Strategies to Reduce Software Costs

Negotiation tactics we used to decrease our SaaS spend by 30% in the last year: It’s amazing to me how much room there is in SaaS pricing. The price is not the price is not the price. You can always negotiate, and there are often loopholes that can save you a ton of money. Here are some of them: - Cancel the renewal before the negotiation. We send cancellation notices to our biggest opportunity negotiations months in advance, and tell them that we will only renew upon having a new deal. Often, account reps can provide special discounts for “at risk” clients. - Get your usage data. We always dig through our data before a negotiation. If our usage is lower than expected, we use that as leverage. For example, our hiring has gone down by about 60% post-ZIRP, but we still paid the same annual price for our applicant tracking system. We showed them the data and made it clear the software wasn’t worth what we were paying. - Be nice. Honestly, sometimes I get frustrated because I know I’m getting the runaround. Every time I do, it backfires. When I’m on my A-game, I’m nice - I tell them I love their software, it is useful, but we just don’t have as much of a need right now. It’s not you, it’s me. I do tell the truth, though, so they know I’m genuine with my praise and critiques. - Compare their costs to other options. There are 3 different types of comparisons: 1) direct competitors. Just call them and get a quote. 2) indirect competitors. Oftentimes another company offers a “basic” version of the software you’re using, so you can use that as leverage: “we don’t need an applicant tracking system because we already pay for Notion”. 3) budget competitors. Compare the pricing of x subscription with y subscription. We regularly compare unrelated products and say: you are the 2nd highest cost product we use, even though you aren’t the 2nd most valuable to us. - Ask 3x. You almost always have to negotiate at least three times to get the best deal. It doesn’t work with every company, but most account reps have latitude and at some point you’re not worth their time. Take advantage and just make sure you press multiple times in a row instead of taking the first offer. I’m surprised at how often we get our way in these negotiations. Sometimes I step in as the founder, but now my team has watched this playbook and gets the same results on their own. You don’t need to be a founder or a business unit leader to do this: act like an owner and make sure your company isn’t wasting money!

There are ways to drive savings and increase the discount on your software contracts, even if your company (or budget) isn’t growing right now. Here’s three ways I’ve learned to do this:👇 1. Explore utilization as a way to reduce consumption. I’m not saying to take away licenses from those who are using them, but let’s take it away from people who aren’t using them. Companies tend to assign licenses to people who they think should use them, but it often results in a bunch of unused or under-used licenses. In a recent negotiation with a well-known supplier, we drove much needed savings by purchasing what we were using, rather than what we thought we needed. Result: Over $100,000 in hard savings. 2. Gain leverage by understanding what type of customer you are. Earlier this month, I read a supplier’s earning release to prep for a negotiation. Found out that only a small % of companies spent more than $1M for their service + a key metric for them is customer growth w/this type of spend (and reducing churn for customers in this category). Even though this supplier had a fairly rigid pricing model, the company I was working with fit this criteria. We were empowered to ask for more because we knew the supplier would be more willing to work with us, since they would hate to lose us. Result: Extra 18% discount. 3. Use the 2x2 matrix to evaluate suppliers based on how competitive their market is + how difficult a transition would be. Competition in many sectors is heating up as more suppliers expand their services (the great migration to the platform). A few months ago, my company bit the bullet, migrated away from a long-time supplier, and paid less than half of what we previously spent by moving a product SKU over to an existing supplier.  Result: 60% savings straight to the bottom line. And 1 supplier where historically there were two. And we aren’t the only ones making the switch. According to CS folks I’ve talked to, software renewal rates have dropped dramatically over the past 12-24 months. Summary: Let’s face it: a much smaller %  of companies are growing right now. And while leveraging growth is amazing, you’ve got to find a way to drive savings even if you don’t have it as a lever. For many companies, they need savings because investors are demanding better financials.  For other companies, It’s survival-mode in this climate. 🤷 #Procurement can add so much value. Companies like Tropic have the tools to help. Anything you’d add?

How I Cut Cloud Costs by $300K+ Annually: 3 Real FinOps Wins When leadership asked me to “figure out why our cloud bill keeps growing Here’s how I turned cost chaos into controlled savings: Case #1: The $45K Monthly Reality Check The Problem: Inherited a runaway AWS environment - $45K/month with zero oversight My Approach: ✅ 30-day CloudWatch deep dive revealed 40% of instances at <20% utilization ✅ Right-sized over-provisioned resources ✅ Implemented auto-scaling for variable workloads ✅ Strategic Reserved Instance purchases for predictable loads ✅ Automated dev/test environment scheduling (nights/weekends off) Impact: 35% cost reduction = $16K monthly savings Case #2: Multi-Cloud Mayhem The Problem: AWS + Azure teams spending independently = duplicate everything My Strategy: ✅ Unified cost allocation tagging across both platforms ✅ Centralized dashboards showing spend by department/project ✅ Monthly stakeholder cost reviews ✅ Eliminated duplicate services (why run 2 databases for 1 app?) ✅ Negotiated enterprise discounts through consolidated commitments Impact: 28% overall reduction while improving DR capabilities Case 3: Storage Spiral Control The Problem: 20% quarterly storage growth, 60% of data untouched for 90+ days in expensive hot storage My Solution: 1, Comprehensive data lifecycle analysis 2, Automated tiering policies (hot → warm → cold → archive) 3, Business-aligned data retention policies 4, CloudFront optimization for frequent access 5, Geographic workload repositioning 6, Monthly department storage reporting for accountability Impact: $8K monthly storage savings + 45% bandwidth cost reduction ----- The Meta-Lesson: Total Annual Savings: $300K+ The real win wasn’t just the money - it was building a cost-conscious culture** where: - Teams understand their cloud spend impact - Automated policies prevent cost drift - Business stakeholders make informed decisions - Performance actually improved through better resource allocation My Go-To FinOps Stack: - Monitoring: CloudWatch, Azure Monitor - Optimization: AWS Cost Explorer, Trusted Advisor - Automation: Lambda functions for policy enforcement - Reporting: Custom dashboards + monthly business reviews - Culture: Showback reports that make costs visible The biggest insight? Most “cloud cost problems” are actually visibility and accountability problems in disguise. What’s your biggest cloud cost challenge right now? Drop it in the comments - happy to share specific strategies! 👇 FinOps #CloudCosts #AWS #Azure #CostOptimization #DevOps #CloudEngineering P.S. : If your monthly cloud bill makes you nervous, you’re not alone. These strategies work at any scale.

If your AI token bill isn’t rising, your teams probably aren’t moving fast enough. Executives everywhere are waking up to a familiar surprise. AI usage is up. Token bills are climbing. And someone asks, “Do we really need to spend $10,000 a month on inference?” The answer: maybe more than that. Because if that $10K makes your top engineers 15 percent faster, shortens delivery by a sprint, and lets operations self-serve instead of waiting on dev, you’re not overspending. You’re under-innovating. The right question isn’t “How do we spend less?” It’s “How do we spend wisely?” AI spend is no different from cloud or compute. You don’t cut it. You optimize it. Here’s how smart orgs are doing that: 1. Use the right model for the right job Every task doesn’t need GPT-4 or Claude Opus. • Use lightweight models like Gemini Flash or Claude Haiku for autocomplete, regex, and summaries. • Use top-tier models like GPT-4o or Claude 3.5 for architecture, planning, or complex code generation. • Fine-tune or host open models internally for repetitive workflows. This alone can cut costs by 30 to 50 percent without losing capability. 2. Route requests intelligently Think of your AI platform like a router. Simple prompt? Route to a fast, cheap model. Strategic task? Route to a high-context one. Every inference doesn’t need a Ferrari. Sometimes a bicycle will do just fine. 3. Empower teams to design efficient prompts Prompt verbosity leads to bloated outputs and wasted tokens. Teach your team to prompt like engineers, not just users. • Use structured prompting and templates • Iterate on shorter context windows • Encourage reuse of optimized chains 4. Monitor value, not just spend Create dashboards that correlate token usage with business impact. Are high-usage teams closing more tickets? Shipping faster? Reducing escalations? If yes, spend more. If not, coach smarter. 5. Expand beyond engineering, but with purpose Support, finance, and ops teams want to use AI. Don’t throttle their enthusiasm. Give them light copilots with constraints, audit trails, and clear use cases. Innovation needs space, but space with guardrails. The bottom line: AI isn’t just an expense. It’s an amplifier. And like all amplifiers, it needs tuning, not muting. The companies that win won’t be the ones that save on tokens. They’ll be the ones that teach their teams to turn compute into capability and models into momentum. Prudent AI isn’t about spending less. It’s about spending with purpose.

4 Ways to Cut IT Costs (Without Derailing Progress) Because budget cuts don’t have to mean broken tools, burnt-out staff, or saying goodbye to innovation. Most cost-cutting plans feel like a panic attack in PowerPoint form. But it doesn’t have to be that way. Here’s how smart IT leaders reduce spend—and increase impact—without setting the place on fire: 1. Find Hidden Cost Traps The biggest leaks aren’t obvious. They’re subtle, routine, and quietly expensive. Too Many Tools ↳ Map all tools to their actual job. If three platforms are all "collaboration tools," it's time to consolidate. Manual Workloads ↳ Automate anything repetitive. Approvals, resets, new user setups—if it happens more than twice a week, it's costing too much. Untracked Assets ↳ Use dashboards to track usage, not just possession. If it’s unused, it’s wasting money. Always Reactive ↳ Stop solving the same fire twice. Every incident should include a review. Fix the root, not just the result. Shadow IT ↳ Rogue tools happen when people don't trust the process. Bring them in, don’t crack down. 2. Make Smart IT Moves Cutting costs doesn’t mean cutting capability. Platform Consolidation ↳ Run fewer systems, better. Centralize requests, assets, and approvals on one scalable ITSM platform. Automation First ↳ Identify 3 tasks your team dreads. Automate those first. That’s ROI with receipts. Asset Visibility ↳ Track what you have, who’s using it, and when it renews. Surprise renewals = surprise budget crises. Shift Left ↳ Move common fixes down the stack. Help frontline teams solve problems faster and free up your experts. 3. Lean Your ITSM Stack Fewer tools. Cleaner workflows. More room to think. Visibility ↳ Build reports that connect tools to outcomes. If you can’t measure value, it’s probably costing you. Efficiency ↳ Automate high-volume, low-thinking tasks. Focus your people on what requires judgment—not clicking boxes. Optimization ↳ Eliminate what’s unused or unloved. There’s no budget line for “we might use this someday.” Strategy ↳ Reinvest the savings. Don’t just slash—build. 4. Use the 4-Month Fix Plan Big wins don’t require big rollouts. Just a focused sprint. Month 1 – Take Inventory ↳ List every app, license, and system. No spin. Just get the facts. Month 2 – Cut Redundancy ↳ Merge what overlaps. Kill what doesn’t serve. Call your vendors. Month 3 – Automate Tasks ↳ Fix the annoying stuff. Automate it. Free up your team for better work. Month 4 – Realign Budget ↳ Apply recovered funds to high-impact projects. Show results in business terms, not ticket volume. Cutting costs doesn’t mean cutting effectiveness. With the right strategy, your team can spend less and deliver more. What’s one cost-saving move your team made that actually worked? ♻️ Repost if you believe IT can be efficient and excellent. 🔔 Follow Bob Roark for IT strategies that reduce chaos, not just budget lines.

In my last year at AWS, I was once tasked with finding $400 million in cost savings for cloud spending in just one year. It was a daunting challenge, but I learned a lot of valuable lessons along the way that I'd like to share with you. First, let's go over what I did to save that $400 million. Here are the top three strategies that worked for me: - Automation of idle instances: It's common for developers and testers to leave instances running even when they're not being used, which can add up quickly. We built automation to identify idle instances, tagged them, sent emails to people, and shut them down automatically if we didn’t get a response to leave them up. - Elimination of unused backups and storage: We found that we were keeping backups of customer data that we weren't using, which was costing us a lot of money. By reaching out to customers and getting their approval to delete backups that weren't being used, we were able to save a substantial amount of money. - Reserved instances: Reserved instances have a much lower cost than on-demand instances, so we made sure to buy them whenever possible. We also used convertible RIs so that we could shift between instance types if there were mispredictions about which types of instances would be in demand. Now, let's talk about what I would do differently if I were facing this challenge today. Here are two key strategies that I'd focus on: - Start with automation: As I mentioned earlier, automating the identification and shutdown of idle instances is crucial for cost savings. I'd make sure to start with this strategy right away, as it's one of the easiest and most effective ways to save money. - Be cautious with reserved instances: While RIs can be a great way to save money, they're not always the right choice. If you're in a world where you might be shrinking, not growing, you need to be much more cautious about buying RIs. Make sure to consider your commitment to buy and whether you'll be able to sell the capacity later. What would you add to this list? #devops #cloud #automation

How to Lower LLM Costs for Scalable GenAI Applications Knowing how to optimize LLM costs is becoming a critical skill for deploying GenAI at scale. While many focus on raw model performance, the real game-changer lies in making tradeoffs that align with both technical feasibility and business objectives. The best developers don’t just fine-tune models—they drive leadership alignment by balancing cost, latency, and accuracy for their specific use cases. Here’s a quick overview of key techniques to optimize LLM costs: ✅ Model Selection & Optimization • Choose smaller, domain-specific models over general-purpose ones. • Use distillation, quantization, and pruning to reduce inference costs. ✅ Efficient Prompt Engineering • Trim unnecessary tokens to reduce token-based costs. • Use retrieval-augmented generation (RAG) to minimize context length. ✅ Hybrid Architectures • Use open-source LLMs for internal queries and API-based LLMs for complex cases. • Deploy caching strategies to avoid redundant requests. ✅ Fine-Tuning vs. Embeddings • Instead of expensive fine-tuning, leverage embeddings + vector databases for contextual responses. • Explore LoRA (Low-Rank Adaptation) to fine-tune efficiently. ✅ Cost-Aware API Usage • Optimize API calls with batch processing and rate limits. • Experiment with different temperature settings to balance creativity and cost. Which of these techniques (or a combination) have you successfully deployed to production? Let’s discuss! CC: Bhavishya Pandit #GenAI #Technology #ArtificialIntelligence

💵 Exploring the Design Principles of Cost Optimization in the 🔥Azure Well-Architected Framework🔥 Cost optimization is critical to ensuring your Azure workloads are not just effective but also efficient. By following the Azure Well-Architected Framework's cost optimization principles, businesses can maximize value while minimizing unnecessary expenses. Let’s break these principles down and see how they apply to Azure IaaS: 1️⃣ Develop Cost-Management Discipline Establish clear cost management practices, such as tagging resources, setting budgets, and implementing cost alerts. 💡 Example: Use Azure Cost Management and Billing to set up budgets for different resource groups and notify your team when you approach 80% of a budget limit. This avoids surprises and helps identify spending trends. 2️⃣ Design with a Cost-Efficiency Mindset Architect workloads to deliver the same or better performance at lower costs by choosing appropriate services and configurations. 💡 Example: For a workload needing VM redundancy, use Azure Availability Sets or Availability Zones rather than overprovisioning standalone VMs. This ensures high availability while keeping costs lower. 3️⃣ Design for Usage Optimization Optimize usage by understanding workload patterns and leveraging auto-scaling and scheduling to match resource demand. 💡 Example: Implement Azure Virtual Machine Scale Sets to automatically scale instances up or down based on demand, ensuring you only pay for the capacity you actually use. Additionally, schedule non-production environments (e.g., dev/test VMs) to shut down during non-working hours using Azure Automation. 4️⃣ Design for Rate Optimization Choose the most cost-effective pricing models, such as reserved instances or spot VMs, for workloads with predictable or interruptible usage. 💡 Example: Use Azure Reserved Virtual Machine Instances for workloads that run 24/7, like a production SQL Server VM, to achieve savings of up to 72% compared to pay-as-you-go pricing. For batch workloads, spot VMs provide significant cost savings. 5️⃣ Monitor and Optimize Over Time Cost optimization is not a one-time activity; it requires continuous monitoring and adjustments. 💡 Example: Regularly analyze your Azure Advisor recommendations to identify idle resources, overprovisioned VMs, or outdated configurations. For instance, rightsizing a VM that is underutilized from a Standard D4 to a D2 can lead to immediate savings. By applying these principles, organizations can align their Azure investments with business goals while staying efficient and agile. #Azure #CloudComputing #CostOptimization #AzureWellArchitected #AzureIaaS #CloudCostManagement #AzureTips #MicrosoftAzure #MicrosoftCloud #CloudArchitecture #AzureCost

Digital PS - the ‘IKEA’ effect on Professional Services. Could our customers self-deliver? The thought and design that goes into making a product that can be self-assembled is significant. The Swedish company, Ikea, has mastered this. As has Blue Apron, the meal-prep self cook company. For SaaS and On-Prem product companies, the drive to keep on-boarding and implementation costs down, has resulted in the rise of packaged offerings, and packaged services. Pre-canned onboarding and implementation projects sold for a fixed-price, fixed outcome. To deliver successful packaged services, we need to get very good at repeating the same playbooks over and over again. We need to get very good at defining the tools, the process and the procedures to deliver value. Software companies doing this very well get to the level of Ikea instruction booklets when it comes to their product onboarding and implementation methods. Imagine if you could onboard a customer simply by giving them the product (Cloud or on-prem), key tools and collateral, detailed instructions, and a ‘dial-a-friend’ support line. Your certified practitioner would come in at the end to sign-off on the build. You could sell coaching services to ensure customers stay on track. A number of things would happen: 1. We would get very good at defining precisely what needs to get done in order to implement our product(s). 2. We would have enough detail to enable customers or partners to self-onboard, or self-implement, thus reducing implementation doubt and risk. 3. We would create a sense of achievement amongst our customers. We wouldn’t let them fail, of course. 4. Our onboarding and implementation costs would reduce. 5. Our onboarding and implementation quality would increase. 6. Our partner community would scale via a franchised implementation model. Our internal PS staff would become world experts building the self-build plans. Spreading th knowledge for success. 7. Our customers would feel empowered through their self-build work. 8. Our customers would feel more vested in the success of the on-boarding/implementation. 9. Our customers would deeply understand what it takes to onboard, and therefore expand their product usage in their environment. 10. Our customers would have greater choice at a reduced cost. There are thousands of start-up and SMB software companies out there, staying lean, and wondering how to onboard or implement for their customers. Digital PS may just be the way forward. P.S. For further reading specifically on The IKEA Effect and DYI - a cognitive bias - have a look at this article: https://lnkd.in/e-gmWPFj

The #1 mistake companies make with IT budgets? Ignoring these hidden costs. Have you ever looked at your IT budget and wondered, "Where is all this money going?" You’re not alone. IT budgets are leaking money—silently, predictably, and worst of all, avoidably. I helped a medical device manufacturing company cut IT costs by 22%—without layoffs, without cutting corners, and without slowing innovation. Here’s how we did it: Step 1: Removing IT Waste 💸 We dug into the numbers and found shocking inefficiencies: 🚀 Eliminated redundant systems (why pay for two tools that do the same thing?) 🚀 Consolidated overlapping applications (less complexity, lower costs) 🚀 Reduced licensing & maintenance fees (goodbye, overpriced contracts) ✅ Result: 22% lower Total Cost of Ownership (TCO). Step 2: Improving Efficiency Once we stopped the money leaks, we focused on making IT work smarter, not harder: 📌 Automated tedious, manual tasks (so teams could focus on real innovation) 📌 Identified bottlenecks & streamlined workflows (less friction, faster execution) 📌 Boosted operational efficiency by 30% 🚀 💡 Faster execution. Lower costs. Better resource allocation. Step 3: Smart Cloud Migration Instead of just "lifting and shifting" to the cloud, we optimized first: 🔹 Right-sized IT infrastructure (no more overpaying for unused capacity) 🔹 Cut legacy maintenance costs (old tech shouldn’t drain new budgets) 🔹 Aligned resources to real business needs (spend smarter, not just more) How You Can Apply This Today ✔ Take a hard look at IT spending—find hidden costs ✔ Automate routine tasks—eliminate unnecessary manual work ✔ Renegotiate vendor contracts—secure better deals 💡 IT should drive growth, not just cost. What’s one way you’ve optimized IT spending? Let’s discuss. P.S. Cutting costs doesn’t mean cutting innovation. If you’re rethinking your IT strategy, I’d love to hear your approach. #DigitalTransformation #CIO #Technology #Innovation