Robust & Resilient: Analytics keep supply chains running
Abboud Ghanem, Regional Vice-President – Middle East & Africa, Alteryx, reveals how analytics can help the supply chain industry adapt to the future
The COVID-19 pandemic had put supply chains leaders under extreme stress and forced many companies, and entire industries, to rethink and transform their global supply chain model to meet the needs of this new normal and ensure resiliency in the era of social distance working.
The UAE has impressively transformed itself from a logistics hub into a supply chain nerve centre in recent years. The Dhs220 billion UAE logistics sector is expected to contribute 8% to the UAE economy by 2021.
With many industries depending on goods and materials from across the globe, ramifications were felt through global supply chains, from raw materials to finished products. Increased globalisation, economic uncertainty, and faster product lifecycles made today’s supply chains much more complex to manage.
The pandemic proved that a single event could have a domino effect across an entire chain, and many businesses had to navigate through unchartered waters. Protecting the supply chain in a crisis requires speed and skill; it’s better to plan ahead than be forced to play catch-up.
Of course, it’s difficult to predict and get ahead of natural disasters and accidents. Still, the inability to fully understand how to plan for disruptions and the inevitable shortages are the signs and symptoms of a stressed supply chain. Being able to play out scenarios and have a disaster recovery plan is key. To do so, requires data transparency, agility, and the prepared recommendations to take actions.
As businesses recover from this disaster, the focus during this year will be to use data to build in transparency first, use that transparency to understand their risk exposure and finally make recommendations to plan accordingly.
There are numerous ways data analytics can improve supply chain efficiency: validating data; detecting anomalies; benchmarking operations; allowing for mobile reporting and visibility into global logistics’ offering real-time route optimisation, improved demand forecasts, and inventory management; and providing for responses to government audits.
A recent Gartner survey revealed that 29% of surveyed organisations said they had achieved high levels of ROI by using analytics for their supply chain business.
Analytics can help augment the emergency response to predict future risks by spotting patterns and trends throughout the supply chain and help keep three major parts of a supply chain moving.
Reshaping demand forecasting
The unexpected rise in demand can prompt planners to quickly evaluate the level of safety stock inventory and move it to mitigate the risk of running out of raw materials or finished goods. Through the analysis of demographics and population densities, planners can easily reprioritise shipping locations as well as utilise drive times and logistic details so that inventory moves to the right locations in time.
To further optimise production during shifting demand patterns, planners and buyers may need to reshape previous forecasts based on alternative suppliers and raw material availability, including current running and safety stock levels.
Analysts need to interpret historical dark data from known situations like previous recessions, or crisis data from flood or hurricane emergencies to model and build a forward-looking forecast into recovery. Data science and predictive modelling is the only way to see into the future. It provides deep and actionable insights for teams looking to optimise the production and distribution of equipment, services or other supply-chain processes required.
Reshaping suppliers and activating new resources
Maintaining a flexible supplier framework is critical in times of crisis and supplier failure can put an instant stop to operations if raw materials necessary for manufacturing aren’t ready in time.
The measurement and optimisation of supplier performance is critical to meeting procurement needs, and complex supply chain environments require a pool of alternative suppliers to draw upon to avoid stoppages down the line. Analytically savvy businesses are:
- Empowering procurement functions to assess risks by analysing goods supplied from alternative suppliers to quickly identify a pre-approved part or material substitutions and activate the product or material redesigns.
- Utilising analytic forecasting to ensure that in-market sourcing groups diversify suppliers to reduce dependence on a possible single high-risk facility or part.
- Evaluating what-if scenarios to source pre-approved alternative tier two and three vendors or product substitutions to cover the shortfall and activate product redesigns based on currently available resources.
Reshaping logistics and time to delivery
When working on redistributing current inventory and materials from possible quarantined areas, or moving safety stock to feed high demand areas, its crucial to be able to quickly analyse and secure additional means of transportation based on individual product lead times as supply and capacity fluctuate.
From understanding carrier options and analysing spatial components — such as drive time variables and trade areas to carry out effective rerouting of deliveries — data from geospatial sources, including real-time satellite positioning, tracking and geofencing can make sense of a company’s complex, distributed supply chain.
Understanding where 100,000 trucks are moving raw or processed materials across continents can lead to better insights around potential bottlenecks or transportation hubs to improve deliveries or reduce downtime. Predictive analytics can model scenarios and help create workflows to deliver real-time estimations of inventory and forecasts for spare capacity or shortfall.
Building robust supply chains
Critical decision-making requires good information and good data. Consequently, data and analytics should serve as stabilisers to help companies model prospective business scenarios so they can enable the necessary evaluation, adaption, and course-correction in response to market conditions.
As businesses across the UAE gear up not just to survive, but to thrive in 2021, predictive analytics will further emerge as a crucial tool for mitigating risks, managing volatility and offsetting risk. During the pandemic we saw forecasting models and processes simply break down.
With supply chains more complex and dynamic than ever, moving forward it will be crucial that they be augmented, automated, and enhanced through the support of analytics processing that matches their sophistication.