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Wal-Mart Integration - Causal Chains And Strategy Essay

¶ … Wal-Mart) Integration - Causal Chains and Strategy Wal-Mart Integration - Causal Chains and Strategy

Walmart's emergence as a global leader of mass merchandising and discount retailing is attributable to the company's continual pursuit of excellence in supply chain management, logistics, advanced reverse logistics processes and an exceptionally strong analytically-driven corporate culture. Walmart openly admits in their filings with the Securities and Exchange Commission (SEC) and in their annual reports that they have their own satellite network, often renting the majority of transporters on satellites circling earth today to transport sales-out, promotion results and pricing analysis from each store directly to its headquarters in Bentonville, Arkansas (WalMart Investor Relations, 2013). Walmart's data-centric culture resembles the Untied Parcel Service (UPS) from the perspective of supply chain planning, execution and optimization (Alghalith, 2005). Walmart also invests heavily in the areas of advanced material handling technologies including Radio Frequency Identification (RFID) to continually improve the accuracy and speed of performance in all distribution centers (Powanga, Powanga, 2008).

The balanced scorecard (BSC) approach is a very useful tool for galvanizing the many functional areas of an organization together in pursuit of a common vision and mission. Combining learning and growth, internal business processes, customer and financial objectives, measures, targets and actions into a unified strategy eliminates distractions and keeps an organization focused on its vision, mission, sort and long-range objectives (Kaplan, Norton, 2001). The BSC approach is also indispensable for enabling a thorough causal chain analysis of an organization, which can quickly highlight areas for process performance improvements (Kaplan, Norton, 2001). The BSC framework and causal chain analysis is especially well suited for Walmart as supply chain management's many process areas have a high degree of variability and dependence on other departments throughout the company (Park, Min, Park, 2011). This analysis progresses through a balanced scorecard analysis of Walmart based on learning and growth, internal business, customer and financial perspectives. Table 1 provides a consolidated analysis of Walmart Operations based on previous analysis of each of these four vital functional areas of Walmart. Please see the Appendix to see the individual tables for learning and growth, internal business perspective, customer perspective and financial perspective. Table 1 is the foundation of casual chain analysis completed in this analysis as well.

Consolidated Analysis of Walmart Operations and Casual Chain Analysis

The BSC framework architected to analyze Walmart performance is balanced between their supply chain and logistics expertise that rivals the United Parcel Service (Alghalith, 2005) and the company's intensive reliance on analytics and metrics. Marketing at Walmart is based on thorough customer analysis using advanced predictive analytics software in conjunction with intensive research into the personas, or aggregate representations of their customer segments (Frazier, 2006). Continual supply chain performance, logistics and pricing improvements are the highest priorities for Walmart, all galvanized around keeping the loyalty of the Price Value Shopper. The distribution of customer segments by customer loyalty is shown to the right.

Table 1: Consolidated Analysis of Walmart Operations

Objective

Measure

Target

Action

Financial

Increase inventory turns

Increase store profitability

Reduce employee turnover

25% in all Supercenter locations

10% through more effective pricing

10% in Supercenters

Expected level of performance: eight times a year

Expected level of performance: 10% Gross Contribution Margin

Expected level of performance: 10% less personnel turnover

Improve internal reporting and analysis and reduce slow-selling products from the mix of all items carried.

More effective price management with specials and coupons to drive up sales and increase customer purchases.

Increase the use of personnel management policies and programs to motivate employees to stay instead of leave; increase the use of compensation and performance raises, recognition programs

Customer

To increase same store sales within the Value Shopper segment

To increase more shoppers in the Price Value Shopper segment nationally

To reduce churn in all customer segments

25% over the next 90 days and sustain this performance level yearly

Increase 2% more shoppers to the Price Value Shopper segment

10% by increasing bundling on electronics and apparel

Expected level of performance: four times a year

Expected level of financial [performance gain: 18% of total sales in most profitable, loyal customer segment

Expected level of performance 10% reduction in churn will lead to a 1% increase in Return on Sales

Using analytics, determine the best possible mix of products to attract Price Value Shoppers back into stores so they will purchase more often

Recruitment through referrals and participation coupons for existing Price Value Shoppers to recruit their friends and family

Reduce churn by offering more discounts and bundles on the most popular product for the Price Value Shopper. Provide coupons for food and clothing for this segment to drive cross shopping in other stores...

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sales-out data for the Price Value Shopper segment
(%) of stock-outs reduced on 100 best-selling products to the price Value Shopper segment

Packaging waste reduction of 35% through recycling and reverse logistics re-use

Reduce inventory carrying costs 20% (admin costs of holding inventory)

Increase inventory turns by 20% through better logistics coordination with top 100 CPG suppliers

Measure impact of operations performance improvement through the use of on-time delivery metrics; gross margin improvement attained through inventory mix optimization and more rapid inventory turns

Expected level of performance: Monthly

Expected level of performance: measured on a quarterly basis

Expected level of performance: Monthly

Measuring forecast accuracy for the Price Value Shopper segment involves defining their most-purchased items and measuring forecast performance monthly relative to sales-out data across all stores.

Using reverse logistics to better manage the highest volume commodity products partnering with Procter & Gamble, Unilever, and other consumer packaged good companies to reduce inventory carrying costs; reverse logistics increases recycling efficiency, reduces inventory carrying costs; increases inventory turns by adding greater accuracy and precision to forecasts

Begin supporting mixed palate mode shipping from top 100 CPG suppliers who provide majority of consumable, commodity-based products for the Price Value Shopper

Learning

Train all supply chain managers in advanced optimization techniques including lean process improvement relating to inventory management

Increase pricing accuracy through the use of advanced analytics and metrics

Reduce turnover of supply chain and logistics experts

Per Supercenter Inventory Turns

Gross Margin on Most Sold Products

Reduction in employee turnover

15% improvement in inventory turns per superstore within 6 months

Increase gross contribution margin by 10% on the 100 most commoditized products

20% reduction in employee turnover in the supply chain, logistics and distribution center operations areas of Walmart.

Provide Six Sigma Black Belt training internally to provide opportunities for employees to gain greater mastery of this area; measure and reward on-the-job performance increases

Increase training on advanced analytics applications from IBM, SAS and other vendors who provide price optimization technologies

Offering Six Sigma Black Belt training and certification will also help with this specific objective, as will paying bonuses to those managers who deliver the greatest gains in supply chain performance.

Over the last decade Walmart has continued to pursue a demand management-based supply chain strategy that is increasingly defined by forecasts and less by purely theoretical optimization strategies (Zhu, Singh, Manuszak, 2009). Lessons learned from failures in Germany and South Korea (Christopherson, 2007) and the turn-around in international operations as evidenced by their success in China (Ming-Ling, Donegan, Ganon, Kan, 2011) served to further validate a very customer-centric demand management supply chain strategy. As a result, as the Price Value Shopper goes in terms of demand forecast, so go much of the focus and prioritization within the Walmart supply chain. This makes supply chain responsiveness to all customer, especially, the Price Vale Shopper, a very high priority. Figure 1, Causal Chain Analysis for Increasing Supply Chain Accuracy and Speed takes into account the high priority of keeping the Price Value Shopper loyal and also alleviating stock-outs with a major factor in shoppers in discount retailers going to other stores (Rosenblum, 2004). This is the most strategic aspect of the Walmart business model, hence its analysis as a casual chain analysis.

Figure 1: Causal Chain Analysis for Increasing Supply Chain Accuracy and Speed

Figure 1, Causal Chain Analysis for Increasing Supply Chain Accuracy and Speed illustrates how Walmart can quickly use investments in training supply chain managements in advanced optimization techniques to drive greater pricing accuracy. This strategy is consistent with their internal culture that places a high value on analytics (Duke, 2010). It is a strategy that addresses the inherent complexities of operating a business model that is highly dependent on supply chain performance, pricing optimization and flawless retail execution to keep costs at a level of generate positive gross margins (Park, Min, Park, 2011) (WalMart Investor Relations, 2013). The training is used as a catalyst for driving internal business improvements in forecasting accuracy with the goal of 30% improvement in key segments, with the Price Value Shopper being by far the most critical. Long-term this will lead to…

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Figure 1: Causal Chain Analysis for Increasing Supply Chain Accuracy and Speed

Figure 1, Causal Chain Analysis for Increasing Supply Chain Accuracy and Speed illustrates how Walmart can quickly use investments in training supply chain managements in advanced optimization techniques to drive greater pricing accuracy. This strategy is consistent with their internal culture that places a high value on analytics (Duke, 2010). It is a strategy that addresses the inherent complexities of operating a business model that is highly dependent on supply chain performance, pricing optimization and flawless retail execution to keep costs at a level of generate positive gross margins (Park, Min, Park, 2011) (WalMart Investor Relations, 2013). The training is used as a catalyst for driving internal business improvements in forecasting accuracy with the goal of 30% improvement in key segments, with the Price Value Shopper being by far the most critical. Long-term this will lead to greater same-store in store sales in the Price Value Shopper segment, leading to a corresponding increase in inventory turns. Within nine to twelve months of intensive training the workflow shown in Figure 1 will yield increases in inventory turns and profitability.

Figure 2, Causal Chain Analysis -- Stabilizing Supply Chain Expertise to Ensure Growth illustrates the second most critical aspect of Walmart's strategic initiatives and programs. The retention and professional development of its key supply chain experts is essential for the company to continually improve forecasting accuracy. Walmart sees this as so strategic, it is called out in their annual report and is perennially one of the top ten initiatives internally (WalMart Investor Relations, 2013). The continual investment in gaining new insights into how the company get improve supply chain operations also typifies their culture, which is heavily influenced by daily analytical analysis of sales, pricing including price elasticity, and discount analysis data (WalMart Investor Relations, 2013). Walmart senior management sees this specific casual chain analysis as essential to transforming knowledge
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