High-tech manufacturing is in a unique position: it is both a driver of change and at the forefront of its impact. The latest evolution of chips is enabling the next wave of consumer and industrial applications from virtual reality to artificial intelligence. High tech has allowed the business, education and domestic worlds to adjust to the pandemic, although not without some well-publicized supply issues. So as the world becomes ever more dependent on high tech and spins ever faster, what will the future look like and how do high-tech manufacturers prepare for it? 

To answer this question, it’s important to understand the unique set of issues facing the industry.

  • Uncertainty: Since many high-tech manufacturers have rapid product life cycles (PLCs) and frequently launch into new segments, a lot of their future revenue is tied up in great uncertainty. Meanwhile channels distance organizations from the nuances of the market.  
  • Complexity: It is not unusual for high-tech manufacturers to manage tens of thousands of SKUs. Since acquisitions are commonplace, this count can proliferate, which translates to extremely complex global supply chains. For many organizations, forecast accuracy has plateaued, meaning that opportunity and growth investment opportunities are missed as funds are tied up in working capital. 
  • Volatility: The pandemic exposed the fragility of supply. In high tech, profitability correlates highly to market share, and market share requires availability. 

The future will be about speed, visibility and automation. Agility at speed needs a real-time view and the ability to see further ahead at a higher resolution. Processing almost instantly, at high levels of granularity, requires a leap in capability and a necessary transformation to achieve the levels of precision that will be needed in tomorrow’s digital world. 

Velocity and volatility are only expected to rise in the post-pandemic world and, at Blue Yonder, we believe the solution to this is the Autonomous Supply Chain™. This is our vision for a future where digital edge technologies like artificial intelligence (AI) and machine learning (ML) augment human decision-makers to streamline supply chains, make more profitable business decisions, and deliver optimized customer experiences.

Below, we present three important considerations—a roadmap, if you will—for high-tech organizations to this accelerated future and how they can get returns now by capitalizing on the digital revolution while planning for an autonomous future:

Get Ahead of the Market

The volatility of the high-tech world puts a premium on accurately sensing demand, planning production, and optimizing distribution to respond quickly and profitably to each customer segment. Fortunately, technology has an answer.

ML can overcome the forecast accuracy challenges of today and scale to tomorrow’s complexity. For example, Blue Yonder recently worked with a global networking company to help predict demand for its hardware products. The company had historically used common statistical techniques that yielded a forecasting accuracy that had plateaued at about 65%. For a company that has billions of dollars tied up in its inventory, this means that 35% will be left unsold due to poor demand planning practices. It needed a solution that could improve its demand planning capabilities and allow it to be more efficient in its inventory allocations. After applying our intelligent ML-based forecasting techniques on over 20,000 SKUs, Blue Yonder increased the demand forecast accuracy by 10-15 percentage points.

Accurate forecasting holds the key to improved sustainability and higher customer service levels. By ingesting a variety of demand-driving variables, ML scales to provide a more precise projection for each SKU together with calculated business impact and risk. This not only leads to less revenue uncertainty but also enables higher planner productivity, better inventory management, and an improved understanding of demand drivers and customer behavior, bringing high-tech businesses closer to the end-user. 

Sense, Compute, Act 

Lean and just-in-time (JIT) have been dominant supply chainphilosophies in the high-tech space, among many other industries. The concept is all about carrying only the inventory that you need and maximizing efficiency. However, COVID-19 has been a catalyst in challenging this practice. Companies with deep pockets came out on top and gained higher market share ultimately because they could afford to invest in their inventory during this unpredictable time.

This is not a sustainable strategy. Rising customer expectations require precision solutions for each customer, no matter if they are a channel or an end-user. Cognitive segmentation powered by ML not only meets these expectations but also provides higher levels of service at greater efficiency. It does this by creating demand clusters that exhibit similar patterns, which inform forecasting and inventory models. This is important in the high-tech industry that traditionally uses complex and potentially expensive postponement strategies to localize and customize orders. 

Consider our work on cognitive segmentation with a client with a significant parts count. This company came to us to help replace its traditional, manually driven segmentation processes and tools, which often resulted in inefficient allocation, high safety inventory levels, and less-than-optimal service levels. Now on Blue Yonder’s Luminate Platform, it can apply ML to both systematically classify spare parts into unique demand clusters and establish the significance of demand attributes. Our partnership has already resulted in a 10% overall reduction in inventory quantity while improving service levels. 

Respond Quickly and Prescriptively

With consumer expectations higher than ever before, rapid response to supply chain disruption is necessary, but not enough. High-tech manufacturers will need to take quick prescriptive action to address supply chain issues from expected disruptions. 

Let’s look at a common logistics problem: a customer order is behind schedule due to a backed-up warehouse. The logistics manager sees this and needs to decide: do I incur overtime to expedite shipping or knowingly accept that the customer will not receive his package on time because of resource constraints? Now imagine having to respond to this same scenario for hundreds—if not thousands—of customers daily and in the middle of significant disruption. It doesn’t seem feasible, right?

The good news is companies can now use data to prescribe action, streamlining this historically manual process. By analyzing hundreds of scenarios and their corresponding decisions and results, ML can learn and predict, prescribing action based on outcomes, and where appropriate automate the action. Humans don’t have the bandwidth to scale and cope with the real-time nature of today’s supply chain, and technology is helping to solve this problem. Tomorrow’s winners in the high-tech space will predict supply chain risks and anticipate both issues and opportunities.


The pandemic has made it clear that expectations are higher than ever and there is little room for error in the supply chain. It has catalyzed our understanding of the necessity of transformation for the digital age, making it an imperative. As high-tech companies look to remain competitive in this new reality and scale for tomorrow, those that can capitalize on big data and AI and use techniques such as cognitive forecasting and segmentation can deliver the service levels tomorrow’s markets will demand to rise above the competition.

I truly believe we are on the cusp of a major technological revolution in supply chains and we at Blue Yonder are at the leading edge of this change. For more information on Blue Yonder’s solutions for high-tech businesses, please visit our website.