1 Introduction
In response to the growing confusion and numerous inquiries from users and colleagues regarding the concept of product velocity, this article aims to demystify this essential metric and its role in the retail industry. Understanding product velocity is crucial for monitoring sales performance and creating effective sales strategies. In the following sections, I will delve into the importance of velocity, its impact on product placement, and how retail suppliers can leverage this metric for long-term success.
2 What is Product Velocity?
Velocity is a metric that measures the rate of sales of a product within a specific store and is usually expressed in units sold per store per week. It is an essential metric for retail suppliers as it provides insights into consumer demand, product popularity, and the effectiveness of marketing and distribution strategies and has a direct impact on growth and sales. Velocity in math represented by: Velocity = Sales \div Distribution, is a critical component of the fundamental retail calculation, where sales can derived from the product’s velocity multiplied by its distribution.
3 Why are We all Fussing over it?
Having a thorough understanding of the interplay between velocity and distribution is crucial in crafting an effective sales strategy. Retailers rely on velocity as a principal metric when allocating limited shelf space as it assists them in predicting the potential turnover of various products. For example, products with high velocity are more likely to be placed in prominent locations within the store, such as gondola, end caps or eye-level shelves, which can increase their visibility and attract more customers.
Velocity also serves as a determinant for curating the most suitable mix of items for a certain category. Retailers can strategically balance innovative products with slower velocities with well-established, high-performing products to optimize sales.
In the retail industry, having high-quality distribution is essential, and velocity serves as a key indicator. When a brand is successfully launched in fitting stores, a virtuous cycle is created, where high-velocity products attract more buyers. As a result of continued placement in compatible stores, the product’s velocity escalates, ultimately ensuring success. However, the reverse can also be true: if a product’s velocity is low and it is situated in inappropriate stores, it becomes less enticing to potential buyers. As an emerging brand eager for distribution opportunities, it’s crucial not to settle for unsuitable stores, even as a small brand.
With above information, velocity is an essential metric, that can determine a product’s success or failure in the retail industry. It is critical to understand the interplay between velocity and distribution to create an effective sales strategy. By disclosing a product’s velocity, suppliers can assist retailers in making informed decisions about product placement and selection. As an emerging brand, it is crucial to focus on finding fitting stores that can help to create a virtuous cycle of high-velocity sales and long-term success.
4 Two key Product Velocity Measures: ROS and SPPD
As previously stated that velocity can be expressed as Equation 1:
Velocity = Sales \div Distribution \tag{1}
Here, distribution has not specifically defined leading to different metrics with different distribution measures used. Distribution can be either store distribution or weighted distribution. With different distribution metric used, there are two key product velocity measures used by business analysts: Rate of Sales (ROS) and Sales per Point of Distribution (SPPD), as illustrated in Figure 1.
flowchart LR A[Velocity] --> G[Sales] A --> B[Distribution] B --> C[Store Distribution] B -.-> D[Weighted Distribution] C --> E[[ROS]] D -.-> F[[SPPD]] G --> E G -.-> F subgraph Metrics E F end style A fill:#00b300,stroke:#333,stroke-width:4px; style G fill:#B9DEF8,stroke:#333,stroke-width:1px; style B fill:#B9DEF8,stroke:#333,stroke-width:1px; style E fill:#e0e332,stroke:#333,stroke-width:2px; style F fill:#e0e332,stroke:#333,stroke-width:2px; style Metrics fill:#ffe0b3;
Both ROS and SPPD are important for consumer health product manufacturers for several reasons:
Inventory management: By understanding product velocity, manufacturers can optimize their inventory levels, reducing the risk of stockouts or overstocking, which can lead to waste and increased costs.
Marketing strategy: These metrics help manufacturers identify trends in consumer preferences and tailor their marketing campaigns accordingly. For example, if a certain cough syrup has a high ROS during flu season, the manufacturer can allocate more promotional resources to capitalize on the increased demand.
Distribution network efficiency: By analyzing SPPD, manufacturers can identify underperforming locations and take corrective actions, such as negotiating better contracts or changing the product mix available in those outlets.
Product lifecycle management: Tracking product velocity helps manufacturers understand the various stages of a product’s lifecycle, allowing them to make informed decisions about when to introduce new products, discontinue underperforming ones, or revamp their offerings.
Using these product velocity measures, a business analyst can provide valuable insights and recommendations to help manufacturers optimize their sales performance, manage inventory effectively, and ultimately increase their bottom line.
For brand teams, ROS helps you understand which locations are driving your velocity. For example, ROS shows an average 100 bottles Vitamin D per week, the best store could be moving 150 bottles and the lowest performer could be at 10 bottles. The store with the strongest demand is either doing something right or their shoppers are your ideal customers. Similarly, the lowest performing store might need to correct some missteps, or their audience might be different than the others. Whatever the case is, you want to understand what’s happening each store and adapt accordingly.
Using SPPD, a manufacturer may analyze SPPD at the retailer level to understand which retailers are generating the most sales for their products. If a certain pharmacy chain has a high SPPD, it could indicate that the pharmacy’s customer base has a strong preference for the manufacturer’s products, or that the pharmacy’s merchandising and marketing efforts are particularly effective. In this case, the manufacturer might choose to strengthen their relationship with this retailer, invest in co-marketing efforts, or use this retailer as a benchmark for best practices in distribution and merchandising.
Similarly, a manufacturer might analyze SPPD at the banner or channel level to identify the most effective sales channels for their products. For instance, they may find that their products perform exceptionally well in health-focused grocery stores or online channels compared to traditional supermarkets. This information would allow the manufacturer to prioritize distribution efforts in these high-performing channels and allocate resources accordingly.
When analyzing SPPD at the total national level, manufacturers can gain insights into their overall market performance in comparison to competitors. For example, if a manufacturer’s SPPD is higher than that of their main competitors, it could indicate that their products are more appealing to consumers, or that their distribution and marketing strategies are more effective. This information can be used to make strategic decisions about product development, marketing investments, and distribution partnerships.
While both ROS and SPPD measure the product velocity,m SPPD is regarded as an improved measures over ROS because it incorporates store size by using a store turnover weighted distribution measure in the denominator.
5 ROS and SPPD Calculation Examples
Take an example of selling allergy products in the state of Queensland, the examples below illustrate how ROS and SPPD are computed. For simplicity we use 10 weeks as the observation period for easier calculation.
5.1 ROS Example
Allergy OTC Drug | No. of Stores | Total Sales | No. of Weeks | ROS |
---|---|---|---|---|
Allergy SKU 1 | 500 | 50,000 | 10 | 10 |
Allergy SKU 2 | 300 | 45,000 | 10 | 15 |
Allergy SKU 3 | 600 | 48,000 | 10 | 8 |
Allergy SKU 4 | 400 | 40,000 | 10 | 10 |
Allergy SKU 5 | 350 | 38,500 | 10 | 11 |
5.2 SPPD Example
Allergy OTC Drug | No. of Stores | Total Sales | Store Turnover(Million) | Weighted Dist(%) | SPPD |
---|---|---|---|---|---|
Allergy SKU 1 | 500 | 50,000 | 560 | 47 | 1071 |
Allergy SKU 2 | 300 | 45,000 | 450 | 38 | 1200 |
Allergy SKU 3 | 600 | 48,000 | 280 | 23 | 2057 |
Allergy SKU 4 | 400 | 40,000 | 380 | 32 | 1263 |
Allergy SKU 5 | 350 | 38,500 | 400 | 33 | 1155 |
Total | 1250 1 | 221500 | 1200 |
6 ROS and SPPD Results Interpretation
As illustrated in the above examples in Table 1 and Table 2, we have 5 Allergy OTC SKUs, each has distributed in different number of pharmacy stores with different size in the state of Queensland. The “Total Sales” column shows the total revenue generated by each SKU across all stores distributed to.
Based on Table 1, we can see that Allergy SKU 2 has the highest ROS
, indicating that it is performing well in the pharmacies where it is stocked. This may prompt the manufacturer to expand its distribution to new pharmacies, as increased distribution could lead to further sales growth. And we can notice that this particular SKU has a low store distribution.
Based on Table 2, we can see that Allergy SKU 3 has the highest SPPD
, indicating that Allergy SKU 3 is moving relatively fast in the pharmacies where it is stocked comparing to other products. This may prompt the manufacturer to expand its distribution to other pharmacies, as increased distribution could lead to further sales growth. And we can notice that this particular SKU has a low weighted distribution, which means currently the Allergy SKU 3 only stocked by those relatively small pharmacies.
Upon reviewing Table 1 and Table 2, we can draw some significant insights that can help manufacturers to evaluate the effectiveness of their distribution network and identify potential areas for expansion or improvement.
Table 1 shows that Allergy SKU 2 has the highest ROS, which indicates that it is performing well in the pharmacies where it is stocked. However, we also note that this particular SKU has a low store distribution, which means it is only available in a limited number of stores. To capitalize on the high ROS and to further increase sales, the manufacturer could consider expanding its distribution to new pharmacies, thereby increasing its reach to a broader customer base.
In contrast, Table 2 reveals that Allergy SKU 3 has the highest SPPD, which suggests that it is moving relatively fast in the pharmacies where it is stocked compared to other Allergy SKUs. This could be an indicator of higher demand for this product, and expanding its distribution to more pharmacies could lead to further sales growth. However, it is worth noting that this particular SKU has a low weighted distribution, which means it is currently stocked only by relatively small pharmacies. To increase its reach and tap into its high SPPD, the manufacturer could focus on expanding its distribution to larger pharmacies and retailers.
While Table 1 and Table 2 show different results, it is important to note that ROS and SPPD are two distinct velocity metrics that measure different aspects of a product’s performance.
ROS measures the rate of sale relative to store distribution, which can provide insights into the product’s performance within a specific store. In contrast, SPPD measures the average sales generated from each market(location) where the product is available for sale, which can provide insights into the effectiveness of a product’s distribution network.
In the case of Allergy SKUs 2 and 3, we observe conflicting results, with SKU 2 having a higher ROS but lower SPPD, and SKU 3 having a higher SPPD but lower ROS. However, this conflict may not necessarily be a problem, as both metrics can provide valuable insights for manufacturers to make informed decisions regarding their distribution network. Indeed, in most occassion we will need to reference to both metric to draw a concrete sales plan.
For example, while SKU 2 may have a high ROS, its low store distribution means that it has limited reach and may benefit from increased distribution to reach a broader customer base. On the other hand, while SKU 3 may have a high SPPD, its low weighted distribution means that it is currently only available in relatively small pharmacies, and expanding its distribution to larger retailers could lead to further sales growth.
We can surely conclude while conflicting results between different metrics can sometimes occur, it is essential to consider the unique insights provided by each metric and how they can be used to optimize a product’s performance within its distribution network.
7 Velocity Time Period Consideration
When conducting velocity analysis for metrics such as ROS and SPPD, I typically prefer to use a 13-week period. This duration allows for a more accurate assessment of performance as it accounts for changes in conditions that can occur over time. In some cases, I may also use a 4-week period, but this may be deemed too short, while a 52-week period may be considered too long. However, it’s important to note that the optimal time period for velocity analysis varies depending on the product. For example, new products may need to be monitored weekly, while slow-moving products may require longer durations. Additionally, data availability and limitations may constrain the choice of time period, with many retailers only able to access 13-week distribution data.
8 Velocity Cross-Geographic Consideration
When analyzing velocity measures such as ROS and SPPD, it is important to consider that comparing data between two different geographic areas with distinct store sizes, populations, and market sizes is not recommended. Such comparisons could lead to inaccurate conclusions. In situations where cross-geographic comparisons are necessary, alternative measures should be employed to ensure a fair and meaningful analysis.
9 References
Footnotes
Please note the total No. Of Store here is not the sum of the column as SKUs share some stores in common. The same for Store turnover, the total store turnover is the turnover of all 1250 stores not the sum of the column.↩︎