Quick Snapshot — Tell Us About Your Lab

• Which role are you filling in this conversation? Options: Lab Director, Head of Screening/Discovery, Automation Manager, QA/Validation Lead, IT/LIMS Engineer, Research Scientist, Other
• Roughly how many samples/assays does your group process per day (typical operating cadence)? Options: < 500, 500–2,000, 2,001–10,000, 10,001–50,000, > 50,000
• Which assay types or workflows are highest priority for scale or automation right now? Options: High-throughput screening (HTS), Compound plating/serial dilutions, ELISA/biochemical assays, Cell-based assays, DNA/RNA prep, Sample normalization/normalizing concentrations, Other
• What’s the single most urgent outcome you want from automation in the next 6–12 months? Options: Increase throughput, Reduce assay variability, Free researcher time, Integrate instruments/LIMS, Accelerate go/no-go decisions, Reduce operational cost, Other
• Is there a specific timeline or milestone driving urgency (e.g., grant deadline, drug program stage, facility move)? If so, please describe.

Are You Comfortable Letting Variability Decide Your Timelines?

• How often does manual technique variability cause you to rerun experiments or question results? Options: Daily, Weekly, Monthly, Rarely, Never
• When variability forces a rerun, how much time and resources does a typical rerun consume? Options: < 1 day / minimal cost, 1–3 days / moderate cost, 4–10 days / significant cost, > 10 days / high cost/critical delay
• Tell us about a recent example where manual handling changed the outcome—what happened and what did it cost in time or confidence?
• Which parts of your workflows do you suspect are most sensitive to human technique (pipetting, plate handling, incubation timing, etc.)? Options: Pipetting precision, Timing/sequence of steps, Plate format transfers, Sample labeling/tracking, Reagent preparation, Other
• How long have these variability issues been affecting your throughput or decision quality? Options: Months, 1–2 years, 3–5 years, More than 5 years, Not sure

What’s Really Slowing Your Science Down?

• If you had to point to one bottleneck that routinely delays projects, what would it be—and why does it persist?
• Which of the following contribute materially to throughput delays in your lab? Options: Manual liquid handling capacity, Instrument scheduling conflicts, Method setup & optimization time, Data transfer / LIMS handoffs, Staffing shortages/shift coverage, Regulatory/validation hold-ups, Other
• How predictable are your day-to-day volumes (are you steady, seasonal spikes, or highly variable)? Options: Very predictable, Moderate variability, High variability/spikes, Completely unpredictable
• When a bottleneck appears, who typically becomes responsible for resolving it and how fast do you expect resolution? Options: Lab staff (same day), Lab manager (1–3 days), Automation/IT (days–weeks), Vendor support (days–weeks), Cross-functional taskforce (weeks)
• Can you share a specific workflow timeline (steps and durations) we could review together to spot where automation could shave hours or days?

Who Holds the Keys — and Are They Aligned?

• If we said the success of automation depends on four stakeholders (Research, Automation, IT/LIMS, QA/Validation), which one do you think is least aligned right now? Options: Research/Scientists, Automation/Engineering, IT/LIMS, QA/Validation, All aligned, Not sure
• How are decisions about capital equipment and integrations currently made (single decision‑maker, committee, devolved budget)? Options: Single decision-maker, Departmental committee, Central procurement, Grant-driven purchase, Other
• Who will own validation and acceptance testing internally, and what capacity do they have to take on that work? Options: QA team (sufficient capacity), QA team (limited capacity), Research team, Vendor-managed, Not yet decided
• How do IT and LIMS teams prefer to be engaged for integrations—early design reviews, formal RFP, or just at deployment? Options: Engage early (design), RFP stage, Only at deployment, Ad hoc as issues arise, Other
• What would confidence look like for each stakeholder (e.g., QA: traceable protocols; IT: secure API; Research: same or better assay results)? Please list the top success criterion for each stakeholder group.

If Automation Could Fix One Thing, What Would You Bet On?

• Imagine one persistent problem disappears after deployment—what single change would most transform your team’s productivity or confidence?
• Which benefit would you prioritize when choosing a vendor: reliability, flexibility to run diverse assays, LIMS/API support, or method development and support? Options: Reliability & precision, Protocol flexibility, LIMS/API integrations, Vendor method development & field support, Cost
• Are you more excited by immediate throughput gains, long-term reproducibility, or by reclaiming scientist time—and why? Options: Immediate throughput, Long-term reproducibility, Reclaiming scientist time, All equally
• Which internal constraints would make you hesitate to commit to a larger automation solution (budget, space, validation burden, staffing, culture)? Please rank the top two. Options: Budget, Physical lab space, Validation workload, Staff training/time, Change resistance/culture, IT/LIMS complexity
• If you had a trusted partner running pilot studies for you, what questions would you need answered before recommending wider rollout?

What Would Perfect Throughput Feel Like Day-to-Day?

• Describe, in a single short paragraph, how your lab would operate differently if throughput and reproducibility were no longer constraints.
• What quantitative metrics would immediately convince you that the system is delivering (e.g., CV%, plates/hour, sample touchpoints reduced)? Options: % CV reduction, Plates per hour, Samples per technician per day, Time to first result, Number of manual touchpoints reduced, Other
• How much variability (in %CV or similar) would you need to see reduced to remove the need for repeat runs or replicate checks? Options: < 5% improvement, 5–15% improvement, 16–30% improvement, > 30% improvement, Don't have baseline
• Beyond metrics, what would a successful change enable your scientists to do more of—deeper assays, faster cycles, more exploratory work? Give specific examples.
• Who should be looped in to celebrate and track these wins internally (names or roles), and how would you prefer to visualize progress? Options: Weekly dashboard, Monthly review meeting, Quarterly exec summary, Shared channel (Slack/MS Teams), Other

What Could Stop a Smooth Deployment Before It Starts?

• What would make you say 'not yet' after a deployment readiness review—what are the non-negotiable no-go items? Options: Network/LIMS not available, Insufficient site power/space, QA validation incomplete, Staffing not trained, Safety/ESD issues, Other
• What are your site's current constraints around network access, firewall policies, or data-sharing that we should know up front? Options: Open access for vendor, Strict firewall with exceptions, No external access allowed, LIMS vendor-managed, Unsure — need IT input
• How much on-site vendor involvement is acceptable for installation and method transfer (full vendor-led, co-delivery, or hands-off)? Options: Vendor-led fully on-site, Co-delivery with internal staff, Remote support only, Hybrid phased approach
• Which internal approvals or documents must be completed before installation (purchase order, IQ/OQ/PQ plan, risk assessment, SOP drafts)? Options: PO issued, IQ/OQ/PQ plan, SOP drafts, Risk assessment, Facility access approvals, Other
• If there have been past deployment problems, briefly describe one and how it was resolved—what would you want us to do differently?

How Will Success Be Measured — and Celebrated?

• Who will sign off on acceptance criteria and what is the minimum evidence they’ll require (raw data, acceptance test reports, LIMS integration proof)? Options: QA/Validation, Lab Director, Automation Manager, IT/LIMS, Cross-functional sign-off
• Which acceptance tests are most critical to you: throughput benchmarks, reproducibility (CV), plate-to-plate consistency, or LIMS round-trip verification? Options: Throughput benchmarks, Reproducibility (CV), Plate-to-plate consistency, LIMS connectivity & metadata integrity, Operator usability
• What cadence of validation documentation and status updates would keep stakeholders comfortable during deployment? Options: Daily during critical windows, Weekly, Bi-weekly, As milestones complete, Only on request
• If initial results fall short of acceptance by a small margin, what remediation approach would you prefer: vendor tweak, joint debugging session, or rollback to manual while we iterate? Options: Vendor tweak & repeat tests, Joint debugging session, Rollback and schedule new deployment, Conditional acceptance with corrective plan
• How would you like to preserve institutional knowledge after go‑live (training certification, recorded sessions, runbooks, or a living LIMS SOP)? Options: Operator certification, Recorded training, Runbooks & SOPs, LIMS-embedded protocols, All of the above

Next Steps — What Would Make This a Good Pilot?

• What would a successful pilot project look like in scope and duration (single assay, plate format, or multi-assay; 2–6 weeks, 2–3 months, etc.)? Options: Single assay, 2–6 weeks, Single assay, 2–3 months, Multi-assay, 2–3 months, Proof-of-concept lab week, Other
• Which internal resources can you commit to a pilot (operator hours, QA time, IT support, space), and what percentage of their time can be allocated?
• What success criteria must be met in a pilot for you to recommend wider rollout (choose top 3)? Options: Throughput target met, CV improvement threshold, Seamless LIMS integration, Minimal operator burden, On-time delivery of documentation, Budget within estimate
• Are there regulatory or audit timelines that would affect pilot timing or reporting needs (e.g., GxP/GLP)? Please describe. Options: GxP/GLP regulated timelines, Internal audit scheduled, No regulatory constraints, Unsure — need input
• Realistically, how soon could you commit to starting a pilot if the plan fits your needs? Options: Immediately, In 1–2 months, In 3–6 months, Later this year, Unsure
• Who should we include as the core decision team to review a pilot proposal (names or roles) and what’s the best way to present the plan to them? Options: Email packet + demo, Short executive briefing, Technical deep-dive session, Shared pilot plan & timeline, Other

Tell Me How It Really Runs

• Walk me through a typical run from sample in to result out — what are the discrete steps and who touches the work at each stage?
• What types of samples and plate formats do you process most often? Options: 384‑well plates, 96‑well plates, tubes/plates mix, PCR strips, microtubes, Bead-based assays, Other
• On an average day and on a peak day, how many samples or plates do you process? Options: <100 samples/day, 100–500, 500–2,000, 2,000–10,000, >10,000
• Roughly what percentage of that end‑to‑end workflow is manual vs automated today? Options: 0–10% manual, 10–30% manual, 30–60% manual, 60–90% manual, Almost entirely manual
• How do you currently measure throughput and cycle time (e.g., plates/hour, samples/day, turnaround time)? Provide the key metric you track.

Where Does Time Leak Out?

• If a morning’s schedule broke down, what single step would you point to as the real cause — and why is that still happening? Options: Sample prep bottleneck, Liquid handling/manual pipetting, Incubation/wait steps, Plate handling/transfer, Data transfer/processing, Instrument availability, Other
• How often do these bottlenecks cause missed deadlines or re‑runs? Options: Daily, Several times/week, Weekly, Monthly, Rarely
• When a bottleneck occurs, who is typically pulled in to resolve it and what is the usual workaround?
• What would it feel like for your team if the current bottleneck disappeared — what downstream changes would you expect (time, staffing, morale)?
• Are there steps you’ve tried to streamline before that didn’t stick? If so, what went wrong and how long did the improvement last?

When Results Surprise You, What’s Usually Broken?

• Which failure modes create the most disruption in your assays (pick up to three)? Options: High CV / poor reproducibility, Edge effects/evaporation, Carryover/contamination, Pipetting volume errors, Failed controls, Software/scheduling errors, Other
• How frequently do you see these failure modes affecting runs (percent of runs impacted)? Options: <1%, 1–5%, 5–15%, 15–30%, >30%
• Tell me about a recent failure that cost time or samples—what happened, how was it detected, and how long to recover?
• What do you believe are the root causes (choose all that apply)? Options: Operator variability, Instrument calibration/maintenance, Consumable quality, Assay sensitivity to handling, Environmental factors (temp/humidity), Software bugs/scheduling, Other
• How do these failures shape how you design experiments or accept risk today?

Who’s Doing All the Heavy Lifting?

• How many full‑time equivalents (FTEs) are dedicated to running assays, maintaining automation, and supporting data each week? Options: <1 FTE, 1–2 FTE, 3–5 FTE, 6–10 FTE, >10 FTE
• How much of a typical operator’s shift is consumed by manual pipetting, setup/cleanup, and troubleshooting (estimate %)? Options: <10%, 10–30%, 30–50%, 50–75%, >75%
• Do you rely on a small group of 'superusers' to keep things running? If yes, what risks do you see if they become unavailable? Options: Yes—single point of failure, Yes—shared risk but manageable, No—cross‑trained team, Other
• How would you describe team sentiment around current workflows — frustrated, stretched but proud, resigned, or optimistic? Give examples. Options: Frustrated, Stretched but proud, Resigned, Optimistic
• What training cycles or certification requirements exist for new operators, and how long do they take to reach independent operation?

How Healthy Is Your Instrument Fleet?

• What instruments and vendors make up your current estate (list names and approximate counts)?
• How old is the core automation hardware and what percentage is under active service contract? Options: All new (0–2 yrs), Mostly new (2–5 yrs), Mixed (some >5 yrs), Mostly legacy (>5 yrs)
• How frequently does instrument downtime occur and what is the average time to repair or workaround? Options: Daily, Weekly, Monthly, Quarterly, Rarely
• What spare‑parts, calibration, or preventative maintenance practices are currently in place — and where do those break down?
• If you were to add or replace one capability in your estate this year, what would it be and why?

Does Data Flow or Drag?

• How does data move from instruments into your LIMS/analysis pipeline today — automated integration, manual export, or both? Options: Automated (API/driver), Manual export/import, Semi‑automated with human checks, No LIMS integration
• Which LIMS, ELN, or analysis tools do you rely on, and do they have native connectors to your instruments?
• When transfers fail or data is inconsistent, what kinds of errors do you see most often and who fixes them? Options: Missing metadata, Wrong plate mapping, Format mismatch, Timestamps off, Human transcription errors, Other
• How long does it take from raw read to validated result in your pipeline, and what manual steps are required in between?
• If you could change one thing about how data is handled today to improve speed or confidence, what would that be?

What Would Stop This From Working Long Term?

• What skepticism or internal resistance have you seen when attempting automation or workflow changes in the past? Options: Budgetary concerns, Fear of job loss, Validation/regulatory risk, Integration complexity, Vendor trust, Other
• Which regulatory or validation requirements must any change meet (e.g., GLP, GxP, ISO) and who owns validation internally? Options: GLP, GxP, ISO standards, Institutional QA only, No formal requirements, Other
• What would an acceptable validation and acceptance path look like for you (documents, tests, owner sign‑offs)?
• How flexible is your procurement and funding cycle for capital equipment this year? Options: Funds available now, Planned in current budget, Next fiscal year, Dependent on approvals, Uncertain
• If we designed a solution that removed your top bottleneck but required a phased rollout, what would be the minimum first‑phase outcome for you to consider it a success?

If We Could Fix One Thing, What Should It Be?

• Looking across throughput, failures, staffing, instruments, and data — which single outcome would deliver the most value to your team right now? Options: Increase throughput, Reduce re‑runs/failures, Lower operator time, Seamless LIMS integration, Lower operating cost, Other
• What timeline would make that outcome meaningful for you (weeks, months, fiscal year)? Options: Immediately (weeks), 1–3 months, 3–6 months, 6–12 months, Next fiscal year
• Who are the must‑involve stakeholders we should engage to validate the scope and constraints for that change?
• What non‑negotiable constraints (space, power, biosafety, IT policy) would any proposed change need to satisfy?
• Finally, can you share one story or example that best communicates why solving this is important to your team right now?

Quick Snapshot — Where You Are Today

• In one sentence, how would you summarize your primary goal for lab automation this year?
• How many samples or wells do you currently process per day (typical range)? Options: < 1,000, 1,000–10,000, 10,000–50,000, 50,000–200,000, > 200,000
• Which workflows are currently highest priority for automation? Options: High-throughput screening, Sample preparation (extraction, normalization), Serial dilutions / plate prep, Assay readout integration (plate reader, HCS), Compound management / reformatting, Other
• Describe your current level of automation across those workflows (manual, semi-automated, fully automated). Options: Mostly manual, Semi-automated in pockets, Automated for single assays, Integrated automated workflows, Don’t know / mixed
• Who would be the primary day-to-day operators of a new system? List roles and typical availability (shifts/week).
• What single metric would convince you that automation is delivering value (e.g., samples/day, CV reduction, FTE hours saved)? Options: Throughput (samples/day), Reproducibility (CV), Hands-on time saved (FTE), Time-to-result, Error reduction, Other

What’s Really Slowing Discovery Down?

• What hidden bottleneck is silently adding days or weeks to your discovery timelines?
• How often do these delays occur? Options: Daily, Weekly, Monthly, Quarterly, Rarely
• Which step(s) most often create the longest waits or variability? Options: Pipetting / liquid handling, Plate setup and labeling, Sample tracking / LIMS handoff, Incubation and timing, Data transfer / analysis, Other
• Quantitatively, how many researcher hours per week are lost to manual tasks tied to these bottlenecks? Options: < 10 hours, 10–40 hours, 40–100 hours, 100–300 hours, > 300 hours
• Tell us about a recent run that went sideways—what happened and what did it cost the project?
• When you face these delays, what business consequences follow (e.g., missed milestones, delayed go/no-go decisions, increased reagent costs)? Options: Missed milestones, Slowed lead discovery, Increased reagent/waste costs, Staff overtime, Compromised data quality, Other

Who's Holding the Keys (and Are They Aligned?)

• If a system were ready to ship tomorrow, whose approval would still stall installation?
• Which stakeholders must be consulted or sign off (select all that apply)? Options: Lab Director / Head of Operations, Automation Manager, IT / Network, QA/Validation, LIMS Administrator, Procurement / Finance, Health & Safety / EHS, Other
• For each stakeholder group you selected, what does success look like to them? (quick bullet points)
• Do you have an executive sponsor or champion who will prioritize this effort? Options: Yes — identified, Yes — informal, No, Unsure
• What is your internal decision timeline for approving capital projects like this? Options: < 1 month, 1–3 months, 3–6 months, 6–12 months, > 12 months
• Have you run internal pilots or proof-of-concepts for automation before? What was the outcome? Options: Successful and scaled, Limited success / not scaled, Failed or aborted, Not attempted

The Invisible Failures — Where Reproducibility Breaks

• Which recurring assay failures keep you up at night?
• Which failure modes are most common in your workflows? Options: Pipetting inaccuracy/air gaps, Cross-contamination, Plate handling misalignments, Inconsistent incubation timing, Data mismatches with LIMS, Other
• How frequently do you see reproducibility outside your acceptable range? Options: Almost always, Often, Occasionally, Rarely, Never sure
• What are your current acceptance criteria for reproducibility (e.g., CV% thresholds) across critical assays? Options: CV < 5%, CV 5–10%, CV 10–20%, No formal criteria
• Describe the troubleshooting steps you use today when a run fails—who investigates and what’s the escalation path?
• How would improved reproducibility change your team’s confidence or decision-making speed? Options: Faster go/no-go, Fewer retests, Higher publication/filing quality, Reduced reagent waste, Other

A Day With Ideal Throughput

• Imagine a no-surprises day — how many samples would you ideally process and with what level of confidence in results?
• What is your target throughput by the end of 12 months (per day or per week)? Options: No change, 10–50% increase, 50–200% increase, > 200% increase
• What maximum variability (CV%) would you accept to consider the system fit-for-purpose? Options: < 5%, 5–10%, 10–15%, > 15%
• How many distinct assay protocols would need to run on the platform without reconfiguration? Options: 1–2, 3–5, 6–10, > 10
• What staffing model supports that day (operators per shift, reagent prep, IT support)?
• Which assays must be preserved exactly as written (regulatory/validated) versus which can be optimized during method transfer? Options: Must preserve (validated), Can be optimized, Mixture — specify per assay

Integration Nightmares or Smooth Sailing?

• If your LIMS and instruments could talk perfectly, what's the single data flow or integration that would unlock the most value?
• Which systems need to integrate with the automation platform? Options: LIMS, ELN, Inventory/Compound Management, Instrument Control (vendor drivers), Data Analysis pipelines, Middleware / Scheduler, Other
• Which LIMS/ELN vendors or in-house systems are you using today? Options: Thermo Fischer/Benchling, LabWare, LabVantage, Custom / In-house, Other / Unsure
• What network or security constraints should we be aware of (firewalls, air-gap, VPN, required certificates)? Options: Open lab network, Restricted VLAN, Air-gapped / no internet, Requires VPN, Requires specific certs, Unsure
• Who owns IT approvals and what is the typical lead time to get network/LIMS access? Options: IT owns; < 2 weeks, IT owns; 2–6 weeks, IT owns; > 6 weeks, Shared responsibility, Unsure
• Describe any past integration attempts and what prevented success.

What Would Need to Change for You to Say Yes?

• What's the single non-negotiable acceptance criterion that would make your team green-light a deployment?
• Which of the following acceptance criteria are required for you? Options: Throughput target met, Reproducibility thresholds met, LIMS integration working, Operator training completed, Validation deliverables documented, Safety controls verified
• Where is your budget and procurement process today? Options: Budget allocated and approved, Budget earmarked but not approved, Need CAPEX approval, Seeking operating lease options, Unsure / discussing
• Who on your team will own validation and acceptance testing responsibilities? Options: QA/Validation team, Automation Manager, Lab Ops / Operators, Vendor with customer oversight, Shared ownership
• What training format works best for your team (select all that apply)? Options: On-site instructor-led, Remote live training, Self-paced e-learning, Shadowing with vendor, Train-the-trainer
• What post-deployment support model would give you confidence (SLA, on-site support, local spare parts)? Options: 24/7 SLA, Business-hours SLA, On-site support blocks, Remote support only, Local spare parts inventory, Managed service

Small Steps, Big Wins — Starting Without Disruption

• What one pilot or proof-of-concept could demonstrate value in a single week?
• Which assay types are the best candidates for a short pilot? Options: Biochemical enzyme assays, Cell-based screening, Plate-based ELISA, Compound serial dilutions, Sample normalization / extraction, Other
• What measurable success criteria would you use for that pilot? Options: Throughput achieved, CV reduction, Hands-on time saved, Successful LIMS handoff, Operator proficiency, Other
• What internal resources can you commit to a pilot (operators, IT time, QA oversight)? Options: Operator time (hours/week), IT time (hours), QA time for validation, None — need vendor-run pilot, Other
• What concerns or constraints would make a pilot risky for you? Options: Disruption to active projects, Insufficient IT support, Regulatory impact, No available operator time, Cost concerns, Other
• If we proposed a pilot, when could you realistically schedule it? Options: Immediately (within 2 weeks), 1–2 months, 2–3 months, 3–6 months, Later / unsure

Quick Introductions — a 60-second snapshot

• What's your role and primary decision responsibility for lab automation? Options: Lab Director, Director of Screening, Head of Automation, Operations Manager, QA/Validation Lead, IT/Infrastructure Lead, Other
• Which lab or program will be the primary pilot for this automation effort? Options: High-throughput screening, Sample prep / ADME, Compound management, Biomarker assays, Core/shared facility, Other
• Roughly how many plates or samples per day does this group currently process? Options: <50 plates / <1k samples, 50–200 plates / 1k–5k samples, 200–500 plates / 5k–20k samples, 500+ plates / 20k+ samples, Unknown / variable
• What is the single metric leadership most asks you about when evaluating lab performance? Options: Throughput (plates/day), Assay reproducibility (CV/Z'), Turnaround time, Cost per sample, Operator headcount, Regulatory compliance, Other
• On what timeline are you hoping to reach a decision about automation (pilot or purchase)? Options: Immediately (0–1 month), Short (1–3 months), Quarterly (3–6 months), Longer (6–12 months), No set timeline

Are you quietly tolerating variability that’s slowing discovery?

• Which assays or steps do you see as the largest sources of unpredictable results? Options: Liquid handling dilutions, Plate-to-plate variability, Incubation inconsistencies, Instrument calibration drift, Sample prep variability, Other
• What measurable variability thresholds are you currently tracking (e.g., CV, Z', signal/noise)? List values if known.
• Tell us about a recent project delayed or re-run because of assay variability — what happened and what did it cost in time or resources?
• Which controls or SOPs are in place today to limit variability? Options: Manual SOPs with checklists, Operator certification, Instrument preventative maintenance, Automated QC scripts, No consistent controls, Other
• How confident are you that automation could reduce this variability meaningfully? Options: Very confident, Somewhat confident, Unsure, Skeptical

Where does time actually disappear in your lab day?

• Estimate hours per week your team spends on manual pipetting, plate setup, and transfers. Options: <10 hours, 10–25 hours, 25–50 hours, 50–100 hours, 100+ hours
• Which specific tasks eat the most hands-on time? Options: Serial dilutions, Plate reformatting, Aliquoting/sample prep, Manual QC/inspection, Method troubleshooting, Other
• How often do staffing gaps or holidays cause critical runs to be delayed? Options: Almost always, Often, Sometimes, Rarely, Never
• When manual steps fail, how quickly can you recover and re-run? Describe a recent recovery scenario.
• If automation reduced hands-on time by 50%, what would your team redeploy that time toward? Options: New assay development, Data analysis, Method optimization, Training/mentoring, Other

What would your ideal lab look and feel like in 6 months?

• What are the specific throughput targets you’d consider a successful outcome for a pilot (plates/day, samples/day)?
• What reproducibility targets would you need to see to call the project a success (e.g., CV%, Z' threshold)?
• What minimum uptime and run reliability must the system provide to be practical for your workflows? Options: >99%, 97–99%, 95–97%, <95%
• If automation freed operators from repetitive tasks, what would success look like for scientists day-to-day? Options: More experiments per week, Faster data interpretation, Better experiment design, Lower overtime, Improved job satisfaction, Other
• Which KPIs should we include in a pilot acceptance test to convince you the system works? Options: Throughput achieved, CV/Z' across plates, Run-to-run reproducibility, Integration with LIMS, Operator proficiency, Training completion

What’s hiding in the gap between instruments and your data?

• Which LIMS, ELN, or data systems must this solution connect to? Options: Epicor/LIMS, Thermo/LabKey, Benchling, Dotmatics, Custom in-house LIMS, None/Manual
• How painful is current data flow from instruments to LIMS or analysis (0 = seamless, 10 = avalanche)? Options: 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
• Which instruments or vendor drivers have been hardest to integrate historically? Options: Liquid handlers, Plate readers, Incubators/robots, Mass spec, Custom devices, We haven’t tried integrations
• Are there network, firewall, or security constraints that would block standard integration approaches? Options: Air-gapped lab, Restricted outbound access, Proxy/VPN required, Open on request, Unknown
• Describe a past integration attempt that failed or under-delivered — what was the root cause?

What keeps your validation and QA teams awake at night?

• Which regulatory or compliance frameworks apply here (check all that apply)? Options: GLP, GMP, 21 CFR Part 11, ISO standards, Internal QA only, Other
• What validation deliverables must the vendor provide vs what your team will own? Options: IQ/OQ/PQ protocols, CSV/21CFR documentation, Traceability logs, Method transfer docs, Training records, Other
• Which acceptance tests are non-negotiable for QA sign-off? Options: Throughput stress runs, Reproducibility across operators, End-to-end LIMS transfer, Security/audit trails, Environmental controls validation
• How long does a typical qualification/validation cycle take at your site? Options: <2 weeks, 2–4 weeks, 1–3 months, 3+ months, Depends on scope
• What evidence or artifacts would make QA comfortable signing off without extensive rework?

Who would need to feel this change is safe, and why might they resist?

• Which stakeholders must be aligned for the project to proceed (choose all that apply)? Options: Lab Director, Finance/Procurement, QA/Validation, IT/Network, Scientists/End users, Facilities, Other
• Which single stakeholder historically has blocked or slowed automation decisions? Options: Finance, QA, IT, Lab leadership, End users, Facilities, No single blocker
• What are the most common objections technicians or scientists raise about automation? Options: Job security concerns, Loss of control over protocols, Fear of complicated software, Downtime during transition, Validation burden, Other
• What training model has worked best here—intensive vendor-led, blended learning, train-the-trainer, or other? Options: Vendor-led onsite, Train-the-trainer, Blended online + onsite, Self-paced materials, Other
• Describe one recent change the team accepted well — what helped that adoption succeed?

Let’s map the first 90 days after installation — who does what?

• Is the intended installation site ready for equipment (space, bench footprint, power, HVAC)? Options: Fully ready, Minor modifications needed, Significant site work required, Unknown / needs assessment
• When will IT/LIMS access and credentials be available for integration work? Options: Before install, During install window, After install, Not yet scheduled
• Who will be the on-site point people for installation, training, and acceptance testing?
• Which sample types, plate formats, and assay reagents should we prioritize for the pilot sequence?
• What acceptance run sequence would prove readiness in the first 90 days (list tests or scenarios)?
• How should early issues be reported, triaged, and escalated during the pilot? Options: Vendor ticketing + weekly review, Onsite daily standups, Dedicated Slack/channel, Email + monthly review, Other

Money, timing, and approvals — what stands between talk and mutual commit?

• Where is this project in your procurement cycle? Options: Budget approved, Budget requested, Seeking budget, No budget yet, Other
• What procurement hurdles or contracting terms typically slow down deals here? Options: Capital approval, Security/IT review, Vendor validation clauses, Lease/finance terms, Other
• Would you prefer purchase, lease, or consumption-based commercial structures? Options: Purchase (capex), Lease/finance, Subscription/consumption, Undecided
• What's the most important commercial term that would make you comfortable signing (warranty, SLAs, acceptance windows, training inclusion)? Options: Extended warranty, Defined SLAs, Clear acceptance criteria, Included training & support, Flexible payment terms, Other
• What internal milestone or approval would signal we should move from discovery to Mutual Commit?

Anything we haven’t surfaced yet that matters to you?

• What is the single biggest risk you haven't mentioned that could derail this project?
• If we could solve only one operational problem in your lab, which should it be? Options: Throughput limits, Assay variability, Integration/LIMS gaps, Operator time burden, Validation complexity, Other
• Would a hands-on workshop or pilot run at our site help you feel more confident? If yes, what would you bring to that session? Options: Yes — bring assays & reagents, Yes — bring operators only, Maybe — need more info, No
• Best time and method to follow up with your stakeholders for a next-step planning session? Options: Weekdays AM, Weekdays PM, Weekly cadence, Ad-hoc as needed, Email summary then call
• Anything else we should know — constraints, preferences, or previous vendor experiences that shaped your expectations?