( 01 )
The Business In Brief
( 02 )
At a Glance
|
Metric
|
Before
|
|---|---|
|
Industry
|
General insurance
|
|
Scale
|
Approximately 2,400 employees and 140 branches
|
|
Starting point
|
More than 400 ad hoc data requests each month
|
|
Solution
|
Ask Your Data, embedded in the CRM and intranet
|
|
Delivery
|
14 weeks, from discovery to rollout
|
|
Measured results
|
Four months after rollout
|
( 03 )
The Challenge
Plenty of data, but no easy way to access it Four problems were affecting delivery and reliability:
The insurer had invested in a claims system, a modern HR management system (HRMS) and a CRM used by its agent network. However, most employees could not get straightforward answers from these systems without raising a request with the six-person analytics team.
More than 400 ad hoc data requests arrived each month, with routine questions typically taking two to three working days to answer. By the time the numbers were available, the opportunity to act on them had sometimes passed.
The insurer also had more than 80 dashboards, but fewer than a quarter were opened in a typical month. Employees often needed specific answers that existing dashboards did not provide, leading some branch and claims managers to rely on instinct when making staffing and escalation decisions.
Meanwhile, analysts spent much of their time writing similar SQL queries instead of focusing on higher-value work such as fraud modelling and pricing analysis.
The challenge was not a lack of data. It was making existing operational data accessible, timely and useful to the people who needed it.
( 04 )
How we Solved it
Natural-language questions, answered with live data
Linnk Innovation Hub deployed Ask Your Data, its conversational analytics solution, to let employees ask business questions in plain language and receive answers generated from operational data.
The system maps the insurer’s business terminology to its underlying data structures, generates structured queries and executes them against read-only copies of live operational data. Depending on the question, the answer is presented as a chart, table or written summary.
This allows employees to explore business information without writing queries or relying on a separate business intelligence (BI) platform.
Embedded in existing workflows
Rather than introducing another standalone tool, Ask Your Data was embedded in the insurer’s existing CRM and intranet.
Claims teams could use it within the CRM, while HR teams and managers could access it through the intranet. This brought data access closer to the decisions employees needed to make in their everyday work.
Access controls and traceable answers
The solution retained users’ existing data permissions, ensuring they could only access information they were authorised to see. Its read-only design allowed users to query data without changing it.
Each question, the query generated and the resulting answer were logged, giving analysts and auditors a traceable record of how results were produced.
Before rollout, a test set of 300 questions based on historical requests was used to compare system-generated answers with those provided by analysts. Rollout to each new team proceeded once its questions consistently matched the analyst answers.
( 05 )
How We Delivered It
The 14-week implementation moved from discovery to a claims-focused pilot before extending access across the insurer.
Discovery — 2 weeks: The team reviewed ticket history to identify the 150 most common questions, then mapped the claims data structure and existing access rules.
Pilot — 5 weeks: Ask Your Data was introduced for claims data, with 60 users across two regions accessing it through the CRM. Answers were checked against analyst results to validate the approach.
Rollout — 7 weeks: The solution was extended to HRMS and agent CRM data, with access expanded to more than 1,200 users. Question logs were reviewed weekly to refine the business vocabulary and improve how the system interpreted employee questions.
( 06 )
The Impact
Employees across claims, HR and sales gained a more direct way to access the operational data relevant to their work. Routine questions no longer had to wait in the analytics team’s queue, helping teams obtain information while it was still useful for day-to-day decisions.
The shift also changed how the analytics team could use its time. With fewer repetitive reporting requests to fulfil, analysts could devote more capacity to strategic projects rather than repeatedly producing similar answers.
The insurer’s existing data systems remained central to the process. Instead of asking employees to adopt another standalone BI tool, the solution made data access part of their existing workflows, with established permissions and traceable results.
( 07 )
The Results
Four months after rollout
|
Metric
|
Before
|
After
|
|---|---|---|
|
Time to answer a typical data question
|
2–3 working days
|
Under 30 seconds
|
|
Monthly ad hoc reporting requests to analytics
|
Approximately 400
|
Approximately 110
|
|
Employees able to query data directly
|
Approximately 40
|
1,200+
|
|
Questions answered per month
|
Approximately 400
|
11,000+
|
|
Static reports and dashboards maintained
|
80+
|
46
|
|
Analytics time spent on strategic projects
|
Approximately 20%
|
Approximately 60%
|