Data & Analytics

We turn messy operational data into decisions leaders trust

Advanced Excel, Power BI, Tableau, Power Automate, Python, data cleansing and Databricks — one team that takes you from a folder of exports to a governed model your board reviews every month.

Advanced ExcelPower BITableauPower AutomatePythonData CleansingDatabricks

Raw messy data

Excel

Power BI

Tableau

Power Automate

Python

Databricks

Data Pulse

Governed outputStrategic Insight

Governed outputPredictive Signals

Governed outputDecision Dashboards

Governed output

Platforms in the toolkit

Excel · Power BI · Tableau · Power Automate · Python · Databricks

Departments modelled

Finance through to HR

Industries served

Real estate to manufacturing

240M

Rows in a nightly pipeline

Processed inside its refresh window

How the work runs

From raw extract to reviewed decision

The same five steps every time. Most teams have the last one and none of the first four — which is why their dashboards get argued with instead of acted on.

Step 1
Ingest
ERP, CRM, files, APIs
Step 2
Cleanse
De-duplicate, validate, classify
Step 3
Model
Star schema, measures, security
Step 4
Visualise
Power BI, Tableau, Excel
Step 5
Decide
Alerts, reviews, actions

Live demo — not a screenshot

A working Power BI-style report

Change the department, the industry or the period and the whole model recalculates — KPIs, trend, mix, rankings and the detail table. Three report pages, exactly as they would be delivered.

Slicers are live — try themThree report pagesEvery total reconciles

s3m-consulting.com / analytics / finance

Manufacturing / Production · Last 12 months

Finance

Revenue, margin and plan variance in one reconciled model

Live model · USD

Total Revenue · 12M

$357.4M

4.6%against budget of $374.8M

Budget: $374.8M
Variance: −$17.4M
Monthly average: $29.8M
Attainment: 95.4%

Revenue

$357.4M

15.7%derived

Sum of 12 months

vs Budget

−$17.4M

4.6%derived

$357.4M − $374.8M

Monthly average

$29.8M

15.7%derived

$357.4M ÷ 12

EBITDA margin

18.7%

2.1%

Rate — not additive

Cash conversion

82.1%

2.2%

Rate — not additive

Revenue vs Budget

Monthly · sums to $357.4M

RevenueBudget

Revenue by stream

5 streams · 100% of total

24.9%Recurring contracts

Core services$65.4M
Recurring contracts$88.8M
Projects$59.8M
Licensing$77.7M
Other income$65.7M

Revenue contribution

By plant · sums to total

Fabrication South
24.0%
$85.9M
Riverside Assembly
22.1%
$78.8M
Components West
18.4%
$65.9M
Northfield Plant 1
16.4%
$58.7M
Press Shop East
12.5%
$44.7M
Central Foundry
6.6%
$23.4M
Total · 6 plants$357.4M

Budget attainment

Actual ÷ budget

95.4%$357.4M of $374.8M4.6 pts under target

What we actually do

Seven capabilities, one delivery team

Not a tool list — the specific work we do inside each platform, and what it changed the last time we did it.

Advanced Excel

Models that survive contact with the business

Power Query and Power Pivot data models
Dynamic arrays, LAMBDA and named formula libraries
Scenario, sensitivity and driver-based planning models
Auditable workbooks with documented calculation chains

Replaced a 40-tab manual pack with a single refreshable model

Coverage

Built for your function and sector

Every one of these is a slicer on the report above, backed by its own measures, hierarchy and definitions.

By department

Nine functional models, each with its own KPI set

Finance
Accounts Receivable
Accounts Payable
Fixed Assets
Inventory
Purchases
Sales
Retail Sales
Human Resources

By industry

Sector logic, naming and benchmarks built in

Real Estate
Property Management
Hotel Management
Restaurant
Hospital Management
Project Management
Logistics
Manufacturing / Production

Want this built on your data?

Send us one messy extract. We'll come back with a working model, the questions it answers, and what it would take to run it every month.