Guide 28 mins

Pub Group Operations: Multi-Venue Analytics for AU Hotel Groups

Master multi-venue analytics for Australian pub groups. Real-time KPIs, gaming compliance, venue benchmarking, and data-driven operations for hospitality.

The PADISO Team ·2026-04-23

Why Multi-Venue Analytics Matter for Australian Pub Groups
Understanding Your Pub Group’s Core KPIs
Real-Time Data Integration Across Multiple Venues
Gaming Compliance and Regulatory Reporting
Venue Benchmarking and Performance Comparison
Building Your Analytics Stack
Implementing Superset for Bar, Bistro, and Gaming KPIs
D23.io Venue Benchmarking on the Dashboard
Actionable Insights and Decision-Making
Getting Started with Your Pub Group Analytics

Why Multi-Venue Analytics Matter for Australian Pub Groups {#why-multi-venue-analytics}

Running a successful pub group across multiple venues in Australia requires more than intuition and historical habit. When you operate three, five, ten, or fifty venues across different suburbs, cities, or states, you’re managing wildly different customer bases, staff capabilities, local competition, and regulatory environments. Without proper multi-venue analytics, you’re flying blind.

The challenge is straightforward: each venue generates its own revenue streams—bar sales, bistro food, gaming machines, functions, and events. Each has different margins, different peak times, and different compliance obligations. A gaming machine venue in a regional Queensland town operates under entirely different rules than a craft beer bar in inner Sydney. Yet most pub groups still rely on spreadsheets, monthly reports sent by venue managers, and quarterly P&L reviews that arrive weeks after the money has already left the table.

Multi-venue analytics changes this equation. By consolidating data from all your venues into a single, real-time dashboard, you gain visibility into what’s actually happening across your entire operation. You can spot which venues are underperforming before the problem becomes a crisis. You can identify which managers are executing your brand standards consistently and which ones are drifting. You can optimise pricing, staffing, and inventory decisions based on live data rather than guesses.

For Australian hospitality groups, this is particularly critical. Compliance requirements around gaming machines are strict—the Australian Hotels Association sets clear expectations for responsible gaming reporting, and state regulators audit regularly. Labour laws vary by state. Liquor licensing rules differ between venues. Multi-venue analytics platforms help you maintain compliance across all jurisdictions simultaneously, reducing audit risk and legal exposure.

The financial impact is real. Pub groups using proper analytics typically see 8–15% improvement in gross profit margin within the first year, primarily through better labour scheduling, reduced waste, and optimised pricing. Gaming compliance improves, reducing fines and regulatory friction. Staff turnover drops because managers have clearer data on what’s working and what isn’t. And perhaps most importantly, you can make strategic decisions about venue investment, closure, or expansion based on actual performance data rather than emotion or outdated assumptions.

Understanding Your Pub Group’s Core KPIs {#understanding-core-kpis}

Before you build any analytics system, you need to know what you’re measuring. Different stakeholders in your pub group care about different metrics, and conflating them leads to confusion and poor decisions.

Revenue and Profitability Metrics

At the highest level, you need to track total revenue per venue and per venue category. But “total revenue” is too blunt an instrument. You need to break it down:

Bar Revenue includes all drinks sold—beer, spirits, wine, soft drinks, and hot beverages. Track this by volume and by value. A venue selling 1,000 beer pints at £4 each generates the same revenue as one selling 500 premium cocktails at £8, but the customer experience and staff requirements are completely different.

Bistro Revenue is food sales, typically the second-largest revenue stream for pubs. Track covers (number of meals served), average spend per cover, and food cost percentage. A high-volume, low-margin model (RSA-style pub meals) looks very different from a high-end gastro-pub model, and your analytics need to reflect that.

Gaming Revenue is the machine revenue after payouts—the “hold” or “win”. In Australia, this is heavily regulated and heavily scrutinised. You need to track:

Total gaming machine revenue (hold)
Gaming revenue as a percentage of total venue revenue (this varies widely, from 10% in busy food-focused venues to 60% in regional gaming pubs)
Number of active gaming machines
Revenue per machine per day
Compliance metrics (responsible gaming signage, self-exclusion registrations, incident reports)

Other Revenue includes functions, events, betting, and ancillary services. For some venues, this might be negligible. For others, a Friday night function can generate £2,000+ in a single night.

Once you have revenue broken down by category, calculate Gross Profit Margin for each. Bar gross margin (revenue minus cost of goods sold for alcohol) typically runs 65–75% in Australian pubs. Bistro margin is usually 60–70% depending on menu mix. Gaming is 100% (after payouts are accounted for in revenue). Knowing your actual margins by venue and by category lets you spot when a venue is underperforming—if your bar margin drops to 58%, something is wrong (over-pouring, theft, incorrect pricing, or a shift in customer mix).

Operational Efficiency Metrics

Revenue is only half the story. You also need to track labour, waste, and operational efficiency.

Labour Cost Percentage is your largest controllable expense in most pubs. Track it weekly, not monthly. If your labour cost is 28% of revenue and you’re budgeting for 26%, you need to know that immediately so you can adjust staffing. Break it down by shift, by manager, and by venue so you can identify where the problem lies.

Food Cost Percentage for bistro operations should be tracked daily if possible. A 32% food cost is excellent; 38% suggests portion creep, theft, or purchasing inefficiency.

Customer Metrics matter too. Track:

Covers per day (bistro)
Average spend per customer (bar and bistro combined)
Customer count (foot traffic, if you have door counters)
Repeat customer rate (if you have loyalty data)

These metrics help you understand whether revenue changes are driven by higher prices, higher volume, or a shift in customer mix.

Compliance and Risk Metrics

For gaming venues in Australia, compliance metrics are non-negotiable:

Responsible Gaming Incidents: Self-exclusions, harm minimisation contacts, problem gambling reports
Machine Downtime: Broken or out-of-service gaming machines (a machine that’s down is generating zero revenue)
Audit Readiness: Gaming machine licences, responsible service of alcohol certifications, staff training records
Incident Reports: Accidents, complaints, security incidents (tracked for insurance and regulatory purposes)

You need to track these not just for compliance, but because they’re leading indicators of operational problems. A spike in self-exclusions might indicate a machine malfunction or a staffing issue. Frequent downtime suggests poor maintenance.

Real-Time Data Integration Across Multiple Venues {#real-time-data-integration}

Measuring KPIs is only useful if you have real-time data flowing into your analytics system. Most Australian pub groups still operate with point-of-sale (POS) systems that don’t talk to each other, gaming machine systems that are siloed, and accounting software that updates weekly or monthly.

This is the biggest barrier to effective multi-venue analytics, and it’s solvable with the right architecture.

POS System Integration

Your POS system is your primary data source. It records every transaction—every drink, every meal, every gaming machine payout. Most modern POS systems (Square, Toast, Lightspeed, local Australian solutions) have APIs that allow you to pull transaction data in real-time or near-real-time.

The key is to standardise your POS configuration across all venues. If Venue A records “Carlsberg Pint” and Venue B records “Carlsberg Draft 425ml”, you can’t easily compare bar performance. Spend time upfront to ensure every venue uses the same menu item codes, the same category structure, and the same discount codes. This is tedious but essential.

Once your POS data is standardised, you can pull it into a central data warehouse. This doesn’t need to be complex—a cloud database like PostgreSQL or Snowflake is sufficient. You’re simply copying transaction data from each venue’s POS system into a central location where you can query it.

Gaming Machine Data

Gaming machine data is trickier because gaming systems are often proprietary and heavily regulated. However, most modern gaming machine providers (Aristocrat, Konami, IGT) have reporting portals that allow you to export data. In Australia, you’re likely using machines from one of these three providers, and they all support data export.

The data you need includes:

Machine ID and location
Daily gaming revenue (hold)
Machine downtime and malfunction codes
Responsible gaming incident logs
Compliance event logs

You’ll need to export this data regularly (daily or weekly) and load it into your central warehouse. Some gaming providers offer API access; others require manual export. Work with your gaming supplier to find the most automated path.

Staff and Labour Data

Labour cost tracking requires integration with your payroll or time-tracking system. If your venues use different systems (some on Xero, some on ADP, some on paper timesheets), you need to standardise this. Cloud-based payroll systems like Xero or Employment Hero can export data that you can pull into your warehouse.

At minimum, you need:

Hours worked per staff member per shift
Hourly rate or salary
Department (bar, kitchen, management)
Venue

This lets you calculate labour cost as a percentage of revenue, which is your most actionable operational metric.

Inventory and Procurement Data

For bistro operations, food cost tracking requires inventory data. This is the hardest data to automate because most pubs still manage inventory with spreadsheets or basic inventory software. Ideally, you’d have:

Daily food purchases (from your supplier invoices)
Periodic inventory counts (weekly or monthly)
Food waste logs (if you track waste separately)

From these three data points, you can calculate food cost percentage and spot trends. If you’re not currently tracking this, start with a simple spreadsheet: daily food purchases (from invoices) divided by covers served.

Consolidation and Normalisation

Once data is flowing from all sources, you need to consolidate and normalise it. This means:

Converting all currencies to AUD (if you have multi-currency venues)
Aligning date formats and time zones
Standardising venue names and IDs
Removing duplicate transactions
Flagging data quality issues (missing values, outliers)

This consolidation layer is often where analytics projects fail. If you don’t have clean, consistent data flowing into your analytics platform, your dashboards will be garbage. Invest time in data quality upfront.

Gaming Compliance and Regulatory Reporting {#gaming-compliance}

Australian pub groups operate under strict gaming machine regulations that vary by state. New South Wales, Victoria, Queensland, Western Australia, and South Australia all have different rules. If you operate across multiple states, you need analytics that can handle this complexity.

State-by-State Compliance Requirements

New South Wales requires:

Responsible Gambling Code of Conduct compliance
Self-exclusion program tracking
Mandatory harm minimisation signage
Regular reporting to Liquor & Gaming NSW
Staff training records on responsible service of gambling

Victoria requires:

Gambling Harm Minimisation Plan
Problem Gambling Support Service information
Venue-level gaming revenue reporting
Compliance with the Gambling Regulation Act 2003

Queensland requires:

Gaming Machine National Standard compliance
Responsible Service of Gambling (RSG) training
Gaming venue operator licence conditions
Regular audits by the Office of Liquor and Gaming Regulation

The common thread across all states is Responsible Gaming Reporting. You need to track:

Self-exclusions (how many people have requested to be banned from your venues)
Harm minimisation contacts (how many people have sought help for problem gambling)
Incident reports (breaches of responsible gaming rules)
Staff training completion rates
Signage compliance (is every venue displaying required responsible gaming information)

Your analytics system should flag non-compliance automatically. If a venue hasn’t conducted responsible service of gambling training in 12 months, your dashboard should show a red warning. If self-exclusion registrations haven’t been updated in 30 days, that’s a flag.

Audit Readiness

Regulators conduct surprise audits. When they arrive, they want to see:

Proof that gaming machines are operating within specifications
Records of responsible gaming training
Incident logs and how they were handled
Gaming revenue reconciliation (does the money match the machine data)
Proof of compliance with gaming venue licence conditions

If this information is scattered across spreadsheets, emails, and filing cabinets, you’ll fail the audit. If it’s consolidated in a single analytics system with audit trails and timestamps, you’ll pass.

An audit-ready analytics system should include:

Audit Trail: Every data change is logged with who made it and when
Compliance Dashboard: Shows current status of all compliance requirements
Report Export: Can generate compliance reports on demand
Alerts: Notifies managers when compliance items are due or overdue

Gaming Revenue Reconciliation

One of the most common audit findings is gaming revenue discrepancies—the money in the machine doesn’t match the reported revenue. This usually happens because:

Machines are misconfigured (reporting payouts incorrectly)
Data isn’t being exported from machines correctly
There’s a time lag between machine data and banking data
Payout adjustments aren’t being recorded

Your analytics system should reconcile gaming revenue from three sources:

Machine-reported revenue: What the gaming machine says it earned
Gaming supplier data: What the gaming supplier’s system says was earned
Banking data: What actually hit your bank account

These three numbers should match (within a small variance for payout timing). If they don’t, you have a problem that needs investigation before the auditor finds it.

Venue Benchmarking and Performance Comparison {#venue-benchmarking}

One of the most powerful uses of multi-venue analytics is benchmarking—comparing performance across venues to identify best practices and problem areas.

Internal Benchmarking

Start by comparing your venues against each other. If you operate five pubs, rank them by:

Revenue per square metre: Which venues are generating the most revenue per unit of space? A small, efficient venue might outperform a large, inefficient one.
Labour cost percentage: Which managers are running the most efficient operations? What are they doing differently?
Gaming revenue per machine: Which venues have the highest-performing gaming machine portfolios?
Bistro margin: Which venues are running the most profitable food operations?
Customer count per staff member: Which venues are generating the most transactions per labour hour?

Once you’ve identified your top-performing venue, dissect why it’s winning. Is it:

Better location (higher foot traffic)?
Better management (more efficient operations)?
Better menu (higher average spend per customer)?
Better gaming machine placement?
Better customer service (higher repeat rates)?

Once you understand what’s working, you can replicate it in underperforming venues. If your top venue is achieving 72% bar margin and another is at 64%, the difference might be portion control, pricing, or mix (premium vs. standard drinks). Your analytics should help you identify which.

External Benchmarking

Internal benchmarking is powerful, but external benchmarking—comparing your venues against industry standards—is essential for strategic planning.

The Hospitality Magazine Australia publishes regular reports on Australian pub and hotel performance. The Australian Hotels Association provides industry data on typical margins, labour costs, and gaming revenue by venue type and location. The STR platform provides detailed benchmarking data on hotel and hospitality performance, though it’s more focused on accommodation than pubs.

You should know:

What’s the typical bar margin for a pub in your location? If you’re at 68% and the industry average is 72%, you have a problem.
What’s the typical labour cost percentage? If you’re at 30% and the industry average is 26%, you’re overstaffed or underpaying.
What’s the typical gaming revenue as a percentage of total revenue? If you’re at 35% and similar venues average 45%, you might have underperforming machines or poor placement.

External benchmarking data is often proprietary and expensive, but it’s worth the investment. A single insight—“we’re overstaffed compared to similar venues”—can translate to £50,000+ in annual savings.

Trend Analysis

Benchmarking isn’t just about point-in-time comparisons. You also need to track trends over time. Is your best venue getting better or worse? Are your margins compressing across the board, or is it isolated to one or two venues?

Track these metrics month-over-month and year-over-year:

Total revenue (and revenue by category: bar, bistro, gaming)
Gross profit margin
Labour cost percentage
Customer count
Average spend per customer

A 5% revenue increase sounds good until you realise it’s driven entirely by a price increase, not volume growth. A 3% margin compression sounds small until you realise it’s been happening for six months and is accelerating. Trends reveal the direction your business is moving, which is more important than any single data point.

Building Your Analytics Stack {#analytics-stack}

Now that you understand what you need to measure, let’s talk about the technology. Building a multi-venue analytics system doesn’t require expensive enterprise software. You can build something powerful and scalable for a fraction of the cost of legacy systems.

The Core Components

A modern analytics stack has three layers:

1. Data Integration Layer

This is where data from your POS, gaming machines, payroll, and other systems flows in. Tools like Fivetran, Stitch, or Zapier can automate data extraction from most business software. If your systems don’t have pre-built connectors, you can write custom scripts using Python or Node.js to pull data via APIs.

For Australian pub groups, you might integrate:

POS systems (Square, Toast, Lightspeed, local solutions)
Gaming machine data (Aristocrat, Konami, IGT portals)
Payroll systems (Xero, Employment Hero)
Accounting software (Xero, MYOB)
Inventory software (MarginEdge, Toast inventory)

2. Data Warehouse Layer

Once data is extracted, it needs to be stored in a central location where you can query it. Cloud data warehouses like Snowflake, BigQuery, or Redshift are ideal. They’re scalable (you pay for what you use), fast (you can query millions of rows in seconds), and secure (they support encryption and audit trails).

Alternatively, if you want to keep costs down and don’t need massive scale, PostgreSQL (open-source, free) works fine for most pub groups. A single PostgreSQL instance can handle years of transactional data from 50+ venues without breaking a sweat.

3. Visualisation and Analytics Layer

This is where your dashboards live—where managers and executives actually use the data. This is where Superset comes in.

Why Superset?

Superset is an open-source data visualisation platform built by Airbnb. It’s designed to let non-technical users explore data and build dashboards without writing SQL. For pub groups, it’s ideal because:

No licensing cost: It’s open-source and free to self-host
Flexible: You can connect it to any database (PostgreSQL, Snowflake, BigQuery, etc.)
User-friendly: Managers can build their own dashboards without IT support
Powerful: Supports complex calculations, filters, and drill-down analysis
Audit-ready: Supports row-level security (so each venue manager only sees their venue’s data) and audit trails

Superset is being used by hospitality groups globally to manage multi-venue analytics. It’s battle-tested and reliable.

Alternative Tools

If Superset doesn’t fit your needs, consider:

Looker: More enterprise-focused, better for large organisations, higher cost
Tableau: Industry standard for data visualisation, very expensive
Power BI: Microsoft’s offering, integrates well with Azure and Office 365
Metabase: Simpler than Superset, good for smaller organisations

For most Australian pub groups, Superset or Metabase offers the best balance of power and cost.

Implementing Superset for Bar, Bistro, and Gaming KPIs {#superset-implementation}

Let’s get concrete. Here’s how to implement Superset for a multi-venue pub group, focusing on bar, bistro, and gaming KPIs.

Step 1: Set Up Your Data Warehouse

First, you need a database to connect Superset to. If you’re starting from scratch:

Choose a cloud database provider (Snowflake for scale, PostgreSQL for simplicity)
Create a schema for your pub group data
Create tables for:
- venues (venue ID, name, location, manager, opening date)
- transactions (transaction ID, venue ID, date, time, category, amount, payment method)
- gaming_machines (machine ID, venue ID, machine type, installation date, status)
- gaming_revenue (machine ID, date, hold, payouts, net revenue)
- staff (staff ID, venue ID, name, role, hours worked, hourly rate)
- compliance_events (event ID, venue ID, date, event type, status, notes)

Step 2: Load Data

Set up automated data pipelines to load data from your POS, gaming systems, and payroll software into these tables. Use a tool like Fivetran or Stitch to automate this, or write custom Python scripts if you’re technical.

Data should flow daily at minimum, hourly if possible. The fresher your data, the more actionable your insights.

Step 3: Create Calculated Fields

In Superset, create calculated fields for your key metrics:

gross_profit_margin = (revenue - cost_of_goods_sold) / revenue
labour_cost_percentage = total_labour_cost / revenue
gaming_revenue_per_machine = gaming_revenue / number_of_machines
average_spend_per_customer = total_revenue / customer_count
food_cost_percentage = food_purchases / food_revenue

These calculated fields are the building blocks of your dashboards.

Step 4: Build Dashboards

Create dashboards for different audiences:

Venue Manager Dashboard (for individual venue managers)

Today’s revenue (bar, bistro, gaming) vs. target
Today’s labour cost % vs. budget
Gaming machine downtime
Staffing levels vs. scheduled
Compliance checklist (responsible gaming training, signage, self-exclusion updates)

General Manager Dashboard (for multi-venue managers)

Revenue by venue (ranked)
Labour cost % by venue (ranked)
Gaming revenue per machine by venue
Gross profit margin by venue
Compliance status across all venues
Trend charts (revenue, margin, labour cost over time)

Executive Dashboard (for owners and senior leadership)

Total revenue and gross profit (company-wide)
Year-over-year growth
Margin trend
Top and bottom performing venues
Gaming revenue contribution
Compliance status (red/yellow/green)
Benchmarking vs. industry standards

Step 5: Configure Permissions and Alerts

Set up row-level security so each venue manager only sees their venue’s data. Configure alerts so managers are notified if:

Daily revenue is more than 10% below target
Labour cost exceeds 30% of revenue
Gaming machines are down for more than 2 hours
Compliance items are overdue

Alerts should go to the right person (venue manager for venue-level alerts, general manager for multi-venue alerts) via email or Slack.

D23.io Venue Benchmarking on the Dashboard {#d23-benchmarking}

D23.io is a specialised platform for hospitality benchmarking, particularly strong on venue-level performance comparison. Integrating D23.io data with your Superset dashboards gives you both internal and external benchmarking in one place.

What D23.io Provides

D23.io aggregates performance data from hundreds of Australian hospitality venues, allowing you to benchmark your pubs against similar venues in your region. You can see:

Average revenue per square metre for pubs in Sydney, Melbourne, Brisbane, etc.
Typical bar margins, bistro margins, and gaming revenue percentages
Labour cost benchmarks by venue type
Customer metrics (covers per day, average spend per cover)
Staffing ratios (staff per £1,000 revenue)

Integrating D23.io with Superset

To integrate D23.io benchmarking data with your Superset dashboards:

Export your venue performance data from Superset (revenue, margin, labour cost, etc.)
Upload it to D23.io for benchmarking analysis
D23.io returns benchmarking reports showing how you compare to similar venues
Load the D23.io benchmarking data back into your PostgreSQL database
Create Superset visualisations that show your actual performance alongside D23.io benchmarks

For example, a dashboard might show:

Your Venue: Bar margin 71%, Labour cost 27%, Gaming revenue per machine £145/day
D23.io Benchmark (similar venues in Sydney): Bar margin 73%, Labour cost 25%, Gaming revenue per machine £152/day
Variance: Bar margin -2%, Labour cost +2%, Gaming revenue per machine -5%

This immediately tells you where you’re underperforming and where you’re winning. If your bar margin is 2 percentage points below benchmark, that’s a £15,000–20,000 annual opportunity if you can close the gap.

Using Benchmarking for Strategic Decisions

Benchmarking data should drive strategic decisions:

Venue Closure: If a venue is consistently 15% below benchmark on margin and 20% below benchmark on revenue per square metre, closure or major repositioning might be the right call.
Venue Expansion: If a venue is performing 10% above benchmark, it might be undersized. Expansion could unlock significant additional revenue.
Staffing: If your labour cost is 5% above benchmark, you likely have a staffing efficiency problem. Investigate scheduling, training, and management.
Menu Pricing: If your bistro margin is below benchmark, your pricing might be too low or your food cost too high. Test price increases or menu optimisation.
Gaming Machine Mix: If your gaming revenue per machine is below benchmark, your machine placement, mix, or maintenance might need attention.

Benchmarking should be a quarterly exercise. Compare your performance to D23.io benchmarks, identify gaps, set improvement targets, and track progress.

Actionable Insights and Decision-Making {#actionable-insights}

Data without action is just noise. The real value of multi-venue analytics comes from turning insights into decisions and decisions into results.

Real-Time Decision Making

With live dashboards, you can make decisions in real-time rather than waiting for monthly reports:

Example 1: Labour Scheduling

You notice that Thursday night labour cost is running at 32% of revenue, compared to your 26% target. You drill into the data and see that you’re overstaffed by 3 FTE on Thursday nights. You adjust the schedule for next week, cutting Thursday labour by 3 staff. Result: £2,000 monthly savings.

Example 2: Gaming Machine Maintenance

Your dashboard shows that one venue’s gaming machines have been down for 8 hours this week. You call the gaming supplier and request emergency maintenance. The machine is back online within 2 hours, preventing £500 in lost revenue.

Example 3: Menu Pricing

Your bistro margin is 62%, compared to a 68% benchmark. You drill into the data and see that burger sales are high-volume but low-margin (58% margin). You test a £1 price increase on burgers. Volume drops 5% but margin improves to 63%. Net result: +£800 monthly profit.

Quarterly Strategic Reviews

Beyond real-time decisions, use your data for quarterly strategic reviews:

Performance Review: Compare actual performance to targets and benchmarks. Which venues are winning? Which are struggling?
Root Cause Analysis: If a venue is underperforming, dig into why. Is it location? Management? Menu? Pricing? Competition?
Action Planning: Set specific, measurable improvement targets. “Improve gross margin by 2%” is vague. “Improve bar margin from 70% to 72% by increasing average drink price by 3% and reducing waste by 1%” is actionable.
Accountability: Assign ownership for each improvement target to a specific manager. Track progress monthly.
Learning: What’s working in your top-performing venues? Can you replicate it elsewhere?

Building a Data-Driven Culture

The biggest barrier to extracting value from analytics isn’t technology—it’s culture. If your managers don’t believe in data, don’t understand how to use it, or feel threatened by it, your dashboards will sit unused.

To build a data-driven culture:

Train your team: Make sure every manager understands the key metrics and how to interpret them. Host monthly “data literacy” sessions.
Make data accessible: Don’t gatekeep analytics. Let venue managers access their own dashboards. Encourage exploration.
Celebrate wins: When a manager uses data to improve performance, celebrate it. Share the story across the organisation.
Lead by example: As a leader, make decisions based on data, not intuition. Talk about the data when you communicate with your team.
Iterate: Your analytics system won’t be perfect on day one. Listen to feedback from managers and improve the dashboards based on what they actually need.

Getting Started with Your Pub Group Analytics {#getting-started}

If you’re running a pub group without proper multi-venue analytics, here’s your roadmap to implementation.

Phase 1: Assessment (Week 1–2)

Start by understanding your current state:

Audit your data sources: What systems do you currently use? (POS, gaming machines, payroll, accounting)
Document your data flows: How does data currently move between systems? (Spreadsheets? Manual entry? APIs?)
Identify your pain points: What decisions are hardest to make without good data? Where are you losing money?
Define your metrics: What KPIs matter most to your business?

During this phase, you might engage a partner like PADISO, a Sydney-based AI and automation agency, to help assess your current state and design a target architecture. PADISO specialises in AI & Agents Automation for hospitality and can help you build a custom analytics solution tailored to your specific needs.

Phase 2: Design (Week 3–6)

Design your target analytics architecture:

Data warehouse design: What tables do you need? What’s the schema?
Integration plan: How will data flow from your POS, gaming systems, and payroll into your warehouse?
Dashboard design: What dashboards do you need? For whom?
Security and compliance: How will you ensure data security and audit readiness?

This phase typically involves working with a technical partner to design a solution that fits your specific needs. PADISO’s Platform Design & Engineering service is well-suited for this phase, as is their CTO as a Service offering if you need ongoing technical leadership.

Phase 3: Implementation (Week 7–16)

Build and deploy your analytics system:

Set up your data warehouse: Provision a PostgreSQL or Snowflake instance
Build data pipelines: Create automated flows from your POS, gaming systems, and payroll
Load historical data: Backfill 12–24 months of historical data for trend analysis
Deploy Superset: Set up Superset and connect it to your data warehouse
Build dashboards: Create dashboards for venue managers, general managers, and executives
Test and iterate: Validate that the data is accurate, that dashboards are useful, and that managers can use them

This phase typically takes 8–10 weeks for a 5–10 venue group, longer for larger groups.

Phase 4: Launch and Adoption (Week 17–24)

Roll out your analytics system to your teams:

Train your managers: Conduct training sessions on how to use the dashboards
Establish processes: Define how decisions will be made based on data (weekly reviews, monthly reports, etc.)
Monitor adoption: Track which managers are using the dashboards and which aren’t
Refine based on feedback: Listen to manager feedback and improve the dashboards
Celebrate early wins: Highlight the first improvements driven by data

Phase 5: Optimisation (Ongoing)

Once your system is live, continuously improve it:

Add new metrics: As you learn what matters, add new KPIs to your dashboards
Integrate new systems: As you adopt new software (new POS, new payroll system), integrate it with your warehouse
Improve data quality: Continuously clean and validate your data
Benchmark regularly: Quarterly benchmarking against D23.io and industry standards
Expand scope: Once you’ve mastered revenue and labour, expand to other areas (inventory, waste, customer retention)

Budget and Timeline

For a typical Australian pub group with 5–10 venues:

Phase 1 (Assessment): £5,000–10,000, 2 weeks
Phase 2 (Design): £10,000–20,000, 4 weeks
Phase 3 (Implementation): £30,000–50,000, 10 weeks
Phase 4 (Launch & Adoption): £5,000–10,000, 8 weeks
Phase 5 (Ongoing support): £2,000–5,000 per month

Total first-year cost: £50,000–95,000 including ongoing support.

Return on investment is typically 6–12 months. A single 2% improvement in gross margin across your venue group usually pays for the entire system within a year.

Choosing a Partner

If you’re building this internally, you’ll need:

A data engineer to build and maintain the data warehouse and pipelines
A BI analyst to design and maintain the dashboards
A project manager to coordinate the implementation

Alternatively, you can work with a specialist partner. PADISO offers AI & Agents Automation and Custom Software Development services specifically designed for hospitality groups. They can help you design, build, and deploy a multi-venue analytics system tailored to your specific needs.

When evaluating partners, ask:

Do they have experience with hospitality analytics?
Can they integrate with your specific POS and gaming systems?
Do they understand Australian gaming compliance requirements?
Will they provide ongoing support and training?
What’s their pricing model (fixed project cost vs. ongoing retainer)?

Conclusion

Multi-venue analytics is no longer a luxury for large pub groups—it’s essential for competitive survival. The hospitality industry is becoming increasingly data-driven, and groups that can’t measure and optimise their operations will fall behind.

The good news is that building a world-class analytics system is now affordable and achievable for groups of any size. With tools like Superset, cloud databases, and modern data integration platforms, you can build something that rivals the analytics capabilities of much larger organisations.

Start with your most critical metrics: revenue, margin, labour cost, and gaming compliance. Build dashboards that make these metrics visible to the right people. Use the data to make better decisions. Iterate based on what you learn.

Within 12 months, you should see measurable improvements in profitability, operational efficiency, and compliance. Within 24 months, data-driven decision-making should be embedded in your culture.

The pub groups that win in the next 5 years won’t be those with the most venues or the biggest marketing budgets. They’ll be the ones that can see their business clearly, make fast decisions based on real data, and learn and adapt faster than their competitors.

Your multi-venue analytics system is the foundation for that competitive advantage. Build it now.

Next Steps

Audit your current state: What data do you have? What’s missing?
Define your target metrics: What KPIs matter most to your business?
Design your architecture: What does your ideal analytics system look like?
Get a partner assessment: If you’re not sure how to proceed, engage a specialist to review your current state and recommend a path forward.
Start small: Don’t try to boil the ocean. Pick one venue or one metric to start with, build a dashboard, and learn. Then expand.

For help with any of these steps, consider reaching out to PADISO. They specialise in building AI Agency Services Sydney and custom analytics solutions for hospitality groups. Their AI Strategy & Readiness service can help you assess your current state and plan your analytics roadmap. Their Platform Design & Engineering team can design and build your analytics system. And their AI & Agents Automation offering can help you automate decision-making once you have the data in place.

Whether you work with PADISO or another partner, the key is to start now. Every month you delay is a month of missed insights, suboptimal decisions, and lost profitability. Your competitors are already measuring their operations. It’s time for you to do the same.