How to Sell to Manufacturers: The Complete Playbook

Introduction

Most SaaS sales playbooks were written for companies selling to other tech companies. The buyer is digital-native, approves software on a card, and moves fast. The playbook works because the culture on both sides of the table values speed.

Manufacturing is different in ways that are not immediately obvious. The gap between "I've closed enterprise SaaS deals" and "I know how to sell into a plant" is wide enough to end careers and stall companies.

This playbook is the one we wish existed when we started working with manufacturing SaaS companies. It covers every stage of the sales motion: how to define your ICP with precision, how to read a manufacturing org chart, how to run discovery on a plant floor, how to design pilots that actually get adopted, and how to turn a single site win into an enterprise standard.

It is not a theory document. Every section reflects what we have learned from working the phones, studying win/loss patterns, and building outbound campaigns across manufacturing sub-verticals. Where we have a strong point of view, we say so directly.

Throughout this guide, we reference concepts covered in more depth in our cluster articles: manufacturing buyer personas, buying committee dynamics, downtime cost messaging, and ERP migration timing windows.

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Chapter 0: What Makes Manufacturing Sales Different

Before tactics, you need to understand the environment. Manufacturing is not a slower version of SaaS sales. It is a fundamentally different selling environment with different risk profiles, different power structures, and different cultural norms.

The Buyer Is Risk-Averse for Good Reason

A plant manager who approves a software purchase that disrupts production for a week has a very bad year. A CTO at a SaaS company who approves a tool that underperforms cancels it next quarter. The asymmetry of consequences shapes everything about how manufacturing buyers evaluate vendors.

Downtime is not an abstraction in manufacturing. It is a number, typically $50,000 to $260,000 per hour for mid-size discrete manufacturers, depending on the line and the product. Safety incidents generate OSHA investigations, worker compensation claims, and in severe cases, criminal liability. Quality failures at regulated manufacturers, including food, pharma, and aerospace, trigger recalls, FDA actions, and customer audits that can threaten the entire business.

When a manufacturing buyer moves slowly, they are not being difficult. They are being proportionate to the stakes.

OT vs IT: Plants Are Not SaaS Offices

Most SaaS companies think about IT security and infrastructure. Manufacturing has two entirely separate technology domains: Information Technology (IT) and Operational Technology (OT).

IT covers the systems you expect: corporate network, ERP, email, cloud infrastructure. OT covers the systems that run the plant: programmable logic controllers (PLCs), SCADA systems, manufacturing execution systems (MES), historians, sensors, and embedded equipment that may be running software from 2003 and cannot be patched without requalifying a production process.

The OT layer is where products live and die. A cloud-native SaaS product that cannot operate in a network-segmented environment, cannot handle intermittent connectivity, or requires an agent installed on a PLC is not a viable product in most plant environments, regardless of how good the UX is. Understand this layer early, or discover it the hard way during implementation.

Corporate vs. Plant-Level Power Dynamics

Manufacturing organizations have two power centers that are often in tension: corporate and the plant.

Corporate sets standards, approves budgets, and manages vendor relationships. The plant runs production and carries the operational risk. A VP of Operations at corporate can mandate a platform. The plant manager can make the adoption so difficult that the mandate fails in practice.

The most successful manufacturing SaaS deployments win at both levels: corporate for the budget and the mandate, plant for the adoption and the expansion. Companies that win only at corporate get shelfware. Companies that win only at plant get stuck in pilot purgatory.

Deal Shape: Land → Expand

Almost no manufacturing SaaS deal starts enterprise-wide. The typical deal shape is a site license or a single-line deployment, followed by expansion to additional lines, shifts, facilities, or workflows once the value is proven.

This has implications for how you price, how you sell, and how you define success in year one. A $40,000 site license that expands to a $400,000 enterprise standard in year three is a fundamentally different deal than a $400,000 enterprise contract signed on day one, and it requires a different sales motion to get there.

Design your sales process around the land, and your customer success process around the expand.

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Chapter 1: Define Your ICP (Stop Selling to "Manufacturing")

"We sell to manufacturers" is not an ICP. It is a category. The companies that grow fastest in manufacturing SaaS are the ones that pick a segment narrow enough to develop real expertise, then expand deliberately from that beachhead.

Segmentation That Matters

Discrete vs. Process Manufacturing

Discrete manufacturing produces distinct, countable units: metal parts, electronics, vehicles, medical devices. Process manufacturing transforms raw materials into outputs measured by volume, weight, or batch: chemicals, food and beverage, pharmaceuticals, plastics.

The distinction matters for product fit. Discrete manufacturers care about unit-level traceability, cycle time, and machine OEE. Process manufacturers care about batch records, yield, raw material variance, and recipe management. The terminology, the metrics, and the buying personas are different enough that messaging built for one will underperform in the other.

Regulated vs. Non-Regulated

Regulated sub-verticals, such as food and beverage (FSMA), pharmaceuticals (FDA 21 CFR Part 11), aerospace (AS9100, ITAR), and medical devices (ISO 13485), buy software differently than non-regulated manufacturers. Compliance creates forced purchase triggers with defined timelines. The procurement process is more formal. Validation requirements (IQ/OQ/PQ in pharma) add 3–6 months to implementation. The ACV is higher and the retention is stickier.

Non-regulated manufacturers move faster and care more about ROI than documentation. The sales cycle is shorter but the switching cost is lower.

Single-Site vs. Multi-Site

A single-site manufacturer with 200 employees is a $20,000–$60,000 ACV deal with a 60–90 day sales cycle and a plant manager with significant purchasing authority. A 15-site enterprise manufacturer is a $300,000+ deal with a 9–18 month sales cycle, a procurement process, and a VP of Operations who has to justify the investment to a CFO.

Know which profile you are optimized to close before you invest in outbound.

Automation Maturity

Where a manufacturer sits on the technology maturity curve determines what they are ready to buy and what they can actually implement.

Paper and clipboard: No digital systems. Long implementation time, high change management burden, highest upside if you can execute.

Excel and email: Partially digitized, but no integrated systems. Fastest-growing segment for point solutions.

CMMS / QMS / ERP island: Has one or more systems but they don't talk to each other. Strong wedge opportunity for integration plays.

MES / SCADA / historian stack: Relatively sophisticated. Shorter implementation time, more complex integration requirements, more demanding IT evaluation.

Red-Flag ICPs

Not every manufacturer is a good prospect. These profiles kill pipeline without generating revenue:

• No named owner of the problem you solve (nobody is accountable for the pain)
• No data available to baseline current performance (no metrics, no ROI narrative)
• No internal champion with even minimal organizational standing
• Perpetual firefighting culture, where every conversation surfaces a new crisis that postpones the decision
• IT organization that prohibits cloud software with no exception process

Identify these early. The qualification time you save is real.

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ICP Scorecard

Score each prospect 1–3 on each dimension. Pursue scores of 18+. Qualify out below 12.

"Why Us / Why Now" Triggers

• New facility opened or announced
• Recent compliance audit or citation
• Leadership change (new VP Ops, new plant manager)
• ERP migration underway
• Unplanned downtime incident (public or referenced)
• Active hiring for roles your product replaces or supports
• Recent funding or acquisition

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Chapter 2: The Org Chart You're Actually Selling Into

The org chart on a manufacturer's website tells you almost nothing about how decisions get made. This chapter maps the real buying committee and explains what each persona actually cares about.

Core Personas

Plant Manager / Operations Director

The day-to-day authority on the floor. They care about throughput, unplanned downtime, and labor efficiency. Their success metric is OEE (Overall Equipment Effectiveness) and whether their shift supervisors can hit production targets. They are your most natural bottom-up champion, because they feel the pain directly, but they often lack the budget authority and organizational standing to drive a purchase through procurement alone.

What gets their attention: specific operational benchmarks, peer references from similar plants, implementation timelines that don't disrupt production windows. What kills the conversation: vague productivity claims, demos that lead with dashboards, and reps who don't know what a changeover is.

Maintenance / Reliability Manager

Owns MTTR (mean time to repair), planned vs. unplanned maintenance ratios, and spare parts inventory. In CMMS and predictive maintenance deals, this is often your primary champion. They are technical, skeptical of vendor claims, and highly sensitive to implementation burden. They cannot take their team offline to learn new software during a production run.

What gets their attention: reduction in unplanned work orders, MTTR improvement data from comparable plants, a realistic onboarding plan that accommodates shift patterns. What loses them: overselling AI capabilities, ignoring the reality of aging equipment, and demos that assume clean data when their data is a mess.

Quality Manager

Owns first-pass yield, scrap rates, CAPA (corrective and preventive action) processes, and customer complaint response. In regulated environments, they also own audit readiness. They are often the most process-oriented person in the buying committee and the most likely to have a compliance deadline driving urgency.

What gets their attention: traceability capabilities, audit trail completeness, integration with existing QMS workflows. What loses them: any implication that your product replaces their existing quality process wholesale.

Engineering (Process / Manufacturing)

Evaluates integration feasibility, process fit, and the technical risk of deploying software near production systems. They are neither buyers nor blockers by default; they are assessors. Bring them in early for complex integrations. Give them clean technical documentation. Do not make them chase you for architecture diagrams.

EHS Manager

Owns safety incident rates, OSHA compliance, and environmental reporting. Often an underutilized entry point for the right product. EHS mandates create procurement urgency that is calendar-driven and non-negotiable.

IT / Security

Almost never your champion. Their job is to evaluate and mitigate risk, not to generate enthusiasm. Treat them as a risk mitigator: get them neutral early, answer their questions completely, and do not give them a reason to raise a flag. Security questionnaire delays kill more manufacturing deals than pricing objections.

Procurement / Finance

Controls the vendor onboarding process and payment terms. They will require insurance certificates, signed MSAs, Net-60 to Net-90 terms, and documentation you did not know you needed. Get them involved earlier than feels necessary. The deals that stall in the red zone almost always stall on procurement process, not on value or fit.

Owner / CEO (sub-$150M manufacturers)

Present in mid-market manufacturers more often than most SaaS reps expect. They care about competitive risk, vendor reliability, and long-term ROI. They respond to peer references and to evidence that you understand their specific industry. A 10-minute call with your CEO or a named reference from a comparable company carries more weight with an owner than any proposal document.

How Decisions Really Get Made

Manufacturing decisions are rarely made by a single person. The typical pattern:

1. The operational pain owner (plant manager, maintenance lead, quality manager) identifies a need and begins informal evaluation
2. IT and engineering assess feasibility
3. Procurement qualifies the vendor and manages the commercial process
4. Finance approves budget above a threshold
5. The ultimate decision is either explicitly or implicitly ratified by the plant manager and, above a certain ACV, by a VP or owner

The blockers are different from the buyers. IT blocks on security grounds. Procurement blocks on process grounds. Finance blocks on ROI clarity. The plant manager blocks when implementation risk feels too high. Understanding which stakeholder can kill a deal, versus which one can advance it, is the core skill of manufacturing sales navigation.

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Stakeholder Map Template

For each active deal, complete this map before every pipeline review.

Sentiment key: Champion (actively selling internally) / Supportive / Neutral / Skeptical / Blocker

Multithreading checklist:

• Economic buyer identified and contacted
• Operational champion identified and active
• IT/Security contacted and questionnaire delivered
• Procurement contact identified and vendor onboarding initiated
• At least one reference call offered and scheduled

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Chapter 3: Manufacturing Pains That Win Deals

Not all pain is created equal. Manufacturing buyers fund solutions to a specific set of outcome categories. Understanding which category your product addresses, and how to quantify it, is the foundation of every effective sales conversation.

The Six Outcome Categories

Uptime and Throughput

The broadest and most universal pain in manufacturing. OEE (Overall Equipment Effectiveness) is the composite metric: availability × performance × quality. A 1% OEE improvement at a mid-size plant typically generates $200,000–$500,000 in recovered production value annually. Unplanned downtime is the highest-urgency sub-category; a single incident often creates a 90-day window of elevated purchase intent for prevention tools.

Winning language: "reduce unplanned downtime events," "improve OEE from X% to Y%," "recover N hours of production per month."

Quality and Scrap

First-pass yield (FPY), rework rates, scrap costs, and customer complaint frequency. In discrete manufacturing, scrap costs often represent 2–5% of revenue. A 10% reduction in scrap at a $50M manufacturer is a $100,000–$250,000 annual impact. Customer complaint reduction matters especially in automotive and aerospace, where repeat quality failures trigger supplier audits and can result in disqualification.

Winning language: "reduce scrap cost by X%," "improve FPY from X% to Y%," "reduce customer escapes."

Compliance and Traceability

Audit readiness, documentation completeness, recall capability, and regulatory submission support. In regulated industries, the business case writes itself: the cost of a failed FDA audit, a recall, or a customer disqualification dwarfs the cost of the software. Position around risk reduction, not feature capability.

Winning language: "audit-ready in 24 hours," "complete batch traceability from raw material to finished goods," "reduce documentation burden by X hours per week."

Labor Productivity

Standard work adherence, training time, changeover efficiency, and supervisor span of control. As skilled trades labor becomes harder to find and more expensive to retain, manufacturers are increasingly willing to pay for software that preserves institutional knowledge and reduces training time for new hires.

Winning language: "reduce changeover time by X minutes," "cut new hire training time from X weeks to Y weeks," "standardize operator procedures across shifts."

Inventory and Scheduling Chaos

WIP accumulation, material shortages, expediting costs, and schedule attainment. For manufacturers with complex BOMs or multi-site supply chains, scheduling chaos is a constant and quantifiable cost. MRP accuracy rates below 85% are common and represent significant working capital inefficiency.

Winning language: "reduce expediting costs by $X monthly," "improve schedule attainment from X% to Y%," "reduce WIP inventory by X%."

Energy and Waste

Utility consumption, yield loss on raw materials, and sustainability reporting requirements. Growing in importance as OEM customers impose scope 3 emissions reporting requirements on their supplier base. Often an easier CFO conversation than operational metrics because energy costs are already a line item.

Winning language: "reduce energy cost per unit by X%," "improve material yield from X% to Y%," "automate utility reporting for ESG compliance."

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Pain → Metric → Dollar Impact Library

Use this to build your ROI narrative for each deal.

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Chapter 4: Positioning and Messaging That Resonates on the Plant Floor

The fastest way to lose a manufacturing buyer is to sound like a software vendor. The fastest way to earn their attention is to sound like someone who has spent time on a plant floor.

Translate Features Into Operational Outcomes

Feature: "Real-time production monitoring dashboard" Outcome: "Your shift supervisors see downtime events within 90 seconds, before they cascade into line stoppages."

Feature: "AI-powered anomaly detection" Outcome: "Equipment failures are flagged 48–72 hours before they cause unplanned downtime."

Feature: "Mobile-first interface" Outcome: "Operators log data from the floor without leaving the line. No paper, no transcription errors, no walking to a terminal."

The rule: if your messaging could describe a product in any other industry, it is too generic. Every claim should be evaluable by a plant manager who has never heard of your company.

Speak in Their Nouns

Manufacturing has its own vocabulary. Using it correctly signals expertise. Using it incorrectly signals that you are not worth their time.

Essential vocabulary by domain:

Production: OEE, cycle time, takt time, throughput, shift, line, cell, changeover, downtime, WIP, yield, FPY, scrap, rework

Maintenance: MTTR (mean time to repair), MTBF (mean between failures), PM (preventive maintenance), work order, spare parts, CMMS, reliability, predictive maintenance, vibration analysis

Quality: CAPA (corrective and preventive action), NCR (non-conformance report), SPC (statistical process control), first-pass yield, defect rate, traceability, batch record, audit trail

Systems: ERP, MES (manufacturing execution system), CMMS, QMS, SCADA, historian, PLC, HMI, DCS

Regulatory: FSMA (food safety), ISO 9001, AS9100, ISO 13485, 21 CFR Part 11, IATF 16949

The Four Messaging Pillars

Risk reduction and low disruption. Every manufacturing buyer is evaluating the risk of a bad implementation alongside the value of a good one. Lead with how you minimize disruption: phased rollouts, no production downtime required for deployment, rollback options, implementation team experience in their sub-vertical.

Time-to-value measured in weeks, not quarters. Manufacturing buyers have been burned by 18-month implementations. A credible 30–60 day path to first value is a competitive differentiator. Be specific: "Operators are logging data on day 3. Your first shift report is automated by day 14. Your maintenance backlog is visible by day 30."

Works with existing systems. The single most common objection in manufacturing SaaS is integration concern. Address it in your messaging before they raise it. Name the ERP systems you integrate with (SAP, Oracle, Epicor, Infor, Plex). Name the historians (OSIsoft PI, Ignition). Name the CMMS and MES systems you have live integrations with. Specificity here is disproportionately powerful.

Operators will actually use this. Adoption failure is the nightmare scenario. Every manufacturing buyer has a shelfware story. Demonstrate adoption by design: offline capability, minimal clicks per transaction, operator-facing UI built for gloves and tablet screens, multilingual support if relevant.

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Persona-Specific One-Liners

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Chapter 5: Pipeline Generation for Manufacturing

Manufacturing buyers do not come inbound through Google the way SaaS buyers do. The channels that fill a manufacturing SaaS pipeline are different, the timelines are longer, and the quality of relationships matters more than volume.

Channels That Work

Industry Events and Associations

IMTS, ProFood Tech, PackExpo, Automate, MD&M, and the dozens of sub-vertical trade shows are where manufacturing buyers go to evaluate vendors, learn from peers, and make purchasing decisions. Unlike SaaS conferences, manufacturing trade shows are genuine procurement environments. Buyers arrive with budgets and shortlists.

Association membership (SME, APICS/ASCM, ASQ, PMMI, AME) gives access to plant managers and operations leaders in a relationship-first context that cold outreach cannot replicate. If you are serious about a sub-vertical, join the relevant association and contribute before you sell.

Systems Integrators, VARs, and OEM Partnerships

The fastest path into a plant is often through a trusted integrator. Manufacturing buyers have existing relationships with their controls engineers, ERP implementation partners, and automation vendors. A warm introduction from a Rockwell Automation partner or an SAP implementation firm carries more credibility than 50 cold emails.

Build a partner program before you need it. Map the integrators in your sub-vertical, offer them referral economics, and co-develop case studies that make them look good for recommending you.

Targeted Account Lists by Plant Footprint

Not all account-based outreach is equal. A list built on plant-level signals (facility expansion, new production line, recent equipment investment, job postings for roles your product supports) dramatically outperforms a list built on firmographic data alone.

Build account lists at the plant level, not the company level. A 20-site manufacturer with 15 facilities in your sweet spot and 5 that are not is 15 outbound targets, not one.

Trigger-Based Outbound

The highest-converting outbound campaigns are timed to events that signal purchase intent. For manufacturing SaaS, the most reliable triggers are:

• New facility announced or opened (greenfield plants need full software stacks)
• Unplanned downtime incident reported (public or referenced in earnings calls, news)
• Compliance citation or audit failure (FDA warning letter, OSHA violation, customer audit notice)
• Leadership change (new VP Ops, new plant manager, new VP Quality, because new leaders evaluate existing toolsets)
• ERP migration announced (creates a halo evaluation of all adjacent software)
• Active hiring for roles your product automates or supports

A cold email sent within 72 hours of a qualifying trigger event converts at 4–6x the rate of a batch send to the same account without a trigger.

Customer Referrals

In manufacturing, referrals travel through networks that are more concentrated and more trusted than in most B2B markets. Plant managers talk to other plant managers at trade shows, in industry associations, and through supplier networks. A reference from a peer at a comparable plant is the highest-value asset in your pipeline.

Build referral into your customer success process. Every QBR should include the question: "Who else in your network is dealing with the same challenge?" The answer is almost always someone.

Why Generic LinkedIn Playbooks Underperform

Standard LinkedIn outbound (connect, message, follow up, repeat) is optimized for buyers who spend their day in front of a computer and treat LinkedIn as a professional channel. Many manufacturing decision-makers are not on LinkedIn regularly. The plant manager who would be an ideal champion is often on the floor, not on a screen.

This does not mean LinkedIn is useless. It means the approach needs to be different: thought leadership content that surfaces through search and recommendation, not high-volume connection requests. A plant manager who finds your article on reducing changeover time through their feed is more likely to engage than one who receives your connection request cold.

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Trigger Library and Outbound Sequences

Top triggers by urgency

3-touch trigger-based sequence

Email 1 (Day 0): Reference the trigger directly. One insight relevant to the operational implication. No ask, or a very small one.

Subject: [Company]'s new [City] facility, and what that means for maintenance ops

[First name], saw the announcement about your [City] expansion. Greenfield facilities are a real opportunity to set up a maintenance program the right way before bad habits form.

We've worked with three [sub-vertical] manufacturers on exactly this. The ones who standardized their CMMS configuration during commissioning rather than after go-live saved an average of 14 months getting to their target OEE.

Happy to share what those configurations looked like if it would be useful.

Best, Alex

Email 2 (Day 5): Add evidence. Reference a comparable company or a specific metric.

Email 3 (Day 12): Make a direct ask for a 15-minute conversation. Keep it specific to one outcome.

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Chapter 6: Qualification for Manufacturing Deals

Standard BANT qualification (Budget, Authority, Need, Timeline) is underspecified for manufacturing sales. It misses the structural factors that cause manufacturing deals to stall or die. The framework below adapts MEDDICC to manufacturing realities.

Manufacturing MEDDICC

Metrics: Which KPI Is Moving?

Do not move forward without a baseline metric. "We have a lot of downtime" is not qualified. "We averaged 11.3 unplanned downtime events per month last quarter, costing approximately $180,000 in lost production" is qualified. The metric creates the ROI narrative, gives the champion something to take to finance, and gives you a success criterion for the pilot.

If the prospect cannot give you a baseline number, work with them to establish one. A quick back-of-envelope calculation during discovery is more valuable than a vague pain statement.

Economic Buyer: Corporate or Plant Budget?

Manufacturing deals can be funded at the plant level (OPEX, maintenance budget, quality budget) or at the corporate level (capital budget, IT budget, strategic initiative). The funding source determines who the real economic buyer is, what approval process applies, and what your ROI narrative needs to say.

Plant-funded deals are often faster but smaller. Corporate-funded deals are larger but require a business case that travels up the org chart. Know which you are in early. The sales motion is different.

Decision Criteria: What Does "Yes" Look Like?

Manufacturing buyers evaluate vendors on criteria that are often unstated. Get them stated early:

• Security posture and compliance certifications required
• Integration requirements (which systems must it connect to, on what timeline)
• Uptime and SLA requirements
• Support model (24/7? On-site? Response time?)
• Implementation timeline and resource requirements from their side
• Vendor financial stability (they do not want to adopt a product from a company that disappears)

Paper Process: Vendor Onboarding Reality

Every manufacturer has a vendor onboarding process. Most SaaS companies are not prepared for it. Identify it early: How long does vendor qualification take? What documentation is required? Who owns it in procurement? What insurance minimums apply? What legal review process does the MSA go through?

The paper process is not a closing formality. It is a 30–90 day parallel track that needs to start the moment a deal looks real.

Deal Kill-Switches

These are the factors that kill manufacturing deals after they are otherwise qualified. Identify them in discovery:

• Data access: Is the data your product needs accessible, clean, and owned by someone who can give you permission to use it?
• Integration owner: Is there a named person on their IT or engineering team who will own the integration? Without one, integration projects stall indefinitely.
• Plant bandwidth: Is the plant in a position to support an implementation, or is it in crisis mode? (A plant running at 95% capacity with a key system down is not ready to implement new software, no matter what the VP Ops says.)
• Internal politics: Is there a competing initiative, a vendor relationship being protected, or an internal build-vs-buy debate that will surface at the wrong time?

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Qualification Checklist and Go/No-Go Rubric

Go/No-Go rule: If three or more factors are Red, pause active selling and address the blockers before advancing.

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Chapter 7: Discovery: Running a Plant-Smart Process

Discovery in manufacturing is different from discovery in SaaS. The best discovery conversations happen on the plant floor, not in a conference room. The best discovery questions surface operational reality, not aspirational pain.

Discovery Stages

Stage 1: Business Context

Before you go deep on operational details, establish the strategic context. Why is this being considered now? What happened, changed, or became urgent that put this on the agenda? The answer tells you whether you are dealing with a trigger event (high urgency, shorter cycle) or a general evaluation (lower urgency, longer cycle), and that shapes how you manage the process.

Questions: "What made this a priority in the next six months versus six months ago?" / "Is there a specific event or deadline driving the timeline?" / "Who put this on the agenda: was it a plant initiative or a corporate directive?"

Stage 2: Process Walk-Through

Ask to walk the process. Not a conference room description of the process, but the actual sequence of events on the floor. Where does information get created? Where does it get lost? Where does variance occur? Where do people work around the system because the system does not work for them?

The process walk-through is where champions are made. Most vendors never ask for it. The ones who do immediately differentiate themselves as operators, not pitch artists.

Stage 3: Systems Map

Understand the existing technology landscape before you demo anything. What ERP are they on? What version? Is there an MES? A historian? A CMMS? What does the OT layer look like? Where does your product sit in that stack, and what does it need to read from or write to?

The systems map also reveals integration landmines. An on-premise ERP from 2009 with no API layer is a different integration problem than a cloud ERP with a published REST API. Find out now.

Stage 4: Constraints

Manufacturing deployments fail for reasons that have nothing to do with software quality. Surface the constraints early:

• IT security policies (What is and is not permitted on the plant network? Is cloud access restricted?)
• Union considerations (Are there labor agreements that affect how data is collected or how roles change?)
• Shift patterns (When are maintenance windows? When can training happen without disrupting production?)
• Downtime windows (Is there a planned shutdown coming? Or a period where no changes are permitted?)

Stage 5: Quantify the Baseline

Leave every discovery conversation with a number. Work backward from their operational reality to a dollar figure. Do it with them, not for them. The calculation is more credible and more useful internally if they built it.

"You said you average 8 unplanned downtime events per month. What is your average downtime duration per event? And what is your production value per hour on that line?" Do the math together. Write down the number. Reference it in every subsequent conversation.

Best Discovery Questions by Persona

Plant Manager: "Walk me through the last significant downtime event: what happened, how long it took to identify, and how long it took to resolve?" / "If your shift supervisor could see one thing they cannot see today, what would it be?"

Maintenance Lead: "What percentage of your maintenance work is reactive versus planned right now?" / "When your team gets a work order, what information do they have before they arrive at the asset?"

Quality Manager: "How long does it take to pull a complete batch record today?" / "What does your CAPA process look like from the time a non-conformance is identified to verified close?"

IT Manager: "What does your network architecture look like between corporate and the plant floor?" / "What would the security review process look like for a new SaaS vendor?"

How to Handle "We're Too Busy"

"We're too busy" is the most common brush-off in manufacturing sales, and it is also the most useful data point you will receive.

A plant that is too busy is a plant under pressure. Pressure is pain. Pain is urgency. The correct response is not to apologize and reschedule. It is: "I hear that. What is driving the crunch right now?" The answer almost always leads directly to the problem your product solves.

"Too busy" from a plant manager is not a no. It is an invitation to diagnose.

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Discovery Script Starter and Plant Tour Checklist

Opening frame: "Before I tell you anything about what we do, I want to understand what's actually happening on your floor. Would it be useful to walk through the [maintenance / quality / production] process as it works today, so I can tell you honestly whether we can help?"

Plant tour checklist:

• Note where data is currently captured (paper, whiteboard, terminal, tablet)
• Identify workflow breakpoints (where does work stop, wait, or get escalated?)
• Observe operator behavior at workstations (what do they actually do vs. what the process says they do?)
• Ask about the last quality or downtime incident: where it showed up first and how it was communicated
• Identify integration touch points (where does information flow to/from ERP, MES, CMMS?)
• Note shift patterns, break times, and changeover frequency

Systems map template:

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Chapter 8: Demo Strategy: Stop Doing Generic SaaS Demos

The standard SaaS demo (45 minutes of features, a dashboard tour, and a Q&A) does not work in manufacturing. It signals that you are a software company presenting software, not a partner who understands what it is like to run a plant.

The Day-in-the-Life Demo Structure

Structure every demo around a specific person's day, not around your product's features. Walk through what that person experiences now (the friction, the manual steps, the information gaps) and show exactly where and how your product changes their day.

The operator: Start here. If your product touches the floor, show what an operator interaction looks like. Operators are the adoption risk. If the operator demo is clean, intuitive, and requires minimal behavior change, every other stakeholder relaxes.

The supervisor: Show how the supervisor sees what is happening on their line without walking the floor or waiting for a report. Focus on exception visibility: what does it look like when something is wrong, and how fast does the supervisor know about it?

The manager: Show aggregate performance visibility, trend data, and the information they need to make decisions and report upward. This is where dashboards belong, after you have established that the underlying data is being captured correctly at the operator level.

The executive: Keep this short. Show one number that matters to them (OEE trend, maintenance cost per unit, or scrap rate over time) and explain the causal chain from operator behavior to that number.

What to Show

Workflow fit before dashboards. Show how work gets done before you show how work gets measured. Dashboards with no underlying workflow are aspirational. Workflow changes that generate data are operational.

Exception handling. What happens when something goes wrong? A system that works flawlessly in the demo and fails gracefully in production is more credible than one that only shows the happy path. Show what an unplanned downtime event looks like from detection to resolution in your system.

The integration story. Where does data come from? Where does it go? Show the ERP write-back, the historian pull, the CMMS work order creation. Integration is the primary risk in manufacturing implementations. Demonstrate that you have solved it before they ask.

Deployment reality. Address cloud vs. on-prem, edge computing requirements, and offline capability before they raise it. If you require internet connectivity on the plant floor, say so and explain your offline fallback. Manufacturing buyers want to know that your product works in their environment, not in a demo environment.

Demo Anti-Patterns That Kill Trust

• Leading with the executive dashboard before showing operator workflow
• Using demo data that looks nothing like their operation (clean, complete, organized)
• Claiming "AI-powered" capabilities without showing the specific mechanism
• Ignoring integration questions until after the demo
• Showing features they explicitly said they do not need
• Asking "does that make sense?" after every screen instead of asking "does that match how your team actually works?"

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Chapter 9: Pilot and POC Playbook

Every manufacturing buyer wants a pilot. Most pilots fail, not because the product does not work, but because the pilot was not designed to succeed.

When to Do a Pilot (and When Not To)

Do a pilot when:

• The product requires behavioral change on the floor and adoption proof is the primary objection
• IT has approved the architecture but wants a bounded deployment before enterprise rollout
• The economic buyer is supportive but needs internal proof to justify corporate budget

Do not do a pilot when:

• There is no named success criteria (pilots without criteria run indefinitely)
• There is no integration owner named on their side (the pilot will stall on data access)
• The champion does not have enough organizational standing to act on a successful result
• The pilot is a delay tactic by a buyer who is not actually committed to buying

Pilot Design

Scope: One line, one cell, one plant, one workflow. Expansion scope mid-pilot almost always results in missed timelines and inconclusive results. Define the boundary and hold it.

Success criteria tied to KPIs and adoption: "Successful" cannot mean "we used it." It must mean: "Unplanned work orders on Line 3 decreased by X% over 60 days" and "80% of planned maintenance tasks logged by operators within the shift they occurred." Quantitative criteria prevent the pilot from being declared unsuccessful for vague reasons.

Data access plan: Before the pilot starts, confirm what data is accessible, who owns the permission to use it, and how it will be connected to your system. Every day spent waiting for data access during a pilot is a day of credibility loss.

Timeline aligned to production cycles: A 30-day pilot that falls across a planned shutdown is a 15-day pilot. A pilot that starts during the plant's busiest month of the year will have low adoption not because the product fails but because nobody has time. Align the pilot timeline to a period of normal operations.

Commercial strategy: Paid pilots signal commitment from both sides and prevent the pilot from being treated as a free evaluation with no consequences. If you offer a free pilot, credit the cost against the first year contract. If the pilot fails on mutually agreed success criteria, the credit is forfeited. Not because you want the revenue, but because the consequence structure keeps both sides honest about the success criteria.

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Pilot SOW Template (Key Elements)

Pilot success scorecard:

• KPI 1: Target achieved / Partial / Not achieved
• KPI 2: Target achieved / Partial / Not achieved
• Adoption threshold met: Yes / No
• Integration stable: Yes / No
• Customer sponsor sign-off: Yes / No

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Chapter 10: Security, IT, and Architecture

IT and security reviews kill more manufacturing deals than pricing objections. Most SaaS companies treat security as a checklist item. In manufacturing, it is a gate, and the companies that prepare for it in advance close faster.

Common Requirements

Certifications: SOC 2 Type II is the minimum bar for most enterprise manufacturers. ISO 27001 is required in some regulated sub-verticals. Have your current certification status, audit date, and remediation timeline (if relevant) documented and ready to share without being asked.

Access controls: SSO via SAML 2.0 is expected by most IT organizations. RBAC (role-based access control) is required to limit data access to appropriate roles. Audit logs (who accessed what, and when) are non-negotiable in regulated environments.

Data handling: Where is data stored? What region? What encryption standard (at rest and in transit)? What is the data retention policy? Who can access customer data internally, and under what conditions?

OT Considerations

Network segmentation: Most manufacturing IT organizations maintain strict separation between the corporate network (IT) and the plant network (OT). A product that requires an agent on the OT network, or that requires the OT network to reach out to the internet, will face significant resistance or outright rejection.

Restricted or offline environments: Some plants, including defense contractors, pharmaceutical cleanrooms, and certain chemical facilities, have no internet access on the plant floor by policy. If your product requires continuous cloud connectivity to function, this is a hard blocker. If you have an edge or hybrid deployment option, lead with it for these environments.

No patches on OT: Control systems in manufacturing often run software that cannot be patched without requalifying a production process. Do not assume that IT's patching process applies to OT. Ask specifically about the OT environment during discovery and design your integration approach accordingly.

Running a Clean Security Review

The goal is to give IT everything they need to say yes, without creating a single reason to say no.

• Deliver your security packet proactively, before they ask. Include: SOC 2 report (or summary), penetration test results (with remediation status), data flow diagram, network architecture diagram, RBAC documentation, data retention and deletion policy.
• Offer a dedicated IT call with your security team within 5 business days of the formal evaluation starting.
• Respond to security questionnaires completely and on time. Incomplete answers extend reviews indefinitely.
• If you have a gap (no SOC 2 yet, no on-prem option), say so clearly and provide your roadmap. Transparency accelerates IT reviews. Discovered gaps during an audit cause them to restart.

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Chapter 11: Procurement and Legal

Every manufacturing deal dies a little death in procurement. The companies that survive it intact are the ones that start the process 60 days before they need it to finish.

Vendor Onboarding Reality

A typical vendor onboarding process at a mid-size manufacturer requires:

• W-9 and banking information
• Certificate of insurance (general liability, cyber liability, E&O; minimums vary, often $1M–$5M per occurrence)
• MSA (Master Service Agreement), their paper or yours, often negotiated
• DPA (Data Processing Agreement), required in most enterprise and all regulated deals
• Security questionnaire (50–150 questions, 2–4 week turnaround for a prepared vendor)
• IT network review and approval (parallel to security questionnaire)
• Procurement system onboarding (Ariba, Coupa, etc.), which can add 2–3 weeks

Plan for 45–90 days from "verbal yes" to signed contract and first invoice. At larger manufacturers, 90–120 days is not unusual.

Timeline Traps

The insurance gap: Your cyber liability coverage limit is $1M. Their minimum requirement is $2M. You find out on day 47 of the procurement process. Add 3–4 weeks while you upgrade your policy and get the new certificate.

The MSA red-line marathon: Their legal team has 47 comments on your standard MSA. Your legal team has 3 people. The review process takes 8 weeks. Meanwhile, your champion has been telling their VP that the contract will be signed "any day now."

The budget year cliff: Their fiscal year ends September 30. It is September 15. The deal is approved but procurement cannot process a new vendor in two weeks. The deal slips to Q1 of their next fiscal year. The budget is not guaranteed to carry.

Pre-wire every one of these. Get procurement introduced in month 2 of an active deal, not month 5. Confirm fiscal year and budget expiration dates in your discovery process. Have your insurance certificates current and at the right coverage levels before you start enterprise conversations.

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Procurement Readiness Checklist

• W-9 current and on file
• Insurance certificates current (GL, cyber, E&O) at enterprise-level minimums
• MSA template reviewed by legal, red-line positions documented
• DPA template ready for customer data requirements
• Security questionnaire answers current and documented
• Procurement system accounts created (Ariba, Coupa, etc.; check customer's system)
• Net-60 / Net-90 payment terms factored into cash flow planning
• Fiscal year calendar confirmed for all active deals over $50K

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Chapter 12: Pricing and Packaging for Manufacturing

The wrong pricing model creates a deal that closes once and does not expand. The right pricing model creates an economic structure that aligns with how manufacturers think about value and how their budgets work.

Common Models

Per site / per facility: Most common for enterprise deals. Aligns with how manufacturers think about their business (by plant, not by user). Enables clean land-and-expand pricing, where each new site is an incremental license at a predictable price.

Per line / per asset: Works well for production-floor products where value is directly tied to the asset being monitored. Makes the ROI calculation straightforward: each line pays for itself based on downtime reduction or OEE improvement.

Per user: Works in office-facing workflows (quality management, maintenance management) but creates friction for shop floor products where "users" are hard to define and headcount fluctuates. Avoid for operator-facing products.

Per production volume: Uncommon but appropriate for products where value scales with output (waste reduction, yield improvement, energy optimization). Creates a natural alignment between vendor success and customer success.

Packaging Principles

Anchor to outcomes, not features. A package called "Predictive Maintenance Starter" is weaker than one called "Unplanned Downtime Reduction: Up to 3 Assets." The second communicates value. The first communicates product category.

Make expansion pricing predictable. The CFO who approves a 3-site deal at $X per site needs to be able to forecast what the 10-site enterprise deal will cost. Predictable expansion pricing removes a major procurement objection and accelerates multi-site rollouts. Show the expansion schedule in the initial proposal.

Separate implementation and services cleanly. Manufacturing implementations require real professional services. Either price implementation as a separate line item (transparent, but creates a larger number) or productize it into an implementation package with a defined scope and fixed price. Hidden implementation complexity discovered post-signature is the fastest way to destroy a reference customer.

ROI narrative: payback period beats features. "Here is a list of features included in your subscription" does not close manufacturing deals. "Most plants your size recover their annual subscription cost in prevented downtime within 90 days" does. Build the payback period calculation into your standard proposal template and customize it with their baseline metrics from discovery.

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ROI Calculator Framework

Inputs (from discovery):

• Annual production hours
• Estimated current unplanned downtime hours per year
• Production value per hour (revenue / production hours, or customer-provided)
• Current scrap cost as % of COGS (or annual scrap cost)
• Number of maintenance FTEs and hourly fully-loaded cost

Outputs:

• Annual cost of current unplanned downtime
• Projected downtime reduction (use conservative 20–30% for Year 1)
• Annual value recovered from downtime reduction
• Annual scrap reduction value (if applicable)
• Total annual value generated
• Software cost / Annual value = payback period in months

Presentation: Always show a conservative case (20% improvement), a base case (30%), and an upside case (40%). Manufacturing buyers trust the conservative case more than the best case, and being right about the conservative case makes them advocates.

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Chapter 13: Implementation and Change Management

The sale ends at the signature. The reference begins at go-live. How you implement determines whether you get one plant or twenty.

Implementation Phases

Phase 0, Pre-implementation (weeks -4 to 0): Integration owner confirmed and active. Data access granted and tested. Network access approved by IT. Training schedule aligned to shift patterns. Executive sponsor briefed on milestone timeline.

Phase 1, Configuration and integration (weeks 1–3): System configured to customer's operational parameters. Integration to ERP / historian / CMMS built and tested in staging. Operator-facing workflows configured and validated with one super-user per shift.

Phase 2, Super-user training and soft launch (weeks 3–5): 1–2 super-users per shift trained to the level where they can train peers. Soft launch on one line or one shift. Daily stand-up call with implementation team to surface issues before they compound.

Phase 3, Full rollout (weeks 5–8): Full production deployment. Adoption KPIs tracked daily for the first two weeks. Issues resolved within 24 hours. Weekly executive check-in to report progress against baseline KPIs.

Phase 4, Stabilization and handoff (weeks 8–12): Adoption threshold confirmed. Baseline KPI movement documented. Customer success team takes over from implementation team. First QBR scheduled.

Training Across Shifts

Manufacturing plants run 24/7. Training cannot happen in a single session. Design your training program for the shift reality:

• Super-user model: 1–2 per shift, trained first, responsible for peer training
• Micro-training: 15-minute sessions at shift change, not 2-hour classroom sessions
• Job aids: laminated quick-reference cards at workstations, not 40-page user manuals
• Video library: 3–5 minute procedure videos for self-service reference

Governance That Drives Adoption

Weekly plant cadence: 30-minute weekly call with the plant-level champion. Review adoption metrics, surface issues, document wins. This call is not optional. It is the mechanism by which implementation problems get identified before they become churn events.

Executive steering cadence: Monthly 30-minute call with the executive sponsor. Report KPI progress against baseline. Preview the next phase. Preview expansion opportunities. This call keeps the deal alive at the level where budget decisions get made.

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Chapter 14: Land-and-Expand

The initial plant deployment is not the deal. It is the proof point that enables the real deal: the enterprise standard.

Expansion Levers

Replicate to new lines and plants. The cleanest expansion path. A successful deployment on Line 3 becomes the model for Lines 1, 2, and 4. A successful deployment at Plant A becomes the justification for Plants B, C, and D. Document the Line 3 results specifically and quantitatively before asking for the Line 1 expansion conversation.

Add adjacent workflows and modules. A CMMS customer who has solved preventive maintenance is naturally ready to evaluate predictive maintenance, spare parts optimization, or contractor management. A quality management customer who has solved NCR documentation is ready for SPC, supplier quality, or audit management. Map the natural expansion path and build the conversation into your QBR cadence.

Integrate deeper into the ERP/MES ecosystem. Each additional integration point increases switching cost and increases the value of the platform. A product that writes to the ERP and reads from the historian is harder to replace than a standalone system. Build toward deeper integration as part of your customer success roadmap.

QBRs That Drive Expansion

A QBR that reviews dashboards and asks "how are things going?" is a status update. A QBR that reviews KPI progress, identifies the next pain point on the expansion roadmap, and presents the business case for the next site is a sales call. Run the second kind.

QBR structure for manufacturing accounts:

1. Results: KPI movement since baseline. Specific numbers. What changed and why.
2. Issues: What is not working, and what we are doing about it. Intellectual honesty before anything else.
3. Expansion opportunity: One specific, quantified opportunity (the next line, the next site, or the next module) with a business case built from their own data.
4. Ask: A specific next step on the expansion conversation, not a vague "we should discuss growing the relationship."

Building the Internal Case Study

Your best expansion asset is a story that lives inside their own organization. Before you ask a plant manager to expand to a second site, make sure the first site's results are documented, attributed, and told in language that travels up the org chart.

The internal case study has four elements: the baseline condition, the intervention, the result (in dollars and operational metrics), and the implication for other sites. Get the plant manager to co-author it. Then ask them who they think should see it.

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Expansion Playbook Checklist

• Year 1 KPI results documented with baseline vs. current comparison
• Internal case study drafted and co-signed by plant champion
• Expansion target sites identified (by footprint mapping or customer conversation)
• Expansion pricing modeled and presented in Year 1 QBR
• Executive sponsor briefed on enterprise standard opportunity
• Reference offer made: "Would you be willing to take a 10-minute call with our team at [target site]?"

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Chapter 15: Objections Library

Manufacturing objections are not the same as SaaS objections. They have different root causes, require different proof, and call for different next steps.

"We'll Build It Ourselves"

Root cause: Underestimation of build cost and timeline. Or, more rarely, a genuinely specialized need that no product addresses.

Response: "We hear that often. A few questions to help you evaluate the build path: Who would own the build? What's the maintenance plan when that person leaves? How long does your engineering team estimate for version 1, and what does version 1 not include? We've seen internal builds take 18–24 months and cost $400,000–$800,000 before maintenance. We can be live in 60 days at a fraction of that cost, and our R&D spend is entirely focused on this problem. Would it be useful to compare the two paths honestly?"

Next step: Offer to build a build-vs-buy comparison with their own estimates.

"IT Won't Allow Cloud"

Root cause: Either a legitimate OT/IT security policy, or an IT organization that has not evaluated the specific architecture yet.

Response: "Let's not assume. Let's get IT involved now and find out specifically what's required. We have deployed in network-segmented environments, air-gapped environments, and on-prem. We have a dedicated security packet we can share with your IT team this week. What typically happens in their security review process, and who should I be talking to?"

Next step: Get IT on a call before they issue a blanket ruling.

"We Don't Have Time"

Root cause: Genuine capacity constraint, or the pain is not urgent enough to prioritize.

Response: "I hear that, and I want to be direct: if the capacity constraint is real, we've designed our implementation to be as low-burden as possible on your team. The heaviest lift in week one is granting data access. After that, we carry the implementation. But I also want to ask: what's driving the crunch right now? Because if it's [the thing your product solves], that's exactly the situation where our customers have told us they wished they had started sooner."

Next step: Quantify the cost of the capacity constraint they just described.

"Operators Won't Use It"

Root cause: Adoption failure experience from previous software implementations.

Response: "That's the most common failure mode we see, and it's a fair concern. Here's what we do differently: [specific operator-facing design decisions]. And more importantly, here's what our adoption data looks like at 30 days, 60 days, and 90 days at comparable plants. I can get you a reference call with a maintenance supervisor at [company] who had the same concern going in."

Next step: Offer a reference call specifically with an operator-level user, not just an executive.

"Integration Will Be a Nightmare"

Root cause: Legitimate experience with integration projects that took 6+ months and required significant IT involvement.

Response: "Integration is where most implementations fail, and we've built our architecture specifically to avoid that. We have a pre-built connector for [their ERP/historian]. Typical integration time is 3–5 days for a standard configuration. Our integration team owns the build. We don't hand you a developer kit and wish you luck. Would it be useful to get your IT lead on a 30-minute call with our integration team to walk through what it would actually look like?"

Next step: Technical call between your integration team and their IT/engineering lead.

"Budget Is Frozen"

Root cause: Real budget constraint, or the ROI case is not strong enough to justify budget release.

Response: "Understood. A few questions: Is this a freeze on new vendor spend, or on capital expenditure generally? Is there an OPEX budget that maintenance or quality owns that this could come from? And can I share what the cost of waiting looks like? If [baseline metric] continues at its current rate, that's [X dollars] between now and the end of your fiscal year."

Next step: Identify an alternative budget source or quantify the cost of inaction.

"We Already Have [MES/CMMS/QMS]"

Root cause: Misunderstanding of where your product fits in the stack, or genuine overlap.

Response: "Tell me more about how you're using it today. In most cases, we're not replacing [existing system]. We're filling the gap [existing system] was not designed to address. [Specific capability]. What does [existing system] do for [the specific problem you solve]?"

Next step: Discovery into how the existing system is actually being used versus how it was designed to be used.

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Chapter 16: Sales Management and Metrics

Manufacturing sales cycles are long and complex enough that pipeline management requires more structure than most SaaS sales processes apply.

Stage Definitions That Reflect Manufacturing Reality

Forecasting With Evidence

Do not forecast based on gut feel or rep confidence. Forecast based on evidence:

• Stakeholder map completeness (are the economic buyer and champion both engaged?)
• Success criteria agreement (have they told you what "yes" looks like?)
• Paper process status (where are we in procurement and legal?)
• Timeline confirmation (has the economic buyer confirmed their decision timeline?)

A deal with a confident rep and an absent economic buyer is not a Q2 close. A deal with a detailed mutual action plan, an engaged procurement contact, and a confirmed budget is.

Deal Review: What to Inspect Weekly

For every deal over $25,000 in active pipeline, review weekly:

1. Last meaningful customer action (not rep action, customer action)
2. Stakeholder map status: who is engaged, who is missing, who is a risk
3. Next customer-committed milestone (what have they agreed to do, and by when?)
4. Kill-switch status: any Red items that appeared since last review?
5. Paper process status: where are we on procurement/legal, and what is blocking progress?

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Downloadable Personas

Plant Manager: Alex Karos

Job: Runs daily operations at a 350-person discrete manufacturer. Responsible for OEE, labor efficiency, and hitting production targets.

Day: Starts at 5:45 AM. Reviews overnight production report. Walks the floor by 6:30. Deals with whatever went wrong on second shift. Back-to-back with shift supervisors, maintenance lead, and production planning by 9 AM. Rarely at a desk before noon.

Goals: Hit monthly throughput targets. Keep downtime below 3%. Hold labor costs flat despite turnover. Not get called by the VP Ops about a quality escape.

Fears: A downtime event he did not see coming. A software rollout that pulls his team off the floor for training. A vendor who disappears after the contract is signed.

Responds to: Peer references. Specific operational metrics. Reps who have clearly been on a plant floor. Proof that implementation will not disrupt his operation.

Shuts down at: Generic SaaS demos. Feature lists. Anything that starts with "AI-powered."

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Maintenance / Reliability Manager: Dana Wojcik

Job: Owns the maintenance program for a 6-line food processing facility. Manages a team of 12 technicians across 3 shifts.

Goals: Shift from reactive to planned maintenance. Reduce MTTR. Get the PM compliance rate above 85%. Stop getting called at 2 AM about equipment failures.

Fears: An implementation that requires his team to enter data twice. A system that only works when the internet is up. New software that his techs on third shift will refuse to use.

Responds to: Real MTTR improvement data. Proof of adoption from comparable plants. A demo that starts with the technician's mobile workflow, not an executive dashboard.

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Quality Manager: Priya Santhosh

Job: Owns quality systems at a Tier 1 automotive supplier. Manages IATF 16949 compliance, customer audits, and CAPA closure.

Goals: Get audit-ready documentation turnaround from 2 weeks to 48 hours. Reduce customer escapes to zero. Close CAPA backlog.

Fears: A failed customer audit. A system that creates more documentation burden than it reduces. Data that is not audit-defensible.

Responds to: Specific audit documentation capabilities. IATF and ISO compliance fluency from the vendor. References from Tier 1 automotive peers.

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Appendix: Email Sequences

Trigger-Based Sequence: New Facility Announcement

Email 1 (Day 0):

Subject: [Company]'s [City] expansion, one thing worth thinking about early

[First name], saw the announcement about your new [City] facility. Congratulations.

Greenfield plants are a rare opportunity to set up the right systems before bad habits form. The manufacturers we've worked with who standardized their [CMMS / MES / quality program] during commissioning, rather than after go-live, consistently reached target OEE 30–40% faster than those who retrofitted later.

We work specifically with [sub-vertical] manufacturers on exactly this. Happy to share what the configuration decisions look like that make the biggest difference early.

Worth a 15-minute conversation?

Best, Alex Christenson | A&C Growth | ancgrowth.com

Email 2 (Day 6):

Subject: Re: [Company]'s [City] expansion

[First name], following up on my note from last week.

[Reference company], a [sub-vertical] manufacturer similar to yours, set up their maintenance program during a new facility commissioning about 18 months ago. They hit 91% OEE by month 6. Happy to connect you with their operations lead directly if the conversation would be useful.

Either way, worth a 15-minute call?

Email 3 (Day 14):

Subject: Last note on [City] facility

[First name], I'll keep this short.

If reducing unplanned downtime in a new facility is something your team is thinking about in the next 90 days, we should talk. If not, I'll follow up when timing is better.

Which is it?

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Trigger-Based Sequence: Compliance Pressure

Email 1 (Day 0):

Subject: [Regulation] deadline: what we're seeing at other [sub-vertical] manufacturers

[First name], [Regulation / audit requirement] is creating real urgency at a number of [sub-vertical] manufacturers we're watching right now.

Most are 60–90 days away from needing documentation systems that are audit-ready. The ones who start now are fine. The ones who start at 30 days are not.

We work specifically with [sub-vertical] manufacturers on [compliance capability]. Happy to share what the documentation gap typically looks like at companies your size and what the fastest path to audit-ready looks like.

15 minutes this week?

Email 2 (Day 5):

Subject: Re: [Regulation] deadline

[First name], I know compliance timelines can feel abstract until they're not.

[Reference company] had 6 weeks to get their [documentation / traceability / CAPA] system audit-ready before a customer audit. They did it. Happy to connect you with their quality manager if it would be useful to hear how.

Worth a conversation?

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Cold Outreach Sequence: No Trigger

Email 1 (Day 0):

Subject: [Specific operational metric] at [sub-vertical] manufacturers

[First name], [Specific data point about a cost or inefficiency relevant to their sub-vertical].

We work specifically with [sub-vertical] manufacturers to [specific outcome]. [One-sentence reference to a comparable company result].

If [specific pain] is something your team is actively working on, I'd welcome a 15-minute conversation.

Best, Alex

Email 2 (Day 7):

Subject: Re: [Specific operational metric]

[First name], following up.

The [specific metric] question comes up most often when [describe the operational condition that signals the pain]. If that sounds familiar, happy to share what the most effective approaches have looked like at comparable plants.

Worth a quick call?

Email 3 (Day 18):

Subject: One more note, then I'll leave you alone

[First name], I won't keep following up after this.

If [specific outcome] becomes a priority, we work with [sub-vertical] manufacturers on exactly this. [One-sentence result from a reference company].

Happy to reconnect when timing is better. In the meantime, [link to a relevant piece of content].

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Related reading

• Why Manufacturers Buy Differently Than SaaS Companies — the structural constraints behind manufacturing purchasing
• Plant Manager vs. VP Operations: How Their Buying Psychology Differs — choosing your entry point
• The Manufacturing Buying Committee — navigating the full committee

A&C Growth builds outbound engines for manufacturing SaaS companies. If you want to see how we would approach your specific ICP, sub-vertical, or sales motion, let's talk.