamma, we used pricing as a proxy for value and kept it pretty much the same for over 2 years. Free usage will lie to you (especially for B2B and prosumer products). Usage spikes feel like PMF. They're not. Usage without payment tests your onboarding, not your value. If you come out with too generous of a free plan, you'll never know what true willingness to pay looks like. Here's how to use pricing as a proxy for value: 1. Pick your value metric Choose the thing customers actually hire you for. Documents generated. API calls. Minutes transcribed. At Gamma, we gated by AI credits as the primary value metric, with business levers like custom branding. 2. Draw a hard boundary between free and paid Let people experience the "aha," then stop them at a generous but bounded gate. We gave users plenty of AI credits up front. Once they hit the limit: upgrade for access to more AI. 3. Research your range, then let behavior decide We used Van Westendorp to find our starting range. Ask users four price points: too cheap to trust, good value, getting expensive, too expensive to consider. Plot where these intersect to bracket your range. Then test a few prices within it. Research shows what people say they'll pay - conversion shows what they actually do. We watched free-to-paid conversion and early churn signals, picked the winner, and moved on. 4. Instrument retention and talk to customers Track whether paid users keep crossing your value threshold each week. Stay close to customers through power-user communities or direct outreach. Ask questions like: "What job were you hiring us for?" and "What would justify a higher price?" 5. Treat pricing changes like product pivots Once you've validated pricing, the only reason to change it is if you've fundamentally changed what you're selling. We haven't changed ours in two years because the value metric (AI usage) hasn't changed. Constantly repricing means you're still searching for product-market fit. Why this matters: Pricing early clarifies who values you, which channels convert, and which segments to double down on. You're better off launching pricing way earlier so you can see who's actually willing to pay for it.

Ukrainian instructors were shocked by the reckless use of air defense systems in the Gulf countries. According to Ukrainian military personnel, multiple missiles are often launched at a single target — up to eight Patriot interceptors costing around $3 million each — even when dealing with relatively simple threats. There have been cases where SM-6 missiles, costing about $6 million, were used to destroy inexpensive drones, even though the “Shahed” drones themselves cost roughly $70,000. In interviews, Ukrainian specialists emphasized that their approach is based on efficiency: using the minimum number of missiles per target whenever possible and avoiding the unnecessary use of expensive interceptors. “I have no idea what our allies were watching for four years while we were at war,” said Ukrainian military instructors currently in the Middle East. Notably, in the first 96 hours of operations against Iran, the U.S. and its allies used about 5,200 munitions of 35 types, including 168 Tomahawk missiles in 100 hours. Over 12 days, total costs reached $16.5 billion. According to President Volodymyr Zelenskyy, Middle Eastern countries launched more than 800 Patriot interceptors in just three days. Ukraine, over four years of war, has received just over 600 such interceptors. Rheinmetall CEO Armin Papperger noted that, at this pace, the U.S. could run out of air defense missiles within a month. It turns out that in the conflict with Iran, Washington’s main challenge is not finances but production capacity. The U.S. defense industry cannot rapidly scale output because: • missile production can take up to 36 months; • supply chains depend on critical components largely sourced from China; • there is outdated equipment and a shortage of skilled labor. The current ammunition shortage poses risks to other priorities, including support for Ukraine and the deterrence of China. Source: Anton Gerashchenko, The Times

Are You Spending Too Much to Acquire a Customer, Or Not Enough? E-commerce brands often focus on lowering their customer acquisition costs (CAC). But what if cutting CAC is actually hurting growth? The real question isn’t just how much does it cost to acquire a customer? It’s how much should you be spending? If you knew with certainty that a customer would generate $500 in long-term profit, would you hesitate to spend $100 to acquire them? Probably not. But many brands take a one-size-fits-all approach, capping CAC at an arbitrary percentage of their first purchase revenue. This can lead to underinvestment in acquiring high-value customers and overinvestment in customers who won’t stick around. A better approach is to align CAC with long-term customer equity, not just at a blended level, but dynamically across customer segments. Some customers have significantly greater revenue potential than others. The challenge is identifying which customers will create sustainable profitability over time. The chart illustrates that customer acquisition cost (CAC) and lifetime value (LTV) are not linear, spending more on acquisition can lead to higher-value customers, but only up to a certain point. Key Insights: There is an optimal CAC range. - Spending too little on CAC (left side of the chart) may result in acquiring lower-value customers, limiting long-term profitability. - Spending too much (right side of the chart) can lead to diminishing returns, where LTV does not justify the extra spend.   The breakeven threshold matters. - The red dashed line represents where CAC = LTV, meaning any spend above this line is unprofitable unless justified by strategic goals (e.g., market share growth). Smarter spending, not just lower spending, drives profitability. - Many brands mistakenly focus only on reducing CAC, but the real goal is to align CAC with future LTV dynamically across customer segments. What This Means for Retailers Instead of asking, “How much does it cost to acquire a customer?”, the real question is: - How much should we spend to acquire the right customers? - How long will it take to break even on acquisition costs? - Which acquisition channels and products lead to the highest-value customers? Retailers who leverage AI-driven insights to align CAC with future Customer Equity, not just at a blended level but dynamically across customer segments, can spend smarter, scale faster, and drive long-term profitability. If you want to go deeper on this topic, Professor Peter Fader has done extensive research on customer-centric growth strategies. Check out this fascinating podcast with Nick Hague on how businesses can take a more data-driven approach to optimizing CAC. https://lnkd.in/eGu5EM5g #CustomerAcquisition #EcommerceGrowth #MarketingStrategy #CustomerEquity #GrowthMarketing #CACvsLTV #RetailStrategy #Profitability #WGBTpodcast