Within the world of consumer packaged goods (CPG), we’ve seen a radical shift in where the power lies. The major incumbents which for so long have dominated the industry thanks to economies of scale, brand tailwinds, and supplier bargaining power are facing a potentially existential risk to their business from companies a fraction of the size. The catalyst for this has been the innovative use of data that delivers agility and precision that can help smaller players to outcompete.1
The use of advanced analytics (AA) and artificial intelligence (AI) is quickly becoming a necessary component of any consumer business and those large CPG companies that don’t catch up are likely going to be left behind.2 One of the most exciting parts of this new landscape is something called a digital twin which Foodpairing, an AI platform provider, lays out as follows:
“The process used today for R&D is not efficient enough for the context the companies are living in now. Anywhere from 75-90% of products are not present in the market after the first two years. So companies have spent money on products that will not last. Using Digital Twins and the right algorithmic models, Food & Beverage manufacturers can lower the inefficiency from 80% to 30%. Potentially, even having 70% of predicted success in the market.”
It's a strong statement, so let’s look at what makes digital twins such a fascinating new technology for Food & Beverage companies.
What is a Digital Twin?
A digital twin of the customer (DToC), to give it its full name, is a dynamic virtual representation of a real customer that can simulate and emulate that customer’s behavior. This representation is fed through a combination of data and artificial intelligence to mimic the structure, context, and behavior of a customer – offering an interface for companies to understand trends and patterns, before making predictions for the future.
Gartner recently named digital twins as a key player in their 2022 Hype Cycle for Emerging Technologies, showing just how much attention this is attracting throughout the industry.3 In a sector where understanding your customer deeply is worth its weight in gold, CPG companies are racing to create these digital twins, pulling from real data first and then augmenting it with synthetic data, in order to build highly realistic buyer personas, and demand predictors. Digital twins can then be used to support new digitization efforts, new product development, service evaluations, and the spotting of new revenue opportunities. The digital twins provide a powerful sandbox that helps to shape how CPG companies interact with their real customers.
What impact will Digital Twins have on CPG companies?
Digital twins offer a range of benefits to CPG companies, many of which can become significant competitive advantages if well-executed:
Improves customer experience. Having the ability to create fully digital representations of customers allows for much more nuanced user experiences to be created. As we move more fully into the digital world thanks to the proliferation of online shopping and the steps towards a fully functioning metaverse, digital twins provide the tools that companies need to understand their customers deeply and provide a highly personalized and authentic experience across all digital platforms.
Reduces product development costs. The insights derived from digital twins are incredibly valuable for various experiments and iterative processes within new product development. According to Foodpairing, “Digital Twins will help improve the efficiency of processes such as Total Unduplicated Reach and Frequency (TURF), Consumer tests to predict buying intent (FMOT) and hedonic liking (SMOT.) This enables companies to predict product success in advance and leverage insights from different countries and consumers to launch relevant yet exciting products for their target consumer.” By leveraging this in a cost-effective way, digital twins can supercharge the ROI on product development and rapidly accelerate how quickly a company can go from an idea to product-market fit.
Reduces personal data collection. When digital twins can achieve the same level of specificity using synthetic data as they can with real data, then CPG companies do not need to collect as much personal data as they currently do. According to research from Gartner, this could reduce privacy violation sanctions by up to 70% and help CPG companies to lean into the growing social movement that demands better privacy controls for consumers.4
Incentivises investment into AI. The power of digital twins for understanding customers will be so impactful that to ignore it would be inexcusable. As such, CPG companies will be forced to quickly upskill themselves in terms of their AI capabilities in order to compete and remain relevant in the years to come. For many, they’ll need to turn to professional partnerships with AI firms that can offer this expertise and experience immediately – to strike while the iron is hot. Mars and Pepsico are two giant companies that have already done this, and we’re likely to see all major CPG companies follow in those footsteps.5-6
These are just a few of the key levers that digital twins will begin to impact in the CPG space but this is just what we can see right now. As with all technology, new use cases will emerge over time as the industry matures and so the next ten years of this innovation will unlock a range of different concepts and ideas that we can’t even fathom just yet.
Where to from here?
For companies who want to leverage this technology, speed is of the essence. There is a race for talent to bring these sorts of AI-related skills into organizations, but there is also a model for partnering with AI providers to make this a possibility much sooner. AI platforms such as Foodpairing already come with their own datasets, experience and understanding of the challenges – and that can offer agility and speed where needed.
Companies need to avoid the trap of spending the next two-to-four years on custom ERP (Enterprise Resource Planning) and PLM (Product Lifecycle Management) solutions to try and supplement their data gaps and instead work on rapid iterations to their workflows to make a dent much sooner than that. By leveraging key technology partnerships with companies that can offer real solutions, CPG giants can get ahead of the curve and start experimenting with their own digital twins in just a month or two.
References
1. BCG Publications (2018, October).
2. BCG Publications (2020, May).
3. Gartner (2022, August).
4. Gartner (2021, October).
6. Nvidia, Pepsico.