After two years of unprecedented turbulence, supply chains are in the middle of a unique change process. More important than ever and with lots of digital capabilities at hand, the supply chain function needs to effectively link people and technology to help protect and grow the business in a new era. In this blog article, you will learn more about the supply chain trends 2022+.

For many of us, the end of the year is the perfect time to step back and reflect, and it seems that this year, we need to take an especially deep breath. The 2020-ies have started with times of unprecedented turbulence and change on a global scale. But are we looking at a one-off event, or a broader trend towards a more chaotic environment? Have we stepped into the BANI-world, the brittle, anxious, non-linear, and incomprehensible environment, as Jamais Cascio coined in his article “Facing the Age of Chaos” in April 2020?

In hindsight, already in the years before COVID, we were experiencing a scenario of accelerating disruptions and intensifying crises. Be it the climate crisis, more and more frequent natural disasters, growing social inequalities, international tensions, or trade wars, the pressure points and cracks in the highly complex global supply chains were becoming more and more evident. With COVID-19 entering the world stage however, we started experiencing a new magnitude of disruptions: the pandemic with its lockdowns, demand and supply shocks, and increasing shortages is now followed by a cascade of structural adjustments like the trend to nearshoring and redundancy and the sustainability transformation of industrial value chains.

New Now in Supply Chain Trends 2022
Fig 1: Shifting environments for supply chains

Five elements of next-generation supply chain planning and orchestration

The new environment described above radically changes the playing field for global supply chains, which are faced with highest uncertainty and increasingly non-linear disruptions running like tsunami waves across the global economy. As an immediate consequence, supply chain management is becoming a more and more critical prerequisite for company success and will stay on top of the executive agendas also in 2022. But the traditional, often still manual, and deterministic approaches of supply chain planning and orchestration are not fit for the New Now, so supply chain leaders need to adapt their approach and grow some fundamentally new skills and muscles to survive. The five elements of next-generation supply chain planning and orchestration will shape supply chains in the years ahead, and increasingly separate leaders and followers.

Supply Chain Trends 2022 and beyond
Fig. 2: From dynamic risk management to upskilling people: five elements for next-level supply chains

1. Dynamic risk management

Black swan events and major disruptions are here to stay, and their frequency, disruptive energy, and non-linearity will further increase. Consequently, supply chain leaders will also need to increase the firepower of their risk management processes, and move to a more dynamic, data-driven way of supply chain risk management.

Over the last two decades, supply chain risk management has come a long way: from simple descriptive models to create visibility on end-to-end networks including external parties to deterministic modelling of the optimal supply chain set up, like for example in multi-echelon inventory optimization. Then, companies increasingly focused on better grasping the impact of uncertainty. Scenario planning was born with the goal of testing the impact of different events on supply chain performance. However, the still deterministic and mostly single-point approach of scenario modelling is no longer sufficient for today’s hyper-turbulent environment.

Supply chain leaders will move to a new supply chain risk management paradigm, which we call dynamic risk management. To optimally use scarce risk mitigation resources (e.g., additional capacities or inventories), they will move to

  • a multi-point optimization approach, which considers the impact of network interdependencies and second-order ripple-effects on supply chain risk,
  • automated experiments replacing manual scenario-planning, like running thousands of waves of disruption profiles through a digital network twin,
  • stochastic decision making and modelling, and
  • continuous risk sensing permanently adjusted to new external and internal data.

The age of hyper-turbulence is here and raising the firepower of supply chain risk management is nothing less than a license to operate for supply chain leaders.

2. From control tower to data mesh

Managing uncertainty and stochastic modelling or risk sensing need a lot of data, for example, data-streaming from physical systems (like production resources and transport vehicles), or external data like COVID-19 infections. But here it becomes more and more apparent that today’s data infrastructures constitute a serious constraint: disconnected data silos, access restrictions, and incompatible formats often restrict comprehensive data use and lead to high redundancy and storage cost. And even worse, they hold back companies from boldly piloting and scaling digital use cases and data-driven decision making.

To unlock the full potential of their data, supply chain leaders are zooming in on new data strategies and moving towards revolutionizing their data governance approach following the data mesh concept (more here) which was brought up by Zhamak Dehghani in 2019. This concept will particularly gain traction in the supply chain domain, as companies need to move away from the limitations of monolithic data lakes and towards more scalable distributed models to build a robust foundation for creating value from end-to-end network analytics.

Following a data mesh approach, supply chain leaders will fundamentally change the way they integrate data science in their processes and organizations by following new principles:

  • moving to a decentralized, domain-oriented data ownership as the key enabler to scale use cases faster, with data scientists and engineers fully embedded in business teams.
  • treating data as a product with optimal customer experience, creating the best environment for scarce digital talents in discovering, accessing, and using data for the benefit of the business.

While the value of data is abundantly clear, supply chain leaders are focusing on scaling digital innovations faster, whilst creating a state-of-the-art environment for digital talents.

3. Concurrent planning

The challenge of siloed decision making between functions and value chain partners is as old as the supply chain discipline itself. While approaches like S&OP and integrated business planning as well as new role concepts (e.g., end-to-end planners overseeing an entire value stream) have contributed to integrating organizational silos, another “silo” remained harder to address: non-integrated plans between different value chain steps and horizons remain a core weak point in many supply chains to date, leading to operational issues (low schedule adherence, firefighting) and excessive buffering in capacities or inventories.

But the uncertain and non-linear environment of the New Now does not forgive slow and siloed planning and execution. To the contrary, it demands precise, quick, total profit-optimal decision making from an end-to-end network perspective. Consequently, using concurrent planning approaches based on next-generation planning technology will be a critical differentiator for supply chain leaders. Available technology, digital twin network models, fast simulation capability based on hyperscaler clouds or tight integration in core transaction and planning systems, allows companies to

  • horizontally integrate decisions along the value chain, ranging from optimal end-to-end parametrization of replenishment to total cost-optimal resolution of supply shortages or bottlenecks, and
  • vertically integrate supply chain decisions, allowing to seamlessly optimize plans across the tactical horizon (demand and supply for example on weekly bucket level) and operational horizon (detailed scheduling on single order level and time-stamp level), thus avoiding plan inconsistencies and creating feasible and optimal schedules as well as stable operations.

Concurrent planning is no longer a fancy idea, but will quickly be adopted across leading supply chains, helping to achieve profit-optimal and feasible supply plans in almost real time.

4. Smart decision automation

Automation in supply chains has been spearheaded over the last decade by automation of physical systems (warehouse automation, e.g., automated guided vehicles) and transactional processes and routines (order and data management automation, e.g., process mining and RPA). However, decision making in supply chain planning has seen only modest automation (e.g., planning heuristics for load balancing and shortage allocation), and still relies largely on coordination, judgement, and execution by planners on a case-by-case basis. But now the new environment demands faster, data-enabled decision making, and since the pandemic, more and more companies are willing to bring digitalization to the next level. Thus, in 2022 we will see an increased focus on automating complex, network-based supply chain decision making with systems of intelligence.

Cognitive automation will deeply transform processes and workflows in classical supply chain decisions across all horizons, especially on the tactical and operational decision horizon. Automation will enable more agile and dynamic decision making in areas such as forecasting review and enrichment, supply chain parametrization, load leveling across the network, continuous plan adjustment for optimal cost and supply, and resolution of bottlenecks and shortages, to name just a few examples.

Cognitive automation in supply chains is here to stay, and it will be fueled by a number of transformational technologies: Automation technology will combine multiple cognitive skills to handle complex tasks end-to-end with so-called hyperautomation platforms, for example, by combining traditional RPA for repetitive tasks, chatbots for personalization and user guidance, and data & analytics for optimal decision making in one workflow. Planning systems will not tackle cognitive automation in a monolithic approach but adopt flexible architectures where microservices or smart decision apps can flexibly access the data lake and play back optimal decisions into the planning core and transaction systems.

5. Upskilling people

All the previous trends converge towards one critical point: the model for decision making–be it with regards to risk management, tactical planning, or operational troubleshooting–will move from human-centered to a human-machine symbiosis. More than a technological challenge, we need to understand and manage this as a change management challenge. Supply chain executives need to address one predominant challenge in 2022 and beyond: how to best link people and technology, and especially how to close the exponential gap between accelerating technological possibilities and human adoption (see also Azeem Azhar, Exponential, September 2021).

Companies need to both address a fundamental change in job profiles and create a purposeful environment to win and retain top talents. This is most evident in the area of supply chain planning, where:

  • Planners need to evolve their roles from task executors, who rely on own experience, judgement, and coordination to solve problems, to tech integrators, who understand a multitude of different rulesets or optimization apps, apply them in the right situation, and effectively work with automation and exception-based management systems. This is not about “from zero to one” and switching from one skill to another, but about building an effective symbiosis of both skills in the supply chain planning team.
  • New roles like data scientists and engineers need not only be hired, but effectively integrated into the planning team purpose, community, vision, and day-to-day collaboration. There are many frictions which often hinder a strong integration of both sides and addressing them is a top leadership priority. Data science talent is scarce and attracting and retaining the best not only needs state-of-the-art technology and data experience, but above all a purposeful integration of new roles in the core supply chain team.

Supply chain transformation will only be successful if the people embrace and drive the new possibilities. Understanding effective human-machine symbiosis and successfully managing upskilling, new ways of collaboration, and change will separate supply chain leaders from the rest in the years to come.


We are living in fascinating times for supply chain management. In the new environment, the spot is on the supply chain discipline, and the importance of supply chain as a function has been irrevocably elevated in many companies.

But also, the race is on. In times where fast and effective supply chain response to unleashed disruptions can be a matter of survival, next-generation supply chain planning and orchestration becomes not only a nice upside, but a core source of competitive advantage.

Supply chain leaders need to up their game. To persist in this new environment, supply chain leaders need to develop five new muscles of network-based supply chain planning and orchestration. Dynamic risk management, new data governance, concurrent planning, cognitive automation, and upskilling people will be key to protecting and growing the business.

The best of many worlds. The way forward is one of symbiosis. Only by linking people and technology, execution and data skills, planning core systems and smart decisions apps, will companies be successful on this journey. Openness for learning, diversity of backgrounds and talents as well as adaptability stand out as the core values to pave the way.

We hope this perspective was helpful for you and has provided some ideas and food for thought. Please let us know your feedback and comments.

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