Sectors
Different industries. The same three constraints.
Across the mid-market we meet the same pattern: data locked in systems chosen for the job rather than for reporting, a technology team of a handful of people, and rising pressure from customers and regulators to prove what the data says.
Data silos
Operational, finance and customer systems from different vendors, joined together by people and spreadsheets.
Thin technical teams
One to five people who understand the data, already busy keeping systems running.
Rising scrutiny
Clients, auditors and regulators who expect numbers that can be traced, explained and protected.
Parking and mobility
Where Kenerix runs in production today. Camera, warden, payment, appeals and debt recovery data, across brands and thousands of sites, turned into answers for operators and their landowner clients.
The data you have
- ANPR and camera reads, matches and overstays
- Warden activity and ticket capture
- Charges, letters, payments and refunds
- Appeals, keeper lookups and debt placement
Where it hurts
- Several brands and legacy systems counted together
- Landowner clients asking for usage data
- Appeal backlogs noticed late
- Cancellation and payment rates argued over
Define once, govern always
- Charges issued, cancelled and collected, with exact rules
- Brand scope enforced per person
- Client portals showing each landowner only their sites
- Evidence for data protection and code-of-practice audits
Which sites issued fewer charges than the same week last year, and why?
Show the appeal backlog by brand and how long the oldest appeals have waited.
Give this client a monthly view of visits, dwell time and returning vehicles.
Property and facilities management
Portfolios of buildings, tenants and contracts, each with its own systems for maintenance, energy, access and finance. Owners want one view; occupiers want their own.
The data you have
- Lease and tenancy management
- Helpdesk and planned maintenance tickets
- Energy, occupancy and access-control feeds
- Service charge and supplier invoices
Where it hurts
- SLA reporting rebuilt for each client
- Occupancy and energy data in different portals
- Service-charge queries answered by hand
- ESG reporting assembled from spreadsheets
Define once, govern always
- SLA met, occupancy and cost per square metre, defined once
- Each client sees only their buildings
- White-label portal for owners and occupiers
Which buildings missed their reactive maintenance SLA this month?
Compare energy use per square metre against occupancy by building.
Build a quarterly client review for this portfolio.
Specialist financial services
Lenders, brokers, insurers and wealth managers with core platforms, CRMs and outsourced servicers, under FCA Consumer Duty and growing AI scrutiny. Governance is the purchase decision.
The data you have
- Core lending, policy or platform systems
- CRM and broker portals
- Complaints, collections and arrears
- Outsourced servicer and partner feeds
Where it hurts
- Consumer Duty outcomes monitored on samples
- Board MI built by hand from several systems
- AI blocked by risk review before it starts
- Proving who accessed customer data
Define once, govern always
- Outcome measures with documented rules
- Field-level access for personal data
- Read-only agents and human-approved change
- Controls mapped to UK GDPR, Consumer Duty and EU AI Act
Show complaints by product and root cause, and flag any rise in vulnerable-customer cases.
Which broker channels have the highest early arrears this quarter?
Alert compliance if any outcome measure moves outside tolerance.
Healthcare and care providers
Private clinics, care groups and digital health services running clinical, rostering and finance systems side by side, where data protection is non-negotiable and staff time is precious.
The data you have
- Patient administration and booking
- Rostering, timesheets and agency spend
- Incidents, complaints and audits
- Finance and commissioning data
Where it hurts
- Occupancy and staffing seen days late
- Agency spend surprises at month end
- Inspection evidence gathered by hand
- Sensitive data kept far from AI
Define once, govern always
- Occupancy, utilisation and staffing ratios defined once
- Role-based access by site and data class
- Aggregate answers without exposing individuals
- Sector assurance such as DTAC and DSPT on our roadmap
Which homes ran below planned staffing ratios last week?
Show agency spend by site against budget for the quarter.
Summarise incident trends by category for the governance meeting.
Logistics and field services
Fleets, engineers and depots generating data in telematics, job management, warehouse and finance systems that rarely agree on what a completed job is.
The data you have
- Job and work-order management
- Telematics and route data
- Warehouse and stock systems
- Customer contracts and invoicing
Where it hurts
- First-time-fix and on-time rates disputed
- Customer SLA reports built by hand
- Margin per job unknown until month end
Define once, govern always
- Job completed, on time and first-time fix, defined once
- Customer portals with their own jobs only
- Alerts on SLA risk before it becomes a breach
Which customers are at risk of an SLA breach this week?
Show first-time-fix rate by engineer team and job type.
What was our margin per job by region last month?
Manufacturing and distribution
ERP, production, quality and sales systems that grew up separately, in companies where the person who knows the data also runs the ERP.
The data you have
- ERP orders, stock and purchasing
- Production and machine data
- Quality, returns and non-conformance
- Sales, pricing and distributor data
Where it hurts
- Forecasts built in spreadsheets
- Quality issues traced to batches by hand
- Distributor sales data arriving in different formats
Define once, govern always
- OEE, yield, margin and fill rate defined once
- Distributor and customer data kept apart
- Drift rules on feeds from partners
Which product lines lost margin this quarter, and was it price, mix or cost?
Show returns by batch and supplier for the last 90 days.
Alert me when any line’s yield drops below its four-week average.
Multi-site retail, hospitality and leisure
Tills, bookings, loyalty, staffing and stock spread across sites and suppliers. Site managers need their own numbers today, not head office’s numbers next week.
The data you have
- Point of sale and bookings
- Loyalty, CRM and online orders
- Rotas and labour cost
- Stock, waste and supplier deliveries
Where it hurts
- Like-for-like sales calculated differently by team
- Labour cost against sales seen too late
- Site managers waiting for weekly packs
Define once, govern always
- Like-for-like, labour percentage and waste defined once
- Managers see their own sites only
- Same-day alerts on sites that drift
Which sites are behind like-for-like this week, and by how much?
Show labour cost as a share of sales by site and day part.
Tell area managers each morning which sites missed target yesterday.
Professional services
Firms whose product is time and expertise, with practice management, timesheets, CRM and finance in different places, and client confidentiality at the core.
The data you have
- Practice or matter management
- Timesheets and resourcing
- CRM and pipeline
- Billing, WIP and debtors
Where it hurts
- Utilisation and realisation debated monthly
- WIP and lock-up visible too late
- Partners asking the same questions of finance
Define once, govern always
- Utilisation, realisation and lock-up defined once
- Access by practice area and client confidentiality
- Agents that answer partners without exposing other matters
Show utilisation by team against target for the last four weeks.
Which clients have WIP older than 60 days?
Build a monthly practice review for each partner, showing only their clients.
Don’t see your sector?
If your data is spread across systems and your team is small, the pattern is the same. Tell us about yours.