Fluctuating raw material prices raise a question for development teams: when does a technically suitable formulation need to be reassessed on economic grounds? Consider a practical example: a coatings manufacturer selects a particular epoxy resin for a new formulation and calculates raw material costs using current purchasing terms. If only the purchase price changes before approval, the technical assessment remains valid. However, the manufacturer must update the cost calculation.
When price volatility is high, the manufacturer reviews this calculation regularly and considers three options. The first is to retain the formulation and suppliers, passing on the additional costs through higher selling prices or accepting a lower margin. The second is to retain the formulation and qualify an additional source of supply for the same raw material. The third is to reformulate using an alternative raw material.
To make this decision, R&D and purchasing need to know which formulations contain the raw material, how their costs change and which alternatives have already been tested and approved. When this information sits in several systems, the work often begins with a search for data.
A connected data foundation links each formulation to its raw materials, experiments, historical and current prices, and approvals. This article explains which questions these links can help answer and how to get started with a manageable use case.
Raw material substitution: Costs beyond the purchase price
Whether a price change leads to reformulation depends partly on the raw material’s share of the total costs, the product requirements and the available alternatives.
Substituting raw materials can change viscosity, drying, film formation or curing behaviour, adhesion and mechanical properties. Switching to a different epoxy resin, for example, may require adjustments to the resin-to-hardener ratio and other formulation components.
These adjustments can change the quantities and costs of the raw materials used. A cheaper substitute therefore does not automatically make the formulation cheaper. Its solids content or active ingredient content also matters: a different addition level may be needed to achieve the required properties. Changes to the manufacturing process can also affect costs. The assessment must therefore consider the total cost of the adjusted formulation, including manufacture.
In addition to these recurring costs, the changeover itself requires one-off work. The team must test the adjusted formulation and, where necessary, trial changes to the manufacturing process. Depending on the raw material and application, it may also need customer approvals, regulatory assessments and updated documentation. Previous experiments with similar raw materials and the associated approvals help the team estimate the work involved. These records must be easy to find and linked to the correct formulation version. The manufacturing and test conditions must also be traceable.
Price volatility: When reformulation is worthwhile
The team cannot judge whether reformulation is worthwhile from today’s purchase prices alone. Prices may rise or fall again while the team investigates and approves an alternative. If the original raw material becomes cheaper, a reformulation already under way may no longer be worthwhile. Equally, a substitute previously rejected on cost grounds may become an option if its price falls. Documented alternatives and experimental results make it easier to reassess whether reformulation is worthwhile as prices change.
The team defines the expected production volume and an assessment period, then calculates costs under several price scenarios for both the existing raw material and the alternative. It also estimates when the new formulation could be approved and introduced into production. Only the volume produced after that point can contribute to savings within the assessment period. The team compares these potential savings with the one-off work required for experiments, process adjustments and approval.
This shows under which price assumptions and at what production volumes the changeover would pay for itself within the assessment period.
The starting point is the agreed purchasing terms for the required raw material grade and order quantity. Their validity period must be clear. Contractual price commitments may delay the effect of market price changes on actual purchasing costs. For periods without binding prices, the team uses price assumptions supported by a clear rationale.
R&D management uses this assessment to decide on the next steps together with purchasing and production.
How much development capacity should be allocated to reformulation?
If manufacturers cannot quickly pass higher raw material costs on to customers, margins come under pressure. Reformulation can reduce costs, but it also ties up development and testing capacity. R&D management must therefore weigh the expected savings against the work required and potential delays to other development projects. The following questions guide this prioritisation:
- How much does the raw material contribute to product costs?
- Under which price assumptions and at what production volumes is a change worthwhile?
- Which product properties must be maintained?
- Which alternatives have already been investigated?
- What additional experiments, tests and approval work are required?
- Which resources are needed, and how would this affect other projects?
The answers help estimate the work required for reformulation and identify other projects that could face delays. Together with the expected savings, this assessment informs the decision on whether reformulation should take priority.
Raw material shortages: When securing supply outweighs cost savings
If a raw material becomes scarce or supply chain risk increases, the manufacturer must check whether supply remains sufficient for planned production. If a source of supply becomes unavailable at short notice, there may be little time to qualify an alternative. Even under time pressure, the alternative must meet the technical requirements and be available in sufficient quantities when needed.
If production is about to halt, even a more expensive alternative can make economic sense. Documented experiments and existing approvals for the application help establish which tests and approvals are still needed for the changeover. Alternatives already qualified for that application may allow a faster switch, provided they are available in sufficient quantities.
Second supplier: Why qualification should start early
Qualifying an additional supplier for the same raw material requires different tests from qualifying a substitute with different properties. Even where specifications are comparable, the team must check suitability for the application. Starting supplier qualification early reduces the number of tests still needed when a supply problem arises. The team must also check whether both suppliers produce at the same site or rely on the same upstream suppliers.
Material Intelligence connects data, workflows and AI
Assessing costs and answering supply questions require the same links between records: which raw materials each formulation contains, which experiments relate to it and whether it has been approved. A formulation management system must make these relationships traceable. To answer supply questions, the team also needs procurement information on current lead times, available quantities and purchasing terms.
In many companies, this information sits in different places. Formulations and experimental results are held in the laboratory, often in spreadsheets or a LIMS, while prices and delivery terms are stored in purchasing’s ERP system. Answering a cost question first requires bringing the relevant data together.
Linking this data forms the foundation of what we mean by Material Intelligence: connecting material and formulation data with structured workflows and AI that supports the team. In formulation management, this allows teams to assess formulation versions, raw materials, experimental results, historical and current prices, and approvals together.
Reliable comparisons require clear links to the relevant raw materials, consistent units and documented manufacturing and test conditions. Price records must identify the currency, order quantity and validity period. For procurement information from the ERP system, the date of the latest import must be traceable.
Workflows define who checks technical suitability, who assesses procurement and which steps are required before approval. They connect the information to specific tasks for R&D, purchasing and production.
AI supports information retrieval and analysis
Using linked material and formulation data and documented experimental results, AI can compile relevant formulation records for expert review. For the epoxy resin in the opening example, it could identify documented experiments with other resins for the same application and flag missing information. This can reduce the time spent searching. Formulation developers must check whether a formulation meets the requirements of the specific application.
Meaningful use of AI requires accessible data, traceable links between records and a clearly defined task. Every AI output must be traceable to the sources and formulation versions on which it is based. Experts check whether the AI presents the underlying data accurately and completely and links it to the correct formulation versions. Any missing or contradictory information must be visible in the results.
The responsible experts assess whether an alternative meets the requirements, using appropriate evidence. Experimental planning, assessment and approval remain their responsibility.
Start with a clearly defined use case
A connected data foundation grows step by step. A manageable use case provides a starting point, such as the product family containing the epoxy resin from the opening example. For these formulations, developers select the relevant historical data and standardise it, then link it to the corresponding formulation versions and to the manufacturing and test conditions. The team builds on this structure as it adds each product family.
Getting started involves four steps:
- Review existing data: What data is available, where is it held and how complete is it? The answers provide an initial estimate of the work required.
- Bring data together: Link formulations, substitution experiments, approval statuses and current purchasing terms. Keep manufacturing and test conditions and data sources traceable.
- Assess price scenarios: Calculate the cost implications for the affected formulations and compare potential savings with the work required for the changeover. Include procurement information where supply risks exist.
- Document new experiments consistently: Agree on the minimum information to record for each experiment, who is responsible and the steps required for assessment and approval. Make this documentation part of the regular development process.
The team assesses the benefits of the connected data foundation using four questions:
- Can teams find affected formulations faster?
- Can they trace how cost impacts have been assessed?
- Can they reliably interpret previous experiments and approval statuses in context?
- Do information gaps and additional development work become visible before the next series of experiments?
Conclusion: What connected data clarifies when prices fluctuate
Material Intelligence makes it easier to assess economic impacts, technical suitability and supply risks together. It can also reduce the time spent searching for information.
In the opening example, the coatings manufacturer can see which formulations contain the epoxy resin and how their costs change under different price assumptions. It can also see which alternative raw materials have been tested and approved for the relevant application and can be delivered in time. R&D management decides on the next steps together with purchasing and production: retain the formulation, qualify an additional source of supply or reformulate.
The assessment may also show that retaining the existing formulation makes more economic sense. This can avoid additional development and changeover work.