Service · Operations intelligence

Resource planning

Right people and machines at the right time, from your own demand history.

The problem

Overtime one week, idle hands the next. Stock that ties up cash and still runs out of the one item you need.

Orders, timetables, attendance and stock movements already describe your demand pattern. Planning rarely uses them.

What it costs today

Typical: 10 to 20 percent avoidable overtime, and working capital locked in safety stock set by instinct.

This is for you if
  • Overtime is a regular line in the payroll, not an exception.
  • You run out of some items while others sit for months.
  • Planning happens in one person's head or one person's spreadsheet.
What we build
  • Demand-aware schedules for lines, shifts, branches or batches.
  • Manpower forecasts by week, with the seasonality your business actually has.
  • Inventory levels set from forecast and lead time instead of a fixed buffer.
  • Scheduling rules or optimisation, depending on what the assessment shows.
How we build itIn this order
  1. 01

    Separate the repeating demand from the noise

    Weekday, season, academic calendar, customer cycles. The part that repeats is forecast; the part that does not is buffered, deliberately and visibly.

  2. 02

    Forecast at the level the planner acts on

    Branch and week, line and shift, item and month. A forecast at the wrong grain is accurate and useless.

  3. 03

    Add the constraints

    Skills, shift rules, lead times, minimum order quantities. The output is a suggestion the planner adjusts, not an order they must obey.

  4. 04

    Land it where planning already happens

    The planner's sheet, a dashboard, or a screen in the ERP. No new tool to learn.

  5. 05

    Publish forecast against actual, every week

    The planner sees when to trust the number and when not to. Trust is earned one planning cycle at a time.

Data you already haveThis is usually enough to start
  • Order and sales history
  • Attendance and roster records
  • Stock movement and purchase records
  • Timetables, bookings or service tickets
In practice

Illustrative example

Cut overtime 18% for a 300-technician field-service operation

Rosters were built each month from the previous month, so technicians were overstaffed in branches where demand had moved and overstretched where it had grown.

Read the case study
Typical engagement
Duration2-week assessment, then 6 to 8 week pilot on one unit
TeamEngineering lead, data engineer, operations analyst
You receiveForecast and planning tool in use by the planner, measured overtime or stock change
PriceFixed price, quoted after the readiness assessment
What you own at the end
  • Forecast pipeline and the planning sheet or dashboard, running on your infrastructure.
  • The weekly forecast-versus-actual report.
  • The planning rules and constraints, documented so they can be changed without us.

Everything runs in your environment and is handed over with documentation. Nothing stops working if we part ways.

Questions we are usually asked

Our demand is unpredictable.

Some of it is. The assessment separates the part that repeats from the part that does not, and plans for both.

Do our planners have to learn a new tool?

The output lands where they already work: a sheet, a dashboard, or a screen in your ERP.

How quickly does it pay back?

In most pilots, one planning cycle shows whether the forecast beats the current method. We measure it, and the gate at the end of the pilot uses that number.

Can this work for a service business, not a factory?

Yes. Service ticket volume, field staff rosters and branch footfall follow the same approach.

Is this an optimisation system?

Only where the assessment shows that rules fall short. Many plants get most of the benefit from a good forecast and three clear rules, and that is what we build first.

Often combined with

Not sure if your data is ready?

Take the free 20-minute readiness check. You get a short scorecard and a plain answer about what, if anything, is worth doing next.