Turning consumer and retail companies into software-driven innovators

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Software is disrupting and transforming every industry, and the impact is particularly pronounced in consumer-facing organizations. With the rise of the direct-to-consumer model, revenue increasingly comes from online rather than traditional channels. More than 500 million people interact with the Nike brand across its apps.1 The Starbucks app is the second-most-popular mobile payment platform in the United States for point-of-sale transactions, trailing only Apple.2 As digital experiences carry the weight of revenue, consumer-facing organizations have to make effective digital investments.

While technology has already revolutionized this sector, not least with the advent and mass adoption of e-commerce, the next wave of transformation is imminent. Customers increasingly expect experiences powered by software and on par with those offered or enabled by the most successful software and tech players. Building a shopping app, for instance, no longer suffices; the experience needs to be as engaging and seamless as it would be if app delivery were the organization’s core competency.

Investing wisely in software across the entire value chain, from initial customer interactions to internal corporate functions, can help consumer packaged goods (CPG) and retail companies meet these rising expectations. And that investment can pay off in the long run. With technology increasingly a competitive differentiator, companies that make software a core part of their organization and harness emerging technologies—such as AI (including generative AI), mixed reality, and robotics—can lay a strong foundation for sustainable growth.

Many retail and consumer players recognize this reality and have already made decisive software and technology investments. For example, Starbucks developed Deep Brew, a tool to leverage AI for various applications. Lego partnered with Epic Games to create a metaverse for kids to connect, playing between digital and physical worlds seamlessly. And L’Oréal invested in Digital Village—a virtual world-building platform and nonfungible token (NFT) marketplace—to bet on opportunities within the metaverse and Web3 for virtual store creation.

Our research shows that consumer and retail companies investing heavily in software outperform their peers: digital leaders have created outsize value to shareholders—three times the returns over the past five years, compared with nondigital leaders.3 Our analysis of more than 120 public consumer and retail companies also reveals that those with a mature technology operating model outperform those that operate more traditionally. Markers of strong DevOps and developer tooling, modern engineering practices, best-in-class product development life cycles, and structural and strategic alignment toward products are directly tied to strong business results: organizations with high maturity across these dimensions boast, on average, 2.2 times greater return to shareholders, as well as 40 to 45 percent higher customer engagement and brand awareness, compared with those that have little or no technology operating culture.

In addition, the advent of generative AI, which helps to accelerate, automate, and augment human tasks, can potentially drive the transition of traditional consumer companies into software entities. Consumer and retail organizations are anchored on many functions where generative AI’s impact is projected to be felt most heavily, including marketing, sales, and customer operations. As a result, the annual productivity impact of generative AI on the sector is projected to be $400 billion to $660 billion, among the highest of all industries. This expectation only raises the already-high stakes of staying ahead of the technology curve for consumer and retail players.

But what exactly does it take to keep up and make that level of technology innovation part of a consumer or retail organization’s DNA? According to our research and experience, six principles are critical for consumer and retail organizations to leverage tech effectively and perform more like software companies. Those principles align broadly with cross-sector trends examined in McKinsey’s recent software transformation research.

Build a software- (and customer-) centric culture

For most legacy companies, cultural change is the biggest challenge in digital transformations. Not only should organizations clearly articulate software’s role in their existing culture, but they also need to ensure that the culture drives customer-centric innovation and fosters a “software mindset.”

Not only should organizations articulate software’s role in their culture but also ensure the culture drives customer-centric innovation and fosters a “software mindset.”

Embedding software into organizational culture requires, first and foremost, that companies outline a clear vision for their software business. That means explaining how the value proposition and strategy will impact customer experience, growth, and talent—and communicating this perspective consistently across internal and external forums. According to McKinsey’s 2022 Voice of Consumer Organizations Survey, managers at high-performing consumer companies are 1.6 times more likely to say their digital agenda is integrated into business units rather than siloed in an IT organization.

The right culture is also essential for driving customer-centric innovation. To build such a culture, companies can work to emulate the operating model of leading technology players that use small, cross-functional teams, or pods, to address specific customer needs or journeys. In this model, pods can include employees from software development, agile coaching, data science, product management, technical program management, and user design/research. The teams are typically empowered to own a customer problem space end to end, set their own objectives and key results, and determine their own product road maps and backlogs. They are actively encouraged to base their decisions on customer data, leveraging technologies such as AI and machine learning to predict customers’ needs and deliver value.

That approach dramatically alters the innovation process. The user design/research and product management functions are so deeply embedded in the pods that they help shape the mission statement and the problem’s definition from the get-go, rather than being used only for fine-tuning after overarching development decisions have been made. From our work with retail and CPG companies, we have seen this type of software-centric culture boost customer satisfaction rates by as much as 40 percentage points. Technology-inspired operating models also help push organizations’ performance closer to that of software players on other metrics. For instance, in one major North American retail brand, we saw this shift lead to a 60 percent improvement in time to market, from idea inception to software delivery, for such offerings as new app features.

Companies looking to make more significant changes should consider investing in a developer-centric culture that empowers software engineers to be a greater focus of innovation. To do so, organizations can create a culture of experimentation, learning, and safe failure that encourages developers to make more innovative, risk-taking decisions. This approach is a significant differentiator, as only 20 percent of executives from large enterprises believe their organization has successfully established a culture of safety for developers.4Developer Velocity: How software excellence fuels business performance,” McKinsey, April 20, 2020.

Drive product management consumer expertise

Investing in product management (PM) capabilities is more critical than ever. Product managers help drive tech development by setting the strategy, road map, and feature definitions while serving as a liaison among consumers, business, data/engineering, and design teams. But in a recent survey, 80 percent of more than 300 consumer product managers said that their organizations’ PM functions were subpar or nonexistent.5What separates top product managers from the rest of the pack,” McKinsey, January 20, 2023. For the sector to fulfill its ambition of becoming true software innovators, that reality has to change.

Finding and developing PM talent are both challenging tasks. Technical skills are mere table stakes for a role as complex and multifaceted as product management. CPG and retail industry product managers need to deeply understand ever-changing consumer habits and preferences, as much of their job is to optimize the digital touchpoint and make the transitions among multiple channels seamless for customers.

Such consumer insight is just part of the overarching talent that sets successful product leaders apart—the ability to deliver enhanced customer experiences creatively. Product managers have a vast canvas of modern tools and platforms to help serve customers and consumers in new, innovative ways. This capability is particularly important in the consumer retail environment, where offering product experiences that deliver value as well as establish and exceed high user expectations is a true differentiator.

Companies looking to invest in empowered product managers should consider three actions:

  • Invest in generative AI tools to automate time-consuming tasks, such as compiling notes or updating documentation, and enable more data-driven decision making.6 This action is crucial because day-to-day responsibilities often limit product managers’ time to understand the market, competition, and consumer needs sufficiently.
  • Develop a culture that relies on continuous testing to improve the product and customer experience. Active testing can be especially valuable for allowing product managers to refine ideas about products and features iteratively.
  • Continuously upskill product managers on product acumen, and deepen their understanding of frequently changing consumer preferences.

Upgrade platform architecture and data management

Next-generation technology innovation requires a robust underlying tech architecture; however, most companies struggle with legacy systems and usually have more than 20 percent of tech assets in the “tech debt” category. Moreover, around 60 percent of CIOs have seen tech debt rise in recent years.7Tech debt: Reclaiming tech equity,” McKinsey, October 6, 2020. At the same time, not all tech debt is bad: modernizing applications adds value, but only up to a point. Consumer companies should prioritize what, how, and when to migrate to a new solution.

A strong, platform-based approach8Products and platforms: Is your technology operating model ready?,” McKinsey, February 28, 2020; “The big product and platform shift: Five actions to get the transformation right,” McKinsey, June 9, 2023. enables better access to underlying services and creates opportunities for innovation in tech capabilities. A tech stack where all platforms talk to one another is critical. For example, platforms to automate marketing efforts should be able to pull from customer and product databases to personalize messaging and showcase the most attractive items. Failing to integrate these components into a unified tech stack will hinder the potential for technology-driven business improvement.

While certain companies take the more challenging route of leapfrogging to an entirely new tech stack that merges all existing customer and product data, more consumer-facing organizations are likely to take incremental steps. For instance, new business logic can be built out iteratively as modular microservices—self-contained units of code that execute specific functions with limited dependencies—effectively replace the legacy stack. Prioritizing platform upgrades according to the value at stake is important: drawing on our experience in the consumer space, we estimate that 20 to 50 percent of platforms may drive up to 80 percent of the value.

Companies eager to upgrade their platform architecture can gradually switch to a cloud-based approach. Those organizations can then leverage reliable data services and flexibility to adjust capacity while modernizing financial records and other important legacy systems. For instance, one leading European fashion retailer built an automated, cloud-based sandbox environment that allows fast access to data, along with flexible usage of analytics and isolated AI testing environments. Anheuser-Busch InBev used cloud infrastructure to create digital twins of its breweries—digital models of physical assets that identify operational inefficiencies in real time.9

Companies eager to upgrade their platform architecture can gradually switch to a cloud-based approach.

When upgrading platform architecture, companies can also optimize their systems to power generative AI technologies. In this context, it is critical to choose a suitable model, set up cloud and data architecture, use MLOps to reduce risk and continuously improve the model in production, and run “Live Ops” to monitor model performance and manage risk.

Another way to advance the engineering landscape is to manage data as a product. This approach helps to deliver high-quality, ready-to-use data sets that people across an organization can easily access and apply to various tasks, such as keeping up with changing customer buying patterns and trends. Traditional approaches, such as grassroots (managing data across the organization on a team-by-team basis) and big bang (managing data en masse in a centralized team), are highly complex and inefficient. In contrast, managing data as a product creates sustainable value by increasing reusability, interoperability, and speed of new application implementation. For example, customer and product data managed as two data products can be connected to drive hyperpersonalization; product and store data can be linked for assortment optimization.

Once an organization manages its data this way, it can more effectively unlock value from it. For instance, building innovative, data-centric applications is one promising vehicle for leveraging existing data in more meaningful ways than simply modernizing existing application features. Generative AI and foundation models now open many new opportunities for data-centric applications by automating content generation based on data. These models essentially supersede much more of the value chain than traditional, discriminative AI models that are used to predict labels or classifications. For example, companies can leverage marketing data and generative AI to automatically create and deliver hyperpersonalized messages with virtually no incremental costs.

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Every company is a software company: Six ‘must dos’ to succeed

Act as a link in the tech and manufacturing ecosystems

Given the rapid pace of tech innovation, consumer and retail companies often find it beneficial to tap into the ecosystem of tech-forward start-ups and supplier partnerships. The attraction is mutual because the retail ecosystem, unlike software, offers tangible products and various services along the value chain. More tech-forward companies also want to be part of a retail ecosystem to access consumers, other retailers, and best-in-class technologies for that complex environment. In addition, consumers appreciate the innovation an ecosystem can provide; seven in ten consumers in a McKinsey survey said they value ecosystem offerings that simplify their purchase journey.

Companies can start by partnering with tech-savvy organizations. For example, Walmart partnered with Salesforce to provide other retailers its white-labeled software solution to power local fulfillment and delivery.10 Companies seeking to go one step further can acquire and build their own internal ecosystem—an in-house B2B solution hub that provides access to other players in the market—to accelerate digital transformations and optimize the customer journey.

For retailers, broader software integration with their supply chain also drives innovative customer experiences. One example is digital additive manufacturing—that is, 3-D printing. It requires deep software integration between brands and manufacturers across multiple points of the product development and manufacturing life cycle. Investing in such integration can unlock faster time to market and product customization at scale. For example, premium shoe insole developer Superfeet uses 3-D printing machines at various retail outlets to scan customers’ feet and rapidly build custom orthotics that can be delivered within a week, reducing lead time and costs.11

Embrace creativity in GTM strategy

In an evolving software-driven landscape, many companies are already taking steps to transform their go-to-market (GTM) strategies by using tech to increase the functionality of their core offering and drive higher engagement with customers. Take the retail apparel industry, where fashion houses and mass retailers alike are expanding physical runway shows and stores into the virtual world with interactive experiences, gamified content, and new ways to generate awareness and monetize merchandise. For example, Gucci launched metaverse fashion exhibits that mirror physical ones,12 Gap opened in-game storefronts with digital replicas of merchandise and fashion mini-games13 and has launched virtual dressing rooms, and Tiffany & Co. raised $12.5 million through the instant sellout of its NFT drops in conjunction with new-product launches.14

Some organizations are using tech to add entirely new revenue streams—for instance, by diversifying from B2C to B2B using analytics offerings. Walmart’s Luminate analyzes consumer data to offer suppliers greater insight into competitive positioning. PepsiCo’s Digital Lab platform provides food service businesses with various digital tools and resources to help the companies improve their operations and customer experiences.

Traditional CPG companies have also been able to enter the direct-to-consumer space by leveraging technology to build a closer connection with their consumers. For example, Oreo has let customers customize its sandwich cookies by empowering them to choose different fillings, fudges, and dips while providing personalized ways of packaging the product through the OREOiD experience on its website. In addition, it created “Oreoverse,” a virtual reality (VR) world where fans can interact with the Oreo brand, connect with other consumers, and create shared experiences.

Develop a deep tech talent bench and modern-technology operating model

To help drive innovation, consumer and retail companies should consider pivoting toward a tech-focused talent pool. High-performing businesses have already taken a more active role toward insourcing employees with digital expertise: according to McKinsey’s 2022 Voice of Consumer Organizations Survey, managers at high-performing consumer companies are 1.4 times more likely to report having tech talent largely in-house for critical areas. Still, insourcing levels are relatively low; our research indicates the share of outsourced IT talent is 40 to 50 percent in retail and 50 to 60 percent in CPG. Insourcing tends to be more prevalent for critical skills, such as product management and app architecture, and less for commoditized roles, such as product support.

For near-term access to bleeding-edge capabilities outside the organization, companies can employ “acquihiring,” or strategically acquiring digital-native companies to access their technology offerings and talent pools. For instance, when L’Oréal acquired ModiFace, a VR company that builds technologies for the beauty industry, it successfully integrated the team into its core organization, resulting in a threefold increase in conversion rate and a twofold increase in engagement.15 L’Oréal created personalized customer experiences through this acquisition, such as lipstick on demand—an AI-powered at-home system that recognizes color from a photo and prepares a lipstick based on it.

Another approach is for businesses to establish their own talent ecosystems (for example, launching open-source projects, hosting hackathons, fostering a developer community) or to become part of existing ones created by tech-savvy organizations, thereby harnessing collective knowledge and resources. For example, Döhler, the natural-ingredient company, joined the SAP Business Network for Logistics to access services and talent from more than 22,000 partners.16Every company is a software company: Six ‘must dos’ to succeed,” McKinsey, December 13, 2022.

In the longer term, companies can attract new talent and differentiate themselves from tech-native companies by focusing on purpose-driven hiring. Consumer companies can distinguish themselves from tech-native enterprises by focusing on the relatability of their brands and the ability for talent to see the tangible impact of their innovations in the marketplace. For example, Nike promotes itself as a company looking to hire “the most creative people in the world” who want to “revolutionize the future at the confluence of tech and sport.”

Consumer companies can distinguish themselves from tech-native enterprises by focusing on the ability for talent to see the tangible impact of their innovations.

Companies can also enhance their operating model to help spur innovation and improve employee experiences. One way is to establish a product and platform operating model, which organizes technology around user-facing products to facilitate user journeys or experiences and the underlying platforms that enable them, such as customer relationship management (CRM) and marketing technology (martech). For example, one North American retail organization chose to reorient its project-based operating model as a product- and platform-based structure, which involved establishing clear roles and responsibilities across pod members, empowering teams to operate autonomously, and speeding up processes by reducing the previously required stakeholder alignment. With team members feeling newly empowered and excited to work together across functions, the company saw a 30-percentage-point increase in its talent satisfaction rate.

Beyond hiring top tech talent, companies can invest in the latest technologies that drive productivity. For example, generative-AI-based automation services have already proved to reduce engineering workload and speed up time to market. A March 2023 McKinsey experiment with GitHub Copilot showed that, in teams working on e-commerce platforms, AI tools resulted in overall performance gains of 25 to 50 percent for lower- to medium-complexity tasks. Developing new features was around 50 percent faster, while refactoring authentication was roughly 25 percent faster.


Consumer and retail companies that embark on this software-driven path will likely have to embrace technology as a strategic capability across many dimensions: culture, product management, ecosystems/partnerships, engineering, GTM, and talent.

Most organizations that pull off the transformation begin gradually. For example, one food retailer decided on a “frontrunner” approach, identifying three high-impact areas of one select business unit where it wanted to pioneer changes before rolling them out more broadly in the organization. As a result, the company gained valuable insights to refine its blueprint for operating in the new model. In addition, team members could double as champions for the new model once the changes started to scale across the rest of the business unit and, ultimately, other business units. The approach was so successful that employees from other parts of the organization actively sought to adopt some of the software-centric best practices that the frontrunners had established.

Ultimately, the commitment to overall change will be more profound and even tougher to get right than introducing new tools or platforms. But by making these fundamental shifts, smart, software-centric retail and consumer companies can lead the way in product innovation and customer experience.

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