By Paul Larson and Harris Fogel, SAP
An interesting irony of today’s consumer products landscape is the surge of small and midsize companies capturing 49% of category growth. In an industry where 100 brand focused companies traditionally controlled most of its sales volume and revenue share, thousands of digital natives and disrupter brands are narrowing that market leadership gap more and more every day.
What’s their secret? Using artificial intelligence (AI), machine learning (ML), and other advanced technologies to meet consumer demands and personalize products with an agile supply chain.
This reality was apparent at this year’s industry events, such as NRF Retail’s Big Show and the FMI Midwinter Executive Conference. Everywhere we looked, there was considerable proof that AI and ML are helping small and midsize companies fuel growth and expansion with continuous innovation, agile operations, and fast response to consumer demand. Yet recent findings from IDC research underscore how such narrow application of these intelligent technologies doesn’t even begin to tap into their vast potential.
Shifting artificial intelligence from hype to hero
In many ways, growing interest in AI and ML should come as no surprise. Industry and technology analysts, such as IDC, have revealed the impactful potential midsize consumer products companies gain by leveraging these intelligent technologies to support innovation.
But according to the IDC InfoBrief, “Becoming a Best-Run Midsize Consumer Products Company,” sponsored by SAP, the true potential of consumer products transformation with AI and ML is more profound than the traditional goals of increasing operational efficiency, speed, and agility. Ultimately, it’s about delivering consumer experiences through a business model that both anticipates future needs and offers products and services that meet the needs that buyers did know – and did not know – they had.
Midsize consumer products brands, which lead their market segment, recognize the competitive advantage of capturing fleeting moments – whether they happen in a brick-and-mortar store, e-commerce retailer site, or a direct-to-consumer channel. These highly specific, individual interactions give a view into the ecosystem of retail customers and consumers that help growing companies understand every market shift and shape their business model to seize on those changes quickly.
By adopting technologies with embedded AI and ML midsize players can identify, analyze, and act on each “moment” early on with well-attuned, sense-detecting mechanisms extended throughout the business network. Doing so enables them to evaluate, for example, real-time online and in-store conversations to guide future product innovation and regional inventory mix. Furthermore, they can form closer partnerships with their retail customers by exchanging critical data necessary to influence and enhance product sales and make better decisions on merchandising and marketing promotions.
Seizing every opportunity that will never come again
For midsize consumer products companies, exceeding consumer expectations is the secret to winning a sizeable share of the industry’s revenue potential. But a certain level of data intelligence is required to capitalize on the right innovation projects, get ahead of market trends, and tap unfulfilled consumer needs – quickly, accurately, and precisely.
By creating a business model based on AI and ML, growing businesses can drive strategies that touch on five fundamental decision-making triggers: top-line growth, revenue margin, workforce developments, and the balance between risk and reward. But more importantly, they can build their currency of brand trust by using those factors to shape responsive actions that matter most to consumers.
Ready to discover new ways to drive revenue, identify and attract new consumers, and improve the consumer experience? Read the IDC InfoBrief, “Becoming a Best-Run Midsize Consumer Products Company.”