To help overcome and manage assortment planning challenges, such as product variety, data, and rationalization decisions, across your retail supply chains, we:

 1. Handle a variety of retail products with advanced data analytics

• Qualitative approach: For strategically important categories with similar stock keeping units (SKUs), take time to check the data and rationalize any duplicative low performers. This helps ensure and account for all performance metrics (for example, sales, margin, purge, etc.).
• Handling different product size: Make sure that the attributes for random weight items are normalized to help ensure customer data is up to date.
• Item’s sustainability: Even if sales of certain item may be low, having this item in the assortment could be crucial to retain a certain type of customer.
• Basket size: Leverage advanced key performance indicators (KPIs) such as avg. basket size by category, basket penetration rate, cross-sell ratio, etc. for tracking an item’s average basket size. This helps gain deeper insights into customer behavior and product performance.

 2. Consider the importance of sales channels 

• Product rationalization: To cater to differing customer preferences between brick-and-mortar, eCommerce delivery, and eCommerce pickup, check performance across all channels before making a rationalization decision.
• Handling asymmetrical item performance: If a given item has asymmetrical performance between channels, consider offering it only in that high-performing channel.

To help overcome demand planning challenges, such as statistical forecasting and promotion lift planning and reviews, we:

  1. Implement data-driven collaborative planning

• Data-driven demand planning: Leverage data from various sources to help algorithms analyze vast historical data and detect subtle demand signals—such as weather patterns, social media posts etc. that may elude traditional analysis.
• Demand sensing: Actively monitor real-time market signals such as customer feedback, social media sentiment and point-of-sale data to adjust forecasts as needed.
• Collaborative planning: Involve multiple stakeholders in the process, such as suppliers, distributors, sales teams, and marketing teams to create a shared and accurate view of the demand.

  2. Determine historical promotional lift

• Unified view: Collate data from different sources to create a combined view of past promotions with relevant information (for example, product, promotion timing, offer, promotion type, channel etc.).

One way to determine historical promotion lift can be to use parameters and statistical analysis:

•  Parameters: Define promotion by a set of promotion parameters (for example, timing, discount, type etc.).
• Statistical analysis: Perform statistical analysis to determine seasonality and historical lift. Lift can be determined by comparing baseline demand for a product in a week against the actual sales that happened during that week.

 3. Generate future promotional lift

• Use machine learning: For future promotions, we can generate a lift based on regression analysis or any advanced machine learning model of historical lifts for similar promotions. Suggested lift from the mechanism can then be used to review the lift coming from the marketing team on an exception basis.

To help overcome supply planning challenges, such as plan generation, plan adherence, and supplier collaboration, we utilize:

 1. Integrated planning

• Advanced planning solutions (APS): Use a centralized system to integrate demand, supply, inventory, and replenishment for full visibility and cross-functional collaboration.
• Concurrent planning: Use real-time data for quick adjustments to the supply plan without waiting for the next cycle.
• Centralized planning process: Centralize inventory and replenishment planning for both distribution centers and stores to align planning and execution.
• Scenario planning: Simulate different supply options to ensure they are operationally feasible and financially viable.

 2. Responsive execution

• Responsive demand-supply matching: Detect demand and supply issues, align supply with business goals, and adjust short-term forecasts based on current constraints.
• One plan: Ensure all teams follow and execute a unified plan.
• Closed loop feedback: Use execution feedback to adjust future supply plans.

 3. Effective supplier collaboration

• Joint business planning: Work with suppliers on strategy, forecasting, and inventory; consider supplier capacities for promotions, and get input on campaigns and displays.
• Digitized collaborative planning, forecasting and replenishment (CPFR): Use digital tools for real-time CPFR across the supply chain.
• Aligned goals and KPIs: Set and track shared goals and performance targets with suppliers, with clear consequences for not meeting them.

To help overcome inventory planning challenges, such as retail inventory management and supply chain capabilities, we:

 1. Define inventory baseline

• Baseline development: Conduct stakeholder interviews and analyze data to establish baseline for current state inventory.
• Target alignment: Obtain leadership alignment on aspired targets and “to be” state.

 2. Deploy inventory analytics to identify excess/insufficient inventory

• Product segmentation: Segment products based on units sold, value, velocity etc.
• Establish target inventory levels: Define target inventory based on product segments, using parameters such as economic order quantity (EOQ), buffer stock, forecast, coverage days, shelf life, etc.
• Determine excess/insufficient inventory: If the Inventory on Hand > Max Target Inventory, flag that as Excess. If Inventory on Hand < Min Target, flag that as Insufficient.

3. Potential resolution steps

• We can clear off excess inventory using measures such as flash sales, volume discounts and product bundling.
• We can remedy insufficient inventory issues by: modifying Safety levels (based on parameters such as fill rate, demand variability, supply variability, and lead time); implementing real-time tracking and automated reordering; and strengthening supplier base with backups.

 4. Scenario development

• Inventory drivers’ validation: Validate the calculation methodology and baseline of key drivers of inventory such as forecast accuracy, supplier variability, lead time, lot size, and replenishment frequency.
• “What if” scenarios: Develop a list of “what if” scenarios, execute them and assess the size of the prize based on impact of these drivers on inventory improvement.

 5. Identify and act on high priority inventory opportunities

• Improvement levers identification: Prioritize the drivers to yield inventory improvement based on the scenario analysis.
• Execution: Define the north star for the identified drivers, develop roadmap and business case to realize capability enhancement for these drivers.
• Monitoring and sustenance: Monitor progress to inventory objectives, and develop ongoing process, governance and cadence to track and report KPIs for the identified capabilities.

To help overcome logistics and distribution challenges, such as infrastructure, shifting focuses, and tax and regulations, we leverage:

  1. Warehousing operations

• Warehouse location strategy: Optimal number and location of warehouses (based on greenfield and scenario analysis) to limit “overservice” and high fixed costs.
• Part segmentation and policies: Parts segmentation considering demand velocity, volatility, and volume is foundational to tailoring network and deployment policies to segments.
• Inventory stocking strategy: Balance increasing stock availability vs. reducing stocking costs while addressing goals of working capital and national fill.

  2. Freight operations (inbound and outbound)  

• Mode and carrier utilization analysis: Right mode mix (intermodal vs. truck) and carrier mix for improved carrier utilization and compliance.
• Flow path analysis: Best path (lane) for flow of products from supplier to dealer and reduce number of unplanned moves or internal transfers that can add costs.
• Freight sourcing opportunities: Optimize the mix of own vs. third-party logistics (3PL) fleet, and minimize the cost of transportation by benchmarking against market prices through sourcing events.