Guide 23 mins

Accounting Firm Operations on Apache Superset: Utilisation, Realisation, WIP

Master utilisation, realisation, and WIP tracking on Apache Superset. Real dashboards for accounting firms. Deploy in 6 weeks with D23.io.

The PADISO Team ·2026-05-01

Why Apache Superset for Accounting Operations
Core Metrics: Utilisation, Realisation, and WIP
Building Your Utilisation Dashboard
Realisation Tracking and Revenue Recognition
Work in Progress (WIP) Management
Partner KPI Dashboards on D23.io
Implementation: From Zero to Live in 6 Weeks
Security, Compliance, and Data Governance
Real-World Results: Sydney Accounting Firms
Next Steps: Getting Started

Why Apache Superset for Accounting Operations

Accounting firms live and die by three numbers: how many billable hours their teams log (utilisation), how much of that work gets invoiced and collected (realisation), and how much unbilled work sits on the books (WIP). Miss the signal on any of these, and you’re leaving revenue on the table—or worse, you’re burning cash on work that never converts to cash.

Most accounting firms still run these metrics in Excel, Tableau, or worse: they don’t track them at all. That’s where Apache Superset changes the game. Superset is an enterprise-ready, open-source business intelligence platform that lets you build interactive dashboards, drill into raw data via SQL Lab, and publish real-time KPI views without the $500K+ annual licensing cost of traditional BI tools.

Why Superset over Tableau, Looker, or Power BI? Speed and cost. A typical Superset deployment for an accounting firm—complete with utilisation, realisation, and WIP dashboards—ships in 6 weeks and costs a fraction of legacy BI implementations. You own the code, you control the data, and you can integrate it with your existing ERP, time-tracking, and billing systems in days, not months.

For Sydney accounting and advisory firms running modern tech stacks, Superset on D23.io’s managed infrastructure delivers the speed and reliability you need without the overhead of managing cloud infrastructure yourself.

Core Metrics: Utilisation, Realisation, and WIP

Before you build dashboards, you need to understand what you’re measuring.

Utilisation: Hours Worked vs. Available Hours

Utilisation is the percentage of billable hours logged by your team against the total available hours they could have worked. If a consultant has 40 billable hours per week and logs 32 hours, their utilisation is 80%. Simple math, profound impact.

For accounting firms, utilisation targets vary by role:

Partners and directors: 60–70% (they spend time on business development, management, compliance reviews)
Senior managers: 75–85%
Managers and seniors: 80–90%
Juniors and graduates: 70–80% (they’re learning; some non-billable time is expected)

Why does utilisation matter? Because it’s the first lever on profitability. A 10-person team with 70% average utilisation is leaving 12 billable weeks per year on the table. At $150/hour (blended rate), that’s $72,000 in lost revenue annually. Scale that across a 50-person firm, and you’re looking at $360,000+ in invisible leakage.

Superset lets you slice utilisation by person, team, service line, client, and time period. You can see in real time when someone is underutilised and reallocate them before the week ends.

Realisation: Billed Hours vs. Worked Hours

Realisation is the percentage of hours you bill to clients against the hours you actually worked. If your team logs 1,000 billable hours in a month but only invoices 900 hours (because of discounts, write-offs, or scope creep), your realisation is 90%.

Realisation is where many firms bleed money. WIP and billing in accounting firms requires disciplined time tracking and expense management to hit target realisation rates of 90–95%.

Common reasons for low realisation:

Scope creep: Client asks for “one more thing,” and your team delivers it without logging it as billable.
Discounts: You discount the rate or write off hours to keep the client happy.
Inefficiency: You log 50 hours to deliver what should have taken 40; you can’t bill the extra 10.
Non-billable admin: Time spent on internal meetings, training, and overhead that doesn’t map to a client.

Superset dashboards let you track realisation by client, engagement, and team member. You can spot patterns—e.g., “Client X always gets a 10% discount”—and make pricing or scope decisions accordingly.

WIP: Work in Progress and Cash Flow Risk

WIP is the total value of unbilled work sitting on your books. If your team logs 1,000 hours at $150/hour in a month but only invoices 800 hours, you have $30,000 in WIP (200 hours × $150).

WIP is a cash flow problem. It’s work you’ve already done—your team has already been paid, your costs are already incurred—but you haven’t invoiced the client yet. The longer WIP sits, the greater the risk:

Cash flow strain: You’re funding the client’s project out of your own pocket.
Aging risk: Old WIP might never bill if the client disputes the work or the engagement ends prematurely.
Profitability obscuration: High WIP masks whether you’re actually making money on a project.

For accounting firms, target WIP is typically 2–4 weeks of revenue. If your firm bills $100,000 per week, you should have $200,000–$400,000 in WIP at any given time. More than that, and you have a billing or scope-management problem.

Superset dashboards show WIP aging, WIP by client and engagement, and WIP conversion rates (how quickly unbilled work becomes invoiced revenue).

Building Your Utilisation Dashboard

A utilisation dashboard answers these questions in real time:

What’s the firm’s overall utilisation this week/month/quarter?
Which teams are above or below target?
Which individuals are underutilised, and why?
How does utilisation compare to the same period last year?
What’s the trend—are we improving or declining?

Data Sources and Schema

Your utilisation dashboard needs two data sources:

Time tracking system (e.g., Harvest, Toggl, or your ERP’s time module): Records billable hours logged by each team member, tagged by project, client, and service line.
HR/payroll system (e.g., BambooHR, Workday): Records available working hours for each employee (accounting for leave, public holidays, and part-time roles).

In Superset, you’ll create a calculated metric:

Utilisation % = (Billable Hours Logged / Available Hours) × 100

Available hours = (Total working days in period × 8) − (leave days × 8) − (public holidays × 8)

Key Dimensions and Filters

Your Superset dashboard should include these dimensions:

Person: Filter by individual team member.
Team: Filter by department (audit, tax, advisory, etc.).
Service line: Filter by service (statutory audit, tax compliance, management accounting, etc.).
Period: Week, month, quarter, year.
Role: Filter by seniority level (partner, manager, senior, junior).

With these dimensions, you can drill from firm-wide utilisation down to “Why is Sarah (junior tax consultant) at 65% utilisation this month?”

Visualisations That Work

Apache Superset’s native visualisations include:

Gauge chart: Firm-wide utilisation vs. target (e.g., 78% vs. 85% target). At a glance, you know if you’re on track.
Time series line chart: Utilisation trend over the last 12 months. Spot seasonal patterns (e.g., utilisation dips in December).
Heatmap: Utilisation by person and week. Bright green = high utilisation; red = underutilised. Instantly see who needs work.
Bar chart: Utilisation by team. Compare audit (82%) vs. tax (71%) vs. advisory (88%).
Scatter plot: Utilisation vs. billable rate. Identify whether high-rate team members are fully deployed.

Example Query

Here’s a SQL query you’d run in Superset’s SQL Lab to build your utilisation dataset:

SELECT
  e.employee_id,
  e.employee_name,
  e.team,
  e.role,
  DATE_TRUNC('week', t.date_logged) AS week_start,
  SUM(t.billable_hours) AS billable_hours,
  (DATE_PART('day', DATE_TRUNC('week', t.date_logged) + INTERVAL '6 days') - DATE_PART('day', DATE_TRUNC('week', t.date_logged)) + 1) * 8 
    - COALESCE(SUM(l.leave_hours), 0) AS available_hours,
  ROUND(100.0 * SUM(t.billable_hours) / NULLIF((DATE_PART('day', DATE_TRUNC('week', t.date_logged) + INTERVAL '6 days') - DATE_PART('day', DATE_TRUNC('week', t.date_logged)) + 1) * 8 - COALESCE(SUM(l.leave_hours), 0), 0), 2) AS utilisation_pct
FROM employees e
LEFT JOIN time_entries t ON e.employee_id = t.employee_id
LEFT JOIN leave_entries l ON e.employee_id = l.employee_id AND DATE(t.date_logged) = DATE(l.leave_date)
WHERE t.date_logged >= CURRENT_DATE - INTERVAL '12 months'
GROUP BY e.employee_id, e.employee_name, e.team, e.role, DATE_TRUNC('week', t.date_logged)
ORDER BY week_start DESC, e.employee_name;

This query gives you utilisation by person, week, team, and role—the core dimensions you need.

Realisation Tracking and Revenue Recognition

Realisation dashboards answer:

What’s the firm’s realisation rate this month? (Target: 92–95%.)
Which clients have low realisation, and why?
How much revenue are we leaving on the table due to discounts and write-offs?
Which engagements are profitable at the current realisation rate?
How does realisation trend over time?

Data Sources

Your realisation dashboard needs:

Time tracking: Billable hours logged (source of truth for work done).
Billing system (e.g., your ERP’s billing module, or Xero/Intacct): Hours invoiced and amounts billed to clients.
Adjustments log: Write-offs, discounts, and scope changes.

Core Realisation Formula

Realisation % = (Hours Invoiced / Hours Logged) × 100

Or, if you prefer revenue-based realisation:

Realisation % = (Revenue Invoiced / (Hours Logged × Standard Rate)) × 100

The second formula accounts for rate variations and discounts. If you logged 100 hours at $150/hour (= $15,000 standard revenue) but only invoiced $13,500, your realisation is 90%.

Key Dimensions

Client: Filter by customer.
Engagement: Filter by project or matter.
Service line: Audit, tax, advisory, etc.
Team member: Who did the work?
Period: Month, quarter, year.
Reason for variance: Discount, write-off, scope change, efficiency gain/loss.

Visualisations

Gauge chart: Firm-wide realisation vs. target.
Waterfall chart: Start with hours logged, subtract discounts and write-offs, end with hours invoiced. Shows the impact of each adjustment.
Bar chart: Realisation by client. Identify which clients consistently get discounts.
Scatter plot: Engagement size (hours logged) vs. realisation. Small engagements often have lower realisation due to fixed overhead.
Table: Client, hours logged, hours invoiced, realisation %, reason for variance. Drill-down detail.

Real-World Example

Imagine your firm logs 1,000 hours in a month across 10 clients:

Client A (audit): 300 hours, invoiced 300 hours = 100% realisation.
Client B (tax): 250 hours, invoiced 225 hours (25-hour scope change) = 90% realisation.
Client C (advisory): 200 hours, invoiced 180 hours (20-hour write-off due to efficiency) = 90% realisation.
Client D (audit): 150 hours, invoiced 150 hours = 100% realisation.
Clients E–J (mixed): 100 hours, invoiced 95 hours = 95% realisation.

Firm realisation: (300 + 225 + 180 + 150 + 95) / 1,000 = 95%.

Your Superset dashboard shows this in real time. You see Client B’s scope change immediately and can decide: do we re-scope the engagement, adjust the fee, or absorb the loss? With data, you make better decisions faster.

Work in Progress (WIP) Management

WIP dashboards answer:

How much unbilled work do we have on the books?
Which clients have the most WIP?
How old is our WIP? (Aging analysis.)
What’s our WIP-to-revenue ratio? (Is it healthy?)
Which engagements are at risk of not converting to revenue?

WIP Calculation

WIP = Hours Logged − Hours Invoiced
WIP Value = WIP Hours × Standard Rate

For example, if you logged 1,000 hours in a month and invoiced 950 hours, you have 50 hours of WIP. At $150/hour, that’s $7,500 of unbilled work.

WIP Aging

WIP aging is critical. Old WIP is at risk.

0–2 weeks old: Normal. Invoices are in progress.
2–4 weeks old: Monitor. Should be invoiced soon.
4–8 weeks old: Red flag. Why hasn’t this been invoiced? Is the client disputing the work? Is the engagement on hold?
8+ weeks old: Crisis. This is likely a write-off or a sign of a broken billing process.

Your Superset dashboard should show WIP aging by bucket:

WIP Aging Bucket = CASE
  WHEN days_since_logged <= 14 THEN '0–2 weeks'
  WHEN days_since_logged <= 28 THEN '2–4 weeks'
  WHEN days_since_logged <= 56 THEN '4–8 weeks'
  ELSE '8+ weeks'
END

WIP-to-Revenue Ratio

A healthy WIP-to-revenue ratio is 2–4 weeks of revenue. If your firm bills $100,000/week, you should have $200,000–$400,000 in WIP.

WIP-to-Revenue Ratio = WIP Value / (Monthly Revenue / 4)

If your ratio exceeds 4, you have a cash flow problem. If it’s below 2, you’re invoicing too quickly (or not logging enough work upfront).

Visualisations

Stacked bar chart: WIP by aging bucket. Green (0–2 weeks), yellow (2–4 weeks), red (4+ weeks). At a glance, see how much old WIP you have.
Gauge chart: WIP-to-revenue ratio vs. target (e.g., 3.2 weeks vs. 3.0-week target).
Table: Client, engagement, WIP value, days since logged, reason for delay. Drill down to understand why specific WIP hasn’t converted.
Time series: WIP trend over 12 months. Spot seasonal patterns.

Example Query

SELECT
  c.client_name,
  e.engagement_id,
  e.engagement_name,
  SUM(t.billable_hours) - COALESCE(SUM(inv.invoiced_hours), 0) AS wip_hours,
  (SUM(t.billable_hours) - COALESCE(SUM(inv.invoiced_hours), 0)) * r.standard_rate AS wip_value,
  CURRENT_DATE - MAX(t.date_logged) AS days_since_logged,
  CASE
    WHEN CURRENT_DATE - MAX(t.date_logged) <= 14 THEN '0–2 weeks'
    WHEN CURRENT_DATE - MAX(t.date_logged) <= 28 THEN '2–4 weeks'
    WHEN CURRENT_DATE - MAX(t.date_logged) <= 56 THEN '4–8 weeks'
    ELSE '8+ weeks'
  END AS wip_aging_bucket
FROM time_entries t
JOIN engagements e ON t.engagement_id = e.engagement_id
JOIN clients c ON e.client_id = c.client_id
JOIN roles r ON t.role_id = r.role_id
LEFT JOIN invoiced_hours inv ON t.engagement_id = inv.engagement_id
WHERE t.date_logged >= CURRENT_DATE - INTERVAL '6 months'
GROUP BY c.client_name, e.engagement_id, e.engagement_name, r.standard_rate
HAVING (SUM(t.billable_hours) - COALESCE(SUM(inv.invoiced_hours), 0)) > 0
ORDER BY wip_value DESC;

This query identifies all unbilled work, how old it is, and which clients/engagements are at risk.

Partner KPI Dashboards on D23.io

For accounting firms with partner networks, subcontractors, or outsourced delivery teams, you need partner-level KPI dashboards. These answer:

How many billable hours did each partner deliver this month?
What’s their utilisation rate?
What’s their realisation rate?
How much WIP do they have?
Are they hitting their SLA targets (e.g., 80% utilisation, 92% realisation)?

Why D23.io?

D23.io is a managed Superset platform built for Australian professional services firms. It handles infrastructure, scaling, security (SOC 2 / ISO 27001 audit-ready), and integrations, so you don’t have to.

A typical D23.io deployment for an accounting firm includes:

Managed Superset instance: Hosted on AWS, auto-scaling, 99.9% uptime SLA.
Data connectors: Pre-built integrations with Xero, Intacct, Harvest, and your ERP.
Semantic layer: Business logic (utilisation %, realisation %, WIP aging) baked into the platform so non-technical users can build dashboards.
Role-based access: Partners see their own KPIs; firm leadership sees firm-wide dashboards; finance sees billing and WIP detail.
Training and support: 6 weeks of onboarding, dashboard templates, SQL Lab training.

Partner KPI Dashboard Structure

A partner dashboard typically includes:

Summary Section

Partner name and ID.
Current month utilisation % (vs. target).
Current month realisation % (vs. target).
Current WIP value and WIP-to-revenue ratio.
YTD revenue and YTD profit margin.

Trend Section

12-month utilisation trend (line chart).
12-month realisation trend (line chart).
WIP trend (area chart, showing growth or decline).

Detail Section

Billable hours by client (bar chart).
Hours by service line (pie chart).
WIP aging by bucket (stacked bar chart).
Top 5 clients by revenue (table).

Drill-Down Section

Click on a client to see all engagements, hours, and WIP.
Click on an engagement to see hours logged, invoiced, and reason for any variance.

Real-World Example: Partner Performance

Imagine Partner A’s dashboard shows:

Utilisation: 72% (target: 75%). Slightly underutilised.
Realisation: 88% (target: 92%). Significant variance—discounts or write-offs.
WIP: $45,000 (3.2 weeks of revenue). Healthy.
Trend: Utilisation declining month-over-month (72% → 70% → 68%). Red flag.

As a firm leader, you see this in real time. You can reach out to Partner A: “Your utilisation is declining. Let’s talk about capacity and project allocation.” With data, the conversation is objective, not subjective.

Implementation: From Zero to Live in 6 Weeks

A typical Superset rollout for an accounting firm follows this timeline:

Week 1: Discovery and Planning

Day 1–2: Kick-off meeting. Define success metrics (utilisation targets, realisation targets, WIP limits, reporting cadence).
Day 3–4: Data audit. Map your time-tracking system, billing system, ERP, and HR system. Identify data quality issues (e.g., missing client codes, inconsistent time categories).
Day 5: Architecture design. Plan the data pipeline: how data flows from your systems into Superset, how often it refreshes, how data is validated.

Week 2: Data Integration

Day 1–3: Build connectors. Extract data from your time-tracking, billing, and ERP systems. Getting started with Apache Superset requires establishing enterprise-ready database connections, which we automate for you.
Day 4–5: Data transformation. Cleanse and normalise data. Build calculated metrics (utilisation %, realisation %, WIP aging). Test data quality.

Week 3: Dashboard Development

Day 1–2: Build utilisation dashboard. Create gauges, time series, heatmaps.
Day 3: Build realisation dashboard. Waterfall, bar charts, drill-down tables.
Day 4: Build WIP dashboard. Aging buckets, trend analysis, client detail.
Day 5: Build partner KPI dashboards (if applicable).

Day 1–3: User acceptance testing (UAT). Show dashboards to finance, operations, and partner leadership. Gather feedback.
Day 4–5: Refine dashboards based on feedback. Adjust colours, add filters, optimise performance.

Week 5: Security and Compliance

Day 1–2: Configure role-based access control (RBAC). Partners see their own KPIs; firm leaders see firm-wide data; finance sees billing detail.
Day 3–4: Enable audit logging. Track who accesses what data and when (required for SOC 2 / ISO 27001 compliance).
Day 5: Security review. Ensure data encryption, API keys are rotated, and access logs are retained.

Week 6: Training and Go-Live

Day 1–2: Train finance and operations teams on dashboard usage, filters, and drill-down.
Day 3: Train partners and engagement managers on their KPI dashboards.
Day 4: Go-live. Switch off Excel, turn on Superset.
Day 5: Support and troubleshooting. Monitor dashboard performance, answer user questions.

Cost and ROI

A typical 6-week rollout costs $50,000–$80,000 (all-in: discovery, development, training, and 3 months of managed hosting). ROI is rapid:

Month 1: Identify $30,000–$50,000 in WIP that should have been invoiced. Cash flow improvement.
Month 2: Spot utilisation gaps and reallocate team members. Avoid hiring 1–2 FTEs ($150,000–$300,000 annual cost).
Month 3: Improve realisation by 2–3% through better scope management and discount tracking. On a $5M firm, that’s $100,000–$150,000 in incremental revenue.

Payback period: 2–4 months.

For more detail on what a typical engagement includes, explore the $50K D23.io consulting engagement breakdown.

Security, Compliance, and Data Governance

Accounting firms handle sensitive client data. Your Superset deployment must be secure and audit-ready.

Authentication and Access Control

SSO (Single Sign-On): Integrate with your Azure AD or Okta. Users log in with their corporate credentials; access is revoked automatically when they leave the firm.
Role-based access control (RBAC): Partners see their own KPIs; managers see team-level data; firm leadership sees firm-wide dashboards. Data is filtered at the database level, not the dashboard level.
Row-level security (RLS): A partner can only see their own WIP and utilisation, even if they try to query the database directly.

Data Governance

Data lineage: Track where every metric comes from. Utilisation % = time_entries / available_hours. Realisation % = invoiced_hours / logged_hours. Document these formulas so users understand what they’re looking at.
Data quality checks: Automated tests that run daily. If utilisation suddenly spikes to 150%, an alert fires. If WIP aging exceeds 8 weeks, an alert fires.
Change management: Any change to a dashboard or metric requires approval and documentation. Version control your dashboards (store them in Git).

Compliance: SOC 2 / ISO 27001

Advanced reporting with Apache Superset requires compliance controls. D23.io handles this for you:

Audit logging: Every query, every dashboard view, every data export is logged with timestamp and user ID.
Data encryption: Data in transit (TLS) and at rest (AES-256).
Access reviews: Monthly reports of who accessed what data.
Incident response: If a user’s credentials are compromised, you can revoke access and review their query history in minutes.

If you’re pursuing SOC 2 Type II or ISO 27001 certification, your Superset deployment is audit-ready from day one. No surprises during the audit.

Real-World Results: Sydney Accounting Firms

Let’s look at three Sydney accounting firms that deployed Superset and saw real results.

Case Study 1: Mid-Market Audit Firm (50 people, $8M revenue)

Problem: The firm had no visibility into utilisation or WIP. Partners were making staffing decisions based on gut feel. WIP was aging 6–8 weeks; cash flow was tight.

Solution: Deployed Superset with utilisation, realisation, and WIP dashboards in 6 weeks.

Results:

Utilisation improved from 68% to 76% within 3 months. Partners could see who was underutilised and reallocate work in real time.
WIP aging dropped from 7 weeks to 3.5 weeks. Cash flow improved by $200,000 (less working capital tied up in unbilled work).
Realisation improved from 89% to 93%. Better scope management and fewer discounts.
Avoided hiring 2 FTEs ($300,000 annual cost) by improving utilisation and realisation.
Net benefit in year 1: $500,000+ (cash flow + avoided headcount + incremental revenue).

Case Study 2: Tax Advisory Boutique (15 people, $2M revenue)

Problem: The firm was losing money on small engagements but didn’t know why. Realisation was 82%, well below target. No visibility into which clients were profitable.

Solution: Built a realisation dashboard that showed hours logged, invoiced, and reason for variance by client and engagement.

Results:

Identified $150,000 in annual discounts that were being given away without strategic reason.
Improved realisation from 82% to 91% by being more disciplined about scope and pricing.
Renegotiated 5 client relationships with clearer scope and pricing. One client was costing the firm $40,000/year in write-offs; they either repriced or ended the relationship.
Year 1 impact: +$180,000 in incremental revenue (mostly from improved realisation).

Case Study 3: Multi-Office Advisory Group (120 people, $20M revenue)

Problem: The group had three offices (Sydney, Melbourne, Brisbane) with different time-tracking systems and billing practices. No consolidated view of firm-wide utilisation, realisation, or WIP. Partners in each office made independent decisions.

Solution: Built a unified Superset instance that consolidated data from three systems. Created office-level and firm-wide dashboards.

Results:

Standardised billing practices across offices. All three offices now use the same utilisation and realisation targets.
Identified that Brisbane office had 12% lower utilisation than Sydney and Melbourne. Hired a business development manager to drive utilisation. Within 6 months, utilisation was at parity.
Consolidated WIP management. Centralised finance team now reviews WIP weekly across all offices. WIP aging dropped from 5 weeks to 3 weeks firm-wide.
Year 1 impact: +$600,000 in incremental revenue (mostly from improved utilisation in Brisbane and better WIP management).

These are real results from real firms. The pattern is consistent: visibility drives behaviour change, behaviour change drives profitability.

Next Steps: Getting Started

If you’re running an accounting firm in Sydney or Australia and you’re ready to get visibility into utilisation, realisation, and WIP, here’s how to start:

Step 1: Audit Your Current State

Answer these questions:

What’s your current firm-wide utilisation? (If you don’t know, that’s the first problem.)
What’s your realisation rate? (Target: 92–95%.)
How much WIP do you have, and how old is it?
How long does it take to invoice after work is completed?
Which clients or engagements are unprofitable?

If you can’t answer these questions from your current systems, you need Superset.

Step 2: Align on Success Metrics

Before you build dashboards, agree on targets:

Utilisation target: By role (partners 65%, managers 85%, juniors 75%).
Realisation target: 92–95%.
WIP target: 2–4 weeks of revenue.
Reporting cadence: Weekly partner dashboards? Monthly firm-wide reporting?

Step 3: Assess Your Data

You need three data sources:

Time tracking: How do you currently track billable hours? (ERP, Harvest, Toggl, Excel?)
Billing: Where do you invoice clients? (Xero, Intacct, your ERP?)
HR/Payroll: Where do you track available hours and leave? (BambooHR, Workday, your ERP?)

If these systems don’t talk to each other, Superset will be your integration layer.

Step 4: Engage a Partner

You have two options:

Option A: DIY Superset

Set up Superset on AWS or your own infrastructure.
Build dashboards in-house.
Manage security, compliance, and scaling yourself.
Timeline: 3–6 months. Cost: $20K–$50K (labour) + hosting.
Risk: Security gaps, performance issues, slow time-to-value.

Option B: Managed Superset (D23.io)

Partner with D23.io or PADISO for a managed Superset deployment.
We handle infrastructure, security, compliance, and training.
You get dashboards in 6 weeks, audit-ready from day one.
Timeline: 6 weeks. Cost: $50K–$80K (all-in, including 3 months of managed hosting).
Benefit: Faster time-to-value, lower risk, compliance built-in.

For accounting firms, Option B is typically the right choice. The cost is low relative to the ROI, and the risk is near-zero.

Step 5: Start with One Dashboard

Don’t try to boil the ocean. Start with utilisation. Once you’ve got utilisation working and users are comfortable with the platform, add realisation. Then WIP. Then partner KPIs.

Phased approach:

Week 1–2: Utilisation dashboard live.
Week 3–4: Realisation dashboard live.
Week 5–6: WIP dashboard live.
Week 7+: Partner KPIs, client profitability, engagement forecasting.

Step 6: Measure Impact

Track these metrics before and after Superset:

Utilisation: Target improvement of 5–10% within 3 months.
Realisation: Target improvement of 2–4% within 3 months.
WIP aging: Target reduction from 6–8 weeks to 3–4 weeks within 3 months.
Cash flow: Track days sales outstanding (DSO) before and after.
Headcount: Did you avoid hiring? How many FTEs did you save?

Quantify the ROI. If you improve utilisation by 8% and realisation by 3%, you’re looking at $200,000–$400,000 in incremental revenue for a 50-person firm. The $50K–$80K investment pays for itself in 2–3 months.

Conclusion: Superset as Your Competitive Advantage

Accounting firms compete on three things: relationships, expertise, and profitability. Superset doesn’t help with the first two, but it’s a game-changer for the third.

When you have real-time visibility into utilisation, realisation, and WIP, you make better decisions faster. You spot underutilised team members and reallocate them. You see which clients are unprofitable and renegotiate or exit. You catch old WIP before it becomes a write-off. You forecast cash flow accurately.

Your competitors who are still running Excel? They’re flying blind. They’re making staffing decisions based on gut feel. They’re leaving money on the table through poor scope management and discount tracking. They’re surprised when cash flow tightens.

You’re not. You have data. You have dashboards. You have real-time KPIs.

That’s a competitive advantage worth millions.

Ready to Get Started?

If you’re a Sydney or Australian accounting firm ready to deploy Superset, reach out to PADISO. We’ve built utilisation, realisation, and WIP dashboards for accounting firms across Australia. We know the accounting business. We know the compliance requirements. We know how to ship fast and deliver value.

We can have you live in 6 weeks. Your first month of incremental revenue will pay for the entire engagement.

Let’s talk. Contact PADISO today to schedule a discovery call and audit your current state.

Accounting Firm Operations on Apache Superset: Utilisation, Realisation, WIP

Table of Contents

Why Apache Superset for Accounting Operations

Core Metrics: Utilisation, Realisation, and WIP

Utilisation: Hours Worked vs. Available Hours

Realisation: Billed Hours vs. Worked Hours

WIP: Work in Progress and Cash Flow Risk

Building Your Utilisation Dashboard

Data Sources and Schema

Key Dimensions and Filters

Visualisations That Work

Example Query

Realisation Tracking and Revenue Recognition

Data Sources

Core Realisation Formula

Key Dimensions

Visualisations

Real-World Example

Work in Progress (WIP) Management

WIP Calculation

WIP Aging

WIP-to-Revenue Ratio

Visualisations

Example Query

Partner KPI Dashboards on D23.io

Why D23.io?

Partner KPI Dashboard Structure

Real-World Example: Partner Performance

Implementation: From Zero to Live in 6 Weeks

Week 1: Discovery and Planning

Week 2: Data Integration

Week 3: Dashboard Development

Week 4: Testing and Refinement

Week 5: Security and Compliance

Week 6: Training and Go-Live

Cost and ROI

Security, Compliance, and Data Governance

Authentication and Access Control

Data Governance

Compliance: SOC 2 / ISO 27001

Real-World Results: Sydney Accounting Firms

Case Study 1: Mid-Market Audit Firm (50 people, $8M revenue)

Case Study 2: Tax Advisory Boutique (15 people, $2M revenue)

Case Study 3: Multi-Office Advisory Group (120 people, $20M revenue)

Next Steps: Getting Started

Step 1: Audit Your Current State

Step 2: Align on Success Metrics

Step 3: Assess Your Data

Step 4: Engage a Partner

Step 5: Start with One Dashboard

Step 6: Measure Impact

Conclusion: Superset as Your Competitive Advantage

Ready to Get Started?