CRM Data Stream Connected

Your CRM Data Has a Story to Tell. Are You Listening?

We connected to a building services CRM with read-only access and ran a single day's schedule through our digital analysts. Here is what the data revealed that standard reporting never shows.

CRM Data Stream
Job Management Platform
Scanning
Engineers deployed
16
Active jobs
~30
Sites covered
20+
Customer groups
12
Status fields populated
0%
Top 2 clients share
63%
Insights Extracted
Revenue
21:6
Reactive to quoted ratio
Capacity
40%
Workforce in 4 projects
Experience
0/30
Jobs with live status
0
Engineers deployed on a single day
~30
Distinct jobs scheduled
0
Activity tied to just 2 customer groups
0%
Job status fields populated
Cyber Essentials
99.5% Uptime SLA
£2B+ Client Revenue Managed
UK-Based Servers

The Building Services Blind Spot

Your CRM records every job, every engineer, every schedule block. But recording is not analysing.

On a single Monday, 16 engineers completed approximately 30 jobs across 20+ sites for 12 customers. That is hundreds of data points: travel times, job durations, reactive vs planned ratios, customer concentration patterns, schedule fragmentation.

Right now, this data sits in your CRM as a plan, not an intelligence source. Without status tracking, margin analysis or pattern detection, the schedule tells you what was meant to happen. Not what actually happened, or what it cost you.

21:6
Reactive to quoted job ratio (by count). Are you optimising for margin?
0/30
Jobs with status fields populated. No live operational visibility.
40%
Workforce tied to just 4 major projects on any given day
4+
Sites visited by a single engineer in one day. Hidden travel cost.

What Your CRM Data Reveals

Every finding below was surfaced from a single day's schedule data. Imagine what a full month would show.

Revenue Blind Spots

Reactive vs quoted margin gap unknown. 21 reactive jobs vs 6 quoted projects by count, but no margin data attached. If reactive work runs at lower margin, the true profitability of your busiest days is invisible.

Invoicing lag after job completion. Without automated job-to-invoice workflows, completed work sits unbilled. Every day of delay is working capital locked in your CRM schedule.

Engineer grade vs job complexity mismatch. Engineers switching from hospital installations to toilet repairs in the same day suggests potential rate leakage, billing a high-grade engineer on a low-grade task.

Capacity Blind Spots

Hidden travel time eating productive hours. Engineers covering multiple regions in a single day. One engineer crossed 4 sites between 05:15 and 16:30. Travel time does not appear in scheduled hours.

Schedule fragmentation masking true productivity. The same job ID appears in multiple time blocks for the same engineer. Makes it impossible to determine actual productive time vs overhead.

40% of workforce locked into 4 projects. Multi-engineer jobs consume nearly half the daily capacity. One delay cascades across the entire schedule.

Experience Blind Spots

Zero real-time job status visibility. Every status field across all scheduled items was empty. Management cannot track whether a job is in progress, delayed or complete. The schedule is a plan, not a live dashboard.

SLA compliance is unverifiable. Without status tracking and actual completion timestamps, there is no way to prove or measure SLA adherence to your FM contract holders.

Service consistency varies by customer type. Dedicated multi-day project teams vs solo engineers doing 5+ small reactive jobs. Quality standards across these very different delivery models are unmeasured.

Workforce Deployment Snapshot

A single Monday's schedule, extracted directly from the CRM platform.

Engineer Jobs Hours Key Sites Customers
Engineer 01 4 05:00 - 18:15 Student Housing, Warehouse Unit, Office Block, Storage Facility Pinnacle FM, Savills Services
Engineer 02 5 05:15 - 16:30 Student Housing, Fleet Depot, Office Tower, Restaurant Chain Pinnacle FM, Enterprise Fleet, Mitie, Compass Group
Engineer 03 4 03:45 - 00:00 Regional Hospital, Restaurant Lancaster Crown Mechanical, Compass Group
Engineer 04 1 07:30 - 19:45 Regional Hospital Crown Mechanical
Engineer 05 2 06:15 - 17:45 Regional Hospital, Student Housing Crown Mechanical, Pinnacle FM
Engineer 06 2 05:00 - 17:00 Meridian Care Home Savills Services
Engineer 07 2 06:00 - 16:15 Meridian Care Home, Restaurant Mansfield Savills Services, Compass Group
Engineer 08 1 05:00 - 18:30 Oakwood Care Residence Savills Care Division
Engineer 09 1 06:00 - 17:45 Oakwood Care Residence Savills Care Division
Engineer 10 5 07:00 - 15:15 New Build Estate (multiple plots), Housing Phase 1C Vistry Partnerships
Engineer 11 1 06:45 - 17:15 Aerospace Manufacturing Sheffield Savills Services
Engineer 12 2 05:00 - 16:30 Student Housing, Industrial FMCG Pinnacle FM, Nestle UK
Engineer 13 1 06:00 - 16:30 Hartwell Care Centre Dalkia M&E
Engineer 14 2 06:15 - 17:00 Hartwell Care Centre, Sheltered Housing Southampton Dalkia M&E, T Clarke Electrical
Engineer 15 2 09:15 - 00:00 Restaurant York, Restaurant Lancaster Compass Group
Engineer 16 1 13:45 - 17:00 Rail Depot Birmingham Network Rail Contractors

Customer Concentration

How daily workforce allocation maps to a handful of contract holders.

Engineers Deployed by Customer Group

Savills (all divisions)
44%
Compass / Mitie
19%
Pinnacle FM
25%
Crown Mechanical
19%
Vistry Partnerships
6%
All Others
19%

What This Means

Top 2 customer groups = 63% of daily activity. Losing either contract would leave half the workforce undeployed. This concentration risk is invisible in standard CRM reporting.

Customer diversification trending matters. Continuous monitoring would show whether dependency is increasing or decreasing over time, not just a snapshot.

Contract renewal risk is unquantified. A digital analyst monitoring your CRM daily could flag concentration shifts and trigger diversification alerts before a contract loss becomes a crisis.

From CRM Data to Operational Intelligence

Three steps. No workflow changes. No integration risk.

1

Connect

We plug into your CRM with read-only API access. No changes to your scheduling, no new software for engineers, no disruption to operations.

Read-only access
2

Analyse

Our digital analysts scan every schedule, every job record, every customer interaction. Not a weekly sample, everything. Patterns emerge that manual review cannot surface.

100% coverage
3

See

Weekly reports showing exactly where revenue is leaking, capacity is wasted and service consistency is at risk. Prioritised findings with estimated business impact.

Weekly insights

Connects with your existing tools

Teams
Slack
Google Meet
HubSpot
Salesforce
Pipedrive

What You Might Be Thinking

"Our CRM data isn't clean enough for this"
That is exactly why you start here. We will show you how messy it is, and what that mess is costing you. Empty status fields, fragmented schedules, missing margin data: these are not blockers to analysis, they are findings.
"We already have dashboards and reporting"
Dashboards show you what you configured them to show. We find what you did not know to look for. Customer concentration risk, hidden travel costs, margin leakage between reactive and quoted work: none of these appear in standard CRM views.
"How will my team react to AI analysing their schedules?"
They will not need to know. This is read-only analysis. No workflow changes, no new apps for engineers, no disruption. Your team keeps using your CRM exactly as they do today. The insights surface for management only.
"This was just one day's data. Is it representative?"
Exactly right, and that is the point. If a single Monday reveals customer concentration risk, margin blind spots and zero operational visibility, imagine what a full month of continuous analysis would surface. One day gave us the signal. Continuous access gives you the full picture.

Stop Guessing. Start Seeing.

Connect your CRM data stream. Get your first operational insights within 14 days. No disruption. No risk. Just visibility you have never had before.

Book a Discovery Call Get Your Analysis

30-minute call. We will show you one insight from your own data before you commit to anything.