Real-time Data Integration: The Key to Agile Manufacturing and Logistics

Real-time Data Integration: The Key to Agile Manufacturing and Logistics

As consumers, we marvel at the advancements in retail technology. From AI solutions that predict our shopping preferences to smart warehouses that route and deliver orders within hours, the seamless interconnectivity between marketing, sales, and fulfillment makes these experiences possible.

However, amidst the wealth of data and insights prevalent in retail, a stark contrast exists down the supply chain. While e-commerce drives the digitization of customer insights, manufacturing, freight, warehouse, and brick-and-mortar retail analytics remain stuck in a different generation.

Real-time data integration is the most challenging task that should not be. Anyone who has attempted it understands the complexity of working with PDFs, Excel files, and unstructured data related to invoices and purchase orders—foundational assets of any supply chain process and analysis. Beyond this, numerous API and EDI endpoints require unique integrations, often leading to disharmony and data silos.

Death to the PDF

Accessing real-time insights across the supply chain is daunting given the volume of PDFs and Excel files shared between suppliers, logistics providers, and customers. Manual data entry remains the preferred method even for the largest organizations. With the advent of AI, we can autonomously ingest and map such data into data warehouse environments. This shift accelerates our understanding and utilization of data.

Working with an international logistics provider, we took an approach to ingest all bills of lading, packing documents, and invoices. We were able to deliver a solution that created a dashboard and tracking insights that fed information in real-time. This solution limited the need for freight accruals in financial reporting through real-time data availability and allowed for costs to relate more directly to individual shipments and draw accurate COGS data.

Invoice Reconciliation

Through real-time ingestion and mapping invoice and purchase order data into centralized environments, we can perform real-time audits of invoices and purchase orders. This allows for the acceleration of production and ensures that order and cost assumptions are accurately communicated and measured in systems.

In one case, we worked with a client that sourced products from dozens of Asian manufacturers to automate the ingestion of purchase order data and reconcile against invoices received. In this case, our client relied heavily on an offshore team to audit documents. Despite the support, this system was prone to human error in data entry and still left open opportunities for price and unit discrepancies. Our solution compared invoices against the original purchase order to ensure that SKUs, quoted prices, quantities, payment terms, entity information, and delivery information were accurate. In cases where this was not the case, the system prompted questions to the supplier to accelerate resolutions or highlight areas of price or SKU changes without human intervention.

ERP Normalization

Across the supply chain matrix, we confront a host of ERP and WMS solutions that present data differently. Integrating these sources between environments and into BI products can become messy. At XponentL, we have developed capabilities that expedite the ingestion and normalization of data, delivering a data lake environment that is source-agnostic. This eliminates the need to manually map data or bring in multiple teams of consultants specialized in each platform.

We frequently see clients for whom the ERP is the source of truth. Yet, as we drill deeper, data entry into the ERP can often be inefficient or prone to error. This can stem from human error around manual data entry of documents or poor compatibility between systems. We have delivered solutions that allow for this data to be ingested autonomously and flow between systems with our approach toward ETL and data lake architecture; creating fewer direct connections between systems and allowing insights to be drawn across data instead of in silos. Every data point has a source document, and our engineering approach has allowed for an ERP to ingest the source rather than a manual input or derivative.

Real-Time Insights

Disparities in data availability across supply chain environments can hinder organizations' ability to make timely decisions. Our capability to aggregate, normalize, and analyze data across the organization positions us to provide real-time insights with procurement and forecasting directly tied to underlying manufacturing outputs and timelines. Business units should not have to rely on lagging indicators or analyze data in isolation. Instead, we offer a suite of data products and services that "Xcelerate" business decisions and visibility.

Working with a retail customer who sold products across e-commerce and through brick-and-mortar retail channels, we developed a solution to harmonize sales data stemming from various API, EDI, and document-based sales receipts and integrated the data with macro data to forecast volatility in time and price across logistics providers and suppliers.

As you evaluate your supply chain environment, we challenge you to analyze data gaps, disparities in data availability, and situations where decision-makers lack visibility across the entire supply chain. A supply chain is a process driven by quantitative results across business units and should be a chain that can react to changes across the way. Too often we confront situations where lack of data availability prevents clients from responding with the agility that we would like to see.