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P&G turns to AI to create digital manufacturing of the future, supported by Microsoft

P&G turns to AI to create digital manufacturing of the future, supported by Microsoft

Consumer goods giant, with help from Microsoft, is adopting the Industrial Internet of Things, digital twin, AI, and machine learning to transform manufacturing at scale.

Vittorio Cretella (P&G)

Vittorio Cretella (P&G)

Credit: P&G

Over the past 184 years, Procter & Gamble (P&G) has grown to become one of the world’s largest consumer goods manufacturers, with worldwide revenue of more than $76 billion in 2021 and more than 100,000 employees. Its brands are household names, including Charmin, Crest, Dawn, Febreze, Gillette, Olay, Pampers, and Tide.

In 2022, P&G sealed a multi=year partnership with Microsoft to transform P&G’s digital manufacturing platform. 

The partners say they will create the future of digital manufacturing by leveraging the industrial internet of things (IIoT), digital twin, data, and AI to bring products to consumers faster and increase customer satisfaction, all while improving productivity and reducing costs.

“The main purpose of our digital transformation is to help create superior solutions for daily problems of millions of consumers around the world, while generating growth and value for all stakeholders,” says Vittorio Cretella, CIO of P&G.

“We do that by leveraging data, AI, and automation with agility and scale across all dimensions of our business, accelerating innovation and increasing productivity in everything we do.”

The digital transformation of P&G’s manufacturing platform will enable the company to check product quality in real-time directly on the production line, maximise the resiliency of equipment while avoiding waste, and optimise the use of energy and water in manufacturing plants.

Cretella says P&G will make manufacturing smarter by enabling scalable predictive quality, predictive maintenance, controlled release, touchless operations, and manufacturing sustainability optimisation. These things have not been done at this scale in the manufacturing space to date, he says.

Smart manufacturing at scale

The company has already undertaken pilot projects in Egypt, India, Japan, and the US that use Azure IoT Hub and IoT Edge to help manufacturing technicians analyse insights to create improvements in the production of baby care and paper products.

For instance, the production of diapers involves assembling many layers of material at high speed with great precision to ensure optimal absorbency, leak protection, and comfort.

The new IIoT platform uses machine telemetry and high-speed analytics to continuously monitor production lines to provide early detection and prevention of potential issues in the material flow. This, in turn, improves cycle time, reduces network losses, and ensures quality, all while improving operator productivity.

P&G is also piloting the use of IIoT, advanced algorithms, machine learning (ML), and predictive analytics to improve manufacturing efficiencies in the production of paper towels. P&G can now better predict finished paper towel sheet lengths.

Smart manufacturing at scale is a challenge. It requires taking data from equipment sensors, applying advanced analytics to derive descriptive and predictive insights, and automating corrective actions. The end-to-end process requires several steps, including data integration and algorithm development, training, and deployment. It also involves large amounts of data and near real-time processing.

“The secret to scale is to lessen complexity by providing common components at the edge and in the Microsoft cloud that engineers can work with to deploy diverse use cases into a specific manufacturing environment — without having to create everything from scratch,” Cretella says.

Using Microsoft Azure as the foundation, Cretella says P&G will now be able to digitise and integrate data from more than 100 manufacturing sites around the world and enhance AI, ML, and edge computing services for real-time visibility. In turn, this will enable P&G employees to analyse production data and leverage AI to support decisions that drive improvement and exponential impact.

“Accessing this level of data, at scale, is rare within the consumer goods industry,” Cretella says.

Data and AI as digital fundamentals

P&G took the first steps in its AI journey more than five years ago. It has moved past what Cretella calls the “experimentation phase” with scaled solutions and increasingly sophisticated AI applications. Data and AI have since become central to the company’s digital strategy.

“We leverage AI across all dimensions of our business to predict outcomes and increasingly to prescribe actions through automation,” Cretella says.

“We have applications in our product innovation space, where thanks to modelling and simulation we can shorten the lead time to develop a new formula from months to weeks; in the way we engage and communicate with our consumers, using AI to deliver to each of them brand messages delivered at their right time, right channel, and with the right content.”

P&G also uses predictive analytics to help ensure the company’s products are available at retail partner “where, when, and how consumers shop for them,” Cretella says, adding that P&G engineers also use Azure AI to ensure quality control and equipment resilience on the production line.

While P&G’s recipe for scale relies on technology, including investment in a scalable data and AI environment centred on cross-functional data lakes, Cretella says P&G’s secret sauce is the skills of hundreds of talented data scientists and engineers who understand the company’s business inside and out.

To that end, P&G’s future is about embracing automation of AI, which will allow its data engineers, data scientists, and ML engineers to spend less time on manual, labor-intensive tasks so they can focus on the areas where they add value.

“Automation of AI also allows us to deliver with consistent quality and to manage bias and risk,” he says, adding that automating AI will also “make these capabilities accessible to an increasingly larger number of employees, thus making the benefits of AI pervasive across the company.”

The power of people

Another element to achieving agility at scale is P&G’s “composite” approach to building teams in the IT organisation. P&G balances the organisation between central teams and teams embedded in its categories and markets.

The central teams create enterprise platforms and technology foundations, while the embedded teams use those platforms and foundations to build digital solutions that address their units’ specific business opportunities.

Cretella also notes that the company prioritises insourcing talent, especially in areas such as data science, cloud management, cyber security, software engineering, and DevOps.

To accelerate P&G’s transformation, Microsoft and P&G have created a Digital Enablement Office (DEO) staffed by experts from both organisations.

The DEO will serve as an incubator to create high-priority business scenarios in the areas of product manufacturing and packaging processes that P&G can implement across the company. Cretella considers it as more of a project management office than a centre of excellence.

“It coordinates all the efforts of the different innovation teams that work on business use cases and ensures an efficient scaled deployment of proven solutions that develop,” he says.

Cretella has some advice for CIOs trying to drive digital transformation in their organisations: “First, be driven and find your energy in the passion for the business and how to apply technology to create value. Second, be equipped with tons of learning agility and genuine curiosity to learn. Last, invest in people — your teams, your peers, your bosses — because technology alone does not change things; people do.”


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