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Consumer packaged goods (CPG) companies are responding to inflation, pricing-sensitive consumers and supply-chain volatility by linking demand information more closely to planning and production. Examples range from Danone’s described factory practices to PepsiCo’s announced digital-twin pilots and P&G’s account of a broader data-and-supply-chain strategy—but those examples represent different stages of implementation, not comparable proof of results.
Why CPG companies are rethinking how they operate
CPG companies sell everyday goods such as food, beverages, personal-care products and household items. Their operating challenge is not simply to make products more cheaply: they must also decide what to make, where to make it, and how to keep products available when consumer demand, input costs or supply conditions change.
PwC’s inaugural CPG Executive Survey included more than 200 global senior executives and was conducted April 16–May 2, 2025. In its August 2025 report, 49% of respondents said their business model would not be viable in a decade. Yet one in three executives said they were not planning to restructure. The contrast points to a practical difficulty: recognizing that change is needed does not automatically mean an organization is ready to alter how it works. PwC’s survey and analysis
Pressure comes from several directions. Consumers can be more selective when prices rise, while companies face changing input costs, trade uncertainty, competition and supply-chain disruption. Deloitte’s 2025 discussion of the sector and its 2026 outlook describe these as forces prompting companies to revisit growth and operations; the mix and severity will differ by company and market. Deloitte’s 2025 CPG analysis Deloitte’s 2026 outlook
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PwC also reports an expectation of 10–15% direct-to-consumer (DTC) growth over five years. That is an expectation reported in the 2025 article, not a realized growth rate or a guarantee for any brand. PwC’s CPG survey article
The operating shift: connect demand signals to decisions
A factory-efficiency project can improve one part of production without addressing whether the company is making the right products, in the right quantities, at the right time. The broader transformation described by CPG leaders is to connect consumer and demand information to planning and operations, so that production and supply decisions can respond to what customers are likely to want.
In a March 2026 McKinsey interview, Danone COO Vikram Agarwal described the company’s ambition as an end-to-end supply chain responsive to consumer demand. EY’s 2026 State of Consumer Products report likewise frames the ability to respond to valuable demand complexity as a leadership capability. These are leadership perspectives, not evidence that every company has achieved the same degree of responsiveness. McKinsey’s interview with Danone’s COO EY’s 2026 State of Consumer Products report
In practice, connecting the signals means treating planning, production and distribution as related decisions rather than separate efficiency programs. Better information may help teams identify a demand change or an equipment issue sooner; it does not, on its own, resolve shortages, cost increases, data-quality problems or disagreements over priorities.
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The examples below illustrate different operating locations and evidence stages. A company interview describing an operating practice, a corporate strategy page and an announcement of pilots should not be read as equivalent proof of scaled performance.
| Example | Where the change sits | What is reported | Evidence and stage |
|---|---|---|---|
| Danone | Factory operations and end-to-end supply chain | Operators monitoring production lines on tablets; equipment identifying a potential motor problem and alerting employees for preventive action; an ambition to make the supply chain responsive to consumer demand. | Practices and ambition described in a March 4, 2026 McKinsey interview with Danone COO Vikram Agarwal; company account, not an independent outcome comparison. Danone’s Opole factory was designated a World Economic Forum Advanced Fourth Industrial Revolution Lighthouse in 2022. McKinsey interview |
| PepsiCo | Selected U.S. manufacturing and warehouse facilities | A multi-year collaboration with Siemens and NVIDIA to create digital twins of selected facilities, with early pilots underway at the time of announcement. | Announced January 6, 2026. The announcement establishes a collaboration and early pilots at that point in time, not proven results from a scaled deployment. PepsiCo announcement |
| P&G | Across brands, consumer information, innovation and supply chain | P&G describes integrating consumer data, innovation, supply-chain capabilities, data platforms, AI and automation across its value chain. | Company strategy in P&G’s 2026 annual-report content; it is P&G’s description of its approach, not an independent evaluation of results. P&G’s account of the future CPG company |
These approaches address different points in the operating system. Danone’s example focuses on production visibility, maintenance and responsiveness. PepsiCo’s announcement concerns facility modeling through digital twins, which create virtual representations of physical operations for analysis and planning. P&G describes a wider integration strategy spanning consumer understanding and supply-chain capability. None of these examples alone establishes that one approach is more effective than another.
Where AI and automation fit—and what adoption figures do not prove
AI and automation can support several different tasks: forecasting and planning, monitoring production lines, predicting maintenance needs, or helping marketing teams analyze consumer signals. The operational value depends on the task, the quality of the underlying data, integration with existing workflows, and whether employees can act on the output.
Deloitte’s 2026 outlook reports that 80% of surveyed beauty and personal-care companies said they had made significant investments in AI, robotics and/or automation to improve operational efficiency. That result applies to the beauty and personal-care subset shown in the survey questions, with n=55; it should not be generalized to the entire CPG sector. An investment or reported adoption is also not a measured return on investment or proof of cost savings. Deloitte’s 2026 outlook and survey
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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchDanone’s described equipment alert is an example of predictive maintenance: using equipment information to flag a potential failure early enough for a team to intervene. PepsiCo’s announced digital-twin pilots, by contrast, concern modeling selected facilities. These are distinct applications and should be judged against different operational goals, such as preventing unplanned downtime or improving the ability to model a facility change.
Why technology alone does not transform an operating model
New software or equipment has to be incorporated into decision rights, team routines, skills and incentives. PwC’s 2025 CPG article states: “Despite the attention on AI and digital transformation, the No. 1 challenge to organizational change isn’t cost or technology.” The statement reflects PwC’s article, not a universal measurement of every company’s experience. PwC’s analysis of CPG transformation
This distinction matters because an organization can buy a tool without changing how it makes decisions. A demand forecast has limited value if planners do not trust it, a maintenance alert helps only if responsibility and response procedures are clear, and a digital twin is useful only if teams can connect its analysis to operational choices. The internal work—revising processes, building capabilities and coordinating across functions—is part of the transformation, not a minor implementation detail.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the readiness rankings can—and cannot—show
IMD’s 2025 CPG Future Readiness Indicator includes 26 companies. Its displayed top five are L’Oréal, Coca-Cola, Unilever, P&G and Nestlé, in that order. This is an index-based comparison of future readiness, not an audited measure of factory efficiency and not evidence that a particular investment caused a company’s position. IMD’s 2025 CPG Future Readiness Indicator
A ranking can offer a broad comparison within the index, while an operating example can show what a company says it is doing in a specific part of its business. Neither substitutes for common, comparable outcome data across firms. The sources here provide survey findings and company descriptions, rather than a controlled comparison demonstrating which transformation produces the best results.
How to assess whether a CPG transformation is working
For consumers and investors trying to understand what a company’s transformation means, the most useful questions separate the pressure, the intervention and the evidence:
- What problem is it meant to address? A program may target cost, product availability, demand volatility, equipment downtime or growth. Those are different outcomes.
- Where does the change happen? Distinguish planning and forecasting from factory operations, warehousing, organizational redesign or the consumer interface.
- What stage has been reached? Separate a stated ambition, a described current practice, an announced pilot and a scaled operating program.
- What supports the claim? A survey records respondent views; a company announcement or annual-report page describes the company’s own plans or capabilities; an interview offers an attributed account; an index ranks companies according to its methodology. These evidence types answer different questions.
- What outcome is actually reported? Investment, implementation and readiness are not interchangeable with demonstrated improvements in cost, service or growth.
The broader pattern is a move from isolated efficiency projects toward more connected decisions about consumers, planning and operations. Whether that improves resilience or financial performance depends on execution—and should be judged by reported operating outcomes, not technology labels alone.
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