The challenge
An Indian colorant and plastics manufacturer works alongside a sister company that makes flexible film. It needed an ERP for colorant manufacturers that followed the business as it really runs, starting with the buyers who ask to test a product before they commit.
Many buyers asked for a sample first, and those trials were hard to follow up. The two companies also take orders in very different terms. A colorant order is a product code and a weight in kilograms. A film order needs micron, width, core and box counts.
Later, the gaps moved to the plant. Raw material prices changed, so cost reports went stale. Incoming material needed a quality check before use. And nobody could see output by machine or batch, or tie electricity use to the runs that consumed it.
What we built: an ERP for colorant manufacturers
We built the system on the web in stages, each one closing a gap the last one exposed.
Sales and dispatch. Inquiries split into regular leads and sample leads, with the product, a trial code and the quantity. Each lead has stages, notes and reminders. Orders are booked with each company's own fields. Dispatch records the transporter and LR number, and the customer gets an email and SMS when the order is complete.
Stores and QC. A raw material master holds the current price of each material. The inward team adds stock as it arrives, and QC verifies each receipt and records a QC report.
Production. Machines and sub-units are set up in masters. The production team logs raw material and electricity use against each machine and batch, and raises issues when something goes wrong, closing them once fixed.
Roles and permissions control who sees what. The later modules run on React, Node.js, Express.js and MongoDB; the earlier sales portal used AngularJS.
How it works day to day
Start with a production manager on a weekday morning. The production dashboard shows what each machine has run and which issues are still open. A batch that used more raw material or power than usual is visible in the machine-wise and batch-wise reports, not buried in a register.
Behind that dashboard, the stores team has already logged the morning's deliveries, and QC has verified them. Material reaches production only after that check, so a batch record starts from material with a QC report attached.
On the sales side, a buyer who asked for a trial last week is still a live sample lead, with a reminder due. When the trial turns into an order and the goods leave, the customer hears about it by email and SMS without anyone picking up the phone.
The result
Sales staff now follow a customer from sample request to order to dispatch in one system. Stores and QC work from one record of each receipt. Managers see production machine by machine and batch by batch, with efficiency and cost reports that use the prices in the raw material master.
What the research says
Smaller firms lag on ERP. Eurostat reports that 46.45% of EU enterprises used ERP software in 2025, ranging from 41.08% of small firms to 88.71% of large ones (Eurostat, e-business integration). A system built around one plant's own sales, inward and production steps is one way a mid-sized maker closes that gap.
Plant data is still often handwritten. A 2024 Manufacturing Leadership Council survey found 70% of manufacturers still collect data manually (Manufacturing Leadership Council). Here, machine runs, batches and QC reports are entered once into screens that feed the dashboards directly.
Quality is where factories aim AI first. Industrial automation vendor Rockwell Automation surveyed 1,560 manufacturers and found quality control was the top AI use case for the second year running, with 50% planning to apply AI or machine learning to product quality in 2025 (Rockwell Automation). Recording a QC result against every inward receipt builds the history that kind of tool would need.
Where AI fits next
The plant runs this ERP without AI; its batch records would support a few additions. A model could flag batches whose raw material or electricity use drifts from the usual for that machine.
It could draft follow-up messages for sample leads that have gone quiet, for sales staff to send, and summarize QC reports by supplier to show where rejects start.
Planning something similar?
Before you build an ERP for a process plant, it helps to answer four questions:
How do sample or trial requests turn into orders today, and who follows them up?
Do different companies or product lines need different order fields?
What must QC record before material can be used?
Which costs, such as power and raw material, should be logged against each machine and batch?
For a different plant, read how we built a manufacturing ERP that put four departments on one system. There is more on our ERP development work, on what an ERP does for manufacturers, and on our factory and process clients.
