Welcome back to the Mind Your Data Series, the training series focused on improving data quality one element at a time.

DATA NEWSLETTER

This month, we're spotlighting utilization, one of the most misunderstood data points in HMIS. At its core, utilization measures how fully a project’s available inventory (beds or units) is being used over time. While the calculation itself is straightforward, the data behind it often reveals deeper workflow and data quality issues that can affect federal reporting, funding conversations, and system-level planning.

Understanding how utilization is calculated and what drives over/under utilization can help agencies identify and correct data issues before they surface as flags in HUD reporting.

What Is Utilization? In HMIS reporting, utilization is calculated as:

Bed Utilization: Daily Average Number of People Served / Daily Average of Number of Beds Available.

The resulting rate is evaluated at both the project and household type level.

This calculation relies on two foundational data sources:

Enrollment data (entries, exits, household type, and move-in date (PH only))
Inventory data (beds/units, inventory dates, household type)

If either side of that equation is inaccurate, utilization will be skewed.

Note: Utilization applies to all residential projects (Interim Housing, Time Limited Subsidy and Permanent Housing), not just projects that are using the inventory module.

Why Utilization Matters: Utilization impacts multiple HUD related processes, including:

Longitudinal System Analysis (LSA)
System Performance Measures (SPMs)
Annual Performance Reports (APRs)
Capacity planning and funding decisions

High or low utilization flags may prompt additional review, targeted outreach, or data correction requests. Utilization data also feeds directly into the Annual Homelessness Assessment Report (AHAR), which HUD uses to produce national estimates of homelessness. Accurate utilization ensures system performance is interpreted correctly and that programs are not misrepresented in federal reporting.

Under Utilization

Under-utilization occurs when fewer people are recorded as being served than the number of beds available. Common causes include:

All Project Types:

Delayed or missing client entries

Night-by-night shelters:

Missing bed services

Permanent housing, move-in dates that are:

Missing
Invalid (move in date is prior to project start date)
Recorded for someone other than the head of household
Household enrollment errors (accidentally enrolling a child separate from their guardian)
Inventory start or end dates not aligned with actual operations
A gap between a project’s operating start date and when it served its first client
A gap between when a project stopped serving clients and when the project was closed
A mismatch between household type served and inventory setup can result in under-utilization. For example, a project configured with 30 beds for Households with Children but serving an average of 20 people per night will show a utilization rate of 66.7% (20 people ÷ 30 beds).

Under-utilization does not always mean that beds are physically empty, but it could indicate that the data is not fully reflecting program activity. If the project is under-utilized and the rate is not the result of a data quality issue, providers are encouraged to submit a support ticket to connect with the Data Analytics team for further discussion.

Over Utilization

Over-utilization occurs when more people are recorded as being served than the number of beds available. This is often caused by:

Missing or delayed exits
Household enrollment errors, such as enrolling a child separately from their guardian, may result in people being counted against inventory for household types the project does not operate.
Beds removed from inventory without corresponding enrollment updates
Enrollments spanning outside active inventory dates
A mismatch between household types served and inventory household type designations (a project with 100 beds expected to serve 70% Single Adult Households and 30% Households with Children, set their inventory to 70 beds for Single Adults and 30 for Households with Children. However, they ended up serving 20 Households with Children on average each night, resulting in a utilization rate for Households with Children of 66.7% (20 avg people/30 average beds).

How to Improve Utilization Data

Agencies can proactively reduce utilization errors by:

Running the GNRL-106 Program Roster to validate who should still be enrolled

Confirm inventory bed counts and dates
Ensure entries and exits are recorded in real time
Verify household size and type at entry
Review Length of Stay for stalled or missing exit

If daily census consistently exceeds available beds → over-utilization.

If census is consistently below available beds → under-utilization.

Important Reminder: Utilization is not corrected in a report, it is corrected by updating HMIS:

Entries and exits
Household composition
Inventory setup (when appropriate)

The report only surfaces the issue. Small, routine data checks throughout the year can prevent large scale corrections later.

FINAL THOUGHT: Utilization reflects how inventory and enrollment data interact in HMIS and may indicate data quality issues, operational constraints, or program performance trends. When data accurately reflects day-to-day operations, utilization becomes a valuable tool for understanding capacity, planning services, and interpreting system performance.

Mind your data now, so it doesn't surprise you later...

Submit a support ticket:

LAHSA's Enterprise Ticketing System

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Every Thursday from 2 PM - 3 PM

HMIS Office Hours

Data, Explained: LAHSA's Data Quality Monitoring Plan

LAHSA’s Data Quality Monitoring Plan (DQMP) ensures HMIS data is accurate, reliable, and actionable so providers and policymakers can understand needs, track progress, and improve outcomes. Check out our website to take a deeper dive into LAHSA's data quality framework:

LAHSA's DQMP Website

LAHSA is a joint powers authority of the City and County of Los Angeles, created in 1993 to address the problem of homelessness in Los Angeles County. LAHSA is the lead agency in the HUD-funded Los Angeles Continuum of Care, and coordinates and manages federal, state, county, and city funds for programs providing shelter, housing, and services to people experiencing homelessness.

Los Angeles Homeless Services Authority