Most business process automation content is rubbish.
Generic examples. Theoretical possibilities. “Imagine if you could…” nonsense that never translates to reality.
This is different. These are 15 automations that UK businesses are running right now — ones I’ve either built, recommended, or seen deliver measurable results. Each one includes what it does, what tools you need, and what kind of impact to expect.
No fluff. Just workflows that work.
Finance Automations
1. Invoice Processing and Approval
The problem: Someone manually opens emails, downloads PDFs, types data into accounting software, chases approvals, and finally posts invoices. It takes 15–20 minutes per invoice. Multiply that by 50 invoices a month, and you’ve lost a full working day.
The automation:
Email arrives with invoice attachment → AI extracts supplier name, amount, due date, line items → Data pushed to Xero/QuickBooks → Approval request sent to correct manager via Slack/Teams → Once approved, invoice posted automatically → Payment scheduled based on terms
Tools: Make or Zapier + an AI extraction tool (Parseur, Docparser, or OpenAI’s API) + your accounting software
Impact: 15 minutes → 2 minutes human involvement. 87% time reduction. Error rate drops from ~5% manual entry to near zero.
2. Expense Report Processing
The problem: Staff submit expense receipts by email (or worse, paper). Someone manually categorises them, checks policy compliance, seeks approvals, and enters into the system.
The automation:
Receipt photo submitted via Slack/email → AI extracts merchant, amount, category, date → Policy compliance checked automatically (amount limits, valid categories) → Approval routed to manager → Approved expenses pushed to accounting software → Employee notified of status
Tools: Expensify or Dext (purpose-built), or Make + OpenAI Vision for custom builds
Impact: 10 minutes per expense → 30 seconds oversight. Finance teams report reclaiming 8–12 hours per week.
3. Bank Reconciliation Alerts
The problem: Cash flow surprises. Unexpected charges. Reconciliation happens weekly (or monthly), and issues surface too late.
The automation:
Bank feed syncs daily → System flags unmatched transactions → Unusual amounts or new payees trigger alerts → Weekly summary of reconciliation status sent automatically → Cash position report generated every Monday morning
Tools: Accounting software APIs + Make/Zapier + Slack or email
Impact: Reconciliation issues caught in 24 hours instead of 7–30 days. One CFO told me this “saved my sanity.”
Sales Automations
4. Lead Scoring and Routing
The problem: Leads hit the CRM, and sales reps spend hours deciding which ones are worth calling. The hot leads get cold while someone’s reviewing a spreadsheet.
The automation:
New lead enters CRM → AI analyses company size, industry, engagement history, source → Lead scored 1–100 → High-score leads auto-assigned to senior reps → Medium scores to SDRs → Low scores to nurture sequence → Assignments pushed to reps via Slack with context summary
Tools: HubSpot or Salesforce (built-in scoring) + Make for custom routing + AI for enrichment
Impact: Lead response time drops from 4+ hours to under 10 minutes. Conversion rates typically improve 15–25%.
5. Proposal Generation
The problem: Creating proposals takes 2–3 hours each. Copy-pasting from templates, customising sections, getting pricing right, formatting, proofreading.
The automation:
CRM opportunity reaches “proposal stage” → System pulls client data, requirements, pricing from CRM → AI generates customised proposal draft → Proposal created in Google Docs/PandaDoc → Sent to sales rep for review and tweaks → One-click send to client with tracking
Tools: CRM + Make + OpenAI API + PandaDoc or Proposify
Impact: 2–3 hours → 20–30 minutes (review time only). One agency I work with went from 8 proposals per week to 20.
6. Follow-Up Sequences
The problem: Sales reps forget to follow up. Or they send the same generic email five times. Prospects go cold.
The automation:
Meeting completed → CRM updated → Follow-up sequence triggered based on meeting outcome → Day 1: Personalised thank-you email → Day 3: Case study relevant to their industry → Day 7: Check-in with specific value proposition → Day 14: “Is this still a priority?” email → All emails logged to CRM, replies break the sequence
Tools: CRM + email sequencing tool (Reply.io, Instantly, or built-in CRM sequences)
Impact: Reply rates increase 30–50%. Pipeline velocity improves. Reps focus on conversations, not admin.
HR and Operations Automations
7. Employee Onboarding Workflows
The problem: New hire starts, and someone scrambles to set up accounts, assign equipment, schedule training, send documents. Things get missed. IT finds out about the new hire on their first day.
The automation:
Offer accepted in HR system → IT ticket created for equipment and accounts → Facilities notified for desk setup → Manager assigned tasks: schedule intro meetings, assign buddy → New hire receives welcome email sequence with pre-reading → Day 1 agenda auto-generated → 30/60/90 day check-in reminders scheduled
Tools: HR system (BambooHR, Personio) + Make + Slack/Teams + calendar integrations
Impact: Onboarding admin drops from 4–6 hours per new hire to 30 minutes oversight. New hires are productive days faster.
8. Leave Request Processing
The problem: Leave requests via email. Manager forgets to respond. Someone’s on holiday but nobody updated the calendar. Coverage isn’t arranged.
The automation:
Employee submits request via Slack/app → System checks leave balance and conflicts → If approved by policy, auto-approved and calendar blocked → If requires review, routed to manager with one-click approve/deny → HR system updated → Team notified of absence → Coverage reminders sent if critical role
Tools: HR system + Slack/Teams integration + Google/Outlook Calendar
Impact: Request-to-approval time drops from days to minutes. Zero missed calendar updates. Managers love not having to track this manually.
9. Candidate Screening
The problem: 200 applications for one role. HR spends 10+ hours just reading CVs to create a longlist.
The automation:
Application submitted → AI analyses CV against job requirements → Candidates scored and categorised (strong fit, possible fit, not suitable) → Strong fits auto-scheduled for screening call via Calendly → “Not suitable” candidates receive polite rejection email → Hiring manager gets daily summary of pipeline
Tools: ATS (Workable, Greenhouse) + AI screening (built-in or custom via OpenAI) + Calendly
Impact: 10+ hours screening → 1 hour review. Time-to-first-interview drops by 60%. Candidate experience improves (faster responses).
Customer Service Automations
10. Ticket Routing and Prioritisation
The problem: Support tickets hit a shared inbox. Someone manually reads each one, decides priority, assigns to the right team. Urgent issues wait behind password reset requests.
The automation:
Ticket received → AI reads content and categorises (billing, technical, complaint, general) → Priority assigned based on keywords, customer tier, sentiment → Ticket routed to correct team → High-priority issues flagged in Slack → Response time SLAs tracked automatically → Escalation triggered if SLA at risk
Tools: Help desk (Zendesk, Freshdesk, Intercom) + AI classification + Slack alerts
Impact: Routing accuracy improves from 70% to 95%. Average first-response time drops 40%. Escalations catch issues before customers complain.
11. FAQ Bot with Handoff
The problem: 40% of support tickets are the same 10 questions. Your team answers them manually, every time.
The automation:
Customer asks question via chat/email → AI attempts to answer from knowledge base → If confident (>85% match), provides answer with option to escalate → If uncertain, routes to human immediately → All interactions logged → Unanswered questions flagged for knowledge base updates
Tools: Intercom, Zendesk AI, or custom (ChatGPT + your docs via RAG)
Impact: 30–50% of tickets deflected. Human agents focus on complex issues. Customer satisfaction typically improves (faster answers to simple questions).
12. Customer Sentiment Alerts
The problem: Unhappy customers churn silently. By the time you notice, they’re gone.
The automation:
Support interactions analysed for sentiment → Negative sentiment flagged → Multiple negative interactions from same customer triggers account review → Customer success team alerted → NPS/CSAT responses feed into same system → At-risk accounts get automatic check-in scheduling
Tools: Support platform + sentiment analysis (built-in or via AI) + CRM integration
Impact: Churn risk identified 2–4 weeks earlier. Customer success teams can intervene before cancellation requests.
Marketing Automations
13. Report Generation and Distribution
The problem: Monday morning report takes 3 hours. Pull data from five platforms, paste into slides, format, email to stakeholders. Every. Single. Week.
The automation:
Sunday night: System pulls data from Google Analytics, ad platforms, CRM, email tool → Data compiled into template → Charts regenerated → PDF/slides created → Report emailed to distribution list Monday 7am → Key metrics also posted to Slack channel
Tools: Make or n8n + platform APIs + Google Slides/Docs + email
Impact: 3 hours → 15 minutes review. Reports never late. Data always current.
14. Social Media Scheduling and Recycling
The problem: Posting consistently takes hours. Your best content gets shared once and forgotten.
The automation:
Content created and approved → Scheduled to optimal posting times per platform → Evergreen content flagged and added to recycling queue → High-performing posts automatically re-queued (with variation) → Engagement alerts sent for comments requiring response → Monthly performance summary generated
Tools: Typefully, Buffer, or Hootsuite + Make for recycling logic
Impact: Posting time reduced 60%. Content gets multiple impressions instead of one. Engagement actually monitored.
15. Lead Qualification and Nurture
The problem: Marketing generates leads. Sales says they’re rubbish. Marketing says sales doesn’t follow up. Nobody wins.
The automation:
Lead downloads resource → Nurture sequence begins based on content type → Behaviour tracked: email opens, page visits, additional downloads → Lead score increases with engagement → Score threshold reached → Sales notified with context: “This contact downloaded the pricing guide, visited the case studies page 4 times, and opened 6 emails” → Warm handoff, not cold call
Tools: Marketing automation (HubSpot, ActiveCampaign) + CRM + scoring rules
Impact: Marketing-to-sales handoff quality improves dramatically. Sales conversion rates increase 20–40%. Both teams stop blaming each other.
Implementation Tips
These automations aren’t complicated. But they do require:
1. Clear process first — Automate a mess, and you get an automated mess. Document the current process. Fix the obvious problems. Then automate.
2. Start with one — Pick the automation that will save the most time with the least complexity. Prove it works. Build confidence. Then expand.
3. Build in monitoring — Every automation should alert you when it fails. Things break. APIs change. You need to know immediately, not when a customer complains.
4. Train your team — The automation is only valuable if people trust it and know how to work with it. Budget time for training and documentation.
5. Review quarterly — Processes change. What you automated six months ago might need updating. Schedule regular reviews.
The Numbers
When these automations work properly, UK businesses report:
- 2,000+ hours saved annually for mid-sized companies
- 40% reduction in time spent on repetitive tasks
- 99% error reduction in data entry processes
- 22% cost reduction over three years
- 6–12 month payback on implementation investment
The ROI is real. But only if you implement properly, monitor consistently, and iterate when things change.
Start with one. Get it working. Measure the impact. Then pick the next one.
FAQ
Which automation should I start with?
Invoice processing or lead qualification — both have high volume, clear ROI, and relatively simple implementation. Pick whichever costs you more time right now.
Do I need developers to build these?
Not necessarily. Most can be built with Make, Zapier, or n8n by someone with moderate technical skills. Complex integrations or AI components might need developer support.
How long does a typical automation take to implement?
Simple workflows: 1–2 weeks. Complex integrations: 4–8 weeks. Factor in testing, training, and iteration.
What if the automation makes mistakes?
All automations should have human oversight points for important decisions. Start with approval steps, then remove them once you trust the system.
Can small businesses afford this?
Yes. Tools like Make and Zapier start under £50/month. The question isn’t cost — it’s whether you have the time to implement. If not, even a £5k project pays back quickly if it saves 10 hours per week.
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