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How to Calculate Andon System ROI

Learn how to calculate Andon system ROI. Framework for building a business case including downtime costs, labor savings, and payback period calculation.

"Cost and ROI justification to owners needed."

That sentiment appears frequently when manufacturers evaluate Andon systems. The technology makes sense operationally—but the business case needs numbers.

This article provides a framework for calculating Andon system ROI. You'll learn how to quantify current costs, estimate realistic improvements, and build a credible business case that finance teams can support.

The ROI Framework for Andon Systems

ROI calculation follows a straightforward formula:

ROI = (Annual Savings - System Cost) / System Cost × 100

For Andon systems, savings come from three primary categories:

  1. Downtime reduction — Less wait time means more production
  2. Labor efficiency — Less time walking and searching
  3. Quality improvement — Faster support reduces defects
The system cost is typically a one-time investment (hardware, software, installation), possibly with minimal ongoing costs. Savings accumulate monthly, making payback period the most useful metric for evaluation.

Step 1: Calculate Your Current State Costs

Before estimating what an Andon system will save, you need to understand what the current state costs.

Identifying Wait Time

Wait time is often invisible because it isn't tracked. But the examples are everywhere:

"I had one guy the other day go into our other building... for an hour and a half, he wasn't—he didn't know that they're pressing."

That's 90 minutes of lost response time from a single missed call. The operator waited. Production stopped. No one knew.

"Operators wait for forklift to drive past to request help."

That's ad hoc communication—hoping someone happens by when you need them.

"Welders and tradesmen waiting hours for supervisor rounds."

That's systematic waiting built into the process—help comes on a schedule, not on demand.

How to Estimate Wait Time If Not Tracked

If you don't have wait time data, use one of these approaches:

Time studies: Have supervisors track call-to-response times for one week. This provides baseline data, though manual tracking typically underestimates wait time.

Operator interviews: Ask operators how long they typically wait for maintenance, materials, or quality support. Their estimates tend to be accurate because they experience the wait.

Shift observation: Shadow a production area for a shift and record every help request and response time.

Even rough estimates are better than nothing. If operators say they wait "about 10 minutes" for maintenance on average, use that number.

Calculating Downtime Cost Per Minute

Downtime cost depends on your operation, but the formula is:

Downtime cost = (Operator rate + Lost production value) × minutes

For operator rate, use loaded labor cost (wages plus benefits), typically 1.3-1.5× base wage.

For lost production value, consider:

Example: If an operator costs $30/hour loaded, and the line produces $200/hour in margin, downtime costs ($30 + $200) ÷ 60 = $3.83 per minute.

Labor Walking Time

Beyond operator wait time, calculate time spent finding people:

Responder search time: Maintenance techs walking the floor looking for who called. Quality inspectors checking multiple stations. Supervisors doing rounds.

Supervisor status checks: Walking the floor to identify problems because there's no automated visibility.

Operator abandonment: Operators leaving their station to find help because no one responded.

Estimate weekly hours spent on these activities. Convert to annual cost.

Quality Costs

Delayed quality support creates defects:

Quality costs are harder to quantify precisely, but even a rough estimate belongs in the analysis.

Step 2: Estimate Improvement Potential

This is where many ROI calculations lose credibility. Assuming 90% improvement sounds impressive but triggers skepticism.

Use Conservative Estimates

For credible projections, assume:

These ranges are achievable and defensible. You can exceed them, but starting conservative builds trust.

What Drives Improvement

Automatic notification: Instead of hoping someone notices, every call reaches the right responder immediately. No missed pages. No forgotten radio calls.

Escalation: If the primary responder doesn't acknowledge, backup responders get notified. Calls don't sit unanswered.

Documentation: Every call is logged with timestamps. This enables identification of chronic issues and targeted improvement.

Visibility: Dashboards show current status. Supervisors see problems without walking the floor.

Step 3: Calculate Payback Period

Payback period is typically more useful than ROI percentage because it answers the practical question: how long until this pays for itself?

Payback period = System cost ÷ Monthly savings

Example Calculation

Current State:

VariableValue
Calls per day30
Average wait time8 minutes
Operator loaded rate$30/hour
Days per month22
Daily wait cost: 30 calls × 8 minutes × ($30 ÷ 60) = $120/day

Monthly wait cost: $120 × 22 days = $2,640/month

Estimated improvement: 40% reduction in wait time

Monthly savings: $2,640 × 40% = $1,056/month

System cost: Assume $15,000 for hardware and software

Payback period: $15,000 ÷ $1,056 = 14.2 months

This example only includes operator wait time. Add walking time, production value lost, and quality costs for a more complete picture.

Variables That Accelerate Payback

Higher call volume: More calls mean more opportunities for savings. A plant with 100 calls per day sees faster payback than one with 20.

Higher labor rates: Plants with higher wages see larger dollar savings from the same time reduction.

Longer current wait times: If operators currently wait 15 minutes on average, improvement potential is larger than if they wait 5 minutes.

Higher production value: Lines with expensive products or tight margins benefit more from reduced downtime.

Step 4: Include Soft Benefits

Some benefits don't translate directly to dollars but matter for the business case.

Accountability

With documented response times, performance conversations become fact-based rather than anecdotal. "Response time averaged 12 minutes last month" is different from "I feel like maintenance takes too long."

This data enables fair assessment and targeted improvement.

Operator Morale

Operators notice when their calls go unanswered. The frustration of waiting—especially when production targets depend on getting help—affects engagement and retention.

"Paper-driven downtime tracking" doesn't capture this frustration. It just records that there was downtime, not that someone waited 20 minutes feeling ignored.

When operators know that pressing a button produces a response, their experience of work improves.

Management Visibility

"No automated way to track downtime."

Without data, management operates on anecdotes and impressions. Problems that happen during second shift go unreported. Chronic issues aren't recognized as patterns.

Automated tracking provides visibility that paper logs can't match—complete, accurate, and immediate.

Sample ROI Calculation Template

Use this template to build your own analysis:

Input Variables

CategoryVariableYour Value
VolumeCalls per day_____
Operating days per month_____
TimeAverage wait time (minutes)_____
Walking time saved per call (minutes)_____
RatesOperator loaded rate ($/hour)_____
Production value ($/hour)_____
ImprovementEstimated wait time reduction (%)_____
CostSystem cost ($)_____

Current State Cost Calculation

Cost ElementFormulaMonthly Cost
Operator wait timeCalls × Wait × Rate ÷ 60 × Days$_____
Lost productionCalls × Wait × Production ÷ 60 × Days$_____
Walking timeHours × Rate × 4.33 weeks$_____
Quality (estimate)_____$_____
Total monthly cost$_____

Savings and Payback

MetricCalculationResult
Monthly savingsTotal cost × Improvement %$_____
Annual savingsMonthly × 12$_____
Payback periodSystem cost ÷ Monthly savings_____ months
First-year ROI(Annual savings - Cost) ÷ Cost × 100_____%

Common ROI Mistakes to Avoid

Mistake 1: Overstating Improvement

Claiming 80% or 90% improvement looks good on paper but damages credibility. Finance teams and operations leaders will question aggressive assumptions.

Use 30-50% for initial projections. If actual results exceed this, you'll look conservative rather than optimistic.

Mistake 2: Ignoring Walking Time

Many analyses focus only on operator wait time. But supervisors, maintenance techs, and quality inspectors spend significant time walking the floor—checking status, searching for problems, responding to issues they happen to notice.

This walking time is real cost that improved communication can reduce.

Mistake 3: Not Measuring Current State

You can't calculate improvement without a baseline. If you don't know current wait times, conduct time studies before finalizing ROI projections.

One week of measurement provides enough data to establish baselines.

Mistake 4: Forgetting Compounding Value

The initial ROI calculation captures direct savings. But the data an Andon system generates enables continuous improvement:

This data drives operational improvements beyond the initial response time gains. Value compounds over time.

Frequently Asked Questions

What if we don't know our current wait times?

Estimate based on operator interviews, or conduct a one-week time study. Even rough numbers are better than none. If operators say they wait "about 10 minutes," use 10 minutes.

What's a typical payback period?

Payback varies widely based on call volume, labor rates, and current wait times. Typical ranges are 6-18 months. High-volume plants with significant wait time often see payback under 12 months.

How do I present this to finance?

Focus on payback period rather than ROI percentage. Show your assumptions clearly. Use conservative improvement estimates (30-50%). Include sensitivity analysis—what if improvement is only 25%?

Should I include quality savings?

Yes, but estimate conservatively. If you can tie specific defects to delayed quality support, quantify those. Otherwise, include a modest estimate or note it as additional upside.

Building Your Business Case

ROI calculation transforms "this seems like a good idea" into "this will pay for itself in X months."

The framework is straightforward:

  1. Quantify current wait time and its cost
  2. Estimate realistic improvement (30-50%)
  3. Calculate payback period
  4. Include soft benefits for complete picture
Conservative assumptions build credibility. Clear documentation enables approval. And once implemented, actual data proves whether projections were accurate.

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