OMStorm: Creating Value from Data

In the dynamic world of eCommerce, where customer expectations are constantly evolving and competition is fierce, data is king. And nowhere is this truer than in the realm of Order Management Systems (OMS). OMS data is a treasure trove of insights, offering a wealth of information about customer behavior, order patterns, fulfillment efficiency, and much more. But are retailers truly harnessing the full potential of this valuable resource?

In this Order Management Guru brainstorming discussion, experts dive deep into the world of OMS data. They cover the evolving landscape of OMS data, uncover the hidden challenges and untapped opportunities, and spark your imagination with innovative ideas for leveraging this data to drive omnichannel eCommerce success.

Order Management Gurus, Panel 3: OMStorm, Creating Value from Data

Let's call it an opportunity to share all the fancy ideas💡on ways to drive value from OMS data, the velocity, the variety, the volume -whole shebang 🥙 
  ⚡ Let's inflate our (idea) balloons, and let OMGurus poke holes
  ⚡ No stone left unturned, inventory, order, shipment, API, click stream, SaaS, reverse-ETL, personalization
  ⚡ Let's share what we have delivered and are proud, sow the seeds, let ‘em learn

Panelists:

• Abhishek Kalra, VP of Customer Success, Nextuple
• Chap Achen, VP of Product Strategy, Nextuple

The Shifting Sands of OMS Data Value (00:06:06)

The value proposition of OMS data has undergone a dramatic transformation in recent years. Driven by the rise of omnichannel retail, the increasing complexity of fulfillment networks, and the growing importance of customer experience, OMS data is no longer just about tracking orders and managing inventory. It's about:

• Optimizing Fulfillment Performance: Tracking key metrics like order-to-delivery time, on-time shipment rate, and fulfillment costs to identify bottlenecks, improve efficiency, and enhance the customer experience.
• Enhancing Inventory Accuracy: Ensuring accurate inventory data across all channels and locations to prevent stockouts, minimize overstocking, and optimize fulfillment decisions.
• Understanding Cost to Serve: Analyzing the true cost of fulfilling orders, including labor, shipping, packaging, and returns, to identify areas for cost optimization and improve profitability.
• Driving Customer Engagement: Leveraging OMS data to personalize the customer journey, offer relevant recommendations, and provide proactive communication to foster loyalty and drive repeat purchases.
• Unlocking Revenue Opportunities: Using OMS data to identify new revenue streams, such as offering premium delivery options, personalized bundles, and subscription services.
  
  
  

Unearthing the Challenges: Where OMS Data Gets Tricky (00:11:33)

While OMS data holds immense potential, extracting meaningful insights and driving actionable improvements can be challenging. Common obstacles include:

• Data Silos and Integration: OMS data often resides in disparate systems, making it difficult to get a holistic view of the customer journey and identify cross-functional dependencies.
• Data Accuracy and Reconciliation: Maintaining accurate and consistent inventory data across all channels and locations is a constant challenge, requiring robust processes and technology solutions.
• Employee Performance Analysis: Tracking and analyzing employee performance, particularly in omnichannel environments where store associates play a crucial role in fulfillment, can be complex and require specialized tools and metrics.
• Sourcing Optimization: Analyzing sourcing data to optimize fulfillment decisions, minimize shipping costs, and ensure timely delivery can be challenging, especially in dynamic environments with fluctuating demand and supply chain disruptions.
  
  
  

Post-Purchase Power: Leveraging OMS Data to Delight Customers (00:35:00)

The post-purchase experience is a critical touchpoint in the customer journey, and OMS data can be a powerful tool for creating more personalized and satisfying experiences. Consider these innovative applications:

• Self-Service Order Management: Empower customers with self-service tools to modify orders, cancel items, manage backorders, and track shipments, reducing reliance on customer service and enhancing convenience.
• Proactive Communication: Utilize OMS data to trigger automated notifications and updates, keeping customers informed about order status, potential delays, and delivery expectations.
• Personalized Recommendations: Leverage purchase history and browsing behavior to offer relevant product recommendations and targeted promotions, increasing customer engagement and driving repeat purchases.
• Dynamic Order Routing: Utilize real-time inventory data and order information to dynamically route orders to the most efficient fulfillment location, minimizing shipping costs and delivery times.
  
  
  

AI-Powered Integration: Accelerating the Data Revolution (00:37:58)

Artificial intelligence (AI) is transforming the way we manage and utilize data, and OMS is no exception. AI-powered solutions can streamline data integration and mapping processes, enabling:

• Automated Data Mapping: AI algorithms can automatically identify and map data fields between different systems, reducing manual effort and improving accuracy.
• Real-time Data Validation: AI can validate data in real-time, identifying inconsistencies and errors that can impact fulfillment accuracy and customer satisfaction.
• Predictive Analytics: AI can analyze historical data and identify patterns to predict future demand, optimize inventory levels, and proactively address potential issues.

The Ripple Effect: Understanding the True Cost of Inventory Inaccuracy (00:40:43)

Inventory inaccuracy has a ripple effect that extends far beyond the warehouse. It can impact customer service interactions, increase return rates, and ultimately, erode customer lifetime value. To fully grasp the consequences of inaccurate inventory, retailers must:

• Connect the Dots: Analyze the relationship between inventory accuracy, fulfillment performance, customer service inquiries, and return rates to understand the full impact on the business.
• Quantify the Costs: Calculate the financial impact of inventory inaccuracy, including lost sales, expedited shipping fees, increased customer service costs, and lost customer lifetime value.
• Invest in Data Visualization: Utilize data visualization tools to communicate the impact of inventory inaccuracy to stakeholders and drive investment in improvement initiatives.

The OMS Digital Twin: A Glimpse into the Future of Fulfillment (00:44:46)

The concept of a "digital twin" for the OMS is gaining traction as a powerful tool for optimizing fulfillment operations and predicting future outcomes. By creating a virtual replica of the OMS, retailers can:

• Simulate Scenarios: Test different scenarios and analyze their impact on fulfillment performance, inventory levels, and customer experience.
• Predict Potential Issues: Identify potential bottlenecks and disruptions before they occur, allowing for proactive mitigation strategies.
• Optimize Decision-Making: Use real-time data and historical patterns to inform fulfillment decisions, such as order routing, inventory allocation, and capacity planning.

The Perfect Order Index: A Holistic Measure of Operational Excellence (00:47:29)

The Perfect Order Index (POI) is a valuable metric for assessing the overall effectiveness of order fulfillment, taking into account factors like on-time delivery, order accuracy, and damage-free shipping. To maximize the value of the POI, retailers should:

• Go Beyond the Number: Analyze the underlying factors that contribute to the POI score, such as inventory accuracy, picking and packing efficiency, and carrier performance.
• Identify Areas for Improvement: Use the POI to pinpoint specific areas where improvements can be made to enhance fulfillment accuracy and customer satisfaction.
• Track Trends Over Time: Monitor the POI over time to assess the impact of process changes, technology implementations, and other initiatives aimed at improving fulfillment performance.

Returns Optimization: Turning a Cost Center into a Value Driver (00:49:22)

Returns are an inevitable part of eCommerce, but they don't have to be a drain on profitability. By optimizing the returns process, retailers can:

• Reduce Costs: Minimize the costs associated with processing returns, including shipping, handling, and restocking.
• Improve Customer Satisfaction: Offer a hassle-free return experience that builds customer trust and loyalty.
• Gather Valuable Data: Analyze return reasons to identify product quality issues, improve sizing and fit information, and optimize product descriptions.
• Drive Recommerce Initiatives: Resell returned items through dedicated channels or partnerships to recapture value and reduce waste.

Recommerce: Embracing the Circular Economy (00:52:28)

Recommerce, the selling of previously owned or used products, is a rapidly growing segment of the eCommerce market, driven by increasing consumer awareness of sustainability and the desire for affordable options. OMS systems will play a crucial role in enabling recommerce initiatives, requiring new functionalities and integrations to:

• Manage Inventory: Track the condition and location of returned items and integrate with recommerce platforms or marketplaces.
• Process Orders: Handle recommerce orders efficiently, including pricing, fulfillment, and customer service.
• Ensure Transparency: Provide clear and accurate information about the condition of recommerce items to manage customer expectations.