Consulting

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.

🚫 How to Run UX Research Without Access To Users. With practical techniques to avoid guesswork and gather insights if you can’t talk directly to users. Attached cheatsheet (with and without access to users) by Nielsen Norman Group. 🚫 Ask for reasons for no access to users: there might be none. ✅ First, study job openings to map existing workflows/tasks. ✅ Make friends with sales, customer success, support, QA. ✅ Find colleagues who are the closest to your customers. ✅ Convey your questions indirectly via your colleagues. ✅ If you can’t get users to come to you, go where they are. ✅ Ask to observe or shadow customers at their workplace. ✅ Listen in to customer calls and interview call centre staff. ✅ Request access to analytics, CRM reports, call centre logs. ✅ Use Google Trends to find product-related search queries. ✅ Gather insights from search logs, Jira backlog, support tickets. ✅ Explore past/ongoing NPS and Voice-of-Customer programs. ✅ Study reviews, discussions, comments for your product/competitors. ✅ Map key themes and user sentiment on TrustPilot, AppStore etc. ✅ Recruit users via UserTesting, Wynter (B2B), Maze, UserInterviews. ✅ Ask for small but steady commitments: 5 users × 30 mins, 1× month. 🚫 Avoid ad-hoc research: set up regular check-ins and timelines. As H Locke noted, if we shed the light strongly enough from many sources, we might end up getting a glimpse of the truth. Ironically, the stakeholders who can’t give you time or resources to talk to users often are the first to demand evidence to support your initiatives. Sometimes the reason why companies are reluctant to grant access to users is simply the lack of trust. They don’t want to disturb relationships with big clients which is carefully maintained by the customer success team. They might feel that research is merely a technical detail that clients shouldn’t be bothered with. Show that you deeply care about that relationship and that you don’t want to disturb it any way. What you do want though is to reduce costs and risk — the risk of drawing wide-reaching conclusions from very little research, or none at all. Your best shot is to explain research as a powerful risk mitigation tool. And: search for people whose priorities align with yours — people who value and see the impact of UX in their units. They would absolutely love to support your work because it also supports their work — and they will put up a good word for you if they only had known that you existed. ✤ Useful resources: UX Research Cheat Sheet, by Susan Farrell from NN/g (attached) https://lnkd.in/eUTHKWvF What Can You Do When You Have No Access To Users?, by H Locke https://lnkd.in/ewHEKhBS UX Research When You Can’t Talk To Users, by Chris Myhill https://lnkd.in/ez5-b6zf #ux #research

🌍 We Can’t Afford to Get Climate Policy Wrong—A Look at the Data Behind What Really Works 🌍 In the race against time to combat climate change, bold promises are everywhere. But here’s the critical question: Are the policies being implemented actually reducing emissions at the scale we need? A groundbreaking study published in Science, cuts through the noise and delivers the insights we desperately need. Evaluating 1,500 climate policies from around the world, the research identifies the 63 most effective ones—policies that have delivered tangible, significant reductions in emissions. What’s striking is that the most successful strategies often involve combinations of policies, rather than single initiatives. Think of it as the ultimate teamwork: when policies like carbon pricing, renewable energy mandates, and efficiency standards are combined thoughtfully, the impact is far greater than any one policy could achieve on its own. It’s a powerful reminder that for climate solutions the whole is indeed greater than the sum of its parts. Moreover, the study’s use of counterfactual emissions pathways is a game changer. By showing what would have happened without these policies, it provides a clear, quantifiable measure of their effectiveness. This is exactly the kind of rigorous evaluation we need to ensure that every policy counts, especially when we’re working against the clock. If we’re serious about meeting the Paris Agreement’s targets, we need to focus on what works—and this research offers a clear roadmap. Let’s champion policies that have proven to make a difference, because we don’t have time to waste on anything less. 🔗 Full study in the comments #ClimateAction #Sustainability #PolicyEffectiveness #ParisAgreement #NetZero #ClimateScience

Consulting sells AI, but bills like 1990. Reality caught up to the narrative. Booz Allen's latest results beat expectations: → Revenue: up 12.4% to $12 billion → Adjusted EPS: up 15.5% to $6.35 → GenAI revenue: nearly $800 million, up 30% → Record backlog: $37 billion, book-to-bill of 1.39 Yet the stock crashed 20% in the last 10 days, erasing $3.5 billion in market value. Why? Because beneath strong headline numbers, Goldman Sachs' May 28 downgrade exposed a critical vulnerability: Despite claiming to be an "advanced tech company" with $800M in AI revenue, Booz Allen still derives 98% of its business as a government contractor billing by the hour. The company recently announced 2,500 job cuts (7% of their workforce) due to the Trump administration’s crackdown on federal contracting. I dug into their yearly report to learn more. How Booz Allen Actually Makes Money: The Revenue Reality: → 98% from U.S. government ($10.5B of $10.7B total) → Defense (47%), Civil (34%), Intelligence (17%) → Only 2% commercial revenue 79% of revenue ($8.4B) comes from billing hours: → 55% cost-reimbursable contracts → 24% time-and-materials → Only 21% fixed-price CFO Matt Calderone confirmed their historical growth formula on their earning call: "headcount growth plus 3%". Despite AI claims and the CEO pushing outcome-based contracts for years, only 21% of revenue is fixed-price. Government procurement keeps them billing hours. The Labor Reality: → 36,000 employees driving revenue → 2,500 layoffs (7%) announced after DOGE reviews → Revenue explicitly tied to headcount → When contracts shrink, people get fired The math doesn't lie. You can't justify tech multiples when: → Your entire business depends on one entity → Growth requires hiring more people → Government owns rights to most developed IP  → Margins collapse when contracts face pressure Every firm claiming AI transformation faces this reality: → They pitch cutting-edge technology → They showcase AI capabilities → They demand premium valuations → But their economics remain tied to billable hours When CEO Rozanski said they're "restructuring to match anticipated demand," he revealed the core problem: Revenue directly tracks headcount. Tech companies scale through IP. Traditional consulting scales through hiring - and shrinks through firing. The 20% crash wasn’t about a single quarter. It was Wall Street repricing Booz Allen’s reality - a government contractor at the mercy of federal budgets, not a tech innovator building scalable IP. First, the narrative cracks. Then, the analysts notice. Finally, the market reprices. Booz Allen completed the cycle in 10 days. For consulting firms still betting their "AI story" covers their hourly reality: You're not different. You're just next.

Hot take: the #legalengineer is now the most critical role in the in-house legal department. Not the GC. Not the deputy. Not the head of legal ops. The person who sits at the intersection of legal process expertise, technology fluency, and change management and who can re-engineer how legal work gets done as AI reshapes what's possible is what separates the teams that will come out of this period ahead from the ones that will have a lot of expensive technology and not much to show for it. In-house legal is redesigning itself right now. What goes to outside counsel? What does AI handle? How do we staff? You can't answer those questions or execute on the answers without someone who can architect the new model. I've been in this space for over two decades. This is the role I'd prioritize above almost anything else right now. https://lnkd.in/gCy6tQr5

How to Do Financial Due Diligence Before Selecting Stocks? Stock picking isn’t just about looking at charts and following trends—it’s about understanding the financial health of a company. Before investing, a structured Financial Due Diligence (FDD) process can help you avoid bad bets and spot strong opportunities. Here’s a framework to follow: 1. Understand the Business Model & Industry - What does the company do? - Who are its competitors? - Is it in a growing or declining industry? 2. Analyze the Financial Statements - Income Statement (Profit & Loss) – Revenue growth, profitability (Gross, Operating, Net Margins), EPS trends - Balance Sheet – Debt levels, cash reserves, working capital position - Cash Flow Statement – Operating cash flow vs. net income, free cash flow trends 3. Check Key Financial Ratios - Profitability: ROE, ROA, Gross & Operating Margins - Liquidity: Current Ratio, Quick Ratio - Leverage: Debt-to-Equity, Interest Coverage - Valuation: P/E Ratio, P/B Ratio, EV/EBITDA 4. Assess Management & Governance - Background & track record of leadership - Insider buying/selling trends - Transparency in disclosures & corporate governance 5. Review Competitive Position & Moat - Does the company have a sustainable competitive advantage (brand, network effect, patents, cost advantage)? 6. Industry Trends & Macroeconomic Factors - Economic cycles, inflation, interest rates - Global supply chain, geopolitical risks - Market trends affecting revenue streams 7. Cross-Check with Analyst Reports & News - Read Equity Research Reports, Investor Presentations, Credit Reports - Stay updated on company news, regulatory changes 8. Look at Historical Performance & Future Guidance - Compare past financials vs. projections - Evaluate management’s growth expectations 9. Risk Assessment & Downside Protection - What’s the worst-case scenario? - How resilient is the business in a downturn? 10. Compare with Peers & Make an Informed Decision No company operates in isolation—compare financials and valuations with competitors before buying. Smart investing is about discipline, not hype. By doing thorough due diligence, you increase your chances of picking winners while avoiding pitfalls. What’s your go-to method for analyzing stocks? Let’s discuss.

70% of change initiatives fail. (And it's rarely because the idea was bad.) Here's what actually kills transformation: You picked the wrong change model for the job. It's like performing surgery with a hammer. Sure, you're using a tool. But it's the wrong one. I've watched brilliant CEOs tank their companies this way: Using individual coaching (ADKAR) for company-wide transformation. Result: 200 people change. 2,000 don't. Running a massive 8-step program for a simple process fix. Result: 6 months wasted. Team exhausted. Nothing changes. Forcing top-down mandates when they needed subtle nudges. Result: Rebellion. Resentment. Resignation letters. Here's what nobody tells you about change: The size of your change determines your approach. Real examples from the field: 💡 Startup pivoting product: → Used Lewin's 3-stage (unfreeze old way, change, refreeze) → 3 months. Clean transition. Team aligned. 💡 Enterprise going digital: → Used Kotter's 8-step process → Created urgency first. Built coalition. Enabled action. → 18 months later: $50M in new revenue. 💡 Sales team adopting new CRM: → Used Nudge Theory → Made old system harder to access → Put new system as browser homepage → 95% adoption in 2 weeks. Zero complaints. The expensive truth: Wrong model = wasted months + burned budgets + broken trust Right model = faster adoption + sustained results + energized teams Warning signs you're using the wrong model: • High activity, low progress • People comply but don't commit • Changes revert within weeks • Energy drops as you push harder • "This too shall pass" becomes the motto Match your medicine to your ailment: Small behavior change? Nudge it. Individual performance? ADKAR it. Cultural shift? Influence it. Full transformation? Kotter it. Enterprise overhaul? BCG it. Stop treating every change like a nail. Start choosing the right tool for the job. Your next change initiative depends on it. Your team's trust demands it. Your company's future requires it. Save this. Share it with your leadership team. Because the next time someone says "people resist change," you'll know the truth: People don't resist change. They resist the wrong approach to change. P.S. Want a PDF of my Change Management cheat sheet? Get it free: https://lnkd.in/dv7biXUs ♻️ Repost to help a leader in your network. Follow Eric Partaker for more operational insights. — 📢 Want to lead like a world-class CEO? Join my FREE TRAINING: "The 8 Qualities That Separate World-Class CEOs From Everyone Else" Thu Jul 3rd, 12 noon Eastern / 5pm UK time https://lnkd.in/dy-6w_rx 📌 The CEO Accelerator starts July 23rd. 20+ Founders & CEOs have already enrolled. Learn more and apply: https://lnkd.in/dwndXMAk

This is the most underrated way to use Claude: (and it has nothing to do with writing or coding) It's competitive intelligence. Using data that's free, public, and updated every single week. Here's my extract step by step guide: Step 1. Go to claude .ai. Step 2. Select the new Claude "Opus 4.6." Step 3. Turn on "Extended Thinking." Step 4. Pick a competitor. Go to their careers page. Step 5. Copy every open job listing into one doc. (Title. Team name. Location. Full description) Step 6. Save it as one .txt or .docx file. Step 7. Search the company at EDGAR (sec .gov) Step 8. Download its recent 10-K or 10-Q filing. (Official strategy, risks, and financials - all public.) Step 9. Upload both files to Claude Opus 4.6. Step 10. Paste this exact prompt: "You are a competitive intelligence analyst at a rival company. I've uploaded [Company]'s complete current job listings and their most recent SEC filing. Perform a strategic intelligence analysis: → Cluster these roles by what they suggest is being built. Don't use the team names they've listed. Infer the actual product initiatives from the skills, tools, and responsibilities described. → Identify capabilities or teams that appear entirely new — not mentioned anywhere in the SEC filing. These are unreleased bets. → Find roles where seniority is disproportionately high for a new team. This signals executive-level priority. → Cross-reference the SEC filing's Risk Factors and Strategy sections with hiring patterns. Where are they investing against a stated risk? Where did they flag a risk but have zero hiring to address it? → Predict 3 product launches or strategic moves this company will make in the next 6-12 months. State your confidence level and cite specific job titles and filing sections as evidence. Format this as a 1-page competitive intelligence briefing for a CMO." What you'll find: → Products that don't exist yet but will in 6 months. → Priorities that contradict what the CEO said. → Risks they told the SEC but aren't addressing. This is what consulting firms charge $200K for. It took me 10 minutes. I used the new Claude 'Opus 4.6' for a reason: ✦ It read 60 job listing & a 200-page filing together.  ✦ And connects dots across both. ✦ It is superior in thinking and context retrieval. That's why I didn't use ChatGPT for this.

Secret for Tax Person to Influencing the CFO: Speak in Cash Impact, Not Regulations! As tax professionals, we often get caught up in quoting sections, clauses, and legal jargon. But when you're talking to the CFO, remember - cash flow speaks louder than compliance. CFOs think in numbers that impact business decisions. Instead of presenting tax issues as a regulatory challenge, frame them as a financial impact. Instead of “Non-compliance with TDS can lead to disallowance under Section 40(a)(ia).” Say “Missing TDS can hit our P&L by ₹X crore in disallowed expenses, increasing our effective tax rate.” Instead of “GST input credit restrictions under Rule 36(4).” Say “We risk losing ₹Y lakh in ITC, directly increasing operational costs and impacting margins.” Instead of “Customs duty changes under the new FTP.” Say “The increased duty rate will raise our import costs by ₹Z crore, affecting pricing strategy.” When tax teams align their messaging with business objectives, they shift from being compliance enforcers to strategic advisors. A CFO wants to know: a. How does this affect cash flow? b. Will it impact profitability? c. Can we optimize our tax position? What’s your approach to engaging finance leaders? Share your thoughts below! #TaxStrategy #CFOInsights #BusinessImpact #TaxandFinance

Great seeing our paper out in Science! Stefano Carattini, John List and I argue that policy evaluation should be combined with a causal analysis of public support. Starting point of our argument is that policies that are generally considered socially desirable by the scientific community are not always popular among voters, because of a lack of understanding or biased beliefs. Congestion charges and carbon taxes are a case in point. However, recent empirical studies have shown that, in cases like these, experiencing the policy may lead voters to correct their beliefs and increase their support. A credible policy evaluation may further help voters to learn about the policy's effects. Our article describes how credible policy evaluation can be fruitfully combined with a causal analysis of public support. If it becomes more widely documented that opposition to sound policies dissipates when voters experience a policy, then policy-makers may be more inclined to experiment with such policies. Learning when and why public support does not increase after policy implementation would be very important as well. Indeed, this may even lead to a change in the consensus about the policy's desirability, for instance when scientists learn that they overlooked some negative aspects of the policy that voters strongly care about. Read the full article here: https://lnkd.in/ed2EAj9G Science Magazine