The 9-Step Process the Best R&D Teams Use for New Product Development

Top-performing R&D teams don’t rely on creativity alone. They rely on disciplined, repeatable systems that make product innovation faster and more scalable. This framework was developed by Nasim Rokni, M.Sc, MBA, DBA, a Senior Research and Development Manager at the Schwan Group with over 15 years of experience leading product development and quality programs across bakery, confectionery, and prepared foods.

Through her years of bringing products from concept to commercialization under regulatory, cost, and manufacturing constraints, Nasim has refined a practical approach to new product development. 

The 9-step process below reflects the methods she uses to move faster with fewer mistakes and to help teams avoid the common traps that slow R&D organizations down.

1. Start With a Clear Idea

Every project begins with an idea - but defining and framing these ideas is important.

Ideas can develop from both internal and external sources. 

Internal ideas can come from:

• Internal innovation pipelines
• Customer or sales requests

External ideas can come from:

• Market and trend scouting
• Competitive products
• Regulatory or ingredient changes

Best-in-class teams document the problem the new product is solving and define clear commercial or technical objectives for the project up front.

2. Run a Feasibility Study First (Regulatory, Cost, Technology, Equipment)

Before any formulation work begins, one of the most critical steps in Nasim’s process is the Feasibility Study. This includes running an initial check for: 

• Regulatory constraints (claims, ingredients, labeling restrictions)
• Cost targets and margin requirements
• Technology, material and shelf life constraints
• Equipment and scale limitations

This step answers a critical question: Is this product actually buildable within our constraints?

Teams that do this well catch issues early:

• An ingredient that won’t be allowed in a target market
• A process that won’t scale on existing equipment
• A cost structure that can’t hit commercial targets

Skipping feasibility could feel faster in the short term, but it increases the probability of late-stage project failure. The cost of killing a bad idea early is far lower than reformulating or relabeling after pilot production.

3. Define Specifications Before You Formulate

Top teams create spec sheets before they touch formulation.

This includes defining:

• Label and claim restrictions (clean label, gluten-free, non-GMO, etc.)
• Target viscosity
• Target pH
• Color expectations
• Texture and sensory targets

This creates a technical “map” for R&D. Instead of formulating blindly and checking compliance later, teams design toward known constraints from the beginning.

Some teams reverse this sequence: they formulate first, then ask regulatory to “make it work.” This increases iteration cycles and creates tension between R&D and compliance. Designing within constraints is slower up front but faster overall.

4. Create Your Formula 

Once constraints are defined, formulation begins.

High-performing teams:

• Use base formulas from trusted suppliers when available
• Leverage formulation tools and internal databases
• Treat AI and digital tools as starting points, not final answers
• Maintain clear version control and documentation

This stage is about creating an initial formulation that fits within the defined spec.

5. Source Raw Ingredients Strategically

Ingredient sourcing is part of formulation design.

Strong teams:

• Validate regulatory acceptability of suppliers
• Compare functional performance across vendors
• Evaluate supply chain risk
• Consider availability in target markets
• Align with internal quality standards

Sourcing decisions affect formulation stability, labeling, cost, and scalability.

6. Build Prototypes and Design Controlled Experiments

Discipline in prototype development and testing is key.

Best practices:

• Change only one variable per experiment
• Ensure tests are repeatable and reproducible
• Document every iteration
• Scale-up to production batches and ensure quality holds

Making sure that a prototype works in the lab and works at scale on production-ready equipment is where many products stall and can create costly mistakes if not properly tested at this stage.

7. Conduct Sensory Evaluation and External Feedback

The best R&D teams do not rely solely on internal opinions or assumptions.

They use:

• Structured sensory evaluation
• Consumer or customer feedback
• Statistical analysis tools to detect meaningful differences
• Iterative refinement based on data

External feedback introduces friction, but it reduces the risk of launching technically sound products that fail commercially. This step ensures technical success translates into market success.

8. Scale-Up and Plant Trials

At this stage, the lab formula and processing method are converted to large-scale production in the plant. This is often where products that were technically “successful” in the lab can fail if R&D does not account for real-world manufacturing constraints.

Key activities:

• Identify equipment-driven constraints (mixing, baking, extrusion, cooling, packaging)
• Run pilot plant and line trials
• Adjust formulation or processing parameters to maintain product performance at scale
• Validate yield, throughput, and quality consistency
  
  

This step requires deep, category-specific manufacturing expertise. The knowledge required to scale a bakery product can differ significantly from dairy products, beverages, or confectionery.

9. Launch With Confidence 

Successful product launches are the outcome of a disciplined process, not a single milestone.

Most product failures are not due to poor ideas. They stem from a lack of process discipline. The teams that consistently win are the ones that combine creativity with structure, and focus on building products that are feasible, compliant, scalable, and validated before they ever reach production.

What Separates the Best R&D Teams

Across industries, the best teams share common traits:

• They design with constraints, not around them
• They validate early and often
• They document decisions and assumptions
• They treat scale-up as a separate technical phase
• They integrate regulatory thinking into R&D, not after it

‍