Rebooting the Supply Chain – Shifting the Focus from Cost to Risk

By CK Tan, Senior Director, Solutions and Value Engineering at Qlik

Headshot of blog author CK Tan

CK Tan

6 min read

Two men in a warehouse wearing hardhats discussing inventory

For decades, companies worldwide ran on a just-in-time inventory approach to meet consumer demands with minimum delays. This approach - used in selecting suppliers, planning for production and deciding how much stock to keep on hand - focuses mainly on cost, not risk. However, a series of unfortunate world events like the COVID-19 pandemic and political instability in Europe and Asia have exposed major fractures in such supply chain models.

Even with more governments relaxing border restrictions, the world is still running short of everything. From computer chips to metal parts, plastics to raw materials, these shortages are impacting every manufacturer, supplier and business that sells product worldwide. A recent Chief Procurement Officer survey by Deloitte revealed that 32% of companies say they are losing revenue due to supply shortages, with 11% citing damage to their brands.

Arial image of shipping containers with text overlayed of bullet points for top causes of material shortages

Shortages are not the only issue. Supply chains are also constantly getting disrupted in many different ways. It could be transportation congestion due to container shortages, rail and trucking difficulties, or warehouses not operating at total capacity due to worker quarantines. Even a black swan event like Ever Given - one of the largest container ships ever built - getting stuck in the Suez Canal halted traffic on a vital waterway linking Europe to Asia for a week. This added to logistics operations mayhem and a backlog that took several months to clear.

Such a mismatch between supply and demand has even been seen at Tesla. The world's biggest electric car maker recently suspended production largely due to battery shortages and supply disruptions in China, even while electric car orders spiked globally. Worldwide sales of electric cars doubled in 2021 and will remain strong this year because of policy support and greater driver environmental awareness. Tesla CEO Elon Musk said its new factories in Texas and Berlin are "gigantic money furnaces," losing billions of dollars as they struggle to increase production.

These challenges are compelling supply chain executives to think differently. They have to act fast or risk slashing production, impacting sales and losing customers to competitors. After years of focusing on cost efficiencies or cost savings, 93% of supply chain executives now say they plan to increase the level of resilience across their supply chains.

Supply chain leaders are investing in technology such as supply chain analytics to get complete visibility of their operations across planning, sourcing, production and distribution. This visibility will create early warning signals about potential bottlenecks and enable automated workflows to increase planning agility and respond to sudden business events.

Retailers like IKEA are innovating ways of working within a complex supply chain that depends heavily on external players. The largest furniture retailer rolled out a Supplier Scorecard in IKEA's Supplier Portal to create suitable pre-conditions for IKEA suppliers to take full responsibility for their performance and follow up on their goals. By sharing information within their network, they are now better able to deal with emergencies and unforeseen situations.

Achieving a higher level of data-driven supply chain competency requires looking at data differently. Data historically has been seen as a by-product, something to review at a later date to facilitate S&OP discussions, operations and logistics planning - designed only to inform. Instead, data must be integrated as an element that powers supply chain processes and action. Both the supply chain and technology teams need to come together and work out business actions, using common underlying technology to remove friction and increase agility in supply chain processes.

Urban Outfitters is an excellent example of a company that adopted a fully data-driven culture in its supply chain practices. The brand operates more than 650 stores across the US and Europe and has worked to ensure every employee is aligned with in-store performance metrics and new purchasing patterns. Every employee in each store can get up-to-the-minute data on all aspects of the individual store's KPIs, including inventory, store conversions, exceptions analysis, and top 50 sales by store – and act on those insights immediately. All these insights have helped the brand considerably in its ability to match supply to market demands.

Here are a few technology tips to help make the switch to a just-in-case approach, which prioritizes minimizing the chances of goods running low in stock or falling behind the production schedule required to fulfill orders on time.

**Greater visibility in the cloud**Devise a data strategy centered on maximizing the efficiencies and scalability of the cloud. Through the cloud, Urban Outfitters can quickly scale access to near real-time analytics. "The more data we have in the cloud, the easier it is for us to set up new stores and connect them from anywhere around the globe" – Urban Outfitters Technology Director, Paul Reigel.

**Near real-time data enables quick decisions by everyone**With real-time data replication, gone are the days when data from supply chain systems like SAP are only extracted at the end of a business day. With real-time data feeding their Snowflake cloud data warehouse, Urban Outfitters can confidently scale access to more near real-time data for in-store employees and provide store managers with instantaneous insights about store operations.

**Brings the power of predictive analytics directly to the business**Most organizations struggle to understand what will happen in the future and why – unless they can invest in data scientists to create machine learning models and make predictions. Automated machine learning (‘AutoML’) brings predictive analytics capabilities directly to the business in an easy user experience. Skullcandy, a leading audio accessories maker, uses AutoML to predict product demand to ensure correct manufacturing throughput, forecast features and parts that failed in the field, and make improvements before going to the market.

As we embrace the uncertainties in this changing world, let's stop the age-old supply chain practice of just-in-time and using natural human instincts to lead our decision-making, and make the shift to evidence-based decision making, augmenting our intuition through machine intelligence and real-time data.

A recent Chief Procurement Officer survey by Deloitte revealed that 32% of companies say they are losing revenue due to supply shortages, with 11% citing damage to their brands.

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