The year 2019 seemed to be the year of unpredictability, not the least of which was the seemingly ever-changing foreign trade policy of major world economies. Interestingly, it’s that same unpredictable nature of foreign trade policy that serves as a springboard for supply chain predictions for 2020. 

Here are the top five predictions that will have a major impact on the world’s global supply chains.


Historically, digital transformation of the supply chain has taken place by targeting various functional silos within their own walls. This approach lacked the ability to evaluate the interconnected nature of supply chain decisions. 

 The rise of algorithmic intelligence and cloud computing power has made it possible to render a digital model of the supply chain. Gartner recently identified the digital supply chain twin as one of the 8 top technology trends for the supply chain. The “twin” depicts the horizontal nature of the supply chain in a “farm-to-fork” fashion while simultaneously representing the vertical nature of the supply chain within the four walls of facilities, for example, the manufacturing lines and machines within a production facility. The digital twin will provide the ability to create scenarios and simulate real-world events in order to predict outcomes. Predictive analytics generated by the digital supply chain twin will increasingly be the basis for strategic decisioning as they highlight the implications of interconnected decision making.


Executives realize that running the same packaged applications as their competitors often does not equate to gaining a competitive advantage. The key is focusing on the pressing business challenges, and then bringing components of data science to build an application at an enterprise scale where they can harness an algorithmic advantage.  

Emerging platforms built by innovative solution providers include standard components of data science, which organizations will leverage to quickly solve their unique challenges in a fashion that is on an enterprise scale by nature.  Here are three example use cases where momentum will increase during 2020:

Predicting Volatile Order Patterns: AI and ML will give companies the ability to predict less stable, highly volatile order patterns from customers. The supplier community is seeing increased volatility in demand signals due to an uptick in order volumes from leading online retailers.  At the same time the power is shifting to the on-line retailers and they are demanding more just-in-time deliveries to keep their working capital lower and cater to the emerging same-day delivery needs.

Market Sensing: AI can help harness the power of external causal data such as weather, GDP, CPI, employment levels, industrial production, etc., as better predictors of markets shifts and demand drivers.  This brings better sensory capabilities into the supply chain, product portfolio, capital expenditure decisions, and long term strategic and capacity planning. For long-range strategic planning sales orders that were taken last week are much less relevant than understanding the macro-economic drivers that dictate sales growth or decline.

Chargeback Reduction: Retailers charge hefty penalties to brand owners for missed OTIF (on-time, in-full) deliveries. Deep learning algorithms allow sifting through key shipment data including order types, times, quantities, locations and transportation modes to identify root causes for chargebacks and predict points of failure so brand owners can avoid being charged these hefty penalties.

While we will see other unique use cases emerge, some of the most innovative of those will remain hidden for interests of competitiveness and first-mover advantage.


Trade wars and economic nationalism have kicked supply chain conversations into high gear during 2019. Hard set strategic decisions and policies governing supply chains are being reevaluated far more dynamically considering the changing global economy.  For 2020, regionalization efforts will continue in the physical supply chain and will cascade into the digital form as the splinternet trend gains momentum. 

Some 50% of companies with exposure to China were already looking for other sources of supply and manufacturing due to rising wages in China when the trade wars started.  The trade wars have increased the awareness of C-Level leaders to potential geopolitical exposure and risk and will drive more companies to reconsider their global sourcing decisions.  

Manufacturing, warehousing, fulfillment, and transportation will continue to be automated – thus driving down the percentage share of labor costs contained an item.  As the share of capital costs of items increase labor costs advantages will eventually be mitigated. This will further reduce the need for low cost labor as industry 4.0 will serve as an equalization factor for manufacturing economies to thrive in all regions. As the number of organizations who onshore or near shore materials continues to grow, they will benefit from being able to more quickly respond to rapidly changing customer preferences because of their shorter supply lines. This will lead to a decrease in inventory and working capital that will be partly reinvested into local infrastructure where capacities and manufacturing capabilities will need to be built as existing capacities are exited overseas.

The EU’s GDPR legislation had impacts that were global in nature considering data privacy and ownership.  This is not an isolated event. It serves as a proxy for similar policies that will be issued from other governing bodies on a global basis as ownership of data becomes critically important in a digital world.  The GDPR and China’s “Great Firewall” have led to the splinternet of things; the Internet splintering and dividing due to factors such as nationalism, politics and regional data legislations. We will see an increasing number of countries requiring that data need to be housed in their countries and with that will come more physical builds for the data centers in various geographies. Along with data, we will see requirements for a minimum investment in local manufacturing or value-added services that need to take place on their soil as a condition of doing business in their country.


Retailers are trying to combat the problem of declining foot traffic into their brick and mortar store locations while simultaneously revamping their direct-to-consumer models. This year, Kohl’s and Amazon announced a partnership that will allow Kohl’s stores across the USA to accept Amazon returns at its physical store locations.  When a customer takes an Amazon return to Kohl’s they often receive a 25% off coupon for in-store shopping. This trend will cause us to see a rise in these strategic partnerships during 2020.


The gap between the skills needed to compete in an increasingly digital world and those available in organizations are widening and will continue to do so at an even faster pace. The rise in robotics and algorithmic intelligence will continue taking over many activities that were previously part of the supply chain professional’s tasks. To close the skills gap and turn it into a competitive differentiator, more organizations will invest in the up skilling of their workforce through online platforms and continuous learning initiatives. Companies will increase their investments in cognitive automation to make the most of structured and unstructured data so that it can be analyzed, processed and structured in a way to feed predictive analytics for a new generation of business leaders. As AI/ML and cloud systems are broadly adopted more organizations will realize that they need less hyper-specialized experts with narrow and deep skill sets. Companies will look to promote collaboration and broader end-to-end thinking by rotating high-potential employees through different functions. The citizen data scientist with supply chain acumen will be in more demand than ever and new talent will be targeted earlier in the recruitment cycle as companies create more intern and co-op positions.

These are the top traits that companies will look for from current and new employees as they manage their data-driven supply chains:

  • Deep understanding of data and knowing how to effectively communicate with data
  • Having unbiased thinking – high EQ becomes critical as you build solutions for people
  • Deep dive data skills – it’s such a data intensive place now that you need to be familiar with data and how to use it to make decisions
  • Leadership and results orientation
  • Passion & charisma 

Additionally, the physical logistics jobs including drivers and warehouse staff that are also experiencing shortages, will increasingly use the gig economy to help fill jobs and alleviate the shortages to some extent.


Executive leaders would be well served by ensuring that their respective organizations seriously consider the implications that these five predictions may have on their supply chains during 2020.  Ultimately the companies who embrace the algorithmic, human and geopolitical changes with vigor and excellence will be the ones that thrive in what surely will be one of the most hyper-competitive global markets this coming year.

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