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1、1Guide to Next.2024CONSUMER PRODUCTS ISSUE 32Guide to Next.How Consumer Products companies can create the most impact in the coming yearon their business and their shoppers.20243Guide to Next.041221Making Net Zero Goals ProfitableModernizing for AgilityPreparing for Artificial IntelligenceTABLE OF C

2、ONTENTS4Guide to Next.5Guide to Next.Making Net Zero Goals ProfitableCAN CPGS ACHIEVE PROFITABLE SUSTAINABILITY?Increasing global inflation has exposed the fragility of what Stephen Picard,vice president of strategy consulting at Publicis Sapient,deems“green pet projects”that is,sustainability or em

3、issions goals that do not create market value.How can consumer products(CP)companies,from electronics to consumer-packaged goods(CPG)to luxury,determine the difference between a green pet project and a sustainable company transformation that provides long-term value?6Guide to Next.As soon as compani

4、es engage in sustainable actions beyond compliance,which very few have done,their long-term value increases due to a perceived ability to mitigate reputational risk and bolster customer and employee loyalty.“”STEPHEN PICARD,VICE PRESIDENT OF STRATEGY CONSULTING AT PUBLICIS SAPIENTThere are three pil

5、lars of sustainable transformation:consumer behavior,data and action.When combined,these pillars will make sustainable efforts truly profitable.7Guide to Next.Engaging consumers in sustainabilityWhile consumer discourse around sustainability strengthened in 2023,consumer behavior has been slower to

6、change than many CP firms imagined.A Publicis Sapient survey found that 77 percent of U.S.adults say they would avoid retailers that arent sustainable,but only 54 percent also say they purchase products even if they know they arent sustainable.It seems that although most consumers care about sustain

7、ability,it doesnt always influence their purchasing behavior.This is often because of rising costs of living limiting sustainable purchasing power.8Guide to Next.According to Emmanuel Krantz,senior director of CX and innovation at Publicis Sapient,the cost-of-living crisis has continued to accelerat

8、e polarization between consumers and societies that act on sustainability and those that dont.During economic downturn,higher-income consumers are still able to purchase more expensive and more sustainable products,while lower-and median-income consumers fall back to looking for the lowest prices.At

9、 the same time,even if many consumers are prepared to pay more for sustainable products,a lack of accessible recycling and product disposal options can get in the way of a products intended impact.For example,around 25 percent of recycling from“single-stream”recycling programs(found in the majority

10、of U.S.neighborhoods)is contaminated,and goes straight to the landfill.On top of that,research suggests that U.S.consumers only recycle about half of their household recyclables.This means CP firms need to think beyond consumer behavior to achieve net-zero goals.Initially,many CP companies turned th

11、e responsibility of sustainability onto consumers,asking them to pay more for sustainable products,or go out of their way to reuse or recycle goods and packaging.As the economy has worsened,we see a growing sentiment among consumers that this responsibility should in fact sit more with big companies

12、as it is often their large-scale business practices that are doing the most harmand that many of their consumer-facing efforts to address sustainability are superficial.“”EMMANUEL KRANTZ,SENIOR DIRECTOR OF CUSTOMER EXPERIENCE AND INNOVATION AT PUBLICIS SAPIENT9Guide to Next.Using emissions data for

13、sustainability As looming regulations come to the forefront,sustainable consumer behavior needs to be combined with robust emissions data,which will also help to drive profitable corporate action.Companies operating or incorporated in the EU will have to begin to measure scope 3 emissions in the 202

14、4 financial year,to begin reporting in 2025,according to the EUs Corporate Sustainability Reporting Directive(CSRD).This is because scope 3 emissions account for the majority of overall emissions in most industries,and more than 90 percent of overall emissions for the capital goods sector,specifical

15、ly.While reporting mandates in other regions like the U.S.havent been confirmed,CP firms that invest in the technology required to collect this data will not only be prepared for future regulations closer to 2030 but will also be able to use the data to strategically identify areas of opportunity th

16、at will lead to maximum emissions reductions.Only 44 percent of companies in manufacturing and apparel industries report scope 3 emissions,according to research from 2021.In order to respond to this growing need for scope 3 emissions data,CP firms need to take a new approach:Invest in cloud-based,ER

17、P emissions data management to store and analyze scope 1,2 and 3 emissions and operations data in real time on a single platform Identify the top contributors to GHG emissions from suppliers,transportation and manufacturing,and identify where emissions reductions can also reduce costs10Guide to Next

18、.Creating sustainability partnerships Deciding which sustainability project to implement to actually move the needle toward net zero(and long-term profitability)is still a major obstacle for CP companies due to lack of internal knowledge and resources.In 2024,long-term collaboration across technolog

19、y providers and sustainability experts will be essential,because most CP firms dont have the internal expertise required to create impact.Technology providers can help marry ERP operations data and real-time carbon emissions to optimize the product lifecycle Sustainability experts can analyze the co

20、mplexities of environmental impact while offering out-of-the-box solutions like green manufacturing processes.The challenge is there,but finding a unique competitive differentiator can help organizations set new industry standards Environmental,social and governance(ESG)consulting can help test the

21、viability of a completely new business model and scale it profitablyWithout partnerships,true sustainable transformation,involving data,consumer behavior,and action isnt possible.“”ODED LAVIE,VICE PRESIDENT OF INNOVATION,CREATIVE TECHNOLOGY AND BUSINESS DEVELOPMENT AT PUBLICIS GROUPE11Guide to Next.

22、To drive sustainable transformation through emissions data,consumer behavior and corporate action,contact Publicis Sapient.2024 sustainability trends by sector Finally,CP firms should think about the maturity of their sector when it comes to 2024 investments.These are the top sustainability recommen

23、dations from our industry experts,based on consumer trends,proprietary research and sector expertise:CONSUMER ELECTRONICS AND WHITE GOODS INDUSTRY SUSTAINABILITY E-waste management:Many consumers dont properly recycle or dispose of e-waste,but retail partnerships for reuse and secondhand purchases c

24、an make a circular economy more accessible for consumers Carbon-neutral shipping:Maritime shipping contributes to 3 percent of worldwide GHG emissionsmore than flying.As the airline industry latches on to sustainable airline fuel,electronics companies need to measure their shipping emissions to make

25、 progress toward net-zero goalsBEAUTY AND PERSONAL CARE INDUSTRY SUSTAINABILITY Clean beauty:As consumers embrace the trends of“de-influencing”and“minimalism,”consumer engagement,healthcare and subscription models can increase customer lifetime value without incentivizing consumerism Personalization

26、:Consumers will pay more for personalized beauty products that address all of their needs at the same time,combined with sustainable ingredients as an added bonusFOOD AND BEVERAGE INDUSTRY SUSTAINABILITY Industry partnerships:Sector partnerships,like the sustainability partnership between AB InBev,C

27、olgate-Palmolive,Coca-Cola and Unilever,will drive industry-wide standards and learning while also reducing costs Product lifecycle management:To systematically reduce scope 1 and 2 emissions,engage in product lifecycle management,partnering with experts on solutions to reduce waste,rather than silo

28、ed sustainability projects that dont drive long-term value12Guide to Next.13Guide to Next.Modernizing for AgilityWHY OPERATING MODEL TRANSFORMATION SHOULD BE THE#1 PRIORITY FOR CPGSConsumer products(CP)is arguably the industry facing the most disruption and behavioral changes caused by widespread ad

29、option of generative artificial intelligence(AI).From the potential to remove the retailer as the middleman,scale content and marketing personalization and connect with younger customers,CP firms have a lot to gain from innovation.What will separate the technology leaders from the technology laggard

30、s in the consumer products industry?It comes down to whether or not companies are centralizing their digital capabilities and strategies through a digital operating model.14Guide to Next.For years,CP companies have used a business operating model centralized around their products,siloed by region an

31、d even by departments within regions.As technology like generative AI becomes more and more powerful,the importance of operational agility cant be ignored.But after a year of economic headwinds,how can CP firms make the transition from a product-based operating model to a digital operating model eff

32、iciently and cost-effectively?It comes down to an iterative,step-by-step approach.Without a consolidated digital operating model,employees have to work with fragmentedartificial intelligence models across different brands,and will create less intelligent generative AI tools because knowledge and res

33、ources arent connected.For brands that end up in thisscenario,its then 3x more expensive to fix things.“”DANIEL LIEBERMANN,MANAGING DIRECTOR AT PUBLICIS SAPIENT15Guide to Next.Why 2024 is the year to transition to a digital operating model In 2024,experts predict reducing inflation across regions,pa

34、ssing on potential cost savings across the supply chain to CP firms and,with the advent of AI-based technologies increasing in public usage,consumer firms need to stay ahead of the game.Reducing costs due to inflationAfter a year of sustained inflation,many CP brands are facing smaller-than-expected

35、 margins,and they have to make tough decisions on what to invest in and where they can cut costs.At first glance,the costs of building out a new digital-first operating model(centralizing and consolidating digital capabilities)are daunting for many firms.But in the long term,having a central artific

36、ial intelligence and data hub can save CP brands money and time across brands,especially when utilizing first-party(1P)data for new large language models(LLMs)and algorithms.16Guide to Next.2024 is the year where being digital-first is fundamental.Theres no choice but to invest in generative AI,whic

37、h requires a lot of agility,and means theres also no choice but to transition to a digital operating model.“”SABRINA MCPHERSON,SENIOR MANAGING DIRECTOR AT PUBLICIS SAPIENTDIGITAL OPERATING MODELS IN PRACTICE:CENTRALIZED CONSUMER INSIGHTSA global consumer electronics company wants to create a consume

38、r insights hub,where employees can analyze consumer data to personalize marketing for the Gen Z segment.Smaller regions dont have the budget to invest in analytics talent,technology and training resources and because theyre organizationally siloed from larger regions,they cant scale data insights.If

39、 business units from different brands and regions can all access data from the same centralized structure,smaller regions can still access and utilize centralized consumer insights and apply them to their own decision-making to decrease time-to-market.Rapidly taking advantage of new technologyGiven

40、the complex organizational matrix between regions and brands within global CP firms,the operating model is often the key linchpin to success with new technology.DIGITAL OPERATING MODELS IN PRACTICE:GENERATIVE AI INCUBATORA global spirits company wants to create a conversational AI-powered chatbot fo

41、r retailers to answer shipping and delivery questions for several brands in the U.S.market,but some brands have fully siloed sales processes,from manual to self-service as well as in-person.Some brands dont have the technical capabilities to pilot a chatbot,and any efficiencies from generative AI co

42、uldnt be scaled or transferred across brands in the future.If digital capabilities were centralized at a company level,new projects and learnings from generative AI could be efficiently scaled across the company and progressively honed over time.Three opportunities for conversational AI in the CPG i

43、ndustry17Guide to Next.The three stages of AI operating model transformationGENERALLY,MOST CP FIRMS START WITH A DECENTRALIZED OPERATING MODEL THAT IS NOT TRULY“DIGITAL-FIRST.”STEP BY STEP,FIRMS CAN BEGIN TO CONSOLIDATE THEIR DIGITAL CAPABILITIES,LIKE AI,FROM BEING DECENTRALIZED TO A DIGITAL CORE.HE

44、RES HOW EACH OF THESE DIGITAL OPERATING MODELS WORKS IN CONJUNCTION WITH AI CAPABILITIES:In this model,each business unit manages AI technology,strategy and delivery independently,with very little exchange.This model isnt scalable,and it often comes with a lot of cross-region duplication.Usually,AI

45、solutions are purpose-built for specific needs or groups,and theres minimal digital resource allocation.A DECENTRALIZED DIGITAL OPERATING MODEL18Guide to Next.This operating model(the DCoE)creates expertise and consistency around AI across business units and provides a single source of AI metrics an

46、d data.However,the AI strategy and execution are still left up to siloed brands and regionsand the AI centers success still relies on the separate business units budgets.The digital core operating model gives a centralized hub full control of all AI investments and budgets,as well as digital experie

47、nce and OKRs.While regions would still have a limited ability to execute AI strategy,theyd use solutions and resources from a global AI team.When CP companies adopt this top-down mentality to drive acceptance across the organization,it makes it easier for each business unit to adapt to AI changes be

48、cause they dont need to reinvent the wheel with new AI projects and can start from a central repository.A DIGITAL CENTER OF EXCELLENCE(DCOE)OPERATING MODELA DIGITAL CORE OPERATING MODEL19Guide to Next.How can consumer products firms prepare for an AI-optimized operating model?While the goal of trans

49、itioning to a digital-first operating model is to create more speed and agility to adapt to new technology like AI,successfully transitioning digital capabilities the center of a company takes longer than expected.TAKING A STEP-BY-STEP APPROACHUsing a pilot operating model,CP firms can isolate one o

50、r two strategic priorities,like generative AI,to test with a new operating model while they still have the rest of the business operating as usual.This allows the business to work out the kinks and gathers feedback to iterate on and does it in a seamless way that doesnt fully disrupt the rest of the

51、 business.FOCUSING ON ACCOUNTABILITY AND ORGANIZATIONAL CULTUREThe other piece to enabling digital operating model success is change management.CP firms can stand up a solid DCoE or hub,but if business units arent motivated to utilize that center of excellence through AI projects and AI budgets,they

52、re not going to be able to advance quickly enough.Many companies realize only after investing in new technology that its more about the people and process components and not about the data,the tool or the luminary behind it.“Its been decades since weve seen a technology as powerful as generative AI.

53、Were already seeing that the companies ready to receive this technology,and that are converting it into profits,are the ones with digital-first operating models.If theres ever been a perfect time to invest in this,it is right now.”DANIEL LIEBERMANN,MANAGING DIRECTOR AT PUBLICIS SAPIENT20Guide to Nex

54、t.2024 operating model takeaways,by sector And with many nuances dependent on the product types CP firms cover,Publicis Sapient experts have broken down the key next steps for each of the biggest sectors:CONSUMER ELECTRONICS AND WHITE GOODS INDUSTRY OPERATING MODEL B2B customer engagement:As B2B sal

55、es go digital,generative AI capabilities can power customer service interactions,from emails to chatbots to product information.A centralized digital operating model ensures that processes and advancements can scale across brands and regions,and avoids duplication of effortsBEAUTY AND PERSONAL CARE

56、INDUSTRY SUSTAINABILITY Move quickly through test-and-learn:Because beauty and personal care brands have more direct-to-consumer interaction with consumers,generative AI has the opportunity to make more of an impact through personalized marketing messaging faster than other sectors that only engage

57、through retailers.Your digital operating model needs to support centralized AI capabilities that can surface insights and engage with consumers across brands Tap into consumer insights:Generative AI can quickly surface upcoming trends from consumer channels,like TikTok or YouTube,to inform new produ

58、cts and predict customer needs.A centralized AI-powered insights function can disseminate trends and predictions across brands and regionsFOOD AND BEVERAGE INDUSTRY SUSTAINABILITY Accurately forecast demand:Generative AI can produce synthetic data to predict demand from retailers and consumers,but t

59、his requires centralized analytical and artificial intelligence capabilitiesTo transition to a digital operating model fit for the future,contact Publicis Sapient.21Guide to Next.22Guide to Next.Innovating to Stay Ahead Gen AIWILL GENERATIVE AI FINALLY SOLVE THE CUSTOMER DATA GAP IN CONSUMER PRODUCT

60、S?Artificial intelligence,or AI,has been available to consumer products(CP)brands for years,but in 2024 its rapidly evolving its ability to perform tasks due to the advancing area of generative AI.AI can now sit on new large language models,which can ingest“big data,”or vast quantities of complex an

61、d unstructured data sets that have previously been very difficult for CP companies to tap for insights.For an industry thats previously been reliant on retailers for customer data,large language models present an incredible opportunity to understand consumers much more quickly and efficiently,and re

62、spond to those insights.Generative AI enables brands to outsmart their competition via scalable personalization and trend forecasting.As a result,companies can now surface emerging trends,predict demand and react much faster than ever before.“”RUBA FARAH,CONSUMER PRODUCTS DATA STRATEGY LEAD AT PUBLI

63、CIS SAPIENT23Guide to Next.What are the best sources of consumer data?Consumer data comes in many forms and from many different sources.There are also a wide variety of data types that arent about consumers,but that give CP brands insight into consumer behavior.Big data sets that could be useful to

64、CP companies in understanding consumer behavior across sectors include:E-commerce product reviews Social media posts and comments Weather data Retail transactions Social media brand/consumer engagement Member acquisition touchpoints Third-party consumer research Property and real estate transactions

65、CONSUMER GOODS DATA STRATEGY:THE BASICSConsumer data strategy,generally,refers to the acquisition,management and use of data.This means establishing a process to capture,organize and analyze data across multiple sources to inform decision-making across the entire organization.In 2024,brands should b

66、e using this data to analyze and reveal patterns,trends and associations about consumers and business strategy.For example,many CP firms stand up direct-to-consumer(DTC)selling channels as part of a larger consumer data strategy,in an effort to get more first-party data.For example,a furniture manuf

67、acturer could anticipate demand in zip codes with hot real estate markets using real estate transaction data.A makeup brand could anticipate new trends through an influx of customer product reviews on Amazon.The possibilities are endless,and now with generative AI,theyre a lot more accessible.24Guid

68、e to Next.Why is consumer data strategy important for consumer products brands?Consumer data has always been an underutilized resource for CP firms,because of how difficult it is to scrape for practical insights at pace and at scale.Thus far,many CP firms have a fractured consumer data strategy,due

69、to a lack of first-party consumer data.Very few CP firms currently utilize large consumer data sets to inform business decisionsmost advanced analytics use cases,like predictive analytics,for example,use smaller,structured data sets that dont cross business functions.But if CP firms did have data se

70、ts as large as the entirety of Instagram or Google search results as their playground,they could drastically increase their profits.USE CASE:BEAUTY BRANDS ON TIKTOKAccording to Google,40 percent of young people conduct internet searches on Instagram and TikTokusing influencer videos to decide what b

71、eauty products to buy.TikTok data,like comments and videos,is unstructured and difficult to analyze.But using a large language model,artificial intelligence can easily predict trends,preferences and patterns from this large and unstructured data set,telling a brand which influencer to work with,what

72、 their ads should look like and which products are about to go viral.25Guide to Next.How does generative AI change consumer data strategy?In order to extract insights automatically and at scale from big data,CP firms need to invest in artificial intelligence,and specifically,large language models ac

73、ross key data sets.Right now,some CP firms democratize consumer data,customer data,supply chain data and more in a centralized,cross-functional“hub.”But these data hubs are often only usable by internal analytics experts that surface insights manually and on a lag,to the point where its not able to

74、keep up with the pace of consumer demand.There are two new main use cases for CPG companies when it comes to big data,with the advancement of LLMs:demand forecasting and trend forecasting.Traditionally,demand forecasting models rely on historical data,are prone to manual errors and have such a high

75、margin of error that they can be difficult to trust.At the same time,consumer trend forecasts are so far behind the pace of social media that manufacturing cant keep up.If CP companies can layer an LLM onto their demand and trend forecasting,theyll be able to predict at a higher level of accuracy,le

76、ading to less waste,higher revenue and more consumer engagement.When businesses talk about generative AI,its often discussed or portrayed as a simple undertaking,another implementation project.However,for a medium-sized CPG company,the reality is quite different.Implementing generative AI demands a

77、strategic investment in data management and a well-thought-out strategy from the outset.This early commitment sets the foundation for smoother and faster data utilization,creating the efficiency and agility needed.“”RUBA FARAH,CONSUMER PRODUCTS DATA STRATEGY LEAD AT PUBLICIS SAPIENT26Guide to Next.E

78、stablish clean and usable dataDedicate resources to data managementStart small with test-and-learnWhile LLMs can analyze unstructured data,artificial intelligence will derive far less meaning from unlabeled numbers in locked spreadsheets than from organized data in a cloud-based data lake.CP firms s

79、hould remember the motto:“Garbage in,garbage out.”CP firms should begin by taking inventory of different data sources,cleansing the existing data and finding interoperability between those sources.Without passionate and expert stakeholders,valuable data will sit and collect dust.CP firms should dedi

80、cate resources to internal data experts to drive a modern,innovative consumer insights and overall data strategy thats company-wide.This data core will become more and more valuable as generative AI gains the ability to create content and make predictions,as CP firms will need strict safeguards in p

81、lace to prevent misinformation and bias.2024 is the year for CP firms to overcome obstacles and find competitive advantages through big data thats already out there.Tackling a specific problem or use case,like the continued impact of inflation on holiday shopping or the opinions of consumers on new

82、packaging,can quickly prove out the best value for LLMs within an organization,and help shape the future trajectory of big datas impact.Three ways to unlock the value of big data for consumer products companies In 2024,most CP brands wont yet be able to unlock the full value of big data for demand a

83、nd trend forecasting,but that doesnt mean its not time to invest.In fact,the opposite is true.The more data an LLM has,the more useful it is,which means the faster the better for data-driven CP firms.These are the top priorities for CP firms looking to utilize generative AI as a part of their overal

84、l data strategy in 2024:27Guide to Next.2024 big data priorities,by sector And with many nuances dependent on the product types CPG firms cover,Publicis Sapient experts have broken down the key use cases for big data in each of the biggest sectors:ELECTRONICS AND WHITE GOODS INDUSTRY IoT interactivi

85、ty:Generative AI has the power to connect data across personal electronic devices to form better responses,recommendations and insights.Generative AI combined with natural language processing(NLP)will improve engagement across electronics products.BEAUTY AND PERSONAL CARE INDUSTRY Personalized Rx:Co

86、nsumers want tailored and personalized beauty and personal care products and regimens,which are currently impossible for large CP brands to offer.Generative AI can synthesize recommendations from large data sets to create a better recommendation model for consumers.FOOD AND BEVERAGE INDUSTRY Decreas

87、e waste,increase sustainability:If CP firms can increase the accuracy of demand forecasts,they can decrease retailer waste.Using retailer data and inflation forecasts,generative AI can inform a more accurate and efficient prediction algorithm.To unlock the value of consumer data with more revenue an

88、d more precision in 2024,contact Publicis Sapient.ELIZABETH PAPASAKELARIOU Consumer Products Lead,North America HELEN MERRIOTTConsumer Products Lead,EMEA/APAC Next starts now.Contact one of our industry experts to assess how your unique business can apply these insights to realize high-value outcome

89、s.Or learn more about the proven offerings that help consumer products businesses transform at Sapient is a digital business transformation partner helping retailers like Carrefour,Pandora and Falabella get digitally enabled,both in the way they work and the way they serve their customers.As digital pioneers with 20,000 people and 50+offices around the globe,our experience in technology,data sciences,consulting and customer obsession enables us to evolve our clients businesses with products and services that put shoppers first.2023 Publicis Sapient Corporation