The optimization of supply chains means different things in different organizations. However, it is only in the aftermath of the COVID-19 pandemic that we have come to fully appreciate the value of a robust and functional supply chain. Many businesses were forced to rethink their entire operational models due to supply chain disruptions to continue fulfilling customer orders. Organizations that were already investing in the optimization of their supply chains prior to the pandemic managed to thrive, or at least continue investing in optimizing their supply chains during the pandemic. Those that failed to allocate adequate time and resources towards optimizing their supply chains were unable to capitalize on opportunities during the pandemic or advance their position in the market, while some were left inoperable.
Less than a decade ago, most supply chain leaders were focused on functional operational issues within their own areas of the supply chain, such as procurement, logistics or manufacturing operations. Cost-cutting was often perceived as an added value option that supply chain partners could offer. In those times, the conversations often sounded like this:
“I have X amount of budget and Y SLA to meet. Please send me a presentation that displays how your solution will be better (aka cheaper) than my current service provider and also looks fancy when displayed on the screen in a board meeting.”
Or perhaps like this,
“My boss has been given cost reduction and service improvement targets because our sales teams claim they can’t sell because our logistics cost are too high and product stock levels too low.”
In a contemporary business environment, the supply chain is understood as a service stream that acts as a catalyst for change and delivers synergies across different departments; especially production, inventory management, delivery, operational excellence and most importantly, customer satisfaction. Supply chain leaders are now shaping their strategies around pivotal operational and customer-centric models that improve inventory availability, resilience and speed of delivery and many make use of big data in this process.
Imagine a global manufacturer of consumer electronics with a strong presence in the Asia-Pacific and Europe regions. Historically, the company's supply chain was primarily seen as a cost function aimed at minimizing expenses and ensuring the timely delivery of products to customers. However, in recent years, the company has shifted its understanding of its supply chain from a cost function to a service and revenue stream. Such a paradigm change allows the company to expand its product offering, increase sales and provide its customers with a superior buying experience, ultimately increasing brand awareness and loyalty. To achieve this transformation, the company focused on developing a customer-centric supply chain model that could quickly respond to the changing market demands and customer preferences adding agility and customization to their standard service offerings.
Before an organization begins to rethink its supply chain model, a thorough analysis and health check of its current supply chain is crucial. Some critical questions companies should be asking themselves include:
Has your organization conducted an analysis of revenue contribution by product SKU?
Do you review your product portfolio on an annual basis?
What is more important to your company – fast or reliable delivery?
Global benchmarking is another critical step in strategic supply chain planning.
In addition, customer inability to provide commitment on short- and medium-term business volumes can often be a challenge for investment planning. In considering this issue, an important question arises. “Is the absence of volume certainty in the short-mid-term run a cause for pumping the brakes on supply chain optimization investments?” The answer is more than likely no, especially if a company has been conducting due diligence and regular assessments of its supply chain, and it has a clear, forward-thinking business strategy.
Amazon is a great example of how a simple online book-selling business can be transformed into a major global eCommerce player by rethinking and redesigning the supply chain. Initially, it relied on traditional supply chain methods to source, manufacture and deliver products to customers. However, the company realized that their business was limited by the inefficiencies of this approach. To advance forward in the market, they invested heavily in technology, cloud-based businesses and data analytics that paved the way for them to become a leader in the market.
One concrete example of the modernization of contract logistics operations is the utilization of new drone technologies for inventory accountability.
The benefits of doing a “sky” (drone-based) inventory count include:
No freeze of inbound or outbound order activities - business as usual
Inventory counts can be concluded within hours instead of days
Free from human error as there are no manual activities
Typically 20% to 40% in cost reduction due to less labor required and business flow continuing
Most drone-based inventory counts work well for palletized inventory as the technology uses label recognition software that reads pallet and location labels. When a drone hovers over the warehouse, it compares the actual stock levels with current stock levels in the warehouse management system (WMS). If there is a discrepancy, it will be flagged immediately and can be manually checked while the drone continues the stock count.
Even in the face of the headlines about robotics and AI creating highly automated warehouses, they do not eliminate the need for human labor. Let’s take a look at a real-life business example.
Take for example a state-of-the-art 80,000 square meter warehouse in Europe operates 24/7 with an output of 500 units per day is equipped with an automated shuttle storage system linked to a pocket sorter, packaging machines and kilometers of conveyor belts. On a quiet day, this warehouse is managed by 1,500 to 2,000 people and during the peak season, it nearly doubles for a 24-hour cycle. The peak output exceeds 700,000 units per month. Given labor shortages across Europe, making the warehouse more automated with technology is inevitable given rising consumer demand and order volumes. Withouth improved automation, this particular warehouse would require a 1.5x (or more) increase in human labor and additional warehousing space to keep up with demand.
To efficiently run a highly-automated warehouse, it is necessary to implement a control room concept that shifts the steering from a decentralized to a centralized model. With this method, the control room is at the core of the warehouse operation. The centralized steering mechanism drives the overall fulfillment chain, ensuring that all sub-processes are streamlined and all operations are seamless. Capacity control, equipment control and IT are the three main disciplines represented in a control room. They must work together to make sure the day-to-day operation runs as smoothly as possible.
While highly automated warehouses are operated with less human labor, they still require human intervention and innovation to have a synchronized system, such as a control room, to achieve high levels of automation and efficiency. The automation frees up the human labor to devote more time to higher order, more complex tasks, adding value.
In today’s world, we have unprecedented access to data from a variety of systems related to freight and capital markets, international commodity trends, and other information. We strive to turn this data into predictive insights that can help businesses make informed decisions. This data, combined with cloud technologies, like computer vision, machine learning and simulation, produces a powerful tool. Access to big data and data technology is more affordable and accessible now than ever before, but the transportation and supply chain industry is still rather slow to adopt these tools.
To put this topic into perspective, a few years ago, logistics service providers in the Middle East were tasked with designing solutions for multi-million-dollar investments with a single-scenario based approach because simulating multiple scenarios was either not technically possible or not financially feasible. As such, this approach failed to reflect the operational reality that on the ground, the companies that needed these services were highly dynamic, with ever-changing changing business needs. The idea of a single scenario-based approach raised too many doubts. The questions that needed to be asked included topics like: “Should we automate a portion of the processes in one of our warehouses to benefit from cost advantage and leave another warehouse as a flexible buffer?” And, “How much stock should we keep in each facility in each region to reach our cost and speed objectives?”
In 2023, cloud technologies allow simulations that help answer questions like the ones above. While the problems that simulations can solve are significant, common pitfalls related to the effective use of simulations include a lack of high-power hardware and a specialized workforce.
The logistics and supply chain industry is transforming and becoming less and less of a truck-driver or forklift operator type of labor market. In the current labor market conditions, we are seeing a trend where many roles in logistics require tech-savvy, engineer-style profiles eager to pioneer new solutions. In addition, we are faced with an industry-knowledge-rich baby-boomer generation that generally lacks a deep understanding of new technologies and big data works. This generation is now working alongside millennials and gen Z workers who often have a different understanding of how processes should or could work.
Many agree that the right approach is to pass on industry knowledge to younger generations and give them the freedom and flexibility to reimagine the optimization of the logistics and supply chain industry with new technologies and tools. Each generation stands on the shoulders of previous generations while applying new ideas and innovating new solutions.
To attract the right talent, industry players must enhance the awareness of careers in logistics among the next generation of employees through delivering the right messages and understanding their expectations. Logistics leaders need to understand what drives the next generation of workers’ decisions about their careers.
To remain successful in a world of constant change, identifying and adapting to key industry trends requires constant vigilance. In the logistics and supply chain industry, implementing solutions that optimize operations requires a healthy and balanced approach to these important topics.
Decision makers must understand the value of logistics and supply chain operations.
A forward-thinking plan to modernize the supply chain is paramount to short- and long-term success.
Regardless of the level of automation, successful logistics and supply chain models still require the most critical aspect – the people.
Big data will help with decision making if it’s properly embraced and adopted.
Recognizing and adapting to the generational gap between logistics and supply chain leaders and the younger workforce will propel innovation and industry progress.