Bottom line: Big data is providing supplier networks with greater data accuracy, clarity, and insights, leading to more contextual intelligence shared across supply chains.
Forward-thinking manufacturers are orchestrating 80% or more of their supplier network activity outside their four walls, using big data and cloud-based technologies to get beyond the constraints of legacy Enterprise Resource Planning (ERP) and Supply Chain Management (SCM) systems. For manufacturers whose business models are based on rapid product lifecycles and speed, legacy ERP systems are a bottleneck. Designed for delivering order, shipment and transactional data, these systems aren’t capable of scaling to meet the challenges supply chains face today.
Choosing to compete on accuracy, speed and quality forces supplier networks to get to a level of contextual intelligence not possible with legacy ERP and SCM systems. While many companies today haven’t yet adopted big data into their supply chain operations, these ten factors taken together will be the catalyst that get many moving on their journey.
The ten ways big data is revolutionizing supply chain management include:
- The scale, scope and depth of data supply chains are generating today is accelerating, providing ample data sets to drive contextual intelligence. Source: Big Data Analytics in Supply Chain Management: Trends and Related Research. Presented at 6th International Conference on Operations and Supply Chain Management, Bali, 2014
- Enabling more complex supplier networks that focus on knowledge sharing and collaboration as the value-add over just completing transactions. Big data is revolutionizing how supplier networks form, grow, proliferate into new markets and mature over time.
- Big data and advanced analytics are being integrated into optimization tools, demand forecasting, integrated business planning and supplier collaboration & risk analytics at a quickening pace. These are the top four supply chain capabilities that Delotte found are currently in use form their recent study, Supply Chain Talent of the Future Findings from the 3rd Annual Supply Chain Survey (free, no opt-in). Control tower analytics and visualization are also on the roadmaps of supply chain teams currently running big data pilots.
- 64% of supply chain executives consider big data analytics a disruptive and important technology, setting the foundation for long-term change management in their organizations.
- Using geoanalytics based on big data to merge and optimize delivery networks.
- Big data is having an impact on organizations’ reaction time to supply chain issues (41%), increased supply chain efficiency of 10% or greater (36%), and greater integration across the supply chain (36%). The Big Data Analytics in Supply Chain: Hype or Here to Stay? Accenture Global Operations Megatrends Study found that companies are achieving significant results using big data analytics to improve supply chain performance and gain greater contextual intelligence.
- Embedding big data analytics in operations leads to a 4.25x improvement in order-to-cycle delivery times, and a 2.6x improvement in supply chain efficiency of 10% or greater.
- Greater contextual intelligence of how supply chain tactics, strategies and operations are influencing financial objectives.
- Traceability and recalls are by nature data-intensive, making big data’s contribution potentially significant. Big data has the potential to provide improved traceability performance and reduce the thousands of hours lost just trying to access, integrate and manage product databases that provide data on where products are in the field needing to be recalled or retrofitted.
- Increasing supplier quality from supplier audit to inbound inspection and final assembly with big data. IBM has developed a quality early-warning system that detects and then defines a prioritization framework that isolates quality problem faster than more traditional methods, including Statistical Process Control (SPC). The early-warning system is deployed upstream of suppliers and extends out to products in the field.