Welcome — Quick Snapshot of Your Operation

• How would you briefly describe the primary purpose of this DC/fulfillment site? Options: Retail replenishment, E‑commerce fulfillment, 3PL (multi‑tenant), Manufacturing distribution, Returns & reverse logistics, Other
• What is the typical operating scale at this site (headcount, shifts, and daily units)? Please include the number of active associates per shift.
• How many SKUs or active picking locations does the operation manage? Options: < 10k SKUs, 10k–50k SKUs, 50k–200k SKUs, > 200k SKUs, Unsure / need to confirm
• Which systems currently hold your work and labor records (select all that apply)? Options: WMS (name it in the next question), TMS, Payroll/time clock, Homegrown systems/Excel, Third‑party labor module, Other
• Who will be our day‑to‑day contact for coordinating floor access, time studies, and data pulls?

Are We Carrying Invisible Labor That’s Quietly Eating Margin?

• Do you suspect there is significant invisible unproductive time today that your aggregate reports are masking? Options: Yes — likely >20%, Yes — likely 10–20%, Possibly — unsure of magnitude, Unlikely / not a concern
• When did you first notice throughput per labor hour declining or labor cost per unit rising? Options: Last quarter, Last two quarters, Last three or more quarters, We haven't tracked trend timing
• What current reports are you using to surface productivity issues (examples: picks per shift, labor cost per unit, exceptions)? List the top 3.
• Can you share a recent example where aggregate metrics suggested 'normal' performance but operational leaders felt something was off? Describe what happened and why it stayed invisible.
• How confident are you that existing metrics can isolate individual performance versus team or process variability? Options: Very confident, Somewhat confident, Not confident, We don't currently try
• If the operation is carrying unexpected unproductive time, what impact is that having on your weekly/monthly goals (labor cost, OT, delivery promises, safety)?

Who Holds the Keys — Decision Roles, Politics, and Timing

• Who are the stakeholders that must sign off on a pilot and eventual rollout (list names and titles if possible)?
• Which single person or committee has the authority to approve moving from pilot to broader rollout? Options: Site Director/GM, VP of Operations, VP of HR, Procurement/IT joint approval, Other
• How does your organization typically make technology purchase decisions—fast (weeks), moderate (1–3 months), slow (3–9 months)? Options: Weeks, 1–3 months, 3–9 months, Longer/indeterminate
• What timelines would count as acceptable for starting a pilot and then making a go/no‑go decision? Options: Start in 2–4 weeks, Start in 1–2 months, Start in 2–3 months, Flexible/undetermined
• What are the usual internal blockers (finance, legal, union, IT, data access) that we should anticipate and who owns each blocker?
• Have you run similar pilots before? If so, what decision process determined success or failure in those projects? Options: Yes, formal decision rule, Yes, informal consensus, No, first pilot, Other

If This Pilot Succeeds, What Will That Actually Unlock?

• What measurable improvements would make this pilot a clear success for you (choose up to three)? Options: Productivity % uplift (specify), Labor cost per unit reduction, Supervisor adoption of dashboards, Improved associate retention, Reduced overtime, WMS integration reliability
• Please state the numeric targets you would use to call the pilot successful (e.g., productivity +12%, supervisor dashboard use >70%, associate sentiment net +x).
• How will HR and your union representatives measure the pilot's fairness and acceptability? Options: Associate sentiment survey results, Independent audit of time studies, Union observer participation, Formal labor agreement checkpoints, Unsure / need to define
• What short‑term business outcomes (reduced backorders, faster SLA, lower overtime) must be visible to keep executive support?
• If the pilot achieves the numeric goals but associates report negative sentiment, how would you weigh those outcomes? Options: Prioritize productivity, Balance both equally, Prioritize associate sentiment, Depends on severity
• What's the minimum evidence you'd accept before approving a site‑wide rollout?

What Could Break This — Risks, People, and Perception

• What worries you most about introducing engineered standards and individual productivity tracking on the floor? Options: Union pushback, Associate morale/turnover, Fear of surveillance, Inaccurate standards, Safety concerns, Other
• Have you or a peer experienced a rollout where perceived unfairness derailed adoption? Tell us what happened and how long it took to resolve.
• What protections or assurances would HR or the union require to consider the pilot acceptable? Options: Transparent methodology, Union observers at time studies, No immediate incentive changes, Data privacy/limited access, Independent validation, Other
• If the pilot caused an increase in churn or grievances, what would be the immediate escalation path and acceptable remediation?
• How much weight do you put on reference customers (same vertical/size) when evaluating risk? Options: High, Moderate, Low, Not relevant
• Are there regulatory, safety, or local employment rules that could constrain how we measure or use productivity data? Options: Yes—significant constraints, Yes—some constraints, No constraints, Unsure

Do Your Systems Tell the True Story or Just Tell a Story?

• How much do you trust the WMS timestamps and work assignment records to reflect actual on‑task work? Options: Fully trust, Generally trust, Somewhat unreliable, Not reliable at all
• Which WMS do you use and what version? Please include any overlay or customizations that affect task timestamps.
• What data feeds can we access for a pilot (select all that apply)? Options: Real‑time WMS task assignments, WMS task completion events, Time clock punches, Associate IDs / badges, Work order and SKU master, None / need to arrange
• Has your IT team integrated external dashboards or analytics tools with the WMS before? If yes, what was the experience? Options: Yes—smooth, Yes—with effort, No—not attempted, Other
• Are there data retention, encryption, or privacy requirements we must meet before accessing associate‑level data? Options: Yes—strict, Yes—standard, No special requirements, Unsure
• Who in your organization will be responsible for granting data access and mapping fields for the pilot (name/role)?

Will Supervisors and Associates Embrace a New Way of Working?

• If presented with a real‑time dashboard that scores individual tasks, will supervisors use it to coach in the moment or will it likely become another ignored report? Options: Active coaching likely, Some will use it, some won't, Unlikely to be used, Unsure
• Describe the current supervisor to associate ratio and how much time supervisors spend in active coaching versus admin work.
• What training cadence and format do you prefer for supervisor onboarding (select all that apply)? Options: Half‑day classroom, Hands‑on floor coaching, Micro e‑learning modules, Train‑the‑trainer, Other
• How digitally comfortable are frontline associates with tablet/handheld dashboards and receiving performance feedback digitally? Options: Very comfortable, Moderately comfortable, Some discomfort, Not comfortable
• Would you prefer to run the pilot measurement period without activating incentives, to build trust first? Options: Yes—measurement only, No—measurement + incentive, Open to discussion
• What communication channels and cadence have historically worked best to introduce changes to associates? Options: Town halls, Shift briefings, Supervisor 1:1 coaching, Printed notices, Digital messages, Union meetings

Where Exactly Do We Draw the Pilot Fence?

• Which zone(s) or process(es) are you considering for the 60‑day pilot (pick the best fit)? Options: Picking – piece‑pick, Picking – batch/zone, Packing & staging, Returns processing, Replenishment/putaway, Other
• What tasks within that zone should be included in time studies (e.g., pick, travel, pack, label, verification)? Please list the top tasks to observe.
• Who will physically conduct time studies and who will validate the engineered standards on your side? Options: CI Team, Operations Supervisors, External consultant, Vendor team with site observer, Other
• What guardrails should we set for this pilot (number of associates, shifts included, minimum days of data)?
• Do you require observers from HR or the union during time studies? If yes, how many and under what conditions? Options: Yes—HR, Yes—Union, Yes—both, No, Unsure
• What verification criteria will you use to accept the standards we produce (examples: spot audits, supervisor sign‑off, independent review)? Options: Spot audits, Supervisor sign‑off, Union/HR confirmation, Comparison to industry benchmarks, Other

How Will We Measure and Prove Value During the 60 Days?

• What baseline metrics can you commit to share so we can compare before/after (examples: baseline picks per hour, labor cost per unit, error rate)?
• How frequently would you like progress updates during the pilot (daily, weekly, biweekly), and who should receive them? Options: Daily, Weekly, Biweekly, Only milestone reports
• Which of the following acceptance signals matter most to you during validation? Options: Measured productivity delta, Supervisor dashboard adoption, Associate sentiment results, WMS integration fidelity, Retention/turnover signals
• What sample size or confidence level will you require before trusting productivity uplift numbers (e.g., % of associates, days of data)?
• Would you accept parallel tracking (standards measured but incentives paused) as part of the validation approach? Options: Yes, No, Maybe—need terms
• Who on your team will be responsible for signing off the final validation checklist?

The Money Question — Economics, Incentives, and Decision Rules

• What ROI, payback period, or absolute savings would justify a rollout at scale for you? Options: < 3 months payback, 3–6 months, 6–12 months, Depends on strategic value
• Would rollout require a budget line, reallocation of existing funds, or an operational savings reinvestment? Select all that apply. Options: New capital budget, Operational budget reallocation, Savings reinvestment, Vendor financing, Unsure
• What incentive model do you find fair and acceptable for associates once standards are active? Options: Individual piece‑rate, Team incentives, Non‑monetary recognition, No incentives initially, Other
• What decision rule will translate pilot results into rollout (for example: productivity >12% AND supervisor adoption >70% AND associate sentiment neutral‑positive)? Please describe.
• Who must be present or briefed before signed contractual commitment for rollout (roles or committees)?
• Are there procurement or contracting templates we should prepare for (e.g., preferred suppliers list, PO process)? Options: Yes—standard PO, Yes—SOW and SLA, No special templates, Unsure

Logistics: Access, Security, and Practicalities

• What are the floor access rules for vendor personnel, observers, and tools (badging, escorted, restricted areas)?

Quick Snapshot — Where are we starting from?

• Briefly describe the immediate issue that prompted this conversation (what changed, when, and who raised it)?
• Which of these metrics do you currently monitor most closely? Options: Picks per labor hour, Orders per labor hour, Lines per hour, Labor cost per unit shipped, Overtime hours, Accuracy / error rate, Throughput by shift, Other
• How often do you receive these reports and in what form (dashboard, daily email, WMS export, spreadsheet)? Options: Real‑time dashboard, Daily report, Weekly summary, Manual spreadsheet, Ad‑hoc exports from WMS, Other
• Who is the primary consumer of those reports (name roles — e.g., DC Director, Ops Manager, Supervisor, HR)?
• If you had to name the single biggest blind spot in your current reporting, what would it be?

Are We Carrying Invisible Time That Nobody Can Explain?

• We often find operations carrying 10–25% invisible unproductive time — where do you see signs that productive hours might be overstated? Options: Shift-level averages feel high but throughput fell, Frequent unexplained overtime, Supervisors report small delays adding up, Accuracy holds while throughput drops, Associate complaints about unreasonable targets, Other
• Can you point to concrete examples (a week, shift, or zone) where aggregate numbers looked fine but operational problems were later discovered?
• Who on your team has attempted to diagnose those invisible losses and what data or observations did they rely on? Options: Supervisors' notes, Manual time studies, WMS logs, Associate interviews, Third‑party audits, No one has looked closely, Other
• Roughly, what percent of total paid hours do you suspect is currently unproductive and unreported? Options: <5%, 5–10%, 10–15%, 15–20%, 20–30%, >30%
• How does discovering hidden unproductive time feel to you — a solvable nuisance, a systemic risk, or something in between? Options: Solvable nuisance, Significant operational risk, People / morale risk, Urgent business problem, Unsure

When Reporting Lets You Down — How decisions get distorted

• If your leadership makes staffing or incentive decisions using current reports, what costly choices have followed from incomplete data?
• Have you ever increased headcount, changed schedules, or paid overtime to address a throughput drop that later proved to be a reporting or process problem? Tell us what happened.
• Which of these kinds of granularity is missing today and most frustrates you? Options: Per‑associate time on task, Task element breakdown (walk, pick, pack), Zone‑level cycle times, Supervisor activity logs, Real‑time deviation alerts, Other
• How much do you trust the WMS‑native labor reports for diagnosing performance issues (scale)? Options: Completely trust, Mostly trust, Somewhat trust, Barely trust, Do not trust at all
• Share an example of a decision that would have changed if you’d had associate‑level productivity versus only shift averages.

How Supervisors Actually Manage — vs how you think they do

• Supervisors often rely on instincts and spot checks — how do your supervisors currently discover who needs coaching or rebalancing? Options: Visual checks on the floor, End‑of‑shift reports, Team huddles, Associate self‑reports, WMS task lists, Other
• How frequently do supervisors perform one‑on‑one coaching or corrective conversations per shift or week? Options: Multiple times per shift, Once per shift, A few times per week, Rarely, Never documented
• What tools do supervisors use to prioritize who to coach (paper, whiteboard, WMS, spreadsheets, gut)? Options: Paper notes / whiteboard, WMS dashboards, Spreadsheets, Mobile apps, No formal tools, Other
• Describe a recent situation where a supervisor missed an opportunity to intervene early — what signals were available but unused?
• If supervisors had real‑time, associate‑level standards and alerts, how would that change their daily routine? Be specific.

What Would Clear, Fair, and Actionable Look Like?

• If you could wake up tomorrow with one new capability in your reporting, what single thing would remove the most uncertainty?
• Which pilot success signals would convince you the approach is working? Options: % Productivity delta vs baseline, Supervisor adoption rate, Associate sentiment scores, WMS integration accuracy, Error/accuracy maintained, Retention/turnover change, Other
• What minimum productivity improvement (percent) over baseline would feel like a meaningful win for a 60‑day pilot? Options: <5%, 5–8%, 8–12%, 12–20%, >20%
• What guardrails would you require to ensure productivity measurement is seen as fair and not punitive (examples: observer method, parallel measurement, delayed incentives)?
• Who must be satisfied internally for the pilot to proceed to a broader rollout (roles/stakeholders) — and who is likely to raise the loudest objections?

People & Politics — unions, HR, and the team’s feelings

• What concerns does HR or labor relations have about measuring individual performance more granularly? Options: Morale impact, Turnover increase, Perceived surveillance, Pay fairness disputes, Contract / CBA violations, Other
• Have you run any pilot or change initiative recently that affected associate sentiment? What went well or poorly in communications?
• What would reassure associates and union reps that standards are engineered fairly rather than arbitrarily assigned? Options: Transparent time‑study methods, Third‑party validation, Associate input sessions, Parallel measurement period before incentives, Guaranteed safety & accuracy metrics, Other
• Who are the internal champions and who are the likely blockers for a standards‑based pilot (names or roles)?
• How would you like us to participate in stakeholder conversations — technical brief, all‑hands Q&A, union walkthrough, or other? Options: Technical brief for IT/WMS, Operations leadership walkthrough, Supervisor training session, Union/HR joint session, All of the above, Other

Data & Systems Reality Check — can we measure what matters?

• What systems produce the primary operational records we’d need (WMS vendor/version, TMS, labor timeclock, scanner logs)?
• Which of these data feeds are available to export or stream today? Options: WMS task logs, Scanner/timestamp events, Timeclock punch data, Associate roster with roles, Zone maps & task definitions, None available / need enablement
• How often is WMS mapping and work assignment logic updated, and who owns the mapping? Options: Daily, Weekly, Monthly, Rarely/never, Unknown
• Do you have historical task‑level samples or time‑and‑motion studies we can review, and if so, how many observations exist? Options: None, Fewer than 50 observations, 50–200 observations, 200–1000 observations, 1000+ observations
• What are the biggest integration risks you foresee (data latency, mismatched task IDs, missing timestamps, headless devices)?

Picking the Right Pilot — a practical path to proof

• If we run a 60‑day pilot, which zone or task set would give the clearest signal of impact (high volume SKUs, peak zone, mixed SKUs, packing)? Options: High‑volume pick zone, Packing/packout, Returns processing, Multi‑SKU case pick, Staging/shipping, Other
• What criteria will you use to select the pilot area (volume, variability, supervisor skill, union sensitivity)? Options: High volume, Representative processes, Willing supervisor, Low union sensitivity, Easier integration, Other
• Who will be the operational owner of the pilot (name/role) and who will own data access and sign‑offs?
• What would be an acceptable timeline from kickoff to live measurement in that zone? Options: 2–4 weeks, 4–6 weeks, 6–8 weeks, 8–12 weeks, Longer
• Identify the top three blockers you expect to slow a 60‑day pilot and how you might mitigate each.

How We’ll Know We’ve Succeeded — acceptance and decision rules

• Beyond productivity percentage, what qualitative signals would indicate the pilot is ready to scale (supervisor confidence, associate acceptance, stable integration)?
• What minimum supervisor adoption and dashboard usage rate would you require to call the pilot operationally adoptive? Options: >90%, 75–90%, 50–75%, <50%
• How should we treat incentives during the pilot — withheld, deferred, or live from day one? Options: Withheld (measurement only), Deferred until verification, Live with guardrails, Decide after initial period
• What specific documentation or artifacts do you need at pilot close to make a go/no‑go decision (standards, raw time studies, integration logs, associate survey)? Options: Engineered standards document, Raw time‑study files, WMS integration mapping, Supervisor adoption metrics, Associate sentiment survey, ROI projection
• If the pilot hits its targets, what is the fastest realistic path to a broader rollout in months and scale (other zones, entire site, multi‑site)? Options: 1–2 months, 3–4 months, 5–6 months, 6+ months, Unsure

Quick Check‑In: Who I’m Talking With and What Matters Most

• What is your role and the primary DC or site you want us to focus on for a pilot? Options: DC Director, Operations Manager, Continuous Improvement Leader, HR Leader, Other
• How long have you been in this role at this site? Options: < 6 months, 6–12 months, 1–3 years, 3–7 years, 7+ years
• Right now, what single problem is keeping you up at night about this DC?
• Which of these metrics do you review most often when you try to understand labor performance? Options: Throughput per labor hour, Picks per shift, Labor cost per unit shipped, On‑time order fulfillment, OT hours / %, Accuracy / errors, Other
• If we ran a 60‑day pilot here, what's the one outcome that would make it an unqualified success for you?

Are We Quietly Carrying 10–25% Invisible Time?

• If your current reporting only shows aggregate picks per shift, how confident are you that it reflects individual performance variability? Options: Very confident, Somewhat confident, Not confident, I don't know
• Tell me about a recent day or week where volumes were 'normal' but throughput dropped — what did that feel like operationally?
• Where do you believe the majority of unmeasured or invisible time lives (select all that apply)? Options: Waiting for work / idle between tasks, Handoffs / batching delays, Scanning or system latency, Breaks / relief coverage gaps, Task switching / travel, Other
• How do you currently try to find the root cause when aggregate KPIs worsen—what steps have you taken and with what results?
• Who on your team owns the question 'why did productivity decline?' and how do they usually investigate it? Options: Operations Manager, CI Leader, Warehouse Supervisor, IT/WMS Admin, HR, Other

When the Numbers Don’t Tell the Whole Story

• What if your WMS‑native reports are masking a persistent 15–20% gap to what’s achievable—how disruptive would that be to your cost model? Options: Transformational, Significant, Moderate, Minimal, Unsure
• Which WMS reports or modules do you rely on today for labor insight? Options: Task completion logs, Workforce management module, Labor events / scans, Custom dashboards, None/Manual spreadsheets, Other
• Describe a specific example where the WMS or existing reports led you to the wrong conclusion about performance.
• How often do supervisors receive individual associate productivity feedback, and through what channels? Options: Real‑time dashboard, Daily huddle, Weekly reports, Ad hoc conversations, No formal feedback
• What data do you wish you had that you currently don't—be specific (events, timestamps, task granularity, associate context)?

What’s It Like for Supervisors and Associates?

• How concerned are you—and how does HR feel—about the risk that a productivity system could damage morale or increase turnover? Options: Extremely concerned, Somewhat concerned, Neutral, Not concerned
• Walk me through the last time an operational change (new tooling, metric, or incentive) was introduced—what went well and what didn't?
• What messages or communications have been effective here when introducing changes to front‑line associates? Options: All‑hands meetings, Supervisor briefings, On‑floor training, Printed job aids, Incentive examples, Other
• Do you have collective bargaining or union representation in this site? If yes, who is the primary point of contact and what are their typical concerns? Options: Yes — Local steward(s), Yes — Regional rep, No union presence, Prefer not to say
• How would you rate supervisor readiness to use a real‑time coaching dashboard on a scale from 'enthusiastic' to 'resistant'? Options: Enthusiastic, Open but cautious, Skeptical, Resistant, Mixed across supervisors

Where Does the Work Happen—and What Should We Measure?

• Which physical zones and task families do you think are the highest‑leverage for a pilot (e.g., small‑parts picking, pallet building, returns, packing)?
• If you had to pick one zone to prove the full methodology quickly, which would it be and why?
• How well are individual tasks decomposed today—do you have time studies, element lists, or only aggregate task labels in the WMS? Options: Detailed time studies exist, Partial element lists, Only aggregate task labels, No decomposition
• Which task elements would you prioritize for engineered standards (select up to three)? Options: Walking / travel, Picking per stop, Putaway placement, Packing unitization, Staging / loading, Returns handling, Other
• Are there seasonal or abnormal workflows (e.g., promotions, returns surge) we should avoid or include in a pilot? Options: Include — important to test, Avoid — skews baseline, Either — we can compensate, Not sure

What Would Real, Measurable Success Feel Like?

• If a pilot delivered a 12–20% improvement in measured productivity, what would you do first with that improvement (redeploy labor, reduce costs, improve service, etc.)? Options: Redeploy to peak areas, Reduce headcount/costs, Improve service / throughput, Improve OT / reduce overtime, Invest in training, Other
• Beyond % productivity gain, which acceptance criteria matter most for you (select up to three)? Options: Supervisor adoption rate, Associate sentiment, WMS integration fidelity, Accuracy / quality maintained, Retention impact, Forecasting improvements, Other
• Tell me about any reference accounts or prior pilots you’d like us to align against—what benchmarks or outcomes do you trust?
• What minimum measurable delta vs baseline would you personally view as a 'pass' for this 60‑day pilot? Options: ≥ 20%, 15–20%, 10–15%, 5–10%, < 5%
• How will final pilot success be presented and who signs off—operations, finance, HR, union, or an executive committee? Options: Operations, Finance, HR, Union rep, Executive sponsor, Cross‑functional committee

Integration & Data Reality Check — Can We Trust the Feeds?

• If our standards and dashboards rely on WMS events, what technical feeds are available today (select all that apply)? Options: API/REST access, Database read, Flat file/CSV exports, Message queue/EMM, None — manual logs only, Other
• Who owns WMS/data access decisions and approvals, and what is the expected timeline to grant read access for a pilot?
• Have you ever had mismatches between system‑assigned work and what an associate actually did (e.g., interleaving, cross‑dock exceptions)? Describe an example.
• How clean are your timestamps and scan events for correlating tasks to individuals (select one)? Options: Highly reliable, Mostly reliable with gaps, Sparse/noisy, No usable timestamps
• What constraints—security, privacy, or union rules—should we plan for when requesting event‑level data?

The People Equation: Communications, Training, and Union Engagement

• Who will be the pilot's day‑to‑day champions on the floor and in HR (names or roles)?
• How do you prefer associates be introduced to measurements—anonymous baseline period, training then measurement, or measurement with incentives from day one? Options: Anonymous baseline then reveal, Training → measurement → incentives, Measurement with immediate incentives, Other / hybrid
• What communications have historically reduced pushback during change (select all that apply)? Options: Supervisor‑led briefings, Union briefing and agreement, Printed FAQs, Incentive examples, Preview dashboards with reps, Other
• If union engagement is required, what outcomes do they typically insist on (e.g., third‑party validation, joint standard setting, appeal process)?
• What training cadence do you think supervisors need to adopt and sustain real‑time coaching habits (hours and format)? Options: 1–2 hour workshop, Half‑day hands‑on, Weekly coaching sessions for 4 weeks, Ongoing micro‑learning, Other

Risk, Trust, and What Could Break This Pilot

• What keeps you most worried about running a standards‑based pilot here? Options: Associate backlash, Inaccurate standards, WMS mismatches, Data access delays, No measurable improvement, Other
• Have you run a similar pilot before? If so, what was the single biggest lesson learned we should not repeat? Options: Yes — multiple pilots, One pilot, No prior pilots, Not sure
• If we encounter a contested standard or disputed measurement during the pilot, what process would you prefer to resolve it? Options: Joint review with union/rep, Third‑party time study, Supervisor investigation + documentation, Pause incentives until resolved, Other
• What dependencies outside our control could delay the pilot start (e.g., IT freeze, peak season, contract negotiations)?
• What would make you stop a pilot early—specify measurable or qualitative stop signs? Options: Significant associate churn, Accuracy degradation, Data feed failure, Worsening KPIs, Union injunction, Other

Commitment, Timeline, and Practical Next Steps

• Who must be involved and sign off to start a pilot within the next 30–60 days (roles/names)?
• Assuming approvals, how quickly can you provide the necessary sample data and system access? Options: < 2 weeks, 2–4 weeks, 4–8 weeks, Longer / need to discuss
• Which pilot model do you prefer to minimize disruption: run parallel measurement with no incentives, run with a small incentive test, or a phased rollout? Options: Parallel measurement (no incentives), Small incentive test, Phased rollout, Undecided
• What are two concrete criteria you want included in the pilot SOW (e.g., zones, KPIs, data ownership, dispute process)?
• Realistically, when would you like to reconvene to finalize scope and approvals? Options: This week, Next week, In 2–4 weeks, Longer than a month

Quick Snapshot — A 60‑second tour of this site

• Which description best fits this distribution center? Options: Retailer-owned DC, 3PL/fulfillment provider, Manufacturer distribution, Hybrid/multi‑use facility, Other
• How many associates are on site across all shifts (total headcount)? Options: Under 50, 50–149, 150–499, 500–1,499, 1,500+
• How many shifts and what are your primary shift patterns? Options: Single shift, Two shifts, Three shifts, Split shifts / flexible hours, Mix of above
• Which warehouse management or execution systems do you currently use? Options: WMS (commercial), Proprietary WMS, ERP-native WMS, No WMS / basic system, Other
• In one sentence, what would you say keeps you up at night about labor and productivity right now?

What If Your Numbers Are Hiding The Real Problem?

• If your reporting could be hiding 15–25% invisible unproductive time, how would that change your view of recent performance? Options: It would explain everything, It would explain some but not all, Unlikely — we'd investigate other causes, Not sure / need to explore
• Walk me through the trend: when did throughput per labor hour begin to decline, and what operational changes happened around that time?
• How do you currently calculate labor cost per unit and who owns that calculation? Options: Payroll-derived cost model, WMS task-based cost, Finance model (ERP), Ad‑hoc spreadsheets, Other
• Which parts of your current reports feel most misleading or incomplete (pick all that apply)? Options: Aggregate picks per shift, No per‑associate visibility, No task‑level standards, Inaccurate time stamping, No integration with WMS assignments
• Tell a specific story of a day or week that felt inexplicably bad — what happened and how did leaders respond?

Who Holds the Keys — and Who’s Quietly Worried?

• If a pilot changed how we measure individual productivity, who in your organization would be the most enthusiastic — and who would be most resistant? Options: Operations leadership, Continuous improvement, HR/People, Frontline supervisors, Union/associations, Finance
• Who is the formal decision owner for piloting new labor measurement tools (name/role)?
• What are HR’s top three concerns about introducing engineered standards and individual measurement? Options: Associate morale, Turnover risk, Legal/union pushback, Pay fairness, Privacy / surveillance
• Have you had prior union discussions or grievances related to performance measurement? If yes, briefly describe the outcome. Options: None, Informal conversations, Formal grievances filed, Existing collective bargaining language, Ongoing discussions
• How do frontline associates typically react to new performance initiatives — curiosity, skepticism, acceptance, or backlash? Give a recent example.

Show Me the Baseline — Where Do We Start Measuring?

• Which baseline KPIs are you currently tracking that a pilot must align with? Options: Picks per labor hour, Cartons per hour, Lines per hour, Labor cost per unit, Order accuracy, On‑time ship rate
• What critical reporting gaps would make a pilot’s results hard to trust? Options: No timestamped task data, Mismatch between WMS and time clocks, Missing headcount reconciliation, Unknown idle time causes, Poor historical data
• Which specific tasks or zones do you suspect contain the largest invisible productivity loss (e.g., picking, sorting, staging)? Options: Piece picking, Bulk picking, Packing/pack stations, Putaway, Replenishment, Staging & loading
• What magnitude of productivity improvement versus baseline would you consider meaningful (pick one)? Options: <5% (marginal), 5–10% (noticeable), 10–15% (valuable), 15–25% (transformational), 25%+ (unlikely but ideal)
• Are there seasonality or special campaigns during the upcoming 60 days that would skew pilot results? If so, list them and dates.

If We Could Measure Individual Work, How Would You Use It?

• Imagine supervisors had a real‑time dashboard showing per‑associate productivity against engineered standards — what would you want them to do differently? Options: Rebalance workloads, Deliver on‑the‑spot coaching, Adjust staffing or breaks, Investigate exceptions, Change shift assignments
• How frequently are supervisors coached on performance management today, and how comfortable are they with data‑driven coaching? Options: Daily — very comfortable, Weekly — somewhat comfortable, Occasionally — need training, Rarely — avoid data, Not sure
• What acceptance signals will convince you that supervisors actually adopted the tool during the pilot (examples: active sessions/day, coaching logs, reduction in exceptions)?
• How should we measure associate sentiment about feedback and measurement during and after the pilot? Options: Anonymous pulse surveys, Focus groups, One‑on‑one interviews, Union feedback sessions, HR metrics (turnover/absences)
• If a supervisor used the dashboard well for 60 days, what tangible operational changes would you expect to see? Options: More consistent throughput, Lower overtime, Faster exception resolution, Improved accuracy, No change

What Would Fair, Defensible Standards Look Like Here?

• If standards feel unfair to associates, what are the real consequences you worry about most? Options: Increased turnover, Lower morale/productivity, Union complaints, Safety incidents, Legal exposure
• Have you used time‑study or element‑based standards before? Briefly describe what worked or failed. Options: Never used, Used successfully, Used with resistance, Tried and abandoned, Ongoing program
• Which elements would make a standard defensible to labor reps here (pick all that apply)? Options: Transparent methodology, Representative sampling, Associate participation, Third‑party validation, Clear appeals process
• What percentage of daily tasks would you be comfortable being observed for time studies during the pilot? Options: <1% (small sample), 1–5%, 5–10%, 10–20%, 20%+
• Describe any legal, contractual, or cultural constraints we must honor when developing standards (e.g., bargaining unit clauses).

Who Needs to Touch the Data — and Can We Get It?

• If we asked for full WMS task logs and clock data for 60 days, how confident are you that those feeds exist and are accessible? Options: Fully accessible, Mostly accessible with engineering help, Partial / some missing, Not available
• Which systems should we plan to integrate for the pilot (select all that apply)? Options: WMS task/assignment API, Time & attendance system, HR roster/payroll, Mobile devices / scanner logs, TMS / shipping data, Other
• Who will be our technical contact for data access and mapping (role or team)?
• Are there specific privacy, security, or PII constraints we must follow for associate data? Options: Yes — strict constraints, Yes — standard confidentiality, No special constraints, Unknown / need to check
• Where have you seen the most mismatch between WMS work assignments and what associates actually do? Options: Assignment timing, Task types, Scan missing events, Interleaving / multi‑tasking, Other

Pilot Mechanics — Design a 60‑Day Test You’d Trust

• If you could pick one zone to pilot that would be both high‑impact and politically feasible, which would it be? Options: Primary picking zone, Packing/pack stations, Sortation/staging, Inbound putaway, Returns processing, Other
• Which core tasks should the pilot establish engineered standards for (select up to five)? Options: Piece picking, Case picking, Packing, Replenishment, Putaway, Loading/manifesting, Returns processing
• What does a defensible measurement plan look like to you (choose components we must include)? Options: Baseline time study, Engineered standard development, Parallel tracking period (no incentives), Supervisor coaching logs, Associate sentiment surveys, Integration validation checks
• How would you like the pilot’s decision rule for broader rollout to be framed (examples: X% productivity lift AND supervisor adoption threshold)?
• What incentives or gating criteria should tie to pilot success (financial, operational, or governance triggers)? Options: Productivity gain threshold, Supervisor adoption metric, No negative impact to accuracy, HR/union acceptance, Data/integration stability

What Could Break the Pilot — And How Would We Recover?

• If associate morale dipped during the pilot, what immediate actions would you expect operations and HR to take? Options: Pause communications, Halt pilot, Increase town halls/education, Adjust standards, Offer temporary incentives
• What are the top three technical failure modes you fear (e.g., integration mismatch, data latency, device outages)?
• How would disputes about a standard or measurement be escalated and resolved here? Options: Supervisor assessment, CI team review, HR mediation, Union grievance process, Third‑party audit
• If the pilot produced conflicting signals (e.g., productivity up but accuracy down), which outcome would be prioritized for go/no‑go? Options: Prioritize accuracy/safety, Prioritize productivity, Require both to pass, Contextual review
• Who on your team will own day‑to‑day pilot issues (name/role) and who signs the final go/no‑go?

How Will We Know This Was Worth Doing?

• Beyond the headline productivity number, what three outcomes would make you call the pilot a success?
• Which long‑term metrics would you expect to track after rollout to validate sustained value? Options: Labor cost per unit, Turnover rate, Overtime hours, Order accuracy, Supervisor coaching frequency, Service level
• What reference evidence from other accounts would make you more comfortable (e.g., case studies showing X% lift in similar size facilities)? Options: Peer DC case studies, Industry benchmarks, Third‑party validation, On‑site demo results, None required
• If we commit to a 60‑day pilot, what is your preferred pilot start window (next 30 days, next 31–60 days, next quarter, flexible)? Options: Next 30 days, 31–60 days, Next quarter, Flexible / TBD
• What would make you personally confident enough to champion a pilot to your leadership team?

Practical Next Steps — Who, When, and How Much?

• Who are the three must‑involve stakeholders we should schedule a kickoff with (name/role)?
• What is the internal timeline for a pilot decision and budget approval (choose the best fit)? Options: Decision in 2 weeks, Decision in 1 month, Decision in 1–3 months, Undetermined / needs alignment
• What level of investment would you expect to allocate for a defensible 60‑day pilot (options are ranges)? Options: <$25k, $25–50k, $50–100k, $100k+
• How would you prefer we present pilot results to your leadership — a short executive brief, a detailed technical report, or a joint onsite review? Options: Executive brief, Detailed report, Onsite presentation, Interactive dashboard access
• Is there anything else we haven’t asked that you think would make this pilot fair, useful, and defensible for your operation?