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How to harness AI's capabilities effectively and efficiently in new product development
In every corporate boardroom meeting worldwide, the conversation invariably turns to the ever-expanding influence and potential of artificial intelligence (AI).
It’s a ubiquitous topic that transcends industries and regions, presenting a common challenge: how to harness AI's capabilities effectively and efficiently.
The results are as vast as they are creative.
From the Heinz ‘Draw Ketchup’ campaign, which asked an AI image generator to draw a bottle of ketchup - and what it got back was thousands of pictures of Heinz to businesses creating fully functional software in under seven minutes for less than one dollar. We are just scratching the surface of the immense potential.
For Global CPG (Consumer Packaged Goods) brands struggling to compete against a growing number of well-equipped and heavily funded market entrants, AI-powered NPD (New product development) strategies offer a promising competitive edge.
In recent years, the consumer goods industry has witnessed a seismic transformation, impacting even the most established CPG brands.
This transition is closely tied to the prevailing consumer trends, stemming from increasing living costs and a significant rise in ethical consumer behaviour.
As a result, the majority of leading CPG brands have confronted a significant downturn in their growth trajectory.
This sharp decline is underscored by staggering statistics, with these brands collectively haemorrhaging over $17 billion in sales to nimble and innovative competitors since 2013.
To compete in this rapidly changing landscape, global innovators must not only acknowledge these consumer trends but also adapt their NPD strategies accordingly. They must draw inspiration from the agile practices of innovative startups and leverage their considerable resources to construct a robust, data-driven, multi-tested, iterative fortress of product launches.
Amidst the daunting CPG landscape, where over 95% of the 30,000-plus new products introduced annually meet their demise, new product development has become a bottomless pit for leading brands, devouring time, funds, and resources.
Reports estimate that an average NPD launch uses 50 days of staff time, €500K in development costs not to mention the impact a failed product has on environmental CO2 goals.
To fly against these reports, the well documented AI-powered NPD, Hell Energy Drink, ventured into uncharted territory when the product development team, along with its proprietary AI, dubbed HELL A.I., was tasked and succeeded in creating a new drink flavour based on current trends and consumer sentiments in a blink of an eye.
With NPD success rates in CPG between 5-25%, the capability of AI to conceive a successful product from scratch is a monumental achievement but it’s not a silver bullet.
The speed and cleverness of AI is about to set off a race in the CPG world, prompting companies to invest heavily and rely on AI to test and launch new products. In the AI-driven future of CPG here are four key strategies that will make or break:
Large consumer goods companies, who are often launching hundreds of new products a year, are underestimating the impact of failed launches on their business. For starters, staff churn is high in NPD teams (reports show that 30% of innovation teams leave after a year).
These setbacks aren't merely missed opportunities but can also tarnish brand reputation. To remain competitive, innovation success rates must be a core metric at the forefront of innovation leaders' agendas.
In today's fast-paced consumer landscape, speed to market is paramount. Manufacturing timelines, often constrained by production and supply chain, demand a quick innovation cycle. Staying relevant requires swift innovation but the right innovation is even more important. Iterative testing and testing often will lead to the right answer quicker.
While startups can readily co-create with their initial consumers, large consumer goods firms must integrate consumer insights into the core of their innovation process. Understanding and responding to consumer preferences are fundamental to launching successful products that are not just based on gut feeling or limited data.
At startups, founding teams have the unique advantage of overseeing all innovations across the company and applying lessons from past failures to improve the innovation process.
However, at the scale of global consumer goods, a different approach is needed. Creating an ‘innovation memory’ - meaning every innovation project is tracked, and measured centrally so that learnings and best practices can be leveraged and understood is essential. Currently, standard practice sees NPD thought of in projects and the consumer data generated is single-use.
The AI-powered future for global CPG brands and their NPD lies in innovative strategies that leverage the predictive and advisory power of AI to drive success. Imagine the NPD process that shifts from 95% failure rate to a 95% success rate. Sounds good to me.
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