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Forecasting and Predictive Analytics

Plan the Next Quarter on Your Own Data, Not Last Year Plus Ten Percent

Most business plans are built by taking last year and adding a number that feels right. Predictive analytics reads your real history, projects revenue, cash, demand and capacity forward, and tells you how confident it is in each figure.

50+ ERP and software projects. Zero failed projects since 2021.

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Revenue projection, next quarter
Forecast
₹16.8 Cr
Projected for the coming quarter
₹9.2 Cr already in the confirmed order book
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Actual Forecast
Confidence range 7% at this horizon, widening beyond 90 days
Illustrative figures
2-3 yr
Of history read
5
Forecast areas covered
Every
Projection carries a range
Monthly
Accuracy reported against actuals
Why It Matters

A plan built on a guess costs money in both directions

Forecast too high and you carry stock, capacity and people you do not need. Forecast too low and you miss orders you could have taken. Both are expensive, and both are avoidable.

Patterns You Cannot See by Eye

Your history already knows more than the spreadsheet does

Seasonality, customer buying cycles, the gap between enquiry and order, and the effect of a price change are all sitting in your transaction data. A model reads them together, which is difficult to do by hand across thousands of records.

  • Seasonality separated from real trend.
  • Customer-level cycles picked up individually.
  • Signals combined, not read one at a time.
Historical business data being analysed for patterns
Honest About Uncertainty

A range you can plan against beats a single confident number

Every projection comes with a confidence range and the assumptions behind it, so you can plan capacity for the middle case and know what the downside looks like. Accuracy is measured against actuals each period, so the forecast earns its credibility over time.

  • A range on every figure, not a false precision.
  • Assumptions written out for your team to challenge.
  • Accuracy tracked and reported openly.
A planning team reviewing forecast scenarios
Beyond Revenue

The same method applied to cash, demand and capacity

Revenue is where most businesses start, but the forecasts that change decisions are usually about cash timing and plant capacity. Each one is built and reported the same way.

Cash inflow projection, next 90 days
Forecast
₹11.4 Cr
Expected collections over the period
Based on each customer paying to their own pattern, not to terms
Wk 1
Wk 2
Wk 3
Wk 4
Wk 5
Wk 6
Wk 7
Wk 8
Collected Projected
Two weeks show a shortfall against committed outflow, flagged for review
Illustrative figures
How It Works

From your transaction history to a forecast your team trusts

1
Decide what to forecast
We start from the decisions you need to make, then pick the measures that support them.
2
Prepare the history
We pull two to three years of records and clean the gaps, duplicates and one-off events.
3
Build and test
Models are tested on past periods you already know, so accuracy is measured before release.
4
Publish with ranges
Each projection is published with its confidence range, drivers and assumptions.
5
Review and adjust
Each period we compare forecast against actual, report the gap and retune the model.
What We Forecast

Six projections leadership teams use most

Each one is built from your own records, carries a stated range, and can be broken down to the customers, products or accounts behind it.

📈

Revenue and order intake

Projected sales by month, product and region, with the confirmed order book separated out.

💰

Cash inflow

Expected collections week by week, based on how each customer actually pays rather than terms.

📦

Product demand

Item-level demand for planning purchase and stock, with seasonality handled properly.

🏭

Capacity requirement

The plant hours, machines or people the projected order book will need, and where it gets tight.

🤝

Customer behaviour

Which accounts are likely to grow, slow down or stop ordering, based on their own pattern.

⚖

Margin and cost trend

Where margin is heading if current input cost and product mix continue as they are.

The Difference

What forecasting on real data changes

Evidence
Behind the annual plan
Earlier
View of a cash squeeze
Less
Stock held against a guess
Better
Capacity and hiring decisions
Stated
Confidence on every number
Tracked
Accuracy, period after period
Why Us

Why teams choose TCB Infotech for predictive analytics

1
We prepare the data properly
We build ERP, so we know where the gaps and one-off entries in your history are.
2
Tested before release
Every model is checked against periods you already know, so accuracy is a measured fact.
3
Model-agnostic
We fit the method to your data pattern and horizon rather than forcing one technique.
4
Ranges, not false precision
We publish confidence ranges and say plainly where the forecast is weak.
5
Planning stays yours
The forecast is an input to your planning meeting. Your team makes the commitments.
6
Proven delivery
50+ projects across industries, with zero failed projects since 2021.
FAQ

Forecasting and predictive analytics questions

What is business forecasting with predictive analytics?
It is projecting what is likely to happen next in your business, using your own history rather than a flat percentage on last year. Predictive analytics reads patterns in sales, orders, collections, production and customer behaviour, projects revenue, cash, demand and capacity forward, and states how confident it is in each projection.
How accurate are the forecasts?
Accuracy depends on how stable your business is and how much clean history exists. Rather than claim a single number, every projection carries a confidence range and we report accuracy against actuals each period, so you can see how the forecast is performing and treat it accordingly.
How much history do you need?
Two to three years of transaction history gives the best result, because it lets the model separate seasonality from trend. Twelve to eighteen months is usually workable for shorter-horizon forecasts, with a wider confidence range to reflect the thinner history.
What can you forecast for us?
The usual set is revenue and order intake, cash inflow and collection timing, product-level demand, plant or team capacity needs, and customer behaviour such as which accounts are likely to reduce or stop ordering. What we build depends on the decisions you need it for.
Can we see why the forecast says what it says?
Yes. Each projection shows the drivers behind it, such as the order book already confirmed, seasonal pattern, recent trend and known events like a price change. The assumptions are written out so your team can challenge them and adjust.
Does the forecast replace our planning process?
No. It gives your planning meeting a starting position built on evidence instead of a guess. Your team adjusts for what the data cannot see, such as a new customer being signed or a line being shut for maintenance, and the plan stays a human decision.

Build Your Next Plan on Evidence

Book a free consultation. Tell us what you are planning for, and we will show you what your own history can already project and how confident it would be.

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No commitment. A practical look at what your data supports.