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<title>ACME Corporation — Portfolio Analysis (Jan 1 to May 11, 2026)</title>
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<header>
<h1>ACME Corporation — Portfolio Analysis</h1>
<p class="subtitle">Jan 1 to May 11, 2026 · 93 weekdays · sensor occupancy + badge entries</p>
</header>
<div class="tldr">
<span class="label">TL;DR</span>
<p>The portfolio runs at a healthy-looking 64% peak Utilization, but the blended number hides two very different stories: New York Headquarters has structurally imbalanced floors (1st and 2nd routinely above sensor capacity, while 3rd, 4th, 6th and 7th sit at 47–56%) and Austin Office is operating at one-fifth of its built capacity. Badge data systematically overstates measured headcount by 18% across both buildings — use the sensor numbers when capacity decisions are on the line.</p>
</div>
<h2>Key metrics</h2>
<div class="metrics-grid">
<div class="metric-card">
<div class="label">Portfolio peak Utilization</div>
<div class="value">64%</div>
<div class="context">3,852 of 6,053 capacity</div>
</div>
<div class="metric-card">
<div class="label">NY HQ peak Utilization</div>
<div class="value">67%</div>
<div class="context">3,789 of 5,700 capacity</div>
</div>
<div class="metric-card">
<div class="label">Austin peak Utilization</div>
<div class="value">22%</div>
<div class="context">79 of 353 capacity</div>
</div>
<div class="metric-card">
<div class="label">Underused NY HQ floors</div>
<div class="value">4</div>
<div class="context">3rd, 4th, 6th, 7th — 47-56% peak</div>
</div>
<div class="metric-card">
<div class="label">Over-capacity NY HQ floors</div>
<div class="value">2</div>
<div class="context">1st & 2nd hit 100-143% on P90 days</div>
</div>
<div class="metric-card">
<div class="label">Badge overcount factor</div>
<div class="value">+18%</div>
<div class="context">Badges vs. sensor headcount</div>
</div>
</div>
<h2>Patterns</h2>
<h3>Day-of-week — NY HQ peak Utilization</h3>
<p>Mondays and Tuesdays are the busiest, with a midweek dip on Wednesday and Friday lighter by 27% versus the M/T peak. Sensor and badge data tell the same story about when the building is busy — they only disagree on the absolute number.</p>
<div class="dow-chart">
<div class="dow-row">
<span class="day">Monday</span>
<div class="bar-track"><div class="bar-fill" style="width: 100%;"></div></div>
<span class="value">73% peak</span>
</div>
<div class="dow-row">
<span class="day">Tuesday</span>
<div class="bar-track"><div class="bar-fill" style="width: 99%;"></div></div>
<span class="value">72% peak</span>
</div>
<div class="dow-row">
<span class="day">Wednesday</span>
<div class="bar-track"><div class="bar-fill" style="width: 87%;"></div></div>
<span class="value">64% peak</span>
</div>
<div class="dow-row">
<span class="day">Thursday</span>
<div class="bar-track"><div class="bar-fill" style="width: 96%;"></div></div>
<span class="value">70% peak</span>
</div>
<div class="dow-row">
<span class="day">Friday</span>
<div class="bar-track"><div class="bar-fill" style="width: 73%;"></div></div>
<span class="value">53% peak</span>
</div>
</div>
<h3>Day-of-week × hour-of-day heatmap (NY HQ badge entries)</h3>
<p>The classic two-peak office pattern: a strong morning rush at 8-9am and an evening exit peak at 4-5pm, with a softer lunch crest at noon. Friday is materially lighter across every hour. Cells outside 7am-7pm are essentially empty and omitted.</p>
<div class="heatmap-wrap">
<table class="heatmap" aria-label="Average granted badge entries per weekday and hour at New York Headquarters">
<thead>
<tr>
<th></th>
<th>7</th><th>8</th><th>9</th><th>10</th><th>11</th><th>12</th><th>13</th><th>14</th><th>15</th><th>16</th><th>17</th><th>18</th>
</tr>
</thead>
<tbody>
<tr>
<th>Monday</th>
<td style="background: #FCFCFF;"></td>
<td style="background: #0A091D;"></td>
<td style="background: #0A091D;"></td>
<td style="background: #FCFCFF;"></td>
<td style="background: #FCFCFF;"></td>
<td style="background: #4F46E5;"></td>
<td style="background: #A6A1F2;"></td>
<td style="background: #A6A1F2;"></td>
<td style="background: #D1CFF9;"></td>
<td style="background: #282373;"></td>
<td style="background: #282373;"></td>
<td style="background: #D1CFF9;"></td>
</tr>
<tr>
<th>Tuesday</th>
<td style="background: #FCFCFF;"></td>
<td style="background: #0A091D;"></td>
<td style="background: #282373;"></td>
<td style="background: #FCFCFF;"></td>
<td style="background: #FCFCFF;"></td>
<td style="background: #4F46E5;"></td>
<td style="background: #A6A1F2;"></td>
<td style="background: #A6A1F2;"></td>
<td style="background: #D1CFF9;"></td>
<td style="background: #282373;"></td>
<td style="background: #282373;"></td>
<td style="background: #D1CFF9;"></td>
</tr>
<tr>
<th>Wednesday</th>
<td style="background: #FCFCFF;"></td>
<td style="background: #0A091D;"></td>
<td style="background: #282373;"></td>
<td style="background: #FCFCFF;"></td>
<td style="background: #FCFCFF;"></td>
<td style="background: #A6A1F2;"></td>
<td style="background: #A6A1F2;"></td>
<td style="background: #A6A1F2;"></td>
<td style="background: #D1CFF9;"></td>
<td style="background: #4F46E5;"></td>
<td style="background: #4F46E5;"></td>
<td style="background: #D1CFF9;"></td>
</tr>
<tr>
<th>Thursday</th>
<td style="background: #FCFCFF;"></td>
<td style="background: #0A091D;"></td>
<td style="background: #282373;"></td>
<td style="background: #FCFCFF;"></td>
<td style="background: #FCFCFF;"></td>
<td style="background: #4F46E5;"></td>
<td style="background: #A6A1F2;"></td>
<td style="background: #A6A1F2;"></td>
<td style="background: #D1CFF9;"></td>
<td style="background: #282373;"></td>
<td style="background: #282373;"></td>
<td style="background: #D1CFF9;"></td>
</tr>
<tr>
<th>Friday</th>
<td style="background: #FCFCFF;"></td>
<td style="background: #282373;"></td>
<td style="background: #4F46E5;"></td>
<td style="background: #FCFCFF;"></td>
<td style="background: #FCFCFF;"></td>
<td style="background: #A6A1F2;"></td>
<td style="background: #D1CFF9;"></td>
<td style="background: #D1CFF9;"></td>
<td style="background: #FCFCFF;"></td>
<td style="background: #4F46E5;"></td>
<td style="background: #4F46E5;"></td>
<td style="background: #FCFCFF;"></td>
</tr>
</tbody>
</table>
<div class="heatmap-legend">
<span>0</span>
<div class="gradient"></div>
<span>~920</span>
<span style="margin-left:8px;">Avg granted entries per hour</span>
</div>
</div>
<h3>NY HQ floor breakdown</h3>
<p>The 64% portfolio number masks an enormous spread floor by floor. Four floors sit half-empty while two are over their declared sensor capacity. This is a relocation problem, not a capacity problem.</p>
<table>
<thead>
<tr><th>Floor</th><th class="num">Capacity</th><th class="num">Avg peak</th><th class="num">Util (avg peak)</th><th class="num">Util (max)</th></tr>
</thead>
<tbody>
<tr><td>1st Floor East</td><td class="num">350</td><td class="num">337</td><td class="num">96%</td><td class="num" style="color: var(--bad); font-weight: 600;">131%</td></tr>
<tr><td>1st Floor West</td><td class="num">520</td><td class="num">477</td><td class="num">92%</td><td class="num">99%</td></tr>
<tr><td>2nd Floor East</td><td class="num">820</td><td class="num">888</td><td class="num" style="color: var(--bad); font-weight: 600;">108%</td><td class="num" style="color: var(--bad); font-weight: 600;">143%</td></tr>
<tr><td>2nd Floor West</td><td class="num">760</td><td class="num">759</td><td class="num">100%</td><td class="num" style="color: var(--bad); font-weight: 600;">125%</td></tr>
<tr><td>3rd Floor</td><td class="num">210</td><td class="num">118</td><td class="num">56%</td><td class="num">72%</td></tr>
<tr><td>4th Floor</td><td class="num">700</td><td class="num">370</td><td class="num">53%</td><td class="num">65%</td></tr>
<tr><td>5th Floor</td><td class="num">900</td><td class="num">671</td><td class="num">75%</td><td class="num">90%</td></tr>
<tr><td>6th Floor</td><td class="num">550</td><td class="num">303</td><td class="num">55%</td><td class="num">100%</td></tr>
<tr><td>7th Floor</td><td class="num">890</td><td class="num">422</td><td class="num">47%</td><td class="num">52%</td></tr>
</tbody>
</table>
<h2>Trend</h2>
<div class="trend-block">
<svg viewBox="0 0 600 80" preserveAspectRatio="none" aria-label="Daily peak occupancy at NY HQ over the window, essentially flat">
<line x1="0" y1="40" x2="600" y2="40" stroke="#e5e7eb" stroke-width="0.5" stroke-dasharray="2,3"/>
<polyline
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stroke="#A6A1F2" stroke-width="1.5" fill="none"/>
</svg>
<div class="trend-stats">
<div class="classification">No clear trend</div>
<div class="meta">−0.04% over 93 days · R² = 0.00</div>
</div>
</div>
<p>NY HQ peak occupancy was essentially flat across the 4½-month window — the visible up-down rhythm is the strong day-of-week pattern (Mon/Tue high, Friday low), not directional change. Today's imbalance won't fix itself.</p>
<h2>Notable days (badge data only)</h2>
<p>The sensor data flagged zero anomalies at z ≥ 2.0 — NY HQ is a regular building. The badge dataset flagged three days, all of which are noise artifacts of badge variance rather than real events. If your badge system raises an alert on one of these days, cross-check the sensor data before treating it as signal.</p>
<div class="anomalies">
<div class="anomaly-card high">
<div class="date">Thu, Jan 8</div>
<div class="headline">5,388 entries</div>
<div class="compare">vs. typical Thursday of 4,696</div>
<div class="z">z = +3.05</div>
</div>
<div class="anomaly-card low">
<div class="date">Tue, Feb 17</div>
<div class="headline">4,097 entries</div>
<div class="compare">vs. typical Tuesday of 4,844</div>
<div class="z">z = −2.66</div>
</div>
<div class="anomaly-card low">
<div class="date">Fri, Apr 24</div>
<div class="headline">3,259 entries</div>
<div class="compare">vs. typical Friday of 3,608</div>
<div class="z">z = −2.22</div>
</div>
</div>
<h2>Data notes</h2>
<p><strong>Sources.</strong> Source occupancy is a daily Occuspace export (one row per location-day with intraday peak preserved); badge data is daily entries plus event-level swipes from the access-control system. The 93-day window is already filtered to operating hours (Mon–Fri, 9am–5pm).</p>
<p><strong>Capacity baseline.</strong> NY HQ 1st and 2nd Floor utilization peaks above 100% likely indicate either real overcrowding or stale capacity numbers in the building system. Confirm with Facilities before headlining the figure externally.</p>
<p><strong>Badge ↔ sensor reconciliation.</strong> Aggregated badge entries reconcile with sensor Traffic at expected ratios (Austin ~1.0; NY HQ ~2.2 — the higher NY HQ multiplier reflects internal floor-to-floor movement, which is exactly the behavior badges count and sensors don't).</p>
<h2>Recommendations</h2>
<ol class="recs">
<li>
<strong>Verify the NY HQ 1st and 2nd Floor capacity baselines with Facilities this week.</strong>
<p>Utilization above 100% on a P90 day means either real overcrowding (a safety conversation) or an outdated capacity number (a data-cleanup conversation). Both block any reliable use of the portfolio Utilization metric until resolved.</p>
</li>
<li>
<strong>Pilot moving one team from 1st/2nd Floor to 7th Floor over the next 60 days.</strong>
<p>The 7th Floor's 47% peak Utilization translates to ~470 empty seats at typical peak — enough to relieve the over-capacity floors with room to spare. Use the existing badge-and-sensor data to measure the rebalance, not just headcount before/after.</p>
</li>
<li>
<strong>Right-size Austin Marketing's footprint.</strong>
<p>14% peak Utilization for 19 straight weeks is a structural mismatch, not a fluctuation. An 80-seat zone supporting an 11-person typical peak should consolidate into the same zone as Operations (which runs at 68% — the only Austin department actually using its space).</p>
</li>
<li>
<strong>Codify Mon/Tue/Thu as anchor days at NY HQ.</strong>
<p>Wednesday dips ~14% and Friday drops 27% versus the M/T peak. A hybrid policy that requires Mon/Tue/Thu in-office while leaving Wed/Fri optional would match the existing pattern instead of fighting it, and it would let Facilities scale services (cleaning, catering, security) accordingly.</p>
</li>
<li>
<strong>Use sensor numbers, not badge numbers, for any capacity discussion going forward.</strong>
<p>Badge data overstates concurrent occupancy by ~18% portfolio-wide. Badges are great for "who came in"; they're the wrong tool for "are we full?" or "do we need more space?" — and the +18% inflation on a capacity question would invite a wrong answer.</p>
</li>
</ol>
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