Analytics and Technology Trends and Predictions for 2023: Toward Resilience

Tech Predictions 2023 (1)
Tech Predictions 2023 3 (1)

Organizations are facing a period of transition and volatility — 2023 will be marked as the year when battle lines are drawn along a technology landscape teeming with promises and pitfalls. Companies will find themselves caught in the push and pull of governments, consumers, and employees rightfully calling for more concrete action toward sustainability. Superapps will find their footing as brands expand and diversify to get closer to consumers, while businesses adopt AI and machine learning to adapt and transform. These realities will test the readiness and openness of businesses to tackle disruptions and remain relevant in the coming year. Lingaro’s experts weigh in on these trending technologies and innovations and where data and analytics figure into the equation.

The postpandemic era is off to a turbulent start. For the past three years, people and organizations around the world experienced remarkable social, economic, and political upheavals that upended traditional norms, habits, and behaviors. Against these paradigm shifts, consumers and employees as well as stakeholders and business leaders and decision-makers will need resilience to weather potential and budding storms.

In 2023, resilience will be the key theme for businesses as they use and adopt new and existing technologies to overcome volatilities in their market and industry. Resilience, however, will be an interconnection of business and technical must-haves. To be resilient, businesses must cultivate trust with their own people, organization, and the consumers and communities they serve while having the confidence and clarity to take on what’ll lie ahead. To have this sense of certainty, strategies must be aligned and efforts concerted toward a long-term, strategic vision as the business explores uncharted territory.

This interconnectedness will shape next year’s business and technology strategies toward resilience — from sustainability initiatives across sourcing, procurement, supply chain operations, and direct-to-consumer (D2C) business models to AI and machine learning.

Tangibly measuring sustainability becomes imperative

In Europe, 58% of adult online consumers strongly prefer buying environmentally friendly products, while new incentives are projected to entice 50% more to join the ranks of socially and environmentally conscious consumers. Meanwhile, governments in the UK and the US will soon mandate private and public companies to disclose the financial impact of climate change on their business. Germany-based organizations are already obliged to, further requiring them to report their efforts to be carbon-neutral and socially responsive. The rest of the EU will soon follow suit.

It’s no surprise that 87% of business leaders expect to increase their organization’s investments in sustainability initiatives. Jacek Warchoł, director of Lingaro Group’s supply chain analytics practice, noted that they’re compelled to do so to alleviate the mounting pressure from consumers, governments, and stakeholders and to address the need to stay afloat and relevant.

“Sustainability is now a critical agenda. We see many manufacturing and consumer-goods companies already implementing some form of sustainability initiative, like reducing their carbon footprint, recycling plastic materials, and reusing water resources,” said Warchoł. Unfortunately, many end up going back to the drawing board because these initiatives fall short of either achieving a sustainability goal or reducing costs. In a recent study of top 500 corporations around the world, only 22% created specific actions or strategies that align with the UN’s Sustainable Development Goals (SDGs), of which only 0.2% developed methods or tools to track their progress.

“For many leaders, sustainability sounds novel and noble, but their efforts and aspirations are often stymied because they don’t know how to start,” Warchoł remarked, adding that 1 in 5 companies don’t have a strategy while 33% lacked a business case for sustainable supply chains. While 76% of chief marketing officers said “green initiatives” are part of their top five priorities, many don’t know where to begin. “Moving toward a sustainable supply chain involves revamping the people, processes, and technology that keep it running while having the means to tangibly measure progress,” Warchoł added.

Warchoł illustrates this intricacy with transport management systems. To report on carbon emissions, for instance, different systems need to be integrated across the company to get full visibility on each material or component used. Then managers need to connect the dots: combining shipments, replacing modes of transport, knowing their impact on emission levels, and checking if they comply with the country’s regulations, to name a few.

“Reporting is only the first step. After all, you can’t reduce, reuse, or recycle what you can’t measure. Reliable and credible data as well as technology are the backbone of sustainability. This is where advanced analytics plays a vital role — it empowers decision-makers with the clarity they need to make concrete and meaningful action and the confidence to meet consumer expectations and mandated responsibilities.”


Achieving sustainability will require third parties

Organizations can amplify the impact of their sustainability initiatives by working more closely with their vendors and their networks of their own suppliers. Given how more than 70% of procurement professionals already work with third parties to use new technologies or other services, the company’s sourcing and procurement function is in an opportune position to unlock and generate more value.

In fact, it’s expected that by 2025, 50% of chief information officers will tie sustainability-related metrics to technology investments, which also include KPIs that assess the environmental, social, and governance (ESG) performance of third-party suppliers. This is part of an overarching trend of using “sustainable technology” to optimize costs, mitigate risks, maximize the use of resources, and create new avenues for growth while adopting responsible business practices.

Igor Vasquez, head of Lingaro Group’s procurement analytics practice, said, “Achieving sustainability across the value chain means collaborating and engaging with partners to adhere to the same goals and standards that the business commits to. This means creating an interconnected ecosystem where diverse and different aspects of the business converge into a cohesive goal — from leadership, procurement, and supply chain to technology.”

Organizations that have done so are now reaping the benefits — 72% of surveyed business leaders reported that they’ve improved their relationships with their suppliers, while 69% noted an increase in sales from their corporate social responsibility (CSR) initiatives.

Vasquez added, “Embedding sustainability in sourcing and procurement not only makes business sense. Companies will also be obliged to as governments include it in their national agenda and tighten the screws on enforcement.” Indeed, 45% of surveyed procurement leaders said meeting legal obligations is the biggest driver of their business’s sustainable sourcing programs. Case in point: Germany’s Supply Chain Act obligates companies with more than 3,000 employees that do business in Germany to monitor their supply chains for risks and violations in human rights and the environment. This includes the company’s direct and indirect suppliers. They must disclose and address them or risk penalties of up to €8 million (US$8.5 million as of December 2022) or 2% of the business’s global turnover. The law will soon include companies with a workforce of at least 1,000.

The key, Vasquez said, is instilling shared trust and ownership in achieving sustainability. “Efforts must be orchestrated with vendors toward sustainable goals. Organizations can do so by sharing data and technologies that will provide third-party vendors and suppliers with key information and insights needed to align themselves with the business’s long-term strategy. Tapping into the potential of AI and the internet of things as well as innovative approaches like spatial allocation of land and water resources can promote innovation that both can coinvest in and benefit from.”


The dawn of superapps will disrupt e-commerce

Interconnectedness doesn’t just apply to sustainability — it’s also expanding the e-commerce playbook of many companies. Mert Burian, senior account director of Lingaro Group’s digital marketing practice, noted the increase of companies diversifying their offerings beyond what they traditionally or originally sell. It’s not just retailers, either. Airlines, for instance, are betting on “superapps” to generate more revenue beyond flying planes. Many are now offering and curating experiences, like making cocktails, shopping for branded products, attending garden exhibitions, delivering food at your doorstep, and even renting bicycles.

“Many brands are trying to elevate the omnichannel experience through superapps. They aren’t exactly new, but changing consumer habits and behaviors spurred by the pandemic opened the online floodgates to a highly competitive direct-to-consumer era. In its wake, it created an economy where engagement, consistency, and convenience are the selling points,” Burian said.

A superapp is an application that provides end users with multiple services. It combines features such as messaging, payment processing, and e-commerce in a single app, becoming a comprehensive, self-contained online platform for commerce and communication.

Alipay and WeChat are examples, widely used in China but have since expanded across the world. WeChat, for instance, combines multiple functionalities in a standalone mobile app — instant and broadcast messaging, social networking, mobile payment, and video gaming, to name a few. Gojek and Grab started out as transportation and ride-hailing apps but have since expanded into food and grocery deliveries, mobile payment, and courier service.

Burian added, “Like direct-to-consumer businesses, the appeal of superapps lies in how they give end users integrated, connected digital experiences in a single package. They ease the friction and hassle of hopping from app to app and simplify transactions. For businesses, they provide new opportunities to use the ecosystem to scale and diversify. Brands can also use the superapp’s data to better understand the products and services that its consumers use so they can personalize cross-promotion offers, uncover better marketing channels, and optimize campaigns.”

The appeal of superapps isn’t lost on Western markets. It’s projected that by 2027, more than 50% of the global population will use multiple superapps daily. In the US, UK, Australia, and Germany, 72% of surveyed consumers expressed interest in integrating multiple digital experiences in a superapp. There are also contenders in other parts of the world: Rappi, which boasts 10 million monthly active users across Latin America, and Starling Bank, which provides a range of financial services for users in Europe. In the US, there’s Venmo and DoorDash. In India, there’s Tata Neu aiming to carve a niche dominated by Amazon and Walmart. Tech giants might soon follow — Amazon Prime’s expansion, Uber Money and Uber’s partnership with France-based CityScoot, and Meta’s Facebook Shops that enables conversational/social commerce.

The promises of superapps also have caveats, Burian cautioned. Brands must find ways to simplify the consumer journey, from discovery and purchase to fulfillment. They need to design people-centric offerings to attract and retain users. They need to develop business and data-sharing models that mutually benefit the company and its partners. They need to invest resources in app development and make it easy to build, test, and integrate miniapps. They must define and implement data security, protection, and governance standards.

“Superapps can cultivate closer and more seamless relationships with consumers like how direct-to-consumer platforms do, but brands need to consider their value to the business and their consumers. Will a superapp align with the business’s broader digital strategy? Do you have the technical and organizational capacity to build one? Do you have the capabilities in analytics for managing data? Maybe you don’t need to develop your own superapp and instead join ecosystems that already exist. These are just the tip of the iceberg, and businesses need to take a hard look if they can move quickly enough to overcome these hurdles,” Burian said.


Adaptive AI and MLOps bring businesses up to speed

Adaptation, flexibility, and personalization have also become catchwords in the technology space, particularly in AI and machine learning (ML). Many organizations have graduated from adoption and operationalization and are now looking into harnessing AI and ML to innovate more quickly, respond more proactively, and act more meaningfully. This need for resilience is epitomized by adaptive AI. It brings together methods and techniques that enable AI- and ML-based systems or solutions to adjust learning and behavior to adapt to real-world — and sometimes near-real-time — situations. It’s projected that by 2026, organizations that adopt AI engineering to develop and manage adaptive AI systems will outperform their peers in operationalizing AI models by at least 25%.

George Polzer, Lingaro Group’s head of practice for machine learning, remarked, “At Lingaro, we’ve seen the importance for our clients to have observable data in its context as ground truth to base their business decisions on. Likewise, we’ve seen the need to go beyond merely operationalizing AI models and engineer smart AI infrastructures. This adopts a holistic approach that builds on agile, multimodal data-AI pipelines that future-proof and automate decision-making.”

Jan Strzelecki, Lingaro’s technology product manager, added, “The future of AI needs to be robust and interactive for human usage. With smart AI engineering, AI solutions become more responsive to end-user feedback. This makes it easier for business users to interact with data through content that’s personalized to augment each user. AI solutions enabled with adaptive AI give business users real, tangible opportunities to analyze and respond to changing environments.”

Strzelecki also shared how clients wanted ways to apply observable data into business decision-making and scale it across the organization. “They’d ask how to synchronize, orchestrate, and apply internal and external data to make faster and more accurate decisions. We build the solutions to capture and interpret business, commercial, and economic events while delivering actionable business recommendations by tying captured and modeled observations directly to commercial decisions. By mapping metadata or raw observable data into commercial activities, they can derive more business capabilities.”

Indeed, AI and ML already permeate almost every corner of the enterprise. By 2026, for instance, 75% of enterprises will rely on AI-powered processes to improve asset efficiency, supply chain operations, and product quality. By 2025, 50% of organizations will implement strategies to achieve intelligent business execution — the convergence and integration of multiple smart, AI-enabled technologies and devices to accelerate and maximize the benefits of automation. Advanced computer vision — which deals with interpreting and understanding images and videos — is poised to disrupt the retail sector. With all these unique, value-driven opportunities, organizations now need to be more strategic in their adoption of AI and differentiate themselves through more practical and advanced tools and practices.

Organizations can capitalize on MLOps (portmanteau of machine learning and operations) to efficiently deploy and scale AI projects. In fact, enterprises that reported reaping the biggest fruits of their AI projects already adopt MLOps, including Lingaro. Norbert Fijałek, Lingaro’s technology product manager, explained, “We also implement AI through Lingaro’s MLOps as a service for Microsoft Azure Machine Learning. The principle behind it is to create scalable assets based on best practices, which, in turn, become accelerators for AI projects such as those in Azure ML. It eschews the often-lengthy processes of training a model and implementing it in production through automation. This can significantly streamline the process from days to minutes.”

Fijałek furthered that the approach helped the practice adapt and scale AI projects more easily, regardless of their size or expected outcome. The optimization and ease of implementation in production can be repeated for new models, including custom and foundation models like those from OpenAI.


Analytics paves the way to resilience

While data remains the lifeblood of businesses, resilience paves the way to keep that data moving. In a time of volatilities, resilience has become critical as employees, business leaders and decision-makers, and consumers ubiquitously look for technologies that cultivate trust, provide clarity, and create opportunities needed to navigate uncertainties.

Digital transformation is indeed in full swing. Technology and innovation cycles have become shorter, enabling businesses to adopt them quickly but also risk creating and increasing unneeded complexity. As the past three years showed, technology alone is not enough — an organization’s success is tied to how it can effectively manage risks and complexities to move the business forward while recognizing its impact on its people and the wider communities.

Coping with today’s unknowns requires flexibility and creativity. Different ways of doing business will be tested. Innovations will come and go, and new business models will upend one after another. Organizations need to look at their data and use analytics to stay ahead of change, conquer priorities, and prepare their people to deliver on a shared vision and create an impact.

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