W. Edwards Deming spent his life teaching leaders how systems produce the results they deserve. Startups often imagine they can bolt on quality once product-market fit arrives. In practice, early habits calcify. Architecture choices, hiring norms, incident rituals, and vendor contracts become the rails that carry you at scale. Deming’s 14 points, usually applied to large manufacturers, translate surprisingly well to a five-person company with a runway measured in months. Done right, they let you grow without spending all your energy cleaning up self-made messes.
I have seen these principles help a seed-stage SaaS team cut churn by half within two quarters, and I have watched founders ignore them and end up with a support queue that swallowed the roadmap. The trick is not to mimic the vocabulary of Total Quality Management, but to internalize the spirit: build a system that learns faster than it breaks.
Constancy of purpose at seed stage
Deming started with constancy of purpose, a phrase that can feel out of place in a market that pivots weekly. The point is focus on long-term value, not a promise never to change.
In a startup, constancy of purpose means naming the enduring problem you solve, the kind of customer you serve, and the competitive advantage you intend to compound. For a data observability company I advised, that constant purpose was “make engineers trust their analytics,” even as product modules moved around. Decisions followed from that center: they deprioritized a dashboard skin that a big prospect wanted, because it didn’t improve trust. Instead they shipped lineage tracking that made root-cause analysis two clicks instead of eight. Revenue grew slower for a quarter, then faster, because the product actually addressed the core pain they set out to solve.
A practical tactic: write a one-page “purpose and advantage” memo and treat it as a standard used in prioritization. Revisit quarterly, not daily. If you pivot, pivot the purpose publicly and commit again. That rhythm balances flexibility with consistency so early trade-offs are not random.
Adopt the new philosophy, not the old startup myths
Deming’s new philosophy insisted that quality is a management responsibility. Quality is not inspection, it is design. Many startups cling to the myth that speed justifies rework. They ship a prototype, promise to refactor “after funding,” then burn cycles for years on defects that come from weak system boundaries.
A better expectation: speed comes from fewer loops, not faster loops. Reduce rework by putting basic quality gates where defects are cheapest to catch. For code, that might be automated tests that validate contracts of your public APIs, a continuous integration check that runs in under five minutes, and a deployment checklist that can be executed by any engineer on a Tuesday at 6 p.m. For support, it may be a single shared definition of severity levels and response times, so your customers do not experience lottery ticket treatment.
When a seven-person fintech team implemented contract tests across their payments and ledger services, their weekly incident count dropped from 9 to 3 within six weeks. They didn’t slow down, they stopped stepping on the same rake.
Cease dependence on inspection to achieve quality
Deming railed against final inspection. Startups do the same thing in a new wrapper: last-minute QA heroes before a launch, manual data cleanups before a board meeting, or spreadsheet spot checks before sending invoices. Those create an illusion of control, but hide systemic waste.
Move quality upstream. Bake invariants into the system, not the checklist. For example, if you must not send an email without a required unsubscribe link, do not rely on humans to remember. Encapsulate an “Email” type in your codebase that cannot be constructed without a footer. If you must ensure customer IDs map to one account, enforce that constraint at the database layer with unique keys, not just in application logic. In an operations context, if refunds must not exceed original charges, enforce it in the workflow system and make it impossible to click the wrong thing.
When you feel the urge to catch errors at the end, ask where the system made it possible to create them at the beginning. Then close that door.
End awards based on price tag alone
Startups often pick vendors and components on sticker price. That looks thrifty until you calculate total cost. The cheaper cloud provider with flaky networking burns a week of engineering time every month. The bargain outsourced support saves payroll, then drives churn when responses slip.
A small B2B startup I worked with reduced their monthly infra bill by 40 percent switching to a cheaper object store. Savings looked great. Then their data retrieval latencies became unpredictable during peak hours, and analytics jobs missed SLAs. Engineering paused feature dev to build retries and caching. Two months later, they paid to move back. The cost of switching and trust losses dwarfed the savings.
Evaluate price as a function of reliability, vendor responsiveness, lock-in risk, and your team’s time. Paying a 20 percent premium to reduce variance in performance can unlock capacity to ship on time. Treat vendors like partners and periodically revalidate assumptions, but do not race to the bottom.
Improve constantly and forever the system of production and service
Continuous improvement is not a slogan. It is a loop with a cadence. Startups benefit from short, light feedback cycles because the environment moves fast.
I like weekly operating reviews that surface leading indicators: build times, deployment frequency, median time to restore after incidents, customer support first response time, sales cycle length by segment, activation success rates. Keep it to 30 minutes, focus on trends, and assign a single owner to each metric who can propose one small improvement per week. The goal is not a dashboard museum; it is system learning.
One founder I coached treated every incident as an opportunity to pay down a unit of systemic risk. They limited postmortem action items to two tasks that would have prevented or shortened the incident. Nothing else. That constraint kept improvements surgical and cumulative. After six months, the graph of incidents bent toward zero without a “big refactor” project.
Institute training on the job
Startups underinvest in training because they hire “smart people who figure it out.” The hidden cost is thrash and high-variance customer experiences. Training should be specific, lightweight, and tightly coupled to the work.
Record a 15-minute loom of your deployment process and keep it current. Maintain a runbook for the top five customer issues with exact wording, screenshots, and decision trees. Pair a new engineer with a senior on their first three on-calls. For sales, listen to live calls weekly and annotate why a deal progressed or stalled. For data teams, codify data contracts and have a single doc that explains dimensions and metrics with examples of correct and incorrect use.
A team of nine can build a training library in a week that saves months of back-and-forth later. The trick is to prune. Archive obsolete material fast, and add examples whenever you update a process. Training is not school, it is friction removal.
Institute leadership, not supervision by fear
Deming drew a hard line between leadership and supervision. Early managers often rely on adrenaline and status checks, which works until it fails catastrophically.
Leadership in a startup looks like clarifying outcomes, removing obstacles, and modeling the behavior you want under pressure. During a live-incident call at a health-tech company, the head of engineering started with two sentences: “Our objective is to restore claims processing within 30 minutes. We will not skip logging the timeline.” That made priorities explicit and kept the team from improvising shortcuts that would later confuse auditors.
Good leadership also means establishing boundaries for sustainable speed. Make it okay to say no to weekend deploys without a rollback plan. Reinforce that raising a risk early is a sign of ownership, not weakness. Fear-driven silence is expensive. It produces delayed surprises that cost you customers and morale.
Drive out fear
Fear hides defects, slows learning, and distorts metrics because people tell you what they think you want to hear. Founders sometimes mistake fear for urgency.
Create two or three rituals that invite candor. Hold a weekly “the one thing I’m worried about” round, each person names a concrete risk in a sentence. No debate, just collection. Then pick one to address. Instituting blameless postmortems helps, but only if you actually remove blame. The language matters. Replace “who broke it” with “how did the system make it easy to break.”
Compensation structures can fight fear too. If bonuses only reward shipping, you will ship undisclosed defects. If sales commissions depend solely on signatures, you will get churn. Tie rewards to long-term measures as a fraction: customer retention at 90 days, defect escape rate, or successful onboarding completion. People optimize what you pay for.
Break down barriers between departments
At ten people, titles are loose and collaboration feels automatic. At thirty, handoffs creep in and friction multiplies. Sales promises features without timelines. Support escalates everything. Engineering hides behind “the backlog.”
Cross-functional ownership cuts through this. Define a few journeys that capture the real experience: onboarding a new customer, resolving a P1 incident, shipping a minor feature safely. Assign an accountable owner for the journey, not the department. Build a shared metric for the journey, and review it together. When a team at a dev tools startup made “first success within seven days” their north star across product, docs, sales, and support, docs improved faster than code because it delivered the biggest win.
Physical proximity still matters in distributed teams. Slack channels help, but co-working days or focused Zoom work blocks for cross-team work make a difference. Make your CRM and issue tracker reflect reality and integrate them so frontline feedback shows up next to backlog items. If your tools fragment conversations, people will duplicate or ignore work.
Eliminate slogans, exhortations, and targets for the workforce
Nothing sours a room faster than posters telling people to “Do it right the first time” without giving them the means. Deming argued that most performance problems come from the system, not the worker.
Replace exhortations with changes to the environment. If you tell support to speed up, build better search for the knowledge base and integrate it into the ticketing system. If you ask engineers to reduce bugs, give them time to write tests, add static analysis to the build, and provide fast feedback loops. If sales must improve forecast accuracy, require a deal health checklist at stage changes and coach on how to use it.
A fintech startup once ran a “zero defect sprint.” Engineers worked late, defects dropped that week, then returned to the mean. After migrating to typed APIs and adding pre-commit hooks, defect rates halved and stayed there. People were the same. The system changed.
Eliminate quotas and management by objective without method
Quotas can be useful as planning inputs, but pure volume targets encourage sandbagging and gameable behavior. You get what you measure. Without a method, MBOs become wish lists.
Tie targets to methods and constraints. Instead of “close 12 deals this quarter,” adopt “close 8 to 10 deals from ICP segment A with fewer than 15 percent discount, using the discovery checklist and mutual action plan.” For engineering, swap “ship three features per sprint” for “reduce cycle time from PR open to merge from 3 days to 1.5 days by limiting WIP and improving review handoffs.” Methods force you to confront bottlenecks. Over time, methods become culture.
Watch out for vanity metrics. Users created is not active users retained. Lines of code is not value delivered. PR count is not throughput. Shorten the distance between work and outcome and hold methods accountable.
Remove barriers to pride of workmanship
People want to do good work. Barriers erode pride: flaky tooling, shifting specs, unclear definitions of done, and managers who bypass craft for speed without consent.
At a product analytics company, designers were asked to finish UI tweaks with no research or usability testing. Complaints rose. They proposed a simple addition to the process: a 24-hour research sprint with three customer calls for any new flow, then a 30-minute synthesis share-out. The product manager agreed, and turnaround time increased by a day while rework reduced so much that overall lead time fell. Designers regained pride because the process respected their craft and improved outcomes.
For engineers, pride can mean autonomy to fix papercuts during on-call, a day a month reserved for refactoring hotspots, or a clear path to deprecate old modules. For support, it might be the authority to issue small credits without a manager. Invest here and you get productivity, retention, and better products as a byproduct.
Institute a vigorous program of education and self-improvement
Training builds current skills. Education grows future capacity. Startups stay relevant when they learn faster than rivals. That requires time and money, even when cash is tight.
Set aside a modest budget per person for courses or conferences. Encourage reading groups. If your core domain is privacy, fund a team member to get a relevant certification and have them teach lunch-and-learns. If your tech stack leans on a specific cloud service, sponsor deeper certification for one engineer. If your product touches regulated domains, maintain a cadence for regulatory updates, not just when a customer asks.
One hardware-software startup designated “exploration sprints” quarterly. Two days for anyone to explore a technology adjacent to the roadmap. They discovered a low-cost telemetry approach that halved their device data costs within a year. Small bets on education compound.
Take action to accomplish the transformation
Deming’s last point is a call to leadership. None of the prior points matter unless leaders accept responsibility for the system. At a startup, that means the founders and first-layer managers define what “good” looks like, codify it in light processes, and protect the time to improve the system despite near-term noise.
Transformation does not require a big program. It needs a backbone and a start. Pick three points that map to your current pain. If you are drowning in incidents, focus on moving quality upstream, leadership during incidents, and postmortems that change the system. If sales and engineering are at war, start with breaking down barriers, eliminating slogans, and redefining quotas with methods.
The practical discipline is to keep changes small and continuous. You do not need a transformation office. You need a calendar reminder on the first Monday of each month labeled “improve the system,” and you need to actually do it.
Translating the deming 14 principles into startup habits
The deming 14 principles are robust because they apply at multiple scales. A basement team and a multinational manufacturer both run systems that produce outcomes. The difference is cycle time and resource slack, which means startups must adapt the how while keeping the why.
Consider three common startup scenarios.
First, a pre-launch product with a tiny beta and constant churn in requirements. Deming’s approach would recommend constancy of purpose framed as the job to be done, not a fixed feature set. Quality moves upstream by defining a few sharp constraints: privacy rules cannot be broken, performance under a threshold must be met for interactive flows, and support scripts must exist for any feature a beta user touches. Training is simple and daily, recorded as you go.
Second, a post-seed startup with a growing customer base and a mounting support burden. Here, drive out fear and break down barriers between departments. Create a shared backlog for the top support drivers, with engineering and product owners, and publish progress weekly. Educate your sales team on product fit so that deals do not import avoidable churn. Replace exhortations with capacity: give support a debugging tool and engineers a budget of time each sprint to fix the top issues ranked by revenue at risk.
Third, a Series B company entering a regulated market. Adopt the new philosophy in a formal way. Establish a quality management system light enough to fit your size, with documented processes for change control, incident response, and data handling. Pay for vendors that reduce compliance risk. Bring leadership discipline to audits. Institute ongoing education so your team understands the regulatory landscape, not just checklists.
Metrics that enable, not punish
Deming reminded leaders that measurement should guide improvement, not assign blame. In early-stage companies, a small set of readouts helps focus attention.
Useful engineering signals include deployment frequency, change failure rate, mean time to restore, and lead time for changes. On the product side, activation rate, time to first value, and weekly active use tied to the core action tell you if you solve a durable problem. Support metrics like first response time and backlog age matter when correlated with customer health. For sales, win rate by segment and retention at 90 or 180 days beat top-line bookings. Finance should watch gross margin early so you do not build a business that scales losses.
Pick a few, define them precisely, and automate collection. Avoid metric roulette where numbers change definitions every month. Assign one owner per metric who curates context and proposes improvements. The point is not to stare at numbers, it is to choose what to change next.
Two lightweight practices to start this quarter
- Write a one-page quality charter. State your purpose, three non-negotiable constraints, the two or three metrics you will watch, and how decisions will trade off speed and quality. Review monthly with the whole team. Run a monthly system improvement hour. Bring one incident or recurring problem, map the workflow for ten minutes, identify where the system made the error easy, and commit to one change that removes the possibility or reduces the blast radius. Track these changes on a single page.
The edge cases and trade-offs that matter
Deming’s approach does not eliminate hard calls. It gives you a lens to make them.
Speed versus quality is the perennial tension. The answer is not always “slow down for quality.” It is “invest in the smallest system change that keeps speed sustainable.” Sometimes you ship a hack behind a feature flag, paired with a scheduled fix in the next sprint and an alert to catch failure. Other times you hold the release because a database migration cannot be rolled back safely. You will be wrong sometimes. The important part is that you are wrong for good reasons, shared openly, and you learn.
Another trade-off lives in vendor choices. Lock-in is not automatically bad. The six sigma cost savings calculus is whether the leverage you gain today outstrips the flexibility you might need tomorrow, discounted by the probability and cost of switching. Track these bets explicitly. A short memo with your assumptions beats relying on memory when conditions change.
Culture scales through artifacts, not charisma. Founders can model behavior in a small room, but that fades as you hire. Write down how you run incidents, how you define a good PR, how you hand off from sales to onboarding. Keep those documents short and living. When you deviate, explain why. Otherwise, the exception becomes the norm, and your system fragments.
When to deviate from Deming, and how
A few of Deming’s principles can be overapplied in startups.
Too much constancy of purpose can mask the need to pivot. I sat with a founder who declared ironclad purpose, then ignored consistent evidence that their chosen persona did not buy. Purpose should anchor a problem, not a market segment. Update it when data shows that your solution fits adjacent customers better.
Eliminating quotas entirely in sales can create aimlessness. Early reps often benefit from a floor and ceiling, provided you tie compensation to retention and fit. The key is to layer qualitative gates and methods, not to remove targets entirely.
Education budgets can become perk wars. Keep them targeted to business needs and shared learning. Ask anyone who attends external training to teach back. You get compounding value and avoid drift into unrelated topics that do not help the company or the person’s craft.
Finally, not every improvement is worth doing now. A safety culture can become procedural bloat if you add a ritual for each mistake. Resist that. Periodically prune. If a checklist item has not caught a defect in six months, remove it and rely on upstream quality. Use data to decide.
The quiet superpower: making quality the path of least resistance
Deming taught that people do their best within the system they inhabit. The startup equivalent is to make it easier to do the right thing than the easy thing. Give engineers a fast local environment so tests run in seconds and get written. Put customer feedback next to product planning so you do not need a meeting to learn. Automate the boring releases so the scary deploy never tempts someone to “just push.”
Quality then stops being a hero act and becomes the default. That shift frees creative energy for what actually differentiates you: solving a real problem well and building trust with customers who stick around.
The deming 14 principles are not a museum piece. They are a set of habits that let small teams punch above their weight and large teams regain their footing. Start early. Choose two or three points where your system hurts most. Change the system, not just the schedule. In a year, you will look back and wonder where the chaos went.