Energy Management System (EnMS) Improvement Opportunity Finder

Explore Facilities Across the US

Click a bubble to search that state's industry

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Powered by DOE Industrial Assessment Center data — 180,000+ recommendations across 20,000+ facility assessments (1976–present). Learn more ↗

Your Facility Profile

How are recommendations ranked?

Recommendations are drawn from the DOE Industrial Assessment Center (IAC) database , which contains over 180,000 energy improvement recommendations from assessments conducted at US manufacturing facilities since 1976.

Each recommendation is ranked using a composite score that weights: median energy cost savings (40%), historical implementation rate (35%), statistical confidence based on sample size (15%), and median payback period (10%).

Results are filtered to facilities with the same 2-digit NAICS industry code as the one you enter. Savings estimates are inflation-adjusted to current dollars.

Industry (NAICS Code)

State

Energy Types Used optional — filters results

Electricity Natural Gas Steam Fuel Oil / Propane

Annual Energy Cost ($) personalizes savings estimates

Adds a personalized savings estimate based on your energy spend.

Number of Employees

Analyzing assessment data…

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Priority Matrix

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Savings Breakdown

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Implementation Rate

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Payback Period

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Savings vs. Payback

Priority Matrix: Where Should You Focus?

What this shows: Each bubble is a recommendation category, placed by how quickly it pays back (X-axis) vs. how much it saves (Y-axis). Bigger bubbles mean more facilities implemented that recommendation.

How it's calculated: Categories are ranked relative to each other in this result set. X-axis uses percentile rank of payback period (shorter payback = further right). Y-axis uses percentile rank of median annual savings (higher savings = further up). Bubble size reflects implementation rate.

Key takeaways:

Quick Wins (top-right): High savings + short payback — start here
Strategic (top-left): High savings but longer payback — plan ahead
Consider (bottom-right): Lower savings but easy to implement
Low Priority (bottom-left): Lower savings + longer payback

X-axis: shorter payback → easier to implement | Y-axis: higher median savings → more impact | Bubble size: implementation rate

Where Do the Savings Come From?

What this shows: The share of total median savings contributed by each recommendation category. Larger slices indicate categories with higher annual dollar savings.

How it's calculated: Each category's median annual savings (in USD) is divided by the total median savings across all categories. Percentages show each category's share.

Key takeaways: The largest slices represent the biggest savings opportunities. Even small-percentage categories can be worthwhile if they're easy to implement.

How Often Are These Implemented?

What this shows: The percentage of times each recommendation was actually implemented after being suggested in an IAC assessment.

How it's calculated: For each category, we count how many times it was implemented vs. total times recommended, based on the IAC database IMPSTATUS field.

Key takeaways: High implementation rates signal practical, proven recommendations. Categories above 50% are well-accepted by industry. Low rates may indicate higher barriers (cost, complexity, or disruption).

How Quickly Do These Pay Back?

What this shows: A boxplot showing how long each recommendation category takes to pay for itself, with the spread from the 25th to 75th percentile and a median line.

How it's calculated: Payback = implementation cost ÷ annual savings. The box spans P25 to P75 (the middle 50% of outcomes). The vertical line inside the box marks the median payback.

Key takeaways: Narrow boxes close to zero pay back quickly and consistently. Wide boxes mean results vary — your specific savings depend on facility details. Color indicates speed: green ≤ 1 yr, blue ≤ 2.5 yr, orange = longer.

Savings vs. Payback: All Categories

What this shows: Each bubble is an improvement category aggregated across all industries. X-axis = average payback period, Y-axis = average median savings. Bubble size = total recommendations in that category.

Key takeaways: Categories in the top-left (high savings, short payback) offer the best ROI. Larger bubbles mean the category appears more frequently across facility assessments.

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Welcome to the Energy Management System (EnMS) Improvement Opportunity Finder