Tech Stack Management

Building your finance tech stack? Here’s a major mistake I see finance leaders make: It’s not overspending. It’s not picking the wrong vendor. It’s something far more fundamental. As monday.com’s CFO, I evaluate all large software purchases - and I’ve noticed a consistent pattern: Many teams obsess over features and discounts, but ignore the 6 factors that actually determine long-term success. Here’s what actually matters at $1B+ ARR and beyond: 👇 1. Don’t Evaluate the Tool in Isolation – But Within the Ecosystem For large purchases, you want to see the full picture - not just the tool itself. Ask: How will this new platform integrate with your existing ones? Most teams evaluate tools in isolation, but real value comes from integrations. Silos destroy efficiency and visibility. The question isn't "Is this the best tool?" but "Is this the best tool FOR OUR ECOSYSTEM?" 2. Benchmark Against Companies at Your Scale It’s a yellow flag if other enterprise organizations aren't using a tool we're considering. When evaluating NetSuite as our ERP, we did research on $500M+ ARR companies to understand their implementation challenges. When we chose Zip for procurement, we looked at companies with similar global reach. The tools that work at $100M ARR don’t necessarily work at $1B+. 3. Assess Implementation Complexity Realistically I am not a fan of solutions that require massive teams just to babysit them. User-friendly and quick internal adoption wins over heavy customization every time. Avoid tools that “promise everything” but deliver nothing for 12+ months. 4. Test for Scalability Early Most finance teams discover scalability issues after it’s too late. Ask: Can the tool scale with us from 100 to 1,000 users without breaking?  We are building our tech stack with enterprise-grade solutions because they grow with us. 5. Strategic Consolidation Beats Best-of-Breed Fewer vendors means better negotiating leverage, simpler operations, and cleaner data flows. At monday, we're ruthless about removing fragmentation that isn’t necessary. 6. Keep Your Stack Evolving with an AI-First Mindset Our finance tech stack is not static. We're constantly updating with a focus on AI capabilities. I suggest you do the same. Every finance leader should reevaluate their tech stack through an AI lens today. *** In summary: The most expensive procurement mistake isn’t overpaying. It’s buying tools that:  1. Can’t grow with you 2. Create siloed data environments 3. Lack AI capabilities in this new AI-first era This mindset has helped us scale efficiently - and avoid million-dollar mistakes.   What’s one finance tool you regret, or swear by? Drop it below👇

Save this image. The smartest accounting firms I know review their tech once per year. They don't have perpetual tech FOMO, and the reward is big money savings and focus. Here's how they do it: Starting today, give yourself 30 days to make decisions, then wait to revisit it until next year. For US tax firms this is the best time for tech change, because you don't want to ride into battle next year on untested tech. But here's what 90% of firms get wrong: Because you already have a tech stack, you look for cute little apps to plug a hole here, make you more efficient there. Bandaids. The result is a broken, oversized stack. You know it, so you window shop 365 days a year. Let's put that to bed right now. While no stack is perfect, you CAN have 100% confidence you're on the right stack. The resulting focus is 🤌🤌 The biggest mistake firms make is choosing their tech in the wrong order. Important: we want our core apps to solve for as many things as possible. Getting the first picks right can reduce the number of tools you use by upwards of 50%. Let's walk through this step by step: 1️⃣ Your Core Functional Tech (Blue) Start with your tax software and your accounting ledger. It's where you'll spend more time than anywhere else, but importantly it also impacts what the right downstream tech selections are. I'm character limited here, if you want my shortlist of tools recs for each category I shared them with my email list yesterday. Sign up this week and I'll send you those recs jasononline.link/3dX 2️⃣ Practice Management & Workflow (Red + Pink) You'll notice these are both rectangles. It's because your workflow tech + your practice management tech should be selected in tandem. The tools in pink are a new category that's developed in the past 3 years, and are now a non-negotiable part of every firm's tech stack. I wish these two categories could be merged, but today they can't. We'll revisit that in 12 mos time. 3️⃣ Engagement (Green) Don't shortcut this one. Presenting 3 options, clarifying scope, creating urgency etc has a very real impact on what your client will pay you. If every engagement your client accepts for the next 5 years was $50 more, you'd make $1.7M more dollars in that time (you're welcome). 4️⃣ Service Line (Teal) These are the tools that support specific service lines. Like a reporting tool for your advisory service, or a bill pay tool, or a spend management tool. Sometimes your upstream tools will handle this fine, sometimes they won't. 5️⃣ Toppings (Yellow) This one's a trap. You fall in love with these tools and it can have an undue influence on the way you pick the rest of your stack. But toppings like RightTool, Zapier or Uncat are listed last for a reason. They'll make you more efficient with the rest of your tech, but don't let the tail wag the dog. Don't be distracted by people like me the rest of the year. Nail your stack now and reap the reward of 12 months of focus.

Buying Clay won’t get you more leads. Buying Gong won’t make your sales team better on calls. Just like: Buying a set of Wüsthofs won’t make you a better chef. Buying that new Titleist driver? Yeah… it’s not going to magically straighten your slice. Too often we buy tools hoping they’ll solve our problems. But tools don’t solve problems. Processes do. And the best Revenue and Rev Ops leaders I know all follow a playbook when it comes to tooling: 1. Start with the problem, not the tool You need a list—not of tools you want to try, but of business problems you need to solve. Some common ones I hear: "We need to improve our pipeline conversion rate" "We need better forecasting data" "We need to stay in closer touch with customers post-sale" Then you can go hunting for tools that solve those problems. But if you’re just chasing every shiny new AI-powered tool? You’re going to waste time, budget, and team attention. Trust me, the 100th AI SDR tool still sounds pretty cool but it might not be what you need for your business at the current time. 2. Use a structured, data-driven evaluation process “I can see us using this” is not a business case. You need a scorecard. How easy is it to implement? How hard will it be to drive adoption? What’s the expected ROI? Does it integrate with our current workflow and tech stack? The best teams run their tooling like procurement pros. Gut feel isn’t enough, especially when budgets are tight and the stakes are high. 3. No process = no payoff Let’s say you buy the tool. Now what? Without enablement, accountability, and integration into daily workflows, that tool is going to sit on the shelf (just like that $500 driver in your garage). At minimum, you need: -Training plans -Change management -Clear documentation -Leadership support -An incentive or consequence to drive usage If you don’t have a process to make the tool work, you’ve bought shelfware. 4. Continuously re-evaluate your stack We’re in an era where AI is creating entirely new categories almost overnight. Point solutions are becoming features. New platforms are emerging weekly. And you can’t afford to run the same stack just because it worked last year. Great revenue leaders are constantly pruning and optimizing, aligning tools with the evolving needs of the team and the business. The bottom line is software doesn’t make you better. Process does. So before you pull the trigger on the next tool, ask yourself: “Do we have the infrastructure, alignment, and plan to make this successful?” Because trust me, your new Titleist is still going to slice 20 yards right unless you’ve put in the reps (or booked some lessons).

Four-step PLAYBOOK to act on the "AI GTM Strategy" ask from your CEO, if you are the CRO or CMO of a B2B organisation with revenue north of $20M ARR. 1. Start with pain points: Don’t go shopping for shiny features or products. Instead, start with something real, something painful, and then look for vendors that solve that specific problem or specific set of problems. I see prospects beginning with a long list of 150 AI tools, and get stuck in "pilot hell". 2. Anchor on one KPI: Pick a single, measurable metric that matters to your business and will solve the most significant pain in your list. Let it guide every decision. Whether it's improving meeting show-up rates by 50%, cutting acquisition costs by 30%, or increasing conversion rates by 15%. That’s how one public company found us. In their research, Docket was one of the few solutions that made sense for their actual need, and today we're running a successful pilot with them. 3. Is your vendor also your consultant? We engage with our customers like consultants who have expertise in both AI & the GTM technology landscape. We can do that because we're knee-deep in AI and are genuinely curious about all the advancements in this industry. I literally left my job as ZoomInfo's CDO (a publicly traded company) to start Docket because I couldn't sleep at night and found myself tinkering with AI. This curiosity helps us make product decisions that benefit both us and our customers in the long run. An example here: https://lnkd.in/eTRUyJUm We've also been in the GTM technology space for more than a decade. This helps us understand how B2B marketing teams work, how internal budgeting and adoption occur. More on AI X Martech adoption here - https://lnkd.in/eVHryY68 Also, another example of how our industry expertise helps us shape the product philosophy - https://lnkd.in/e_mT9u5s It's hard for any vendor to architect a lasting solution that also moves your KPIs meaningfully if they do not understand both. 4. Is your vendor prepared for the long game? We raised our $15M Series A even when we had a lot of cash in the bank because the "window of opportunity" in AI is wild and unpredictable. Large Language Models—the base technology underpinning all your B2B Gen AI vendors — will continue to improve & change. Their runway is a good proxy for assessing whether they are equipped to handle both headwinds and tailwinds in their industry.…

Before you waste money on more tools you don’t need, try my 3-step tech stack audit: 𝗦𝘁𝗲𝗽 𝟭: 𝗗𝗲𝗲𝗽 𝗗𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝘆 • Interviews with key decision-makers • Map the current state by defining core user needs • Document critical business requirements through User Stories • Identify where manual processes create risk 𝗦𝘁𝗲𝗽 𝟮: 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 • Review GTM infrastructure and data flows. • Map tools against actual business capabilities • Grade each system's automation level (1-10) • Identify integration gaps and duplicates 𝗦𝘁𝗲𝗽 𝟯: 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗥𝗲𝗰𝗼𝗺𝗺𝗲𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝘀 • Build implementation roadmap by quarter. • Prioritize highest-impact changes first. • Create a clear ownership structure. • Design process documentation framework The key isn't counting tools—it's matching capabilities to needs. Series A companies might need 10-20 tools, and scale-ups might need 30-50. What matters is how they work together. Your tech stack audit shouldn't just list tools. It should reveal how your systems support (or hinder) revenue growth. #hubspot #techstack #martech  

I spent $50K+ testing agency tools so you don't have to. Here's how I cut that in half while getting better results. The biggest mistake? Buying tools before defining what problem you're solving. Most founders copy their competitors' stacks, then wonder why their $3K/month in tools barely moves the needle. With the right framework, you can avoid that trap: 1. Define your stack pillars Stage fit: Is this stack pillar relevant at your company's current size? If you're a startup doing $10K/mo, you don't need the same CRM as an enterprise doing $5M/mo. Context matters more than features. 2. Define stack goals Get clear on what you're optimizing for: Scalability: Can it handle 10x more leads/clients without breaking? Insight/Reporting: Does it surface the right data to make better decisions? Usability: Is it easy for the actual end users (not just ops) to adopt? 3. Pick who's shipping fastest If two tools look the same now, pick the one releasing updates consistently. That's the team that'll keep future-proofing your stack. Clay ships new features constantly. That's why it's our operating system. 4. Ask the 22 questions These force you to buy based on need (full list in the infographic). My favorites: What problem am I actually solving? Can my current stack do this? What's the cost per successful outcome? Can I test on one client first? 5. Create evaluation criteria Real examples from our stack: Data quality: Apollo has 30% accuracy. Prospeo.io + LeadMagic combined = 70% finding rate for half the cost. 6. Pick your execution framework Must-Have vs Nice-to-Have. Stack Audit. Decision Checklist. Test-Before-Commit. (Full breakdown in the infographic) The difference between a $50K/mo agency and a $500K/mo agency isn't just more clients. It's having a stack that compounds efficiency instead of creating chaos. Want to stop wasting money on tools that don't move the needle? I built a free 7-day email course that walks you through our exact stack selection framework + the tools we actually use to run a lean, profitable agency. Comment "TOOLS" and I'll send it your way. Helpful? Repost ♻️ to help others avoid tool chaos.

One bad tech decision can destroy your startup. I've led the creation of 100+ software products for Silicon Valley startups & global businesses. The 5 key principles for choosing right in 2025: Most founders get their tech stack totally wrong. I've watched companies burn hundreds of thousands rewriting their entire codebase because they chose trendy tech that couldn't scale. Your tech stack choice today will impact: • How easily you scale • How fast you ship features • How much talent you attract Most chase whatever's hot in tech Twitter threads. But your business isn't a testing ground for experiments. Here are 5 principles I've learned from building software for Silicon Valley startups: 1. Avoid Fads Like The Plague Every year brings a new "revolutionary" framework that's supposed to change everything. 90% disappear within months. Your tech stack needs to solve real problems, not win coolness points. 2. Think Long-Term Your tech choices are marriages, not one-night stands. Pick solutions that will still be relevant in 5-10 years. The strongest technologies are usually the battle-tested ones. 3. Accept The Trade-offs There are no perfect solutions, only smart compromises: • Microservices scale better but add complexity • NoSQL gives flexibility but sacrifices consistency • Serverless cuts costs but increases dependency 4. Go Mainstream The more developers using a technology, the better your position: • Easier hiring • Better tool integration • Fewer scaling headaches • Lower maintenance costs Don't get stuck maintaining some obscure framework nobody uses. 5. Get Expert Eyes One bad tech choice = years of technical debt and scaling nightmares. Talk to experienced CTOs. Study where others failed. Ask around. The cost of getting it wrong is massive. I've seen it firsthand: • $300k spent on rewrites • 8-month delays • Entire teams quitting If you're building something serious and want to avoid these expensive mistakes, let's talk. We help companies choose and implement tech stacks that scale. Book a free consultation here: https://lnkd.in/dndQiR9A