Solving Costly Supply Chain Problems Through Data Modernization

Matthew Oatney
Data Driven Supply Chain
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From Inventory Management to Freight Optimization, Scalability to Reporting, Customer Experience to Partner Satisfaction, big data has the ability to tackle modern supply chain problems.

In this article we explore how a modern data platform and data-driven approach can help prevent supply chain disruptions, increase efficiency, and ultimately improve the bottom line.

PO to Pick to Pack. From Loaded to In Transit to Delivered. Big data’s potential to achieve complete supply chain visibility throughout the manufacturing process is significant, and often untapped. A modern data platform cannot only help you solve costly problems, it can proactively alert you to prevent them. Especially in today’s climate of ongoing challenges in the business environment, building a scalable enterprise data warehouse (EDW) is key to ongoing operational efficiency and growth.

State of Data in Today’s Supply Chain Manufacturing

A recent study by Gartner reports 76% of supply chain executives feel they face more disruptions than they did three years ago, with traceability, problem prediction and customer service as the largest pain points. Analysts indicate a renewed focus on productivity improvement and a “commitment to drive out inefficiencies.”

The challenge is often in understanding the potential impact of big data and how it can be leveraged to tackle tasks, including:

  • Data validation and anomaly detection
  • Operations benchmarking
  • Real-time optimization
  • Demand forecasts for improved inventory management

In tighter economic times, businesses have to work harder to retain the same share of customer spending. But what if you could instead work smarter? McKinsey analysts predict companies that “digitalize their supply chains could increase their annual growth earnings by 3.2% and annual revenue growth by 2.3%.” If these results are achievable in down times, imagine the potential of having optimized one’s data solutions when the next upswing begins.

Data-Driven Supply Chain Solutions

Investing in data to evolve supply chain operations can be a long game, but the approach can help position businesses for sustainable growth. Adopting a data-driven culture empowers your workforce for better problem resolution and customer experience optimization, both benefiting your organization’s bottom line.

Unsatisfied Customers & Partners

Never before have customer and partner expectations been so high. With the ability to track an order throughout its entire journey, and a 5-10 minute heads up when one’s package is nearing delivery, customers not only desire, but demand, this transparency.

Meanwhile partners believe that all systems should be talking to one another, and that the business they work with understands what they need to do with the data provided, ensuring delivery in an immediately digestible format.

Both customers and partners know that this type of communication is possible, and if you can’t provide it, they’ll seek out someone who can. Rather than a burdensome hurdle, a modern data platform can often automate such solutions, ensuring satisfaction while streamlining workflows.

Visibility (or lack thereof) into Real-Time Disruptions

Disruptions threaten nearly every step of the manufacturing process. A shipment of raw materials is late, a specific machine goes down unexpectedly, even unseasonable weather can cause issues. True end-to-end visibility connects data throughout the supply chain linking your warehouse, purchasing, shipping systems, etc. This allows for the sort of real-time decision making needed to navigate unavoidable challenges and mitigate additional costs.

With redundancy systems in place, data can help direct resources down the line, resolving issues as efficiently as possible and communicating the solution to all parties involved. As above, communications can effectively disseminate to partners and consumers, managing expectations and strengthening relationships in both the short and long term.

Manual Processes that Can’t Scale

As operations grow, processes that once served the needs of the business become difficult to evolve. One such example, a building materials manufacturer had a legacy Excel based process to determine production needs, which took roughly 12 hours and had accuracy issues.

Leveraging a newly designed EDW to modernize and automate this report, g2o was able to develop an accurate predictive scheduling output that ran in 2 minutes. This new capability not only streamlined operations but increased reliability.

Ineffective and Untrustworthy Reports

When the data isn’t clean or consistent, stakeholders lose trust in its ability to effectively guide decision-making. In fact, 78% of executives surveyed by Talend say that they have challenges using data, in part due to organizational siloes as well as concerns over quality, provenance and/or governance.

Ensuring warehouse management systems (WMS) deliver reliable reports enables more meaningful relationships and sets the state for ongoing development. This is beneficial for both internal and external customer service communications.

Additionally, managers can be clearer in their recommendations to leadership and direction to teams when they have confidence in the data-driving decisions.

Inventory Management Issues

From balancing customer demand and fulfillment to ensuring you have all the right pieces and parts for assembly at the same warehouse, inventory management challenges can affect organizations of any size. Not even Amazon is immune, as it was notoriously over-warehoused in 2022, causing it to run an extra Prime Day between its typical summer sale and Black Friday.

Caution among end consumers affects every business down the line. Being able to get ahead of these instances and balance production ensures you don’t end up having to fire sale, and on the flip side, can help prevent out-of-stock scenarios. In both cases, accurate demand forecasting data can improve inventory management.

Freight Optimization

Similar to managing production, optimizing LTL vs FTL shipments directly affects both the business’s bottom line as well as costs passed through to customers.

Optimizing transport vehicles can save time and money. For a particular manufacturer in the building industry, g2o developed algorithms for customer inventory replenishment and maximum truck loading capacity. Shipping costs and out-of-stock issues were reduced for customers while the manufacturer saw increased revenue.

Is Your Data in the Right State to Solve Your Real Supply Chain Problems?

Does your current data environment allow seamless integration across the entire supply chain? If you can’t confidently answer “Yes,” there’s a solid chance your organization can get more from its data, including increased productivity and insights for proactive problem-solving. An effective EDW is a true powerhouse that can set the stage for continual growth.

Perhaps you have some pieces in place, but everyday business demands have prevented taking your data solutions to the next level. Or, your organization needs to start foundational, with a Data Strategy Roadmap.

In either case and anywhere in between, g2o’s Data and Analytics experts offer a depth of knowledge partnering with supply chain and manufacturing clients to resolve these common business problems and deliver scalable solutions for more meaningful data management.

Reach out today to talk with our Data and Analytics experts to begin building the data systems that will guide growth tomorrow.