Plan with drivers. Decide with confidence.
Budget 360° brings top-down targets and a bottom-up, driver-based budget into one planning model. ERP fills in actuals, AI suggests assumptions, owners decide and finance approves. The forecast then rolls monthly on the same drivers.
| OEM · part family | LY qty | LY growth | AI suggestion | Final | Budget qty |
|---|---|---|---|---|---|
| OEM ABrake parts | 620 | 6% | 7.0% | 8.0% | 670 |
| OEM ASteering parts | 410 | 4% | 5.0% | 5.0% | 431 |
| OEM BBrake parts | 455 | 9% | 10.0% | 14.3% | 520 |
| OEM BCastings | 357 | 3% | 4.0% | 19.0% | 425 |
- OEM B castings+15 pts vs AI
- Castings rejection4.2% vs 2.1%
- Plant 1 Q3 hours108%
OEM B castings are budgeted 15 pts above the AI suggestion. The new platform explains it; a note is attached for approval.
Most budgets are built top-down and checked too late.
For a manufacturer supplying OEMs, the numbers that matter sit in schedules, BOMs and plants, not in last year plus a growth rate.
Revenue starts from a target.
Not from OEM build schedules, platforms and share of business.
Capacity and cost are guessed.
Machine hours and BOM costs are checked after the budget is approved, if at all.
Margin leaks sit outside the budget.
Annual price-downs, rejections and scrap are averaged away.
The budget dies in Q1.
Every reforecast means rebuilding linked spreadsheets.
From drivers to an approved budget, then a rolling forecast.
- 1Driver treeSource, owner, range
- 2Demand and revenueSchedules, platforms, price
- 3Capacity checkAligned with S&OP
- 4Cost, workforce, capexBOMs, headcount, projects
- 5Approve and lockBottom-up vs top-down targets
- 6Rolling forecastMonthly reforecast on actuals
We start from data you already have
Drivers are built from the systems you run today. Templates cover the rest.
- ERP sales, price and part masters
- OEM schedules and EDI forecasts
- BOMs and material rates
- Plant capacity, shifts and yields
- HRMS headcount and CTC
- GL history and OEM contracts
- Driver templatesExcel, CSV
How we work with you
- Driver workshopsDrivers agreed with the people who will own them.
- Client Success SPOCOne accountable owner for your account.
- Live in stagesFirst budget in 8–11 weeks, then monthly rolls.
- Board-readyEvery plan version saved, with its owner.
One planning model, from driver to rolling forecast.
Every number in the budget traces back to a driver, its source and its owner.
- OEM build scheduleSource: OEM EDI forecastsOwner: Key account manager
- Parts per vehicleSource: BOM and part masterOwner: Engineering
- Share of businessSource: OEM contractsOwner: Sales head
- New platformsSource: OEM nominationsOwner: Sales head
- Price and annual price-downSource: OEM contractsOwner: Commercial
- Raw-material pass-throughSource: Steel indexOwner: Purchase
- Rejection and scrapSource: Plant quality dataOwner: Plant head
- Machine hours and yieldsSource: Plant capacityOwner: Operations
- OEM quantity = build schedule × parts per vehicle × share of business + new platforms
- Revenue = quantity × (price − annual price-down + raw-material pass-through)
AI suggests a starting point. Owners decide. Finance approves.
Assumptions this cycle
| Assumption | Last year | AI suggestion | Why | Final | Owner |
|---|---|---|---|---|---|
| Castings rejection | 2.1% | 2.4% | Six-month trend at Plant 2 | 2.6% | Plant head |
| OEM A volume growth | 6% | 7% | Build schedule up 7% | 8% | Key account manager |
| Annual price-down | 2.0% | 2.5% | Contract renewal terms | 2.5% | Commercial |
| Steel price change | +4% | +3% | Index forward curve | +3% | Purchase |
- AI suggests, people decideSuggestions come with the reason; the owner sets the final value.
- Notes above the lineAny final above or below the AI range needs a short note.
- Kept for auditPast, AI suggestion and final kept for audit.
The plan is checked against plants and BOMs while it is being built.
Capacity and cost
| Capacity check | Machine hours by plant and line against planned volumes, aligned with S&OP |
|---|---|
| BOM standard cost | Material, conversion and overhead per part, from the BOM |
| Standard vs actual | Variance by material price, usage, rejection and yield |
| Opex by cost center | Phased by month, with owner and history |
| Workforce | Headcount and CTC by role, plant and cost center |
| Capex | Projects, tooling, phasing and resulting depreciation |
- Over-capacity flaggedPart families above 100% of machine hours, by quarter.
- PhasingMonthly phasing by seasonality or OEM schedule.
Six owners, one calendar, and versions that are locked once approved.
- Key account managersOEM volumes and share of business
- Sales headNew platforms and aftermarket
- CommercialPrice and annual price-down
- PurchaseMaterial rates and pass-through
- Plant headsCapacity, rejection and scrap
- CFOFinal approval and targets
- 1Driver tree agreedWeek 1
- 2AI baseline sharedWeek 2
- 3Owners submitWeek 3
- 4Capacity checkWeek 4
- 5Top-down vs bottom-upWeek 5
- 6RevisionsWeek 6
- 7Approve and lockWeek 7
Each approved plan is locked as a version, comparable with the next, with its owner and date.
Actuals load monthly; the forecast rolls on the same drivers.
EBITDA bridge · budget to forecast (index, axis from 80)
AI commentary: “The OEM B platform launched two months late, and castings rejection ran 1.5 pts above plan. Together they explain 6.5 of the 9-point gap.”
- Monthly actualsLoaded from the closed ledger, by driver.
- Rolling forecastP&L, balance sheet and cash flow reforecast every month.
- Scenarios and what-ifChange a driver and see the full plan move.
The same work, done differently.
What each leader gets
- CEOScenarios answered in minutes, not weeks.
- CFOA budget and forecast the board can trust, linked to the books.
- Business headsTheir own drivers, owned and tracked against actuals.
- FP&ALess time rolling up submissions, more time on analysis.
Three legs: drivers first, then the engine, then the cycle.
- Leg 1 · 3–4 weeks
Driver tree workshops
Drivers, sources and owners agreed with the people who will own them.
Driver treeOwnersRanges - Leg 2 · 5–7 weeks
Data and planning model
ERP, OEM schedule and HRMS data loaded, and the planning model built.
ERP actualsOEM schedulesHRMS - Leg 3 · monthly
First budget, then rolling
The first budget runs on drivers, then the forecast rolls every month.
BudgetRolling forecastScenarios
Integrations we support
Secure connectors for the systems you run today. Uploads are checked before they are used.
AskChamp agents do the pre-work. See your score.
AskChamp planning agents
They prepare the numbers. Owners decide.
- BaselineBuilds the starting point from ERP actuals and trends.
“OEM A brake parts: 7% suggested, from build schedules.”
- Platform and partReads OEM schedules and nominations.
“OEM B platform start moved from June to August.”
- Quality and scrapTracks rejection and scrap by plant.
“Castings rejection 4.2% vs 2.1% planned.”
- Price and pass-throughApplies price-downs and steel indices.
“Steel +3% recovers half the OEM A price-down.”
- Cost driverChecks BOM cost and machine hours.
“Plant 1 Q3 at 108% of machine hours.”
- ReviewFlags finals far from the suggestion.
“3 rows above AI suggestion need a note.”
What would you like to know about the plan?
Answers only from your governed data, linked to source, within each user's access. AskChamp also sends exception alerts and a weekly digest.
Measured every cycle against your starting baseline.
Plans scored on accuracy, not effort.
The Planning Scorecard shows how close each driver lands to actual, cycle after cycle.
- Baseline firstWe record your current cycle time and accuracy during the assessment.
- Actual vs final, by driverEach owner sees how their driver landed.
- Shared monthlyOne score for leadership, with what to fix next.
- Budget cycle time
- Forecast accuracy by customer and product
- Driver accuracy against actual
- Standard cost variance
- Achievement against top-down targets
Our Certifications
Your finance data secured and your AI governed, to international standards.
Outcomes finance leaders can measure.
Indicative outcomes from client engagements, against your own baseline.
higher forecast accuracy
shorter annual budget cycle
from close to actuals in the plan
of submissions with an owner and approval
less time rolling up department submissions
not weeks, to run and compare scenarios
Trusted by finance leaders.
Wow – top team! The Datachamps team have been brilliant and we highly recommend them. Datachamps really got deep in understanding the project and in setting and managing the delivery. The team were equally brilliant, and what impressed us was their willingness to respond no matter what time of the day – there is a time difference, but that did not matter. So thanks for your effort and care on the project, and we will be working together again.
I have had the pleasure of working with Datachamps & team for the past 5–6 years on a variety of projects involving data analytics, Power BI dashboards, data visualisation and financial modelling, across facilities and utilities management for large industrial parks, renewable energy data analysis, management dashboards and investment modelling. What stands out about Datachamps & team is their ability to quickly understand the client’s needs, frame the problem statement with clarity, and deliver accurate, high-quality solutions. Datachamps & team are extremely responsive, professional, and always bring a thoughtful approach to the work. Their solutions have been practical, timely, and of great value to us.
Datachamps and us have been working together for the last 8 years, and they have helped us navigate our MIS and financial modelling requirements effortlessly. They have a keen analytical and entrepreneurial mind, which makes the job much easier for any founder/CXO.
Datachamps have helped us in digitalizing our data & set department KPIs through the MIS system. The business now feels more connected, and every department’s data is visible to the top management.
Datachamps team implemented the project of Budget Compilation on schedule. They were always available & hand over was smooth, post which they were super helpful in providing support leading to customer satisfaction.
The team’s domain knowledge, quick understanding of the business, deep capabilities in BI & contemporary tech tools has transformed our reporting & decision making based on data.
Our decisions viz expansion into new geographies, product pricing, A/R collection strategies and reporting to the HO have been effective thanks to their Management Reporting & Business Analytics solution.
We have frequently used their analytics solutions for strategic decisions including analyzing impact of M&A, annual budgeting and performance appraisal of Human Resources.
Over last 6 years, besides driving process review and checks on data quality, they have added width, depth, efficiency to our MIS reporting and built customized KPIs such as site-level profitability.
Post COVID-19, we had significant changes in our revenue model and their solution appropriately addressed these. Time from our data preparation from multiple sources, has reduced drastically from a week to just a couple of hours!
Month-end reporting 90% faster, with 120+ man-days back every year
An $800M manufacturer automated board, management and group reporting after every close.
SG&A variance analysis 4 days earlier across 29 entities
A global telecom group automated SG&A reporting on Microsoft Fabric for faster cost reviews.
~1,200 hours a year saved, with 15% more billable hours
A 1,000-person software company built one reporting strategy across six functions.
- 100+Customers
- 150+EFT projects
- 98%Client satisfaction (CSAT)
- 100k+Consulting hours
Questions finance leaders ask before they start.
How do you keep our financial data secure?
We're ISO/IEC 27001 certified for information security. Access is role-based, every action is logged, and we share our security documentation during your evaluation.
Where is our data held, and who can see it?
Two options. We host it for you, or we deploy in your own cloud tenant, in the region and under the security policies your IT security team prefers. Either way, only named people on your engagement can access it, and only for the entities they work on.
How is AI governed?
We're ISO/IEC 42001 certified for AI management. AskChamp answers only from your governed data, and only what each user is allowed to see.
Who will work on our account?
Chartered Accountants lead every engagement, with data and AI engineers alongside. Our founders bring 60+ years of corporate finance experience.
How do engagements start?
With a 30-minute assessment. We agree scope and your baseline, then go live in stages, starting with the work that pays back fastest.
What support do we get?
A dedicated Client Success SPOC, a shared query log and escalation to a senior Chartered Accountant. Response times are set in your service agreement.
What's included, and what isn't?
Included: driver-based revenue, workforce, opex and capex planning, an integrated three-statement plan, rolling forecasts and scenarios. Not included: setting targets or final inputs. Those decisions stay with your leadership and owners.
How long until our first budget runs?
Usually 8–11 weeks: 3–4 weeks of driver workshops, then 5–7 weeks to load data and build the planning model.
Does AI set our budget?
No. AI suggests a starting value with the reason. Each owner sets the final value, and finance approves. The suggestion, the final and the note are all kept.
Can our teams still use Excel?
Yes. Linked Excel templates feed the model, and every upload is checked before it is used.
How is the forecast kept current?
Actuals load monthly from the closed ledger, and the forecast rolls on the same drivers through P&L, balance sheet and cash flow.
Is Budget 360° an EPM tool?
Yes. It covers driver-based planning, budgeting, forecasting, approvals and plan-vs-actual reporting, built on the KoshaOS data foundation.
Does it replace our planning model?
It replaces the spreadsheet mechanics. Your drivers and assumptions move into one governed model.
See your budget built from drivers up.
Share your budget file and one product’s BOM. In 30 minutes, we’ll show it running on drivers.