Management Reporting & Analysis Hub
The Exeter - Section 3.0

Management Reporting & Analysis Components

Early concepts for management-level reporting using systems thinking metrics.

Illustrative Data - Visual Specification

Overview

The data model specification in Section 2.1 defines 76 member servicing tasks, each measured across 9 metrics weekly. Combined with 52 complaint categories, this creates a rich operational dataset. This page shows the reporting and analysis components that become possible from that single act of consistent measurement.

Weekly Capture
76 tasks × 9 metrics
→
Dashboards
Operational visibility
→
Patterns
Trend & demand analysis
→
Insight
Root cause intelligence
→
Decisions
Evidence-based action

Weekly Operational Dashboard

Measure What Matters + Decisions at the Work

A single weekly view showing demand volume, SLA performance, member sentiment, and resolution quality. The at-a-glance view for operational leadership.

Total Weekly Demand
1,742
Tasks processed this week across all groups
Value demand (62%)
Failure demand (38%)
SLA Performance
87% On time
New Business
94%
Alterations
91%
Claims
82%
Cancellations
78%
Finance Ops
71%
Member Sentiment
7.2 / 10
Average satisfaction score this week
New Business
8.4
Claims
7.2
Alterations
6.9
Cancellations
5.8
First Touchpoint Resolution
67% FTR

Gap to target: 13 percentage points below 80% ambition.

Volume by Group
Alterations
412
Cancellations
298
New Business
256
Claims
224
Finance Ops
148
Complaints
98
Reinstatements
76
Switchboard
72
Retentions
68
Underwriting
90

Performance vs Ambition

Measure What Matters

Each metric has an ambition target defined in the Data Model Specification. Progress-to-target bars show where performance sits against that ambition, green when on track, purple when close, pink when behind.

On track (≥ 90% of target)
Close (75–89% of target)
Behind (< 75% of target)
Ambition target
SLA Performance
95%
87% 8pp gap
Member Sentiment
8.5
7.2 1.3 gap
First Touchpoint
80%
67% 13pp gap
Failure Demand
≤20%
38% 18pp over
Complaint Yield
≤25
33.3 8.3 over
Avg Touchpoints
≤1.5
2.1 0.6 over

Demand Intelligence

Study Demand First

Breaking down demand by type reveals where the system creates its own workload. Value demand is why members contact us. Failure demand is the system making them chase.

Demand Composition by Group

Value demand
Failure demand
Alterations
412
Cancellations
298
New Business
256
Claims
224
Finance Ops
148
Reinstatements
76

Failure Demand Hotspots - Top 10

Callbacks
610
Chase Letters
378
DD Amendments
268
Manual Letters
240
Doc Re-issue
190
Reinstatement Chase
152
Premium Query
134
Address Change Redo
112
Claim Status Chase
98
Finance Hand-off
86

Top 5 failure demand generators account for 60%+ of avoidable contact. Callbacks alone represent more weekly volume than most entire task groups.

Derived Metric
Failure Demand Ratio = Failure Demand Volume ÷ Total Demand Volume × 100

Complaint Intelligence

Complaints as Intelligence

Complaints are not noise, they are the member telling us where the system fails. Linking complaint categories to tasks reveals which processes generate the most regulated dissatisfaction.

Volume by Category - Top 8

Delay: Processing
42
Failure: Agreed Request
34
Premium: Wrong Amount
28
Delay: Answering Call
24
Info: Wrong/Unclear
18
Cancellation: Error
16
DD: Failed Collection
14
Claim: Delay Decision
12

Task-to-Complaint Linkage

Heatmap showing which tasks generate which complaint categories. Darker cells = higher linkage.

Delay
Failure
Premium
Call Wait
Info
Cancel
DD
Claim
Cancellation
18
8
3
4
–
16
–
–
DD Amendment
6
12
22
–
2
–
14
–
Reinstatement
14
10
6
3
4
–
5
–
Claims
8
4
–
8
6
–
–
12
Address Change
3
9
–
–
8
–
–
–

Week-on-Week Direction

Category This Week Last Week Change Direction
Delay: Processing 42 38 +4 ▲ Rising
Failure: Agreed Request 34 36 -2 ▼ Falling
Premium: Wrong Amount 28 28 0 ▶ Flat
Delay: Answering Call 24 30 -6 ▼ Falling
Info: Wrong/Unclear 18 15 +3 ▲ Rising

Prioritisation Framework

Design Against Demand

With 76 tasks producing data weekly, the prioritisation framework scores and ranks tasks to focus improvement effort where it will have the greatest impact.

Prioritisation Formula
Priority Score = (Volume × 0.30) + (Failure% × 0.25) + (Complaints × 0.20) + (InvSLA × 0.15) + (TouchPoints × 0.10)

Volume vs Failure Rate

Lower Failure %
Higher Failure %
High Volume
Monitor
New Business Processing
General Enquiry
Critical
Callbacks
DD Amendments
Cancellation Letters
Low Volume
Maintain
Beneficiary Change
Moratorium Query
Investigate
Reinstatement Chase
Claim Status Chase
Failure Demand Rate →

Top 10 Priorities

# Task Group Vol/wk Failure% Complaints Score Priority
1 Callbacks Switchboard 610 85% 24 92 Critical
2 DD Amendments Finance Ops 268 58% 28 87 Critical
3 Cancellation Letters Cancellations 240 62% 34 84 Critical
4 Reinstatement Reinstatements 152 50% 18 76 High
5 Address Change Alterations 198 45% 12 72 High
6 Doc Re-issue Alterations 190 40% 8 68 High
7 Premium Query Finance Ops 134 55% 14 65 High
8 Claim Registration Claims 112 35% 12 58 Medium
9 Chase Letters Cancellations 378 30% 6 55 Medium
10 NB Processing New Business 256 22% 4 48 Medium

System Health

Study Demand First + Complaints as Intelligence

RAG status across all groups and the 7 captured metrics. No additional data collection required, calculated from the 9 weekly metrics.

Raw Metrics - System Health at a Glance

RAG status across all groups and the 7 captured metrics. Green = on target, Amber = watch, Red = action needed.

Vol
Dem
SLA
Sent
Touch
FTR
Comp
Alterations
A
A
G
G
A
G
G
Cancellations
A
R
R
R
R
A
R
New Business
G
G
G
G
G
G
G
Claims
G
A
A
G
A
A
A
Finance Ops
A
R
R
A
R
A
R
Complaints
G
-
A
A
G
G
-
Reinstatements
G
R
A
A
R
A
A
Switchboard
A
R
-
R
R
R
A
Retentions
G
A
G
A
G
A
G
Underwriting
G
G
G
G
A
G
G

Vol Volume · Dem Demand Type · SLA SLA Performance · Sent Sentiment · Touch Touchpoints · FTR First Touchpoint Resolution · Comp Complaints