Markup and Markdown
Understanding pricing strategies such as markups and markdowns is essential for suppliers. This article explores the concepts of markup and markdown, their significance, and how suppliers can leverage related data to potentially optimize operations and profitability.
What is Markup and Markdown?
Markup is the increase of the price of merchandise – or marking up – while markdown is the decrease of the price – or marking down. Markups and markdowns are pricing actions that affect the overall profitability of an item. In the Store Markup & Markdown (MUMD) dataset, markups are indicated with a negative number, while markdowns are indicated with a positive number.
Markup
A markup refers to the difference between the cost of goods sold (COGS) and the retail price. Walmart typically maintains low everyday prices through volume purchasing, resulting in markup percentages that are often lower than industry averages.
Markdown
A markdown is a price reduction applied to an item, either temporarily for Rollbacks or permanently for clearance. There are various types of markdowns:
- Reactive Markdown: Used when an item isn’t selling well, to clear inventory.
- Rollback: A temporary price reduction to drive sales.
- Clearance Markdown: Permanent price reduction for items being discontinued.
Common Markups and Markdowns
There are many kinds of markups and markdowns. Below are the most common types:
- Base Price Change: A retail change the Merchant sends to the store due to an error in item setup or to align with other items in the category. A Base Price Change can be a markup or a markdown. These apply only to current inventory in the store.
- Rollbacks: Pass savings on to customers to demonstrate Walmart’s commitment to low prices. Rollbacks are always Home Office-initiated.
- Clearance: Initiated when an item is no longer being sold in-store, and Walmart wants to clear out the current inventory. Clearance can also be initiated at the store level when there is excess stock.
- Customer Value Program (CVP): A markdown completed at the store level to sell a product that is approaching its sell-by date or has damaged packaging.
- CVP Reduction: A markdown taken if the item sells while under CVP pricing.
- CVP Throwaway: The item is marked down to $0 and disposed of.
Other Common Markups and Markdowns
- Damaged Markdown: When a product is damaged in-store, it is marked down to $0 and disposed of.
- Charitable Contributions: Markdown occurs when stock is donated to charities by the store or warehouse.
- Competitive Pricing: Markdown occurs to meet competitor pricing.
- Home Office Tab File: Home Office-initiated markdowns for promotional pricing, holiday pricing, etc.
Supplier Cost Increase: When the supplier provides a cost increase that results in both a cost markup and a retail markup.
How Suppliers Can Use Markup & Markdown Data
Understanding Walmart's EDLP (Everyday Low Price) pricing model may help suppliers align their price strategies more effectively. By analyzing markup and markdown data, suppliers may monitor how stable pricing impacts sales and inventory levels.
Some markup and markdown data provides actionable information. High numbers of CVP markdowns might indicate that there is too much merchandise in the store. Items with high numbers of Damage markdowns might indicate a problem with the packaging or shelving. Competitive Pricing markdowns could indicate a need for further research to ensure Walmart has the lowest price.
Other markup and markdown data is more likely to provide insights. For example, Rollbacks and Home Office Tab Markdowns are Home Office-initiated and generally planned ahead of time. This data informs suppliers of what occurred but does not typically provide actionable next steps.
Products are assessed based on sell-through rates and markdown frequency, making it essential to monitor these metrics regularly. By understanding these trends, suppliers can identify opportunities to adjust inventory planning, improve product durability, or enhance promotional efforts to increase product performance.
Adjusting production and distribution based on insights from markdown data may help avoid overstock and understock situations, leading to more efficient inventory management. Keeping track of how products perform post-markdown provides valuable information for future planning, allowing suppliers to refine their strategies continually.
Strategic markdown planning involves using data to predict the best times for markdowns to help manage inventory without disrupting the EDLP model. This proactive approach may help ensure that inventory levels are maintained optimally, potentially reducing excess stock and enhancing sell-through rates.
Leveraging markdown data may allow suppliers to evaluate product performance and make more informed decisions. By assessing which products require frequent discounts and understanding the reasons behind these discounts, suppliers can adjust production and inventory levels to better match demand. Recognizing products at risk of reduced future orders, discontinuation, or category reset changes may enable suppliers to take proactive measures to address these risks. This might involve improving product design, adjusting pricing strategies, or enhancing promotional efforts to boost product performance.
Products are assessed based on sell-through rates and markdown frequency, making it essential to monitor these metrics regularly. Proposing solutions such as changes to pricing strategies or inventory management can reduce the need for frequent markdowns and potentially improve overall performance. Regularly analyzing markdown data helps identify trends and opportunities for improvement, ensuring that suppliers remain competitive and responsive to market demands.
Adjusting production and distribution based on insights from markdown data may help avoid overstock and understock situations, leading to more efficient inventory management. Keeping track of how products perform post-markdown provides valuable information for future planning, allowing suppliers to refine their strategies continually. Being ready to make proactive adjustments to pricing, inventory, and other strategies based on data insights may help ensure that suppliers can respond swiftly to changing market conditions.
Use Case 1: Seasonal Product Markdown
A supplier of seasonal decorations might use markdown data to plan strategic markdowns after the peak season to clear inventory. By analyzing sales patterns from previous years, the supplier can determine the optimal timing and discount levels for markdowns. This proactive approach may help manage inventory levels and avoid excess stock, ensuring that the supplier can maximize sales without resorting to clearance markdowns.
| Table Name | Technical Name | Business Name |
|---|---|---|
| MUMD | ly_mumd_amt | MUMD Amount - Last Year |
| MUMD | mumd_dt | MUMD Date |
| MUMD | mumd_event_cd | MUMD Event Code |
| MUMD | mumd_event_desc | MUMD Event Description |
| MUMD | mumd_rtl_ind | MUMD Retail Indicator |
| MUMD | mumd_src_cd | MUMD Source Code |
| MUMD | mumd_src_desc | MUMD Source Description |
| MUMD | mumd_type_desc | MUMD Type Description |
| MUMD | ty_mumd_amt | MUMD Amount - This Year |
| MUMD | wm_item_nbr | Walmart Item Number |
| Omni Sales | bus_dt | Business Date |
| Omni Sales | catlg_item_id | Catalog Item ID / eComm Prod ID |
| Omni Sales | ly_auth_based_qty | AUTH Based Item Quantity - Last Year |
| Omni Sales | order_chnl_nm | Order Channel Name |
| Omni Sales | svc_chnl_nm | Service Channel |
| Omni Sales | ty_auth_based_qty | AUTH Based Item Quantity - This Year |
| Omni Sales | ly_shpd_based_qty | Shipped Based Quantity - Last Year |
| Omni Sales | ty_shpd_based_qty | Shipped Based Quantity - This Year |
| Omni Sales | wm_yr_wk_nbr | Walmart Year Week Number |
Use Case 2: Identifying Product Performance Issues
A supplier notices an unusually high number of damage markdowns on a particular product. By analyzing the markdown data, they identify that the packaging is too fragile for store-handling. Based on this insight, the supplier redesigns the packaging to be more durable, reducing damage markdowns and improving overall product profitability.
| Table Name | Technical Name | Business Name |
|---|---|---|
| MUMD | ly_item_qty | Item Quantity - Last Year |
| MUMD | ly_mumd_amt | MUMD Amount - Last Year |
| MUMD | mumd_dt | MUMD Date |
| MUMD | mumd_event_cd | MUMD Event Code |
| MUMD | mumd_event_desc | MUMD Event Description |
| MUMD | mumd_type_desc | MUMD Type Description |
| MUMD | store_nbr | Store Number |
| MUMD | ty_item_qty | Item Quantity - This Year |
| MUMD | ty_mumd_amt | MUMD Amount - This Year |
| MUMD | wm_item_nbr | Walmart Item Number |
Conclusion
Effectively utilizing markup and markdown data enables suppliers to gain deeper insights into product performance, inventory management, and pricing trends. By leveraging this data, suppliers can make informed decisions that may help improve sales forecasting, optimize inventory levels, and refine packaging and promotional strategies. Understanding these pricing actions may help suppliers to adapt to market demands and maintain efficiency in their operations.
