When “New” Doesn’t Mean Innovation

Innovation is often seen as the engine of growth in FMCG. New products bring excitement, attract shoppers and create opportunities to transform product portfolios. According to Deloitte’s 2026 Consumer Products Industry Global Outlook, companies put efforts into establishing category-killer portfolios, and 67% of surveyed companies focus on a faster innovation cycle. On the surface, measuring innovation might seem straightforward: track what’s new, see how it performs and understand its impact. 

In reality, it’s far more complicated. 

The first challenge is surprisingly simple: what does actually count as innovation?

A new product could be a completely new idea, like a different flavour or format that hasn’t existed before. But it could also be a smaller change, such as a new pack size, a limited-edition version or a refreshed product that has been relaunched.

All of these can appear as “new” in the market. But they don’t all represent the same level of innovation. Without a clear and consistent definition, what looks like a strong innovation might just be a minor change.

From an analytics perspective, the distinctions between core, introduction or innovation matter a great deal, and they are not always easy to make. Let’s look at a few scenarios of “new” products in analytics.

Some products are classified as in & out, meaning they appear briefly in the market but don’t stay long enough. They may create short spikes in data, but don’t represent an innovation.

Others are relaunches, where a product is reintroduced with the same characteristics as before. As shown by BCG analysis, 65% of new product launches are renovations rather than innovations. A pack-size change or a new packaging design, may look new to consumers and appear as a new item in the data. However, they are relaunches with minor adjustments, not true innovation.

Then there is what can be considered true innovation: products that are newly launched to the market or meaningful variations of an existing product line, with no sales recorded in the last two years. This could include a genuinely new flavour, a new type of product or a different form of packaging that changes the offer.

If these classifications are not made before the data reaches dashboards or reports, the analysis is already flawed from the start.

Even once something is considered innovation, performance can vary widely. 

Some products are designed to stay long term and build the category. Others are short-lived, created for a specific promotion or season. Some are launched with strong support and distribution, while others remain niche. 

This mix makes it hard to assess performance fairly. A short-term product might generate a quick spike in sales, while a truly innovative product may take longer to build momentum. Looking at them side by side without context can lead to misleading conclusions. 

The complexity increases even further when innovation is analysed alongside seasonality. Many new products are launched around specific moments of the year like Easter editions, summer flavours or Christmas promotions. This raises important questions. Is a product successful because it is truly innovative or because it benefited from a seasonal peak?   

Given all this complexity, how products are identified becomes critical. 

Innovation is not just about launching something new. It plays a critical role in shaping shopper behaviour and driving revenue.

The line between success and noise is thin. Short-lived items, low-distribution launches or products with very small sales can all appear in the numbers. While they technically count as new, they don’t always contribute meaningfully to innovation strategy or growth. This is especially true in the fast-paced FMCG world, where over 80% of product launches fail.

Leveraging innovation for growth only works if it is understood correctly.

This is where having consistent and reliably coded innovation products becomes essential. It provides the foundation needed to identify real opportunities, rather than reacting to what simply appears new. By looking at past launches through a consistent lens, brands can learn what has worked, and what hasn’t. Over time, this creates meaningful benchmarks for successful product launches on speed of sales and distribution, making it easier to assess performance early on and take action when needed.

Data, with smartly coded innovation products, is what turns innovation from trial and error into a measurable growth driver. The right innovation can attract new shoppers, justify premium pricing, strengthen brand perception and create long-term growth.

To make innovation analytics work in practice, a few things need to come together.

There needs to be a shared definition of innovation that is applied consistently. Products need to be correctly identified before they enter reporting, ensuring that relaunches, in & out items and low distributed products are treated appropriately. Clear thresholds, such as minimum sales periods or performance levels, help to ensure that only relevant products are evaluated.

Most importantly, this approach needs to be applied consistently across markets, so that results can be compared.

Innovation will always involve uncertainty. But with the right structure behind the data, it becomes much easier to understand what is truly making a difference and where the next opportunity lies.

At Redslim, we work with clients to bring visibility into how innovation truly performs. Using Smart Coding methodology, we ensure that products are properly coded and identified in the data, distinguishing true innovation from relaunches, in&out items, low distribution or late entries. This creates a strong foundation for analysis from the very beginning.

On top of that, we design intuitive dashboards that allow teams to explore innovation performance across markets and categories over its own launch periods. This makes it easier to track how they are performing, identify opportunities and support innovation and growth strategies.