SmartLink
Manufacturing systems

Production planning and scheduling software in Pakistan

Production planning and scheduling software in Pakistan is often bought to fix something that turns out to be a data problem. The plan gets ignored because the lead times in it are wrong, or because the bottleneck was never modelled at all. SmartLink Services configures demand consolidation, material requirements planning and finite scheduling from Karachi, built around the resource that genuinely limits your plant. This page covers what planning software costs at published market rates, how long it runs before a planner trusts the output, and the decision sitting underneath the whole implementation: whether to plan against finite capacity or infinite. In most plants we walk, the spreadsheet is more current than the system.

Discuss this service
Horizon
Weekly \u00b7 monthly
Constraints
Capacity \u00b7 material \u00b7 shift
Review
Rolling plan cycle
Overview

A plan the plant can actually hold to.

Planning systems are usually blamed for problems they inherited. The material requirements run is only as good as the lead times, safety stocks and lot sizes it was given, and those parameters are frequently the defaults set at implementation and never revisited. So the plan proposes an order the plant cannot start, the supervisor reorders it locally, and within a fortnight the schedule on the wall and the schedule in the system have diverged. After that, the system is a record of intentions rather than a working instrument.

Our starting point is the constraint, not the calendar. Every plant has one or two resources that determine throughput, and a plan built around those will hold better than a plan built by spreading work evenly across everything. Changeover cost is modelled where sequence matters, because a schedule that ignores it produces a sequence nobody will follow. Supplier lead times are set from what suppliers actually deliver rather than from the contract, and the difference between those two numbers is often the whole problem.

Finite and infinite capacity both have a place. An infinite run tells you what the demand implies, which is useful for buying and for negotiating dates. A finite schedule tells you what the plant can do, which is what the floor needs. Confusing the two is how a business ends up committing to dates it cannot meet. We keep both, label them clearly, and make the gap between them the subject of the planning meeting rather than something discovered at dispatch.

Scope

What Production planning & scheduling covers

Everything below is agreed in writing before any factory & operations work starts, so both sides know what is in and what is not.

What the work covers

  • Demand consolidation and forecast input handling
  • Material requirements planning parameter setup
  • Finite capacity scheduling against bottleneck resources
  • Changeover and sequencing rule configuration
  • Supplier lead time and safety stock policy
  • Plan-versus-actual variance reporting

What you get at handover

  • Planning parameter configuration document
  • Scheduling rule set
  • Rolling plan template and cycle calendar
  • Variance report pack
  • Planner training

Typically involves

Discuss this service
01

The parameters nobody has revisited since go live

Lead time, safety stock, lot size, planning time fence, scrap factor. A handful of parameters per item, across an entire material master, and almost always a single default applied across the lot during implementation because there was no time to do better. The result is a material requirements run that orders too early for the fast movers and too late for the awkward ones. Planners then override it item by item, which works while the planner is there and stops working the week they take leave.

Correcting it is a data exercise before it is a configuration exercise. Actual supplier performance is measured from receipt history rather than asked for. Demand variability is calculated per item, so safety stock reflects how erratic the item really is instead of a flat allowance. Lot sizes are checked against changeover and against storage, because an economic order quantity that will not fit in the warehouse is not economic. Items are then segmented, so planner attention goes to what carries the value and the volatility.

Then the parameters need a review cycle with a named owner, because they decay quietly. A supplier who was reliable when the file was built may not be now. Demand shifts. A new product changes the mix and the shared tooling. We prefer a quarterly review driven by exception reporting, where the system nominates the items whose behaviour has moved outside the assumptions, over a full recalculation that consumes a month and is then never repeated.

  • Lead times derived from receipt history rather than from the purchase contract
  • Safety stock set per item from measured demand variability rather than a flat allowance
  • Lot sizes checked against changeover cost and against physical storage
  • Items segmented so planner attention follows value and volatility
  • Exception driven parameter review with a named owner and a fixed cycle
02

Finite scheduling against the resource that actually limits you

A finite schedule is only as useful as its constraint model. Most plants do not need every work centre scheduled finitely. They need the bottleneck scheduled finitely and everything else planned around it, which is a much smaller modelling job and considerably easier to keep accurate. Identifying that resource is empirical work: where queues form, where overtime is spent, where the expediting conversations happen. It is not always the machine people name first, and it moves when the product mix moves.

Sequence rules then do most of the useful work. Grouping by colour, by grade, by tooling or by temperature reduces changeover, and the right grouping is plant specific and already known to the schedulers. Our job is to capture the rule they apply informally and let the system apply it consistently, including on the days when the person who knows it is not in. Where two rules conflict, the system should show the trade off rather than silently pick one and leave people guessing.

Shift patterns, planned maintenance and known absences belong in the capacity calendar, otherwise the schedule promises hours that do not exist. This sounds obvious and is very often missing in practice. A maintenance window agreed with engineering but never entered as a capacity reduction will be scheduled over, and the resulting conflict is settled on the day by whoever shouts loudest rather than by any rule. Public holidays, training days and planned trials belong there too. Putting the whole calendar in one place removes an argument that otherwise repeats every single month.

  • Bottleneck resources identified from queue, overtime and expediting evidence
  • Sequence and grouping rules captured from schedulers and applied consistently
  • Changeover matrices held where the sequence genuinely changes the setup time
  • Shift patterns, planned maintenance and absence reflected in the capacity calendar
  • Conflicts surfaced with their trade off rather than resolved silently by the system
01

What production planning software costs in Pakistan

Typical market rates in Pakistan put a focused single site implementation at PKR 800,000 to 1,500,000, a mid sized scope of five to seven modules with a mobile element at PKR 1,500,000 to 3,000,000, and enterprise scope with several plants and integrations at PKR 3,000,000 upwards. Published module pricing puts manufacturing at PKR 300,000 to 600,000 and multi location capability at PKR 200,000 to 500,000. Subscription products commonly sit around PKR 2,500 per user per month, and planning is one of the few areas where a per user model is genuinely cheap, since a plant with four hundred operators may have three planners.

With production planning software the licence is rarely the cost. Parameter data is. Material requirements planning needs a lead time, a lot size rule, a safety stock level, a scrap factor and a planning calendar for every item it touches, and a mid sized plant touches thousands of items. Those values exist nowhere in most businesses, or they exist as numbers somebody entered during a go live in 2019 and nobody has revisited since. Establishing them means measuring rather than remembering, and measuring is where the effort goes.

Scheduling adds a second data set with its own price. Run rates per product per work centre, changeover times between one product and the next, shift calendars including the overtime pattern actually worked, and planned maintenance windows. A changeover matrix in particular is a data collection exercise performed on the floor with a stopwatch, and its size grows with the square of the product count rather than with the product count. Forecast handling adds a further piece of work where demand comes from a sales plan rather than from firm orders. Multi plant planning adds a rule about where work goes and a person authorised to decide, which is an organisational cost rather than a software one. All figures above are market pricing. A real figure follows discovery, once we have seen the item master and counted the constrained resources.

  • Parameter data established by measurement, since lead times in the system are usually inherited
  • Changeover matrix costed as floor work, because it grows faster than the product count
  • Shift calendars built from the overtime pattern actually worked rather than the published one
  • Per user subscription cheap here, since planners are few even in a large plant
  • Multi plant sourcing rules treated as an organisational decision with a named owner
02

How long a planning implementation takes

Published implementation timelines put a focused scope at two to three months, a mid sized scope at three to four and enterprise scope across several plants at four to six months or longer. Reported go live figures put a focused single company at six to twelve weeks and an SME at three to six months. Planning tends to sit at the longer end of whichever band it falls into, and the reason has nothing to do with configuration.

Parameter data sets the pace. Lead times have to be measured against what suppliers actually delivered over the last year rather than what the purchase agreement says. Changeover times have to be timed on the floor, across the shift patterns where they differ, because a changeover run by the experienced crew is not the changeover run at two in the morning. Neither task can be compressed by adding consultants, since both need people who work in the plant.

Then there is trust, which has its own calendar. Nobody switches off a working spreadsheet because a demonstration went well. The plan runs in parallel with the current method for at least one full cycle, the two are compared where they disagree, and each disagreement is either a model gap to fix or a habit to change. Two or three cycles is a realistic horizon before a planner works from the system by default. Go live and adoption are therefore different dates, and we put both in the plan rather than only the first.

  • Lead times measured against a year of actual supplier performance rather than agreements
  • Changeover times timed across the shift patterns where the crew and the duration differ
  • The plan run in parallel with the existing method for at least one full cycle
  • Each disagreement between the two resolved as a model gap or a habit, and recorded
  • Go live and adoption planned as separate dates, since a planner earns trust in cycles
03

Finite or infinite capacity planning

Infinite capacity planning assumes the plant can make whatever the demand implies. It explodes the bill of material, offsets by lead time and says what to buy and when to start. It is quick to configure, it is forgiving of imperfect data, and for purchasing and material timing it is often all a business needs. Its weakness is stated in its name. Ask it to sequence a plant already running at ninety percent and it will cheerfully schedule three jobs onto one machine at the same hour.

Finite capacity scheduling produces a sequence somebody can work to. It respects a resource calendar, changeover rules, shift patterns and maintenance windows, and it hands the supervisor an order of work rather than a list of due dates. What it demands in exchange is accuracy in six places at once: routings, run rates, changeover times, shift calendars, maintenance windows and an honest view of manning. Get one of them wrong and the schedule is confidently wrong, which destroys trust faster than no schedule at all. A planner who is overruled by the floor twice stops using the system.

The sequence we recommend is almost always the same. Run infinite first. Use the year that follows to correct the parameter data, because a wrong lead time is visible in an infinite plan too and cheaper to find there. Then add finite scheduling on the constraint only. Most plants need finite scheduling on one or two resources rather than on all of them, and scheduling everything finitely is how a project acquires a permanent data maintenance burden it never budgeted for. Somebody has to own that maintenance by name, because every new product needs a run rate and changeover entries before it can be scheduled.

Finite is not worth buying in three situations we see regularly. A plant with one product family and long runs, where the sequence is obvious to the supervisor and always has been. A plant whose real constraint is material supply rather than machine time, where the answer is supplier management and not an optimiser. And a plant where customers change orders hourly, where the honest fix is a frozen horizon with a rule for what may break it, agreed with sales, rather than an optimiser. We model the constraint, prove the plan against last quarter's actual orders before anybody relies on it, and write down what the model deliberately ignores.

  • Infinite planning used first for purchasing and material timing, where it is usually sufficient
  • Finite scheduling applied to the constrained resource rather than across the whole plant
  • Six data sets verified before finite scheduling is switched on, routings and manning included
  • Permanent parameter maintenance assigned to a named owner as part of the decision
  • The plan proved against a past quarter of real orders before the floor is asked to follow it
How we deliver

Delivering Production planning & scheduling

Plant software is scoped against a physical site, so the first two steps happen on the floor rather than in a meeting room. Everything after that is arranged around a production calendar that will not move for us.

  1. 01

    Discover

    Walk the line during the shift being designed for. Where the batch number is written on tape, which machine is read off a display into a notebook, where the network drops at goods-in.

  2. 02

    Blueprint

    Traceability level, confirmation points and the definition of good output, scrap and rework are agreed by production and quality together. Downtime reason codes are written before anybody configures a screen.

  3. 03

    Build

    Screens are built for gloves and a wet hand: few fields, large targets, a scan instead of typing. Terminals go on the line where the work happens, not at a desk in the supervisor's office.

  4. 04

    Test

    Operators run a real order on one line for a full shift, including a changeover and a rejected unit. If a scan needs two hands or a screen times out mid-changeover, we find out here.

  5. 05

    Go live

    One line, one product family, one shift, with the paper fallback printed and rehearsed before the first confirmation is posted. Stock counts reconcile to the ERP before the second line starts.

  6. 06

    Run

    Spare scanners and terminals sit on site with a swap procedure a supervisor can follow. Bills of material and routings get named owners, and somebody walks the line periodically to check the system against reality.

Working together

Planning is a habit before it is a system

A planning implementation that does not change the meeting will not change the plan. The system produces a proposal. Someone has to accept it, challenge it or amend it, at a fixed time, with the authority to commit. Where that meeting does not exist, the software becomes a report people read before doing what they were going to do anyway. We would rather help design the cycle than deliver a tool into a vacuum.

What we build is the supporting machinery: parameters based on measured behaviour, a constraint model the schedulers recognise, a feedback loop that closes automatically, and variance reporting that points at assumptions rather than at people. The plan will still be wrong sometimes. The point is that it becomes wrong for reasons you can see and correct, which is the only version of planning that improves over time.

Credentials

Accreditations behind Factory & operations

Plant systems sit between equipment we do not supply and business systems we do, so accreditation matters most at the joins.

Oracle

Partner

Oracle SCM and EBS manufacturing modules for work orders, routings and costing, with the plant reporting database tuned so a shift report returns while the supervisor is still standing at the terminal.

Microsoft

Partner

Dynamics 365 Supply Chain Management where that is the platform, plus Power BI dashboards showing downtime by reason code on a screen the plant manager sees each morning.

Google

Partner

Google Cloud is where multi-site plant data gets consolidated when each factory runs its own instance, so group reporting stops depending on spreadsheets emailed in from each site after close.

FBR digital invoicing

Compliant integrations

Despatch from the plant triggers the sales invoice, so the goods issue, the invoice and the FBR submission stay in step. Gate passes carry the same document number as the tax invoice.

HIPAA

Compliant practices

Contract manufacturing of patient specific products puts a patient name on a batch record. Those fields are restricted on the shop floor terminal, logged, and covered by a business associate agreement.

Client words

What Factory & operations clients say

Comments from people who run factory & operations systems day to day.

  • The team spent two days on the floor before they proposed anything, which I did not expect. They noticed that our scrap was being written off as a variance instead of recorded as returning metal, and that one change altered how we look at recovery on every press.
    Plant Manager Aluminium extrusion operation
  • The handover was the part I judged them on. Configuration decisions documented with the reasoning, our administrators trained properly, and a checklist we actually worked through. We run it ourselves now, and calling them is a choice rather than a necessity.
    Head of Shared Services Multi site manufacturing group
  • What sold us was that they argued with our brief. We asked for a reporting layer and they came back saying the reporting was fine, the batch data underneath it was not, and fixing that first would cost less. That turned out to be right. Our first mock recall after go live took an afternoon instead of the better part of a week.
    Finance Director Food manufacturing group, Karachi
Questions

Questions about Production planning & scheduling

Typical market rates run PKR 800,000 to 1,500,000 for a focused single site scope, PKR 1,500,000 to 3,000,000 for five to seven modules, and PKR 3,000,000 upwards for several plants with integrations. A manufacturing module is published at PKR 300,000 to 600,000, and subscription products at around PKR 2,500 per user per month. Parameter data collection, not the licence, is where the effort goes. We quote after discovery.

Published timelines put a focused scope at two to three months and a mid sized scope at three to four. Planning sits at the longer end, because lead times have to be measured against a year of actual supplier performance and changeover times timed on the floor. Add two or three planning cycles running in parallel with the current method before the output is trusted.

That is exactly what material requirements planning does, and it is the part that repays the effort soonest. It explodes the bill of material against demand, offsets by lead time and produces purchase proposals. The output is only as good as the lead times, lot sizes and safety stock behind it, which is why we measure those rather than accept what is already in the system.

Yes, if the plan is honest about it. Use the lead time actually achieved over the last year rather than the agreed one, and carry the variability in safety stock or a safety time rather than pretending the average is the truth. Where one supplier is the real constraint, that belongs in a supplier conversation as much as in the planning parameters.

It can, once the changeover matrix exists. That matrix is collected on the floor with a stopwatch and it grows quickly with the product count, so most plants start with changeover groups rather than product to product times. Sequencing rules, running light colours before dark or grouping by tooling, are configured from how your supervisors already sequence rather than invented.

A named planner, and the parameter maintenance is part of that role rather than an occasional task. Every new product needs a lead time, a lot size and, where finite scheduling is in use, a run rate and changeover entries. A planning system without an owner drifts within two quarters and the spreadsheet quietly returns. We train the planner and hand over the parameter register.

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