Performance Management & Analytics
KPI architecture, planning and forecasting, including projections built with machine learning, unit economics, and board reporting.
Management reporting that a monthly meeting can start from.
Dashboards fail for a reason software cannot fix: the organisation never agreed what its numbers mean. Sales books revenue one way, finance recognises it another, and treasury collects it a third, so every meeting starts with a reconciliation.
We build what sits underneath good reporting: a short list of measures with agreed definitions, owners, and source systems. Budgets and rolling forecasts are built on the drivers that move results, increasingly with machine learning models trained on the company’s own history. Unit economics show where the money is actually made, and board packs open with the decisions to be taken. The tools come last, and they are usually ones the company already owns.
How we help clients
KPI architecture
A metric dictionary setting out the definition, formula, owner, and source system for the ten to fifteen measures that actually run the business.
- Metric dictionary
- Definitions
Budgeting and driver-based planning
Annual plans built on the drivers that move results, such as volumes, prices, headcount, and capacity, so the budget can be re-run when the business changes instead of abandoned by June.
- FP&A
- Driver-based planning
Forecasting with machine learning
Projections of revenue, demand, collections, and cash from machine learning models trained on the company’s own history and on external indicators. Each forecast comes with a range rather than a single number, and a plain account of what is driving it, so finance can challenge it and management can act on it.
- Machine learning
- Rolling forecasts
- Scenario analysis
Unit economics and profitability
Profitability by customer, product, channel, and location, using allocation rules management can defend and act on.
- Contribution margin
- Cost allocation
Board and investor reporting
Monthly and quarterly packs organised around decisions, with variances explained by cause and forward indicators shown next to results, built in Excel, Power BI, or the existing ERP.
- Board packs
- MIS
- Power BI
Business cases and financial models
Models for a capital project, a new market, or an acquisition, built to be pulled apart by a lender or a board.
- Financial modelling
- Scenarios
Forecasting with machine learning
A static budget is a single guess made months ago. A forecast built with machine learning updates as actuals arrive, gives a range that widens with the horizon, and shows which drivers moved it, so the board can question the forecast instead of the spreadsheet behind it.
Technology and AI in our workA machine learning forecast gives a range and the reasons behind it, not only a number
Illustrative monthly revenue with a static budget and a machine learning forecast, ₹ crore
Illustrative figures. The interval widens with the horizon; the driver attribution shows which inputs account for the change against last year, so finance can challenge the forecast before it reaches the board.
Source: SA&A analysis
Soni Aditya & Associates
When clients call us
Every meeting begins by reconciling numbers
Sales, operations, and finance each arrive with a different figure for the same measure.
The budget stopped being useful by mid-year
The plan was a negotiation rather than a model, and the business has moved on without it.
Forecasts keep missing in the same direction
Spreadsheet forecasts carry the same optimism every quarter, and nobody can say which assumption is responsible.
Growth is not turning into cash
Revenue rises while margins and cash do not, and nobody can point to the customers or products behind it.
A board has been formed
Independent directors or investors expect reporting that management has never had to produce.
A capital decision is pending
A plant, a new market, or an acquisition needs a model that lenders and the board will challenge.
Our approach
Definitions before dashboards
The metric dictionary is agreed and signed off before anything is visualised.
Models you can question
Machine learning forecasts come with ranges and the drivers behind them. A forecast nobody can explain does not go in front of a board.
Reconciled to the ledger
Operational measures tie back to the accounts, so the management pack and the financial statements tell one story.
Every page earns its place
Each page of a management pack answers a question someone has to act on.
Examples of our work
Removing recurring cash shortages across a highway fuel retail network
Designing a clean-slate structure for a new agri-tourism group with four distinct business lines
Related
Technology & AI
Revenue, demand, collections, and cash forecast with machine learning on the company’s own history, each with a range and the drivers behind it, and refreshed every month as actuals come in.
Audit-readiness diagnostic
Fifteen statements, about four minutes, and a scored view of where your audit exposure is concentrated.
The Brief
Our fortnightly read on reporting, tax, and structure for CFOs, controllers, and founders.
Aditya Soni
Founding Partner, Pune
Leads the firm’s work in performance and analytics. Advises companies and families on financial reporting, audit readiness, group structure, and tax. Previously in the Assurance practice of Ernst & Young in Pune.
Talk to our Performance & Analytics practice
Tell us what you are working on. A first conversation carries no obligation, and confidentiality applies from the first email.