Early adopters of AA and AI in the CPG industry have achieved remarkable successes, demonstrating the value of these new tools and solutions.
In the consumer-packaged-goods (CPG) sector, the tremendous value of advanced analytics (AA) and artificial intelligence (AI) is becoming increasingly evident. AA and AI have been strategically implemented by many leading CPG companies with excellent results in recent years, raising sales, enhancing productivity, and increasing the efficacy of their marketing expenses.
The capability to scale The Bionic Company smoothly is crucial to their success. As businesses struggle with predicting, responding to, and shaping changes in customer demand and behavior in the aftermath of the COVID-19 pandemic, the capacity will become more critical in the months ahead.
Many CPG firms are having trouble utilizing AA and AI effectively. They are usually less advanced in applying for large-scale analytics or technology transformation programs, despite being experts at branding with first-rate marketing, advertisement, and product creation capabilities.
Many CPG companies are decentralized and matrixed, which contributes to this. The framework has resulted in marketing and product creation prowess, but it can also restrain a company's capability to invest in data and analytics platforms or develop the agile working practices required to scale them.
In general, any business that wants to succeed in the digital age must become bionic, which means it must combine technology. To succeed with AA and AI in particular, they will need to improve the skills in these fields.
Companies must create a clear business case for implementing AA and AI, including identifying the necessary investments and the expected benefits. Once a set of AA and AI solutions has been established, they must be prioritized using comprehensive business cases to ensure proper attention and resource allocation.
Companies must assist workers in moving away from seeing AA and AI efforts as the framework of the IT department and toward seeing them as a critical part of the company's strategy and direction. As a result, AI activities should be guided by frontline business leaders in collaboration with the company's technology and analytics experts, rather than being developed solely in an IT or analytics feature silo.
Data Strategy and Governance
Early adopters have identified a coherent data management approach to guarantee they have access to high-quality, structured data, the foundation for AA and AI. Companies can use large, uniform data sets in AA and AI applications that cross conventional brand and organizational boundaries by designing the right data-management strategy and governance.