When to build vs buy software for SAP workflows

“There are only three options,” they say. 𝗕𝘂𝗶𝗹𝗱. 𝗕𝘂𝘆. 𝗜𝗴𝗻𝗼𝗿𝗲. It sounds clean. Confident. Like the kind of choice an executive makes before lunch. Like you’re choosing between chicken and fish at a wedding. Reality?��� The 𝗕𝘂𝗶𝗹𝗱 team is reverse-engineering ChatGPT plugins and calling it “differentiated IP.” The 𝗕𝘂𝘆 team is on its fourth vendor in six months because none of them “fully understood our needs.” The 𝗜𝗴𝗻𝗼𝗿𝗲 camp? Quietly running an AI pilot under a different budget line so they don’t have to explain it to finance. 𝗧𝗵𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺 𝗶𝘀𝗻’𝘁 𝗔𝗜. It’s pretending this decision is clean. 𝗕𝘂𝗶𝗹𝗱 sounds bold. Strategic. A castle you control. Until you realize castles need architects, guards, and moat maintenance. And you’ve got a few interns and a Kaggle-winning prototype. 𝗕𝘂𝘆 sounds fast. Until your shiny new tool updates itself into a compliance nightmare. Or sunsets the feature your workflow depended on. 𝗜𝗴𝗻𝗼𝗿𝗲? It’s a story you tell yourself. Until a competitor launches something half as good but ten times louder—and now the board wants answers. Most companies don’t decide. They drift into what’s easiest to explain. Here’s the truth no one markets: It’s not “Build vs Buy.” It’s: What are you willing to own, break, adapt—or bet on? It’s messier than a matrix. Riskier than a pilot. Too important to leave to instinct. So here’s a Playbook — not a framework, not a template, just how to think clearly in a murky world: 1️⃣ Know what you want. Define it in one sentence. No metaphors. Will it make money? Can you exit? Would customers care if it vanished? 2️⃣ Audit your real capability. Do you truly have ML talent, data, ops maturity, leadership support—or just "interest"? 3️⃣ Build = 5-year marriage. If you’re not budgeting for support, legal, updates, and team retention, don’t swipe right. 4️⃣ Buy = one-night stand with shared bank accounts. Can you live with their roadmap? Get your data back? Exit without wreckage? 5️⃣ Ignore—but on purpose. Write it down. Share it. Set a 6-month trigger to revisit. Silence is not a strategy. 6️⃣ Hybrid is negotiation, not strategy. Buy what you’re not great at. Build what you can’t afford to get wrong. 7️⃣ Run a 'What if we’re wrong?' simulation. Early, late, wrong partner—can you absorb it? 8️⃣ Measure what matters. Shipping ≠ success. If no one uses it, you built something impressive—but ineffective. 9️⃣ Governance is not optional. Assume models will lie. Assume people will believe them. Bake in review. Audit. Fallbacks. Or bake in headlines. There’s no perfect choice. Just trade-offs you understand—or trade-offs that blindside you. AI strategy isn’t about tech. It’s about how brave you are in facing what you can’t control— And how grown-up you are in owning what you can. ✅ Which of these steps do you think most companies ignore—and regret? #AI #Leadership #DigitalStrategy ♻️ Repost ➕ Follow 👉 https://2ly.link/22zte

Every PMM team is racing to build internal AI workflows. But a question almost no one is asking is: What should you not build, but BUY instead? AI has made internal tooling feel easy (and I love it), but not every workflow should be automated, rebuilt, or “AI-ified” in-house. Some categories are simply better (and cheaper long-term) to buy. If you’re a PMM leader or solo PMM prepping for 2026, here’s the Build vs Buy framework I recommend (see graphic): 1️⃣BUILD When: The workflow requires PMM judgment or nuance The workflow is unstable, evolving, or unique to your org The category is immature (no clear SaaS leader) The workflow is internal-facing and low risk You need flexibility + fast iteration, not rigidity You have a clear internal owner to maintain it Here is an example of something you should build:  Your internal messaging and narrative development. This workflow is highly customized, requires significant PMM judgment, needs iteration, and varies by product, audience, and campaign. 2️⃣BUY When: The workflow is mature, repeatable, and well-defined It is cross-functional (touches Sales, CS, PM, Execs) You need reliability + consistency, not customization The workflow requires automation, ingestion, or governance You need fast time-to-value Engineering won’t maintain an internal version Here is an example of something you should buy: customer proof infrastructure. For example, with UserEvidence. This workflow is mature, repeatable, and heavily dependent on automation, ingestion, and governance. It doesn’t benefit from deep customization or human-in-the-loop judgment. Buying is dramatically easier (and more reliable) than trying to stitch together an internal system with agents, spreadsheets, and makeshift permission workflows. Ultimately, deciding whether to buy or build is a trade-off between quality vs. time vs. money. So, before you invest time in AI workflows for yourself or your team,  Ask two questions: 1️⃣ Is this workflow mature enough that SaaS will do it 10x better? 2️⃣ Or is this workflow too nuanced or evolving to outsource? How do you evaluate build vs. buy decisions? I would love to hear your thoughts! #productmarketing #ai #software

Most procurement teams overthink the Build vs. Buy decision... They turn a strategic choice into an endless debate that delays critical projects and frustrates stakeholders. Here's the long and short of it... 95% of the time, the answer is BUY! But the remaining 5%? Those are the decisions that can make or break your competitive advantage. I created this decision tree after watching countless organizations waste months (and millions) building solutions that already existed in the market. The framework cuts through the noise with one fundamental question: → Is this capability core to our competitive advantage? If YES, you dive deeper into capability, resources, and economics. If NO, you should almost certainly buying. Even if something is core, you might BUY if you lack technical expertise, need it NOW or can't acquire it cost-effectively. Even if something isn't core, you might BUILD if no suitable commercial solution exists and it's business-critical. Tempted to build a procurement automation tool that already exists as a mature SaaS product? 👀 (I'm looking at you the "I can code anything with Gen-AI and Power Automate" crowd...) It might look cheaper on paper... But I assure you you're either missing assumptions or your assumptions are just plain wrong... You've got "super(wo)man syndrome". The bottom line? Strategic differentiator + internal capability + good economics = BUILD. Everything else = BUY. Stop debating. Start deciding. Get on with your core business. This is what's important. What's the most common mistake you see in Build vs. Buy decisions? Let me know in the comments 👇 _________________________ 𝗣.𝗦. I help companies choose and implement ProcureTech solutions for a living. Every Sunday, I send out a free newsletter which documents the best practices, trends and frameworks in ProcureTech. It's read by 10,000+ Procurement professionals (and counting...) Subscribe here for free: https://lnkd.in/ezb5wiFK

Buy vs. Build its the decision many corporates face when they have technology requirements. Many choose wrong. Corporates love the idea of building their own technology. It feels like control, customization, and long-term cost savings. But is it really the right move? The reality: Most problems are not worth building for, they’re worth solving in the most efficient way possible. Key Questions for Buy vs. Build: ✅ Is this problem truly unique? If off-the-shelf solutions exist, why allocate resources to reinventing them? ✅ Does this scale? Internal builds often start small but become costly to maintain and upgrade. ✅ What are the hidden costs? Internal teams take time, maintenance is forever, and talent churn can leave you with a fragile system. Hidden Costs of Building Internally: ❌ Time-to-market delay – While your team builds, competitors are already deploying. ❌ Ongoing maintenance – The initial build is just the beginning; updates, integrations, and security are continuous costs. ❌ Talent drain – Key engineers move on, and suddenly no one wants to own the legacy tech stack. ❌ Talent onboarding – New hires will be familiar or even experts on the market tools. There will be additional learning curve to adopt an internally built tool. ❌ Opportunity cost – What high-value projects are delayed because resources are tied up in a non-core build? When to Build: 🔹 When the technology is truly differentiating to your business. 🔹 When off-the-shelf solutions don’t exist or won’t scale. 🔹 When owning the IP gives you a significant competitive advantage. Otherwise? Buy it, integrate it, and move faster. #Startups #Technology #BuyVsBuild #EnterpriseTech #Efficiency

“𝗜𝗳 𝗔𝗜 𝗺𝗮𝗸𝗲𝘀 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝘀𝗼 𝗲𝗮𝘀𝘆 𝗻𝗼𝘄... 𝘄𝗵𝘆 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝗯𝘂𝗶𝗹𝗱 𝗲𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴 𝗶𝗻𝘁𝗲𝗿𝗻𝗮𝗹𝗹𝘆?” HubSpot’s CEO, Dharmesh Shah, shared a great perspective on this, even with hundreds of engineers and world-class AI capabilities, HubSpot has replaced 𝘇𝗲𝗿𝗼 of its core SaaS systems with internally built versions. Not because they can’t build them. Because they shouldn’t. His point is simple: 𝗔𝗜 𝗹𝗼𝘄𝗲𝗿𝘀 𝘁𝗵𝗲 𝗯𝗮𝗿𝗿𝗶𝗲𝗿 𝘁𝗼 𝗰𝗿𝗲𝗮𝘁𝗶𝗼𝗻. 𝗜𝘁 𝗱𝗼𝗲𝘀 𝗻𝗼𝘁 𝗹𝗼𝘄𝗲𝗿 𝘁𝗵𝗲 𝗯𝘂𝗿𝗱𝗲𝗻 𝗼𝗳 𝗼𝘄𝗻𝗲𝗿𝘀𝗵𝗶𝗽. Even the best engineering teams don’t want to maintain 100+ internal tools, keep them up to date, track industry changes, respond to security shifts, and rebuild every time the business evolves. But here’s the part most enterprises miss: 𝗧𝗵𝗲 𝗿𝗲𝗮𝗹 𝗳𝗮𝗶𝗹𝘂𝗿𝗲 𝗱𝗼𝗲𝘀𝗻’𝘁 𝗵𝗮𝗽𝗽𝗲𝗻 𝗮𝘁 “𝗯𝘂𝗶𝗹𝗱” 𝗼𝗿 “𝗯𝘂𝘆.” 𝗜𝘁 𝗵𝗮𝗽𝗽𝗲𝗻𝘀 𝗹𝗼𝗻𝗴 𝗯𝗲𝗳𝗼𝗿𝗲, 𝘄𝗵𝗲𝗻 𝘁𝗵𝗲 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁����𝗼𝗻 𝗱𝗼𝗲𝘀𝗻’𝘁 𝗵𝗮𝘃𝗲 𝗰𝗹𝗮𝗿𝗶𝘁𝘆 𝗼𝗻 𝘄𝗵𝗮𝘁 𝗶𝘁 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗻𝗲𝗲𝗱𝘀. That’s why Build vs Buy decisions go sideways: • Requirements are incomplete or AI-irrelevant • Stakeholders are misaligned on the problem itself • Dependencies between systems and teams aren’t visible early • Operational and governance constraints surface too late • Success metrics are undefined or unmeasurable When you skip this planning layer, Build vs Buy becomes guesswork and guesswork gets expensive fast. Here’s the reality I’ve seen inside enterprise cycles: 𝗕𝘂𝗶𝗹𝗱 𝗺𝗮𝗸𝗲𝘀 𝘀𝗲𝗻𝘀𝗲 𝘄𝗵𝗲𝗻 𝘆𝗼𝘂’𝗿𝗲 𝗰𝗿𝗲𝗮𝘁𝗶𝗻𝗴 𝘀𝗼𝗺𝗲𝘁𝗵𝗶𝗻𝗴 𝘁𝗵𝗲 𝗺𝗮𝗿𝗸𝗲𝘁 𝗱𝗼𝗲𝘀𝗻’𝘁 𝗼𝗳𝗳𝗲𝗿. But you need a full blueprint: problem definition, flows, data, integrations, acceptance criteria, handoff assets. 𝗕𝘂𝘆 𝗺𝗮𝗸𝗲𝘀 𝘀𝗲𝗻𝘀𝗲 𝘄𝗵𝗲𝗻 𝘁𝗵𝗲 𝗺𝗮𝗿𝗸𝗲𝘁 𝗶𝘀 𝗮𝗹𝗿𝗲𝗮𝗱𝘆 𝗮𝗵𝗲𝗮𝗱 𝗼𝗳 𝘆𝗼𝘂. But only if you know which vendor actually fits your exact technical + functional requirements. 𝗕𝗼𝘁𝗵 𝗺𝗮𝗸𝗲𝘀 𝘀𝗲𝗻𝘀𝗲 𝗺𝗼𝗿𝗲 𝗼𝗳𝘁𝗲𝗻 𝘁𝗵𝗮𝗻 𝗽𝗲𝗼𝗽𝗹𝗲 𝗿𝗲𝗮𝗹𝗶𝘇𝗲. Most modern enterprise systems aren’t built or bought, they’re assembled, integrated, and extended. And none of these decisions should rely on instinct, preference, or internal politics. They should rely on 𝗮 𝗽𝗹𝗮𝗻. Because once you have clarity on, what you need → why you need it → who it impacts → what constraints exist → what good looks like → how it scales, the build vs buy answer becomes obvious. Most enterprises don’t struggle because they pick the wrong option. They struggle because they pick before they’re ready. Force Equals is the 𝗽𝗹𝗮𝗻𝗻𝗶𝗻𝗴 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗻𝗴 𝘀𝘆𝘀𝘁𝗲𝗺 that makes both options viable, efficient, and high-confidence. If you're making Build vs Buy decisions for 2026 initiatives and want to see how this would pan out, let's have a chat. Amy Lakshit . Greg Tom #EnterpriseAI #CXLeadership #EnterprisePlanning #ForceEquals

Most build vs buy discussions happen too late And they start with the wrong question.... By the time the conversation comes up, the business is usually feeling the pain. Teams are bogged down in workarounds. Systems no longer fit the way the company operates. Delivery slows. Visibility drops. At that point, the decision feels urgent:  “𝗗𝗼 𝘄𝗲 𝗯𝘂𝗶𝗹𝗱 𝘀𝗼𝗺𝗲𝘁𝗵𝗶𝗻𝗴 𝗼𝘂𝗿𝘀𝗲𝗹𝘃𝗲𝘀 𝗼𝗿 𝗳𝗶𝗻𝗱 𝗮 𝗽𝗿𝗼𝗱𝘂𝗰𝘁 𝗼𝗳𝗳 𝘁𝗵𝗲 𝘀𝗵𝗲𝗹𝗳?” But by then, the choice is reactive and not strategic. A better approach is to start with a few critical questions much earlier: ↠ What are we optimising for? Speed, control, scale, or cost? ↠ Where do we need flexibility, and where can we adapt to standard tools? ↠ How easily can our team adopt and maintain the solution? ↠ What are the longer-term risks of fitting the business around the tool? These questions help shift the decision from tactical to strategic. Most of the time, the answer isn’t fully “build” or fully “buy.” It’s a combination. Commercial tools for standard processes, and lightweight customisation where differentiation matters. Good architecture decisions support the business long after the implementation is done. That only happens when you ask the right questions up front. #scaling #buildvsbuy #software #softwaredevelopment