Can AI Predict Whether Shoppers Would Pick Crest or Colgate?

Can we be doing Consumer market research with Generative AI?    Something we thought about in the 80s.With exactly these consumer products.  So are we close enough to now get a meaningful answer?

Can AI Predict Whether Shoppers Would Pick Crest or Colgate?   From HBS

Is it the end of customer surveys? Definitely not, but research by Ayelet Israeli sheds light on the potential for generative AI to improve market research. But first, businesses will need to learn to harness the technology.

Companies have long poured time and money into surveying customers. Now, with new research showing artificial intelligence provides plenty of rich data about shopper preferences, could customer surveys become obsolete?

Companies turn to people for honest feedback about what they will and won’t buy, but large language models like generative pre-trained transformers (GPTs) may allow companies to rely on AI to uncover consumers’ tastes, according to new research from Harvard Business School and Microsoft. Ayelet Israeli, an associate professor at HBS, and her fellow researchers queried a commercially available version of GPT-3 to elicit thousands of simulated customer responses and found that AI can produce demand patterns that resemble those of human studies.

“UTILIZING THIS TOOL, WHICH IS IN SOME WAYS A CONSUMER SIMULATOR, ACTUALLY GIVES YOU USEFUL AND MEANINGFUL INFORMATION, AS IF IT CAME FROM A SAMPLE OF CUSTOMERS.”

While the recent emergence of ChatGPT has reignited fears that machines may replace humans in the workplace, the results of this study don’t necessarily mean that AI is going to gut marketing departments, the researchers say. Instead, the findings show the potential value of AI as an important tool for increasing productivity, reducing costs, and improving the quality of survey designs and insights generated within the fast-growing, $80 billion market research industry.

“We’re not saying everyone should now use this instead of talking to consumers, but we are saying that utilizing this tool, which is in some ways a consumer simulator, actually gives you useful and meaningful information, as if it came from a sample of customers,” says Israeli, the Marvin Bower Associate Professor at HBS.

Companies all over the world routinely spend heavily on time-consuming market research in hopes of uncovering new insights about their target customers. But, even as market research tools have rapidly evolved, the results of such studies still offer only a snapshot of customer sentiment, and survey data is often flawed, the research team says.

“Humans tend to tell you they would pay more than they’re actually willing to pay. They say they would choose something that they don’t actually choose in practice,” says James Brand, an economist for Microsoft, who cowrote the working paper with Israeli and Donald Ngwe, a former HBS faculty member who is now an economist at Microsoft.

How well did AI do?

The researchers’ first step was to determine whether market research results elicited from GPT were consistent with expectations, based on established economic theory. To do this, they set the large language model to provide responses with the highest-possible rate of randomness. They then crafted prompts—the questions users ask an AI tool—about specific products like toothpaste and laptops, seeking hundreds of responses about whether the “customer” would choose to purchase products at various price points.

“This allows us, for each price, to figure out the mean and the distribution around that, and then look at the overall shape of what we get, and determine whether we are actually getting something that looks like a realistic demand curve or not,” Israeli explains.

When the GPT prompt included information about the simulated customer’s income, varying between $50,000 and $120,000 per year, the responses indicated that higher income was correlated with higher price tolerance. This was in keeping with the pattern that researchers expected to see based on past research on the relationship between customers’ income and their willingness to pay.

“THAT WAS PRETTY INCREDIBLE TO US, THAT YOU’RE ABLE TO IDENTIFY THESE PATTERNS EVEN WITH THIS SIMULATED DATA.”

The team then introduced two brands of toothpaste, Crest and Colgate, and set Colgate as the preferred brand. By altering the price of Colgate, they could see at what point “customers,” on average, would switch to the less preferred but cheaper brand.

“Substitution patterns that you expect to find in observational data, we were able to find by collecting GPT’s responses,” says Israeli. “That was pretty incredible to us, that you’re able to identify these patterns even with this simulated data.”

The researchers also found that telling GPT that it had purchased a product before, such as yogurt, and how much of the product the “customer” already had at home, affected purchasing decisions in predictable ways: the more yogurt they had at home, the lower the price they were willing to pay for one additional unit, but not to the magnitude the researchers expected. Likewise, when asked to behave like a “random restaurant-goer” who had already consumed a few glasses of wine, GPT was still willing, on average, to pay the same price for subsequent glasses. This is contrary to theoretical predictions that would suggest that the more of a good someone consumes, the less they would be willing to pay for an additional unit of that good.

“In this case, prompting that a customer has consumed wine may not only tell GPT about the customer’s prior consumption but also that the customer really likes wine,” Ngwe explains.

Might GPT also consider shifts in the decision-making ability of a restaurant-goer who had consumed a few glasses of wine? Maybe. The black-box nature of AI makes it impossible to know exactly what factors are used to generate responses, the researchers say.

Comparing AI results with customer surveys

In the second part of the study, the research team compared GPT results with a recent study involving actual people to assess the value customers assigned to specific product attributes.

For example, a recent study of human consumers found that shoppers were willing to pay $3.27 for fluoride in their toothpaste, and the GPT study results were “quite similar,” with one estimate coming in at $3.40, according to the working paper.

Consumer studies like these generally cost upwards of $20,000 and take researchers between three and six months to complete, says Brand. Whereas, with AI, “we can get those answers in under 15 minutes,” he says.

Using AI to run this type of analysis prior to embarking on a human study could dramatically increase both the efficiency of testing and the quality of the results, adds Israeli.

“Because I'm not restricted by attributes or human time or human understanding of complexity, I can identify the things that GPT suggests actually matter, and then iterate on those with real data and real consumers to get human-based results,” she says.  ... '   (more) 

Consumer Goods: Unilever, Kimberly Clark, KC -- Jumping Into AI

Used to analyze what Unilever was doing in applications of Advanced tech.  Here related: 

How Unilever Expedites Product Innovation With AI, Automation, and Robots

04/21/2023 By Liz Dominguez Managing Editor,   in Consumergoods

Robots are having a heavy hand in product innovation at Unilever, thanks in large part to the efforts being implemented at the company’s Materials Innovation Factory (MIF) in Liverpool, according to a recent blog post. 

These innovations are having a global impact, influencing product discovery, research, and manufacturing in not just the U.K., but across the sea in the U.S. as well. There’s three special “ladies” to thank, per Unilever, and they’re named Ariana, Shirley, and Gwen. 

These three robots are working alongside 250 R&D experts at Unilever’s 120,000-square-foot facility to help develop science-backed products through the power of automation. 

According to Unilever, MIF has the highest concentration of robots doing material chemistry in the world, and each machine is designed to crunch “colossal amounts of data and maintain consistency across samples and testing.”

The company makes it clear, however, that it isn’t looking to replace human efforts; it’s merely freeing up time by reducing time-consuming, repetitive jobs so that experts can focus on invention and exploration.

“The MIF’s purpose is to create a community of talented future research leaders, exchanging ideas with academic colleagues and accelerating the discovery process,” said Unilever. “Our partnership here allows us to tap into the best minds and resources in robotics, which strengthens our insights and capabilities to power next-level innovation, scientific discovery, and produce products with superior performance.”

Will robot management be a job of the future? CGT thinks so. Find out more.

Meet the Robots

Beauty bot Ariana is preparing mass amounts of hair fiber samples in mere seconds in order to create hair products for Unilever’s brands, including Dove’s Intensive Repair line. Using a patented Fiber Repair Actives technology, Unilever can help consumers reconstruct inner hair fibers to reduce breakage and repair from within the hair strand. 

Shirley

This robot is helping to expedite and mimic the process of hair washing and rising, running through 120 samples of hair every 24 hours. Shirley can rise, detangle, and blow dry hair, speeding up the analysis process so researchers can create accurate haircare product formulas, such as for the TRESemmé’s Colour Radiance Booste product line. The range of products uses tech that Shirley helped invent in order to better protect hair surfaces and keep color vibrant longer within hair fibers.

Gwen 

Robot Gwen plays an important role in the sensory aspect of products, generating, measuring, and analyzing foam. As Unilever uses foam in many of its products to deliver ingredients, the company said it’s important it can accurately attribute performance related to the amount, quality, and type of bubbles and froth. 

“Understanding its physical, chemical and consumer relevance is important in product development,” said the company. 

The Role of AI and Data

Along with robotics, the company has also heavily invested in artificial intelligence, an advance that it said allows Unilever to parse through “vast quantities of data in record time” in order to make discoveries and create new formulas. 

For example, for the company’s Hourglass Confession Red Zero lipstick, Unilever used AI to quickly analyze different color combinations before landing on a specific pigment — a research process that would normally take millions of physical experiments to replicate. 

The company has filed more than 200 patents between 2022 and 2022 using this type of invaluable data, investing more than 100 million euro into its innovation hub in order to benefit from these types of technologies.

“We are nothing without our science-backed products,” said Samantha Samaras, head of science and technology, Unilever Beauty & Wellbeing and Personal Care, in a statement.

Unilever’s relationship with data-powered innovation only grows stronger, as showcased by the company’s commitment to improve digital organization and data warehousing across the enterprise by moving entirely to the cloud. 

Under the new leadership of CEO Hein Schumacher, who has a long track record of transforming supply chains with sustainable and automated technology, it’s expected that Unilever will continue on this path.

An Industry-Wide Effort?

Automation and artificial intelligence go hand-in-hand, and a growing number of consumer goods companies are implementing both as they scale their supply chain transformations, focusing on either end-to-end reinvention or putting special emphasis on a particular area. 

One such area? According to IDC’s Futurescape report, by 2023, 50% of all supply chain forecasts will be automated through the use of artificial Intelligence.

Read more: Building the Supply Chain of the Future: 5 Consumer Goods Companies Investing in Innovative Approaches

Other areas of focus include supply chain workforce, merchandising, fulfillment, and more. 

Take, for example, Kimberly-Clark, which is leveraging an AI-enabled tool to automate the distribution planning and deployment process, as well as improve scheduling. Additionally, Mondelez International chief sales and marketing officer Martin Renaud said earlier this year that more than 1 million stores have access to its automated intelligence-enabled “suggested other” function, which has so far freed up representatives to engage 45% of more time in robust selling vs. administrative tasks. 

More Robotics News

ChatGPT: Do These Transformative Consumer Goods Use Cases Outweigh Concerns?

In this edited webinar transcript, Albert Guffanti, VP of the Retail Technology Group at Ensemble IQ, leads a discussion on the topic of generative AI, touching on use cases and reasons why the consumer goods industry should embrace the tech.

ChatGPT

Henkel To Shift Entire Digital Infrastructure to the Cloud

Henkel has announced plans to migrate fully to the cloud over the upcoming months.

Coty Launches Internal Upskilling Metaverse for Global Workforce

Beauty company Coty has stepped into the metaverse, launching a virtual campus designed to upskill its global workforce.  ....'

Pepsi Doing Technology and AI

Interesting look at Pepsi's Technology Advances

04/05/2023

Tech Transformation Podcast: PepsiCo’s Kate Garner On Consumer Insights’ Evolution

There may be no bigger priority for both retailers and consumer goods companies today than access to consumer insights, and PepsiCo has stood up its own data analytics practice known as Pepviz to seize this opportunity. In this episode of Tech Transformation, we’re talking with Kate Garner, SVP of marketing, demand accelerator, at PepsiCo about some of their latest findings, how the company's use of technology has evolved, and how it's helping them develop more collaborative retail relationships. 

Listen to learn: 

How the use of technology at PepsiCo has evolved over the last 20 years

How Pepviz is helping retailers leverage consumer insights for market share and revenue growth

How they share these insights across the PepsiCo organization 

How PepsiCo overcomes some of the challenges associated with data democratization

What’s next for Pepviz and what Garner sees as the future of retail

The potential of generative AI within consumer goods and retail

How PepsiCo’s use of technology has evolved: “From an insights perspective, we've gone from a world of deep longitudinal surveys, where you're getting a lot of stated purchase behavior, and moving more into a place where we're able to look at actual purchase behavior and link that then to get to that closed-loop measurement that's so critical, to be able to ensure we're delivering that return on investment. 

“And then taking it even a step further and getting down to individual store level. So when we think about the insights that we're able to attain, and transfer that then all the way down to an advantage that we have, which is having our sales associates in all the stores across the country, we’re able then to curate those insights in a very granular way to what's happening in their store.”

How they work with retailers: “We had a Midwestern retailer who was very interested in growing their carbonated soft drink business. And we were able to look across their footprint of stores, and first able to separate out where stores were excelling and where stores had opportunities. Then, within their footprint, we could look to seek and understand what are some of the differences? What are lookalike stores — and lookalike stores doesn’t necessarily mean that they're in close geographical proximity, but specifically, how do we look at the shoppers that are shopping that store? And then identify what's unique or differentiated about those stores, and how do we take the stores that are underperforming, build some of the insights and things that are happening within the stores with higher growth. 

“We were able to then go activate against those execution parameters. Exciting for the retailer, as exciting for us, we were able to deliver incremental growth for both of us, for the retailer to see a 16% lift in their carbonated soft drink business.”

How they leverage consumer insights across the company: “It's almost like a marketing campaign, and you need to break down the target audience into different personas. We have some within our organization who use this capability on a day-in and day-out basis, and so for those folks, we have training, we have webinars, we record them, we put them at their fingertips, and then we have experts, who would have an office-hour type capability to meet with some of our sales and category leaders to answer questions, all the way up to our senior executives, where we're looking to just curate and help inform them on the insights and the learnings.

"And so there, you'll see we have quarterly newsletters that we're putting into the inbox. If you go into Pepviz.com, you also can get those and sign up to see some of those newsletters. So really articulating for the marketplace what are the industry leading insights that we're seeing.”

The potential of generative AI in consumer goods and retail: “One of the areas that I see potential in, having led insights organizations here within PepsiCo, really migrating away from stated behavior. And so when I think about the ability for sentiment tracking, rather than just tracking words, being able to get into tone and understanding, or in search, and helping us articulate more clearly. Those are areas that excite me to think about how we experience those things differently and more nuanced. …

"I think that how generative AI takes off within the CPG and retail space will be dependent upon how they find solutions that connect to those territories of where we are already investing as an industry. So to the extent that they can tap into those areas and show progress in those spaces, I think it will take off quickly. Otherwise, it may be areas of the future.”   ... '

Generative Red Flags for Consumer Goods Generative AI

Consumer goods takes a look ... 

Generative AI and ChatGPT: How the Tech Could Overhaul the Consumer Goods Industry and Red Flags to Look For

By Liz Dominguez, Managing Editor

The top potential use cases for the consumer goods space, says Mukherjee, are “generating novel, diverse, and personalized copy content, audio, video, and images at speed and scale; and saving time and cost for audiences in different languages spread across other geographical boundaries.”

Read also: Coca-Cola Signs As Early Partner for OpenAI’s ChatGPT, DALL-E Generative AI

Not only can this lead to improved product packaging, he says, but can result in faster A/B testing and improved marketing performance, and can even influence some of the growing e-commerce customer support technologies like chatbots, virtual assistants, and avatars. 

“They can provide real-time multilingual customer support and product demos, and any queries can be responded to based on customer sentiment in different regions resulting in improved customer satisfaction and reduced support costs.”

Across product innovation, generative AI can also provide more accurate recommendations,  says Mukherjee. “It can scout for trends, social media data, tweets, sentiments, and features based on what customers are currently looking for.”

Harmon believes artificial intelligence could significantly transform three primary areas of business in the consumer goods space: 

Merchandising: Generative AI can quickly generate product descriptions and stories

Content Creation: Meta, for example, has demonstrated the ability of AI to generate images and landscapes from voice commands

Consumer Engagement: AI/ML can be used to find the language that generates the greatest response from consumers

Within these areas, CGT sees enormous potential, such as using image conversion tech within the beauty industry to streamline clunky AR applications, creating personalized product regiments by leveraging consumers’ past histories, and further tapping into consumer engagement efforts with generative AI-created quizzes and product education.

It’s easy to see this translating to several other categories, and expanding into even more use cases, but the key, according to experts, is to take it slow.

Keeping a Healthy Dose of Skepticism 

Generative AI risks

Why the caution sign? With a technology that is reliant on data inputs, there’s always risk. And in the case of generative AI, these risks include copyright infringement, insensitive content creation, misuse of content, and brand reputation repercussions. 

Take the virtual chat example as noted above: According to Mukherjee, chat agent conversations based on generative AI can lead to “surreal hallucinations or uncomfortable conversations, resulting in customers repelling the brand forever.”

While many companies have specific guidelines and parameters to fine-tune responses and hopefully avoid these situations, Mukherjee notes that these parameters will evolve and train as time goes on. Early on, however, content can result in biased and insensitive content, and it’s especially important that consumer goods companies keep an eye for tech providers without transparent data sources and usage policies.

There are several limitations, says Gartner, which notes that ChatGPT, for example, is only trained on data through 2021, cannot cite its sources, does not provide data privacy assurances, and does not currently have a supported API available. 

Much of the risks are due to the vastness of generative AI, which generates text and graphics based on the huge amount of data it has processed, says Harmon. This could include personal information and copyrighted info, with the potential to generate incorrect information since there is no human involved in the process.  ... ' 

Coke Does Interesting AI and Decision Support Work

Former competitor of mine, their use of AI and more for supply chain.

How Colgate-Palmolive Built a Framework for Supply Chain Analytics

Lisa Johnston, Editor-in-Chief   Colgate-Palmolive has developed an analytics engagement lead role to serve as an organizational coach.

Colgate-Palmolive has developed a foundation to fuel the advancement of supply chain analytics that not only includes a dedicated analytics catalyst team but also a coach to lead them. 

Though it remains in early days, the company is also exploring the future of decision intelligence and what new roles may be required to support it.   

Having a digitized supply chain is a key component of supply chain resilience, but it’s often hampered by a dearth of tech talent and a critical need for upskilling. Like many consumer goods companies, Colgate-Palmolive is taking steps to democratize analytics across the enterprise, including through investments within supply chain analytics engineers. 

What’s a bit novel is that they’ve also developed an analytics engagement lead role to serve as an organizational coach, a role that Jason Bunce, Colgate-Palmolive worldwide director, supply chain analytics enablement, cited in a Gartner webinar this month as critical.  

See also: David Foster Takes CIO Helm at Colgate-Palmolive

This role focuses on educating, socializing, and facilitating analytics within Colgate-Palmolive, and owns the development and delivery of their data literacy program, collating and sharing best practice, and managing the No. 30 publicly owned consumer goods company’s intranet-based practitioner community. 

“It’s an investment that can look to be a bit of a luxury on the face of it,” said Bunce, ”but it's been a really sound investment for us.”

ACT Activate 

The analytics engagement lead also spearheads a key group of citizen data analysts — a virtual team known as the analytics catalyst team (ACT), who are handpicked assistant data analysts from across the global supply chain. These business employees — there are around 40 of them — dedicate 20% of their time to support ACT and are split between analytics developers and analytics translators. 

They not only bring “extra hands on keyboards” to help develop datasets, visualizations, and other analytics, but the translators serve as the power-user glue between business and technical employees.

“They're passionate about analytics, and they want an opportunity to make a difference,” noted Bunce. “Being part of this team [gives] them an opportunity to deliver value, while at the same time developing personally through enhancing their capabilities and gaining great exposure across the business.”  

Upskilling, Top to Bottom 

Culture change starts at the top, and so Colgate-Palmolive kicked off its analytics development program with a bespoke training program for supply chain leaders, including their chief supply chain officer.   Over the course of a week, leaders spent an hour a day in a socially networked self-learning environment with an external facilitator. Each day tackled a different topic, such as the value of building data analytics capability, data as a strategic asset, the importance of collaboration in data analytics, and developing an analytics culture. It was ultimately delivered to 1,000 leaders over the span of a year. 

See also: Out of the Gate: 12 Tips for New CPG CIOs

Different learning personas were subsequently developed to focus on data literacy, an introduction to data science, and storytelling with data — “so we’re all speaking a common language” — as well as monthly newsletters, quarterly practitioner communities, and an active intranet sharing community. 

Look Ahead: Decision Intelligence 

Bunce’s team’s scope includes transforming operational analytics around inventory, transparency, and plant performance, and this year they’re pivoting slightly to complement the enablement focus and expand into advanced analytics — focusing on elevating from descriptive analytics to diagnostic analytics. 

This includes a particular emphasis on demand sensing, as well as network design modeling capabilities and developing additional synchronization within vertical integrations.

Colgate-Palmolive is further exploring the value of decision intelligence, according to Bunce, and the company has begun piloting technology within the space with a third party.  

“At the moment when we're in the early stages of this development, we can contract out a number of these roles," he said. "But I think as we grow in this space, we'll need to have the conversation about what we contract out and what we build within our organization." 

“Whatever we do. I think we need to have a degree of ownership of this, so there will definitely be new capabilities that we're developing internally.”    ... ' 

Veeral Shah Named 1st Chief E-comm & Digital Officer at Nestlé USA

 Came from CPG, and strong use of consumer data, so of interest. 

Veeral Shah Named 1st Chief E-comm & Digital Officer at Nestlé USA

Personnel Moves (of interest) 

Veeral Shah has been named chief e-commerce and digital officer for Nestlé USA, a new role for the company. 

Shah shared the news in a LinkedIn post and indicated in a message to CGT that the move aligns with the company’s previously announced plans to further invest in its e-commerce and consumer data capabilities.   

As part of its strategy, Nestlé intends to grow e-commerce to represent a quarter of its total sales, double its consumer data records, and leverage predictive analytics to improve consumer lifetime value and identify innovation opportunities.   

Most recently VP of commercial strategy and development at Nestlé, Shah has also held roles at Campbell Soup Company, Johnson & Johnson, Kellogg’s, and Accenture.  

“I have always aspired to have a voice on a C-suite level executive leadership team and to achieve this at the world's largest CPG company is truly humbling,” Shah posted on LinkedIn. “Since joining Nestlé four years ago, I have been blown away by the culture, leadership, and people I get to work with everyday. With this newly created position, Nestlé once again confirms its commitment to stay ahead of the curve in the e-commerce and digital space.” 

See also: How Nestlé Gets Close to the Voice of the Consumer  (In Consumergoods) 

CPG Brands and Direct to Consumer

 After Covid influence involved?

Should CPG brands cast their DTC (Direct to Consumer) businesses in a supporting role to stores?

Sep 22, 2022    by Melissa Minkow  in Retailwire

It appears there’s been a significant tide turn for consumer packaged goods (CPG) brands in the direct to consumer (DTC) selling versus retailer distribution debate as marked by a consensus among presenters this week at Groceryshop in Las Vegas.

A year ago, the repeated objective mentioned among CPG executives focused on shifting consumers towards buying from their DTC sites in order to capture the most first-party data possible. This year, regardless of the session, the universal takeaway from the CPG success stories was to instead leverage DTC sites in a way that complements their presence on grocery store shelves and websites.

Charisse Hughes, chief brand and advanced analytics officer of The Kellogg Company, said on day one of the conference that DTC is useful for unearthing consumer insights and for experimenting.

Ms. Hughes said, however, that while DTC is where Kellogg’s innovates and tests, it does present challenges with respect to the last mile. Kellogg’s has determined that DTC sites are best for “swag and new products” so that there’s a differentiated value to the owned channel.

A similar strategy was echoed on day two by Francesca Hahn, VP of digital commerce at Mondelez, who highlighted the engaging ways shoppers can interact with the Oreo and Sour Patch Kids sites.  ... ' 

Six Ways Blockchain Is Bolstering Supply Chains

 Useful piece to consider.

Six Ways Blockchain Is Bolstering Supply Chains

June 13, 2022, Rob Viglione, SCB Contributor  in SupplyChain Brain 

In today's digital world, companies are under pressure to be more transparent with their customers. This is especially true for supply chains, where customers want to know where their products are coming from and how they’re being made.

Ethical compliance is one area that customers are putting under the magnifying glass. In Xinjiang, for example, the Chinese government is using a massive surveillance program to track the movements of the Uyghur Muslims, detaining more than one million people in forced labor camps, according to reports by the State Department and Department of Labor, as well as independent media outlets and the United Nations. As a result, U.S. companies that source products from Xinjiang are finding themselves under increased scrutiny. 

Customers understandably want to know their products aren’t being made in factories where human rights are being violated or lives are at risk. But companies often don't have the information needed to provide this level of transparency.

One way to address the problem of human rights violations within the supply chain is through the use of blockchain technology. Blockchain is a distributed ledger that allows for the secure and transparent sharing of data among multiple parties. Here are some promising applications of blockchain technology in the supply chain.

Digital ID. Blockchain can be used to create a "digital passport" for products, including information on where and how they were made. This tracing function can give customers assurance that they’re buying products from companies that share their values and are operating ethically. It can also help companies become more transparent, building trust with their customers.

Product quality and safety. In the past, there have been several major recalls of products found to be unsafe, such as baby formula and pet food. If manufacturers and retailers share data on ingredients and production processes, it can help to prevent such recalls from happening. And if a product does have to be recalled, the blockchain can allow for a quick and efficient response.

Nestlé is already experimenting with tracking Gerber baby food products on the blockchain. Ensuring the quality and safety of food products is one of the key benefits of supply chain transparency, particularly when it comes to tracing the origins of ingredients.

ESG transparency. If a company wants to qualify the sustainability of materials, it can use the blockchain to track their end-to-end supply chain. Such transparency ensures that the materials are coming from certified sustainable sources and being used in a responsible way. It also helps to prevent the use of unsustainable or unethically sourced materials.

Blockchain can be used to trace CO2 emissions and help companies offset their carbon footprint. By tracking emissions associated with the making of a product, it becomes possible to create a “carbon passport” for that product. It can show the amount of CO2 emissions generated during production, as well as steps taken to offset those emissions  ...' 

Kellogg is Splitting into 3 Companies:

 Quite unexpected, a major CPG.    Can we expect more?  

Kellogg is splitting into 3 companies: Here’s what each one will focus on

The cereal giant will become three distinct companies in a deal that is expected to be completed by the end of 2023.  Kellogg is splitting into 3 companies: Here’s what each one will focus on   By Michael Grothaus  in Fastcompany

Three companies are better than one for one of America’s most well-known brands.  Kellogg Company, the breakfast cereal juggernaut, has announced that it will split itself into three separate companies after the Kellogg board of directors approved the plan.

All three new companies will be publicly traded, and Kellogg says the split companies will be “better positioned to unlock their full standalone potential.” Announcing the news, Kellogg CEO Steve Cahillane said, “These businesses all have significant standalone potential, and an enhanced focus will enable them to better direct their resources toward their distinct strategic priorities.  In turn, each business is expected to create more value for all stakeholders, and each is well positioned to build a new era of innovation and growth.”

The three companies have not been given names yet, but Kellogg has detailed what each company will focus on:

“Global Snacking Co.”: This is the temporary name given to the company that will make and distribute some of Kellogg’s most iconic snacks and international cereals. Snack brands include Pringles, Cheez-It, Pop-Tarts, Kellogg’s Rice Krispies Treats, and Nutri-Grain. International cereals include Special K, Tresor / Krave, Crunchy Nut, and Coco-Pops. Kellogg says this company will be worth about $11.4 billion in net sales based on 2021 numbers.

“North America Cereal Co.”: This company will make and distribute some of the top brands people think about when they think of “Kellogg’s.” It will focus on ready-to-eat cereals in the United States, Canada, and the Caribbean. Cereal brands under this company’s banner will include Kellogg’s, Frosted Flakes, Special K, Froot Loops, Mini-Wheats, Raisin Bran, Rice Krispies, Corn Flakes, Kashi, and Bear Naked. It will be worth about $2.4 billion in net sales based on 2021 numbers.

“Plant Co.”: This final company can be considered the newest one when it comes to brands. That’s because it will make and distribute Kellogg’s plant-based foods. Its main brand will be the MorningStar Farms line of food and will focus on the United States, Canadian, and Caribbean markets. It will be worth about $340 million in net sales based on 2021 numbers.  ....

P&G and Microsoft Collaborate for Advanced Digital Manufacturing

My former employer goes for advanced digital manufacturing with Microsoft.

P&G and Microsoft co-innovate to build the future of digital manufacturing

Microsoft company logo.  (PRNewsFoto/Microsoft Corp.) (PRNewsfoto/Microsoft Corp.)

NEWS PROVIDED BY  Microsoft Corp.   Vis Cision

Microsoft technology empowers scalability for consumer products leader

CINCINNATI and REDMOND, Wash., June 8, 2022 /PRNewswire/ -- On Wednesday, The Procter & Gamble Company (NYSE: PG) (P&G) and Microsoft Corp. announced a new multiyear collaboration that will leverage the Microsoft Cloud to help create the future of digital manufacturing at P&G. ... 

A multiyear collaboration that will leverage the Microsoft Cloud to help create the future of digital manufacturing at P&G

The two companies will co-innovate to accelerate and expand P&G's digital manufacturing platform and leverage the Industrial Internet of Things (IIoT) to bring products to consumers faster, increase customer satisfaction and improve productivity to reduce costs. 

"Together with Microsoft, P&G intends to make manufacturing smarter by enabling scalable predictive quality, predictive maintenance, controlled release, touchless operations and manufacturing sustainability optimization — which has not been done at this scale in the manufacturing space to date," said P&G CIO Vittorio Cretella. "At P&G, data and technology are at the heart of our business strategy and are helping create superior consumer experiences. This first-of-its-kind co-innovation agreement will digitize and integrate data to increase quality, efficiency and sustainable use of resources to help deliver those superior experiences."

With Microsoft Azure as the foundation, the new collaboration marks the first time that P&G can digitize and integrate data from more than 100 manufacturing sites around the world and enhance its AI, machine learning and edge computing services for real-time visibility. This will enable P&G employees to analyze production data and leverage artificial intelligence to immediately make decisions that drive improvement and exponential impact. Accessing this level of data, at scale, is rare within the consumer goods industry.

P&G selected Microsoft as its preferred cloud provider to build the future of digital manufacturing based on a four-year history of successfully working together on data and AI. The new collaborative effort will:

Allow for better utilization of data, AI capabilities and digital twins technology.

Optimize manufacturing environmental sustainability efforts.

Increase workforce efficiency and productivity.

"We are excited to help P&G accelerate its digital manufacturing platform using Microsoft Azure, AI and IIoT to accommodate volatility in the consumer products industry with innovative, agile solutions that can easily scale based on market conditions," said Judson Althoff, Microsoft's chief commercial officer. "Our partnership will further P&G's growth and business transformation through digital technology that seamlessly connects people, assets, workflow and business processes that promote resiliency."

Empowering technicians and advancing operations with IIoT

P&G is already innovating and using Azure IoT Hub and IoT Edge to help manufacturing technicians analyze insights with greater speed and efficiency, creating improvements in the production of its baby care and paper products with pilot projects happening in Egypt, India, Japan and the United States.  .... 

Seeing How Odor Is Processed in the Brain

Worked with the use of Odors for consumer interaction.   Never went far, now a breakthrough?  Very interesting details.

From ACM TechNews | June 3, 2022

Researchers created an odor delivery device, then used machine learning to analyze electroencephalograms to determine how the brain processes scents.

University of Tokyo (Japan)

Researchers at Japan's University of Tokyo (UTokyo) created an odor delivery device, then used machine learning (ML) to analyze electroencephalograms (EEGs) to determine how the brain processes scents.

Their device can dispense 10 unique odors to participants, who rated the pleasantness of each as EEG caps recorded their brain signals.  The ML analysis ascertained when and where the range of odors was processed in the brain, with high temporal resolution.

Said UTokyo's Mugihiko Kato, "We were surprised that we could detect signals from presented odors from very early EEG responses, as quickly as 100 milliseconds after odor onset, suggesting that representation of odor information in the brain occurs rapidly." ... 

During the EEG measurement, participants were asked to rate the pleasantness of the odors. They then evaluated the odors ranging from citrus and tea leaves, to mothballs and wet dog.  ... 

From University of Tokyo (Japan)     

View Full Article

Procter & Gamble Bets on a BeautySphere Metaverse

My long-ago employer.  We played with early capabilities like the metaverse then, but not strongly consumer facing ones.   Much of that experiment was recorded here.  Yes I am surprised. it is unexpected.  Not really the world of their typical customers. Or are those consumers  moving there?    Still don't see it, but a big bet it is.  Please don't screw it up.  Call me if you would like to discuss.

Procter & Gamble is placing a big bet on the metaverse to support its suite of brands Creative and a technical leaders from the consumer goods giant share their reasoning for pursuing the metaverse, which they say they see as a learning opportunity.  A BeautySphere.   Following.  

Procter & Gamble is placing a big bet on the metaverse to support its suite of brands  By  Aman Kidwai         May 25, 2022 6:35 PM EDT  in Fortune.

It may be surprising that a 180-year-old maker of consumer products for the physical world is spending significant time and resources on the metaverse. But as leaders from Procter & Gamble explain, the main purpose of their exploration is to find new ways to interact with prospective customers and add value for them and retail partners.

How is success achieved through transformation

At the Fortune Brainstorm Design conference on Tuesday, Phil Duncan, chief design officer at Procter & Gamble, said “any time that there's a place where consumers are gravitating toward,” P&G is looking “to grow our businesses and, obviously, win the hearts and minds of consumers.”

“We're stepping into this environment to learn and understand how engagement really matters with consumers and ultimately create value,” he later added.

The consumer goods giant is one of many Fortune 500 companies making its mark in the metaverse, an online world where companies and people can maintain avatars, spaces, and other virtual presences. One project P&G has used the metaverse for is to replicate the experience of the Consumer Electronics Show (CES), a premier industry event, during the pandemic. The company made a similar push to put brand activations and experiences from its 2020 Tokyo Olympics sponsorship into the metaverse.

“The pandemic situation made it a bit more real for us to put it in practice and have a big, open mind to try them,” said Ioana Matei, head of emerging/immersive technologies at Procter & Gamble. Duncan credited Matei as his “reverse mentor” for this project, due to his lack of experience in this arena in other design initiatives he’s led.  ... ' 

For more of an inside Procter & Gamble Perspective.

Univever Boosts Availability

 Was our biggest competitor ....

Unilever’s Newest Way to Boost On-Shelf Availability,   Lisa Johnston,  Senior Editor

The tool recommends whether to continue manufacturing products and accounts for such factors as profitability, consumer purchase habits, and retailer benefit.

Unilever shared insight into how it’s leveraging machine learning and advanced analytics as part of its SKU rationalization process.

While long a tool in the CPG toolbox, SKU rationalization accelerated during the pandemic’s unprecedented consumer demand and ensuing supply chain crisis. Many consumer goods companies used the period as an opportunity to cut back poor performers in order to simplify production, optimize on-shelf availability (OSA), and bolster their retail partnerships.

In a company blog post, Unilever said the company is leveraging a new data-driven tool that uses advanced analytics to provide a more holistic and granular assessment of its portfolio. Segmenting the data by brand, customer, category, and channel, the tool recommends whether to continue manufacturing products and accounts for such factors as profitability, consumer purchase habits, and retailer benefit.

[See also: Unilever and Ahold Partner on Consumer Behavior With Visual Learning End Caps]  

It’s said to offers both total and cross-market views of rationalization opportunities; as a result, the Unilever market teams receive greater visibility into top-performing products, as well as insight into where there may be opportunities to invest. The teams can also better track overall portfolio performance, and the No. 4 publicly owned consumer goods company expects the technology to provide additional cost savings within the discontinuation process, as well as optimize both in-store and e-commerce OSA. 

Learn More on CPG Innovation

Like the many consumer goods companies turning to artificial intelligence and machine learning, Unilever emphasizes the role of its employees in the process, pointing to the required “human touch."

Morgan Vawter, global VP at Unilever’s data center of excellence, said the technology helps the company make faster and better decisions by marrying the perspectives of its retailers, consumers, and business.

“This is supported by clear targets from our leadership and by robust end-to-end governance,” she added. “The tool gives us visibility of each SKU delisting execution, so we have full traceability of every step to realizing its value.”

Practical Holograms?

Ever since seeing early versions of holographic images ay Disney World have thought of their uses, both in interaction with consumers, and as a means to graphically  interact with complex analytic data.  In the 90s participated in a SIGGRAPH panel regarding their uses. Especially their use as s means of very engaging packaging and advertising.   Here an excellent update.

Holograms on the Horizon?    By Chris Edwards

Communications of the ACM, November 2021, Vol. 64 No. 11, Pages 14-16   10.1145/3484998

Researchers at the Massachusetts Institute of Technology (MIT) have used machine learning to reduce the processing power needed to render convincing holographic images, making it possible to generate them in near-real time on consumer-level computer hardware. Such a method could pave the way to portable virtual-reality systems that use holography instead of stereoscopic displays.

Stereo imagery can present the illusion of three-dimensionality, but users often complain of dizziness and fatigue after long periods of use because there is a mismatch between where the brain expects to focus and the flat focal plane of the two images. Switching to holographic image generation overcomes this problem; it uses interference in the patterns of many light beams to construct visible shapes in free space that present the brain with images it can more readily accept as three-dimensional (3D) objects.

"Holography in its extreme version produces a full optical reproduction of the image of the object. There should be no difference between the image of the object and the object itself," says Tim Wilkinson, a professor of electrical engineering at Jesus College of the U.K.'s University of Cambridge.

Conventional holograms based on photographic film can capture interference patterns that work over a relatively wide viewing range, but cannot support moving images. A real-time hologram uses a spatial-light modulator (SLM) to alter either the amplitude or phase of light, generally provided by one or more lasers, passing through it on a pixel-by-pixel basis. Today's SLMs are nowhere near large or detailed enough to create holographic images that can be viewed at a distance, but they are just good enough right now to create near-eye images in headsets and have been built into demonstrators such as the HoloLens prototype developed by Andrew Maimone and colleagues at Microsoft Research.

A major obstacle to a HoloLens-type headset lies in the computational cost of generating a hologram. There are three algorithms used today to generate dynamic holograms, each of which has drawbacks. One separates the field of view into layers, which helps reduce computation time but lacks the ability to fine-tune depth. A scheme based on triangular meshes, like those used by games software that render 3D scenes onto a conventional two-dimensional (2D) display, helps cut processing time (although without modifications to handle textures, it lacks realism). The point-cloud method offers the best potential for realism, although at the expense of consuming more cycles. In its purest form, an algorithm traces the light emanating from each point to each pixel in the SLM's replay field. "Light from a single point can diverge to a very wide area. Every single point source creates a sheet of refractions in the replay field," says Wilkinson.

A drawback of the point cloud is that light from every point will not reach every pixel in the target hologram, because it will be blocked by objects in front of it. That calls for software to remove the paths that should be occluded, which increases the number of branches in the code. Though it removes the need to map the light from every point onto every pixel in the SLM, the checks and branches slow down execution. Photorealistic holograms intended for use as codec test images, created using a method developed by David Blinder, a post-doctoral researcher at Belgium's Vrije Universiteit Brussel, and colleagues, take more than an hour to render using an nVidia Titan RTX graphics processing unit. However, numerous optimizations have been proposed that reduce arithmetic precision and the steps required, with some loss of quality, to achieve real-time performance on accelerated hardware.

The MIT approach uses several approximations and optimizations built around a deep neural network (DNN) made up of multiple convolutional layers that generate the image from many subholograms. This involves far fewer calculations than trying to map a complete point cloud directly to a final complete hologram. In conventional optimizations, lookup tables of diffraction patterns can help build those subholograms more quickly, but it is still an intensive process.

The DNN allows a more progressive approach to assembling the final image, which results in fewer calculations, particularly as the network can handle occlusion. The team trained the model on images of partially occluded objects and their sub-hologram patterns. The resulting algorithm can deliver images at a rate of just over 1Hz using the A13 Bionic accelerators in the iPhone 11 Pro. Without the computational optimizations provided by the DNN, the researchers suggest processing would take at least two orders of magnitude longer.   ... ' 

Procter & Gamble and Microsoft: Data and Digital Transformation

Microsoft talks about how they work with key customers.   Notably with my former employer, where I worked on many related problems, and can agree that using data effectively was well understood to be key.  Fairly good detail here about using Microsoft Azure.

For Procter & Gamble, data is at the heart of digital transformation

August 17, 2021   Microsoft

For more than 180 years, Procter & Gamble (P&G) has built a thriving business by challenging norms and delighting consumers. Its range of household products, from toothpaste and soap to paper towels and laundry detergent, can be found in millions of homes—in nearly every country on Earth.

True to its innovative nature, P&G sees data and algorithms as a way to constructively disrupt how it operates, leading to growth. P&G developed a multicloud-driven data strategy—and data culture—that informs every decision the business makes to fuel its future success.

In order for P&G to understand and best serve consumers, we need to drive a data-enabled culture and operationalize algorithms into every major business decision. 

Guy Peri: Chief Data & Analytics Officer, P&G

“The way we approach excellence as a company is to get the right product, the right package, the right communication, and the right in-store execution,” says Guy Peri, Chief Data & Analytics Officer for P&G. “Pretty much everything about how we do that with our customers and the consumers who buy our products is changing—and data and algorithms are central to staying ahead of that change.”

Lots of data, but out of reach

Given its broad scope and long history, P&G had numerous data points about its business, including what drives sales and product preferences. But the data resided in geographically dispersed silos, and P&G’s legacy systems couldn’t link the hundreds of disparate data types to gain collective insights.

P&G sought a platform that could unlock those silos and provide a single view for business users. At the same time, company leaders realized that they needed to foster a data-driven culture—a growth mindset that put data and analytics at the forefront. AI, machine learning, and advanced analytics were all seen as crucial to becoming a true digital leader.

P&G found what it needed with the powerful suite of Microsoft Azure data and AI solutions, such as Azure Synapse Analytics, Azure Data Lake Storage, and Power BI. “Azure is helping optimize the impact of digitization across Procter & Gamble, from democratizing AI with no-code features to embedded capabilities in Power BI,” says Peri. “We appreciated the scale, flexibility, and analytical muscle of Azure. The stack can go up and down depending on our business needs. It also gives us leading data and algorithm capabilities with both the Azure Synapse back-end and front-end Power BI tools.”

For us, only two variables are important: performance and scale. Can we scale at a cost-effective rate? With Azure and the co-innovation we did together, we’re able to get positive outcomes on both fronts. 

Guy Peri: Chief Data & Analytics Officer, P&G

With these scalable, dynamic data solutions, P&G is bringing the power of data to bear on three key challenges: creating a resilient supply chain, improving retail execution, and delivering superior products and packaging.

A more resilient supply chain

P&G data scientists and business analysts combine information from existing and new data sources inside the data lake to create predictions that help ensure consumers can get the products they need, when they need them.

Better retail execution

P&G is using granular analytics capabilities to ensure that retail partners are putting the right products and right in-store displays in front of consumers. 

Superior products and packaging

P&G is using data and analytics in its products and packages to shift from a point-in-time assessment to a real-time, sense-and-respond approach. A key component of this shift is a global architecture with automated collection of data to fuel analysis that uncovers insights, speeds the innovation process, and determines manufacturability and cost optimization.

“We need to act with agility to be competitive with the fast startups in the world,” says Peri. “But we also need to act with precision to leverage our scale for competitive advantage. Data algorithms help us do both. So, the faster we can bring data insights to our decision makers, the more competitive we’ll be.”

Neighborhood analytics and smart selling

In addition to gaining important insights at a global level, P&G has been able to do the same at a local level. One initiative, called “Neighborhood Analytics,” helps P&G understand at a local level how consumers shop and what they need. By combining external and internal data sources, the company can more effectively partner with retail customers to expand specific categories for consumers.

A second initiative, called “Smart Selling,” gives P&G insight into what its distributors are doing in developing markets. By using big data and AI, the company can help distributors be precise when ordering products. “COVID-19 is a great example of where we’ve been able to use these tools to be much more precise,” says Peri. “We overlaid our Azure analytics capability with COVID-19 data and then understood exactly where we had the biggest risk of out-of-stock opportunities to address or where we anticipated the need for inventory.”

Creating a data-driven culture

Beyond specific use cases, P&G is also using Azure to create a strong data culture that makes employees aware of the power of data and how to use it every day.

The ease of use with Azure fosters P&G’s data culture from the technology side, making it easy for employees to understand data, manipulate it, and use it to inform major decisions. These decisions, in turn, positively affect P&G’s ability to better serve consumers and constructively disrupt how the company operates.

“Our data culture is a combination of data technology, work processes, and reward systems,” says Peri. “If we have only one or two of those things, we’re not going to deliver the outcomes we want. We have partnered closely with our line business leadership and our function leadership to really transform in a way that constructively disrupts how we operate.”

A foundation for the future

Looking ahead, P&G will connect more data types and find new ways to delight its customers—and the consumers who fill their homes with P&G products. And it will continue to strengthen its data culture, operationalizing algorithms into key decision processes across the company. Procter & Gamble may be 183 years old, but its future has never been brighter. ...

Very few vendors can serve our needs at scale, given how much data we’re processing. Azure Synapse Analytics can, and Microsoft’s vision on how to scale is among the best in the industry. 

Guy Peri: Chief Data & Analytics Officer ....

CPG Company Innovation Traps

Some useful thoughts in the space: 

CPG companies can dodge three common innovation traps

Implementing proper checks and balances throughout the innovation process can help you create long-term growth. by Sharon Kao and Nicholas Hilgeman

Today’s consumer packaged goods (CPG) companies confront a strange market paradox: continued demand for new products but reduced shelf space in stores. Organizations have long used innovation as a tool to meet the shifting needs of consumers and to drive growth. In fact, in their 2020 annual reports, all ten of the highest-grossing publicly traded global CPG companies highlighted innovation as a key growth lever.

Product development is a highly capital- and labor-intensive process, and left unchecked, results in a questionable return on investment.

But the space to display this proliferation of new products is shrinking as retailers weigh costs and consumer experience, focusing on smaller storefronts with hyperlocal offerings and a less overwhelming array of choices. At wholesaler BJ’s, for example, smaller, new-build stores house 16% fewer SKUs than regular stores. Similarly, British supermarket chain Asda recently revealed plans to cut SKUs by up to 40% as it shifts to a simpler discount model for its stores. Another reason retailers are reducing shelf space is to avoid being overstocked as consumers do more online shopping. In PwC’s June 2021 Global Consumer Insights Pulse Survey, more than half of global consumers surveyed said they became more digital even in just the six-month period from October 2020 to March 2021.  ... " 

P&G Positions for Inflation

My former and longtime employer writes, on the threat of Inflation Challenges.  With innovation. 

P&G Is Positioned for Inflation Challenges

Procter & Gamble Vice Chairman and COO Jon Moeller tells investors it has winning products and strategies in post-Covid world.

Retail prices soared last month, lifting US inflation rates to a 13-month high, according to the Consumer Price Index. But Procter & Gamble COO Jon Moeller said the company is well-positioned to overcome this latest headwind, just as P&G thrived during the Covid-19 pandemic. Speaking at a Deutsche Bank investor conference, Moeller noted that P&G added 40 points to its global market share last year and e-commerce sales are up 50% year-to-date. He credited gains made pre-Covid, during Covid and now, post-Covid (in the US and China) to having the right strategy, the right portfolio and the right organizational structure.

"Despite near term challenges, we are not changing the strategy, We are doubling down and moving forward," said Moeller. "This has been working in driving maket growth. That is the most important mid- to longer term."

He acknowledged that a global recovery won't occur until 2023 or 2024, when enough vaccines can be made to cover the world's entire population. Virus spikes in India and Brazil will delay the global recovery and yet, P&G's market share remains strong in both countries. 

"Predicting year-on-year growth is difficult," he said, acknowledging that the company's two largest markets, US and China, accounted for nearly all P&G growth in the current fiscal year. "Now we have the headwind of rising material and transportation costs, but we will get through this rough patch."

Product innovations will help. New Tide and Ariel formulations provide more cleaning power at lower temperatures. The Oral-B iO Series electric toothbrush promises 100% healthier gums in one week and six times more plaque removal along the gumline. P&G is rolling out plastic-free Gillette razor packaging in France with plans to expand in the US this fall. In dish care, Dawn Powerwash sales reached $150 million in its first year. In hair care, Pantene is adding premium formulas like 3-Minute Miracle and Quench Intensive Shot Mask.

Retail partners like what they see. Procter & Gamble was ranked the No. 1 supplier in the US for the sixth consecutive year. 

"We are driving constructive disruption by acting with the speed and agility of a startup," Moeller insisted.

We'll have more from Moeller in The 2021 Top 50 article in the July issue of Happi.  ...."

Catching Counterfeits with AI

Worked on counterfeit identification for CPG Products,would have helped to be be to quick scan products and packaging.

Catching the Fakes

By Neil Savage    Communications of the ACM, May 2021, Vol. 64 No. 5, Pages 13-14    10.1145/3453696

Counterfeiting is a big business. Nearly $509 billion of fake and pirated products were sold internationally in 2016. In that year, the latest for which data was available, counterfeit goods made up 3.3% of international trade, up from 2.5% three years earlier, according to the Organization for Economic Cooperation and Development.

That figure, which does not include domestic trade in fakes, not only means companies are losing revenue and consumers are not getting their money's worth; counterfeiting also helps fund organized crime. It exploits low-wage laborers. Because it skirts safety regulations, makers of counterfeits could use toxic materials or produce unsafe products.

Now, companies are turning to artificial intelligence (AI) to help them identify counterfeit products and stanch the flow of faux goods.

Amazon, for instance, launched Project Zero in 2019. Makers of products provide the company with data about their logos, trademarks, and other features, and Amazon's machine learning algorithm scans listings on the company's website and automatically removes those it deems fake.

Other companies have rolled out tools to allow retailers to identify fakes using smartphones with scanning attachments.

"Counterfeit goods are among the leading causes of a lot of bad things," says Lakshminarayanan Subramanian, a professor of computer science at New York University and co-founder and chief scientist at Entrupy, a New York-based company founded in 2012 that uses AI to verify the authenticity of luxury goods.

The company's system works with microscopic images of the goods in question, looking for features that are common to an authentic product but not to a fake. Those features could be in the texture of the material, the stitching, a zipper, or the way a logo has been stamped into an item. The leather of a luxury handbag, for instance, will have what appear to be peaks and valleys when viewed at a microscopic scale.

Entropy trains its AI starting with images of an area of handbags, both authentic and counterfeit, and breaks that image into smaller chunks. It then applies bag-of-words, a technique developed for natural language processing that sorts words by their frequency in a text and uses that to make inferences about the text. In the case of handbags, the "words" are small areas of structural features that might repeat or vary from place to place across the material. The computer creates a histogram showing the frequency of these visual words and how that frequency differs between real and fake goods.  ... " 

Consumer Goods Simulation and Digital Twins

This article points out that simulation can be essential in dealing with the understanding of consumer goods.  Even mentions the idea of  'digital twins' as a model design approach for simulations.  Simulation was originally called 'Monte Carlo' simulation,  because at least some of the activity modeled was driven by chance.  And in fact that is still the case.  Things like human behavior or weather or accidents or activity by people or machines are still driven partially by chance.  You expect a twin to be close, but not exactly the same as another agent.   None of this is new, or even close to new. The very earliest models I did for CG were of that type.  But I accept it as a hint for the new generation.  Contact me if you want more insight.

Making Products Without Really Making Them: The Role of Simulation  in CGT Mag.

CGT Staff

Whether by default or design, the consumer goods industry has innovated its way into a continuous cycle of better, faster, more. With demand in their palms (thanks to the consumer electronics vertical), unlimited choice and expectation of brand intimacy, consumers generate an ultra-competitive business environment for manufacturers.

Warp speed is required to deliver — often to the door in one day — high-quality, smart products in a personalized way at reasonable prices. Globalization adds further complexity to all parts of the supply chain, impacting product lifecycles as well. Only the companies that can most effectively deal with the layers of intricacy will survive.

With so little margin for error — and smaller margins in general — CG companies are looking at new ways to improve their products and processes. To provide the best service levels and experiences, while keeping costs low to accommodate shifts in consumer purchasing patterns, many are turning toward more flexible manufacturing — a combination of manufacturing simulation, execution and automation that results in truly agile operations.  ... ' 

Further Emerging Smart Toothbrush

Showing how package goods, like Colgate and my former employer P&G are building smart devices to improve consumer health processes. 

Smart Device Push Brings IT, R&D Teams Together  By The Wall Street Journal  in ACM

Information Technology (IT) staffers at consumer packaged goods companies increasingly are working with research and development (R&D) teams to develop more connected devices.

To develop Colgate's new smart toothbrush, the R&D team worked on the brush head and sensors, while the IT team developed the underlying application, which uses machine learning to analyze data collected by the toothbrush to make recommendations for brushing better.

Colgate's Mike Crowe said, "It is really about maximizing the use of the combined skills."

The IT and R&D teams at Proctor & Gamble (P&G) also have collaborated on a smart toothbrush, a personalized skin-care analyzer, and a facial-hair style assistant.

McKinsey’s Ed Roth said teaming IT and R&D is not without its challenges. “It’s not a natural pairing,” Roth said, because each unit is staffed by people from a different work culture.

From The Wall Street Journal