Holistic Sales Performance Analysis for Veal's Sportswear: Unveiling Trends and Informing Strategic Decisions
Enhancing Sales Performance and Profitability in Regional Retail Channels: A Data Analytics Approach for VEAL Sportswear
- INTRODUCTION
VEAL is a top-rated sportswear manufacturer producing sportswear for men and women, operating through six retail locations across five geological regions: Midwest, Northeast, South, Southeast, and West. The company's product portfolio includes two major categories, namely footwear and apparel, distributed through diverse channels. VEAL's product line consists of athletic and street footwear, as well as apparel for both males and females.
1.1 PROBLEM STATEMENT
VEAL is currently facing challenges, particularly insufficient or negligible sales in the South, Southeast, and Northeast regions. Slow sales have led to a revenue shift between channels, possibly influenced by factors such as shifts in consumer preferences, limited promotional activity, and intense competition. As a result, sales performance has declined, adversely affecting revenue and profit. Nonetheless, there is an opportunity to enhance sales performance between the two product categories.
This study aims to probe the dataset for Veal, understand the nature of the problems, offer appropriate remedies, and make better decisions utilizing decision support systems. Decision aid tools, engaging systems based on computers, empower managers to use information and models to tackle challenges. Decision support systems, commonly referred to as 'Business Intelligence,' combine human intellectual capacity with computer-based systems to raise the standard of decisions.
This article provides an overview of how Business Intelligence (BI) can be utilized to improve sales performance in low-performing regions. Management and various departmental teams at Veal must sift through data for reasons and patterns to enable them to make informed decisions swiftly. Using data, situations, and performances from the past and present years, the company will be able to unearth insights and establish distinct plans for each target market.
- THEORETICAL FRAMEWORK
Management should assess opportunities for improving existing businesses through the implementation of a market-penetration strategy, delving deeper into present marketplaces, drawing in fresh clientele, and convincing current clients to buy more frequently. Management should then develop a market-development strategy to identify or create new markets for its current products. Additionally, they should evaluate the feasibility of developing new products tailored to their current markets. Veal will also evaluate the potential to launch novel products in other areas, adopting a diversification strategy.
2.1 COMPETITIVE ANALYSIS
It is necessary to examine the competitive terrain for Veal, analyzing factors such as strategies (cost leadership and differentiation) and competitive forces. This analysis provides insight into how other brands are performing in regions with low sales.
2.2 SUPPLY CHAIN OPTIMIZATION
To meet sales and consumer demands, the ideas of supply chain optimization and distribution network are crucial. Veal needs to evaluate if its supply chain activities are tailored to meet the needs of each location. Operational monitoring and information accessibility within Veal, throughout its ecosystem, can be provided by enabling technology like supply chain management (SCM) systems.
2.3 DATA-BASED DECISION-PROCESS
Data-based decision-process, defined as the act of making decisions based on information rather than gut feeling, includes business practices related to external and internal data collection and analysis. Veal struggles with sales performance and needs a data-based decision-process.
2.4 BIG DATA ANALYTICS ADOPTION
Big Data is a remarkable variety of data types that are sent at different speeds and frequencies. It investigates minute particulars of Veal's business processes and customer interactions. In addition, there is high-end analytics, an assemblage of various application kinds, which can analyze huge data to comprehend and make sense of Veal's transactions. By leveraging big data and analytics, Veal can efficiently respond to market developments and adjust its tactics based on real-time data by promoting a data-driven approach.
3.1 THE DATA-DRIVEN APPROACH
To harness the benefits of big data, a business intelligence system will be developed to assess the impact of exploited data on the company’s performance. In this context, the procedures associated with employing huge data are split into two levels: data management and data analysis. Level one covers processes and layers for sourcing, storing, drilling, and preparing data for analysis, while level two discusses strategies for deciphering and utilizing massive data sets for insightful analysis. Business Intelligence systems process significant volumes of highly accurate information, housed in a centralized repository, to facilitate decision-making.
3.2 BUSINESS INTELLIGENCE SYSTEM (DATA ANALYSIS)
The ability of Veal to acquire information and generate useful knowledge, derived from data analysis, represents their true competitive advantage (Kopanakis et al., 2016).
3.2.1 DASHBOARD CREATION
Dashboards, as visualization tools, contain multiple layers of graphical data designed to detect exceptions. They communicate performance status and trends to the operational, tactical, and strategic levels within an organization, allowing for the timely implementation of actions .
3.2.2 DATA GATHERING Dataset for over 9,000 consumers was sourced from Kaggle and used. As shown in Figure 3, sales information was compiled. Data from Kaggle was exported into a single excel file, and irrelevant columns were eliminated to enhance data readability. “Month”, "Year", "Age", "Age Group", and "Gender" columns were incorporated to calculate metrics. Following data modification, the excel file was uploaded into the power BI application to analyze sales performance indicators using various variables. With the aid of power BI visualization, a range of visual representations, including pie charts, bar charts, line chart and column graphs were constructed. Subsequently, the performance measures were presented in a power BI dashboard for in-depth display and analysis. Measures were presented in a Power BI dashboard for in-depth display and analysis.
3.2.3 THE SLICERS
Slicers in Power BI are dashboard controls that make slicing and dicing calculations easy. Tables, graphs, and charts can be graphically filtered using them. They are the single most used tool for regulating data summarization. The dashboard slicer depicted in figure 4 is made up of six distinct sections namely Year, Gender, Age Group, Sales Channel, Region, and Retailer. It allows Veal’s management to compare sales performance in-depth across various dimensions such as product type sales in various channels, retailers, and regions.
3.2.4 DASHBOARD ANALYSIS
Figure 5 pie-chart reveals 2020 and 2021 sales performance in relation to the product types it produces. There are two product types: (i) footwear - this recorded the highest sales amount, and (ii) apparel. The two segments recorded excellent sales performance as both segments experienced an increase in actual sales in 2021 due to low demand in the COVID year 2020. The rising demand for new apparel fashion & new footwear designs is the possible reason for sales growth between both years. This gives Veal’s management an insight into what product type contributes more to the revenue line and helps allocate resources between the segments.
Figure 6 pie-chart reveals the 2020 and 2021 sales attributable to gender (Male and Female). The chart shows great sales performance in relation to the two genders in both years. Although both sexes displayed excellent sales performance, Male gender saw a slight increase in actual sales over the female gender, hence the percentage of sales recorded in both markets was 54% and 46% respectively. Veal’s management gets a clear picture of which gender market to serve more.
Figure 7 bar chart details 2020 and 2021 sales results of Veal’s product type classified further, across genders. The footwear product type is split between athletic and street type while apparel remains the same. It shows more sales were made selling female apparel while athletic and street footwear sold more in the male category than the female. Veal Managers can use this chart to share data on the best sellers whilst also helping to formulate strategies to stir up sales in slow-moving goods.
Figure 8 bar chart details 2020 and 2021 sales results of both genders across its age group. The age-group is divided into: Youth, Young Adult, Adult, and Seniors. This shows that both genders in the adult bracket recorded the highest sales followed by the senior’s bracket. Upon drill down, Veal’s management can get a much clearer view of gender’s performance as well as identify the areas for targeted production of footwear that will serve the adult market.
Figure 9 bar chart displays the 2020 and 2021 sales from sales channels. The sales channels are divided into: In-store, Online, and Outlet. The chart shows that In-store, Online, and Outlet channels contributed 40%, 28%, and 33% of the sales revenue made. By inference, customers find physical stores and outlets attractive to visit and make their purchases. This information will help both the company’s sales managers & management to ensure that customer shopping experiences in retail stores and outlets are made memorable through hospitality services and loyalty programs offerings to keep them coming back for more purchases. Also, this information could also provide insight for management into proper re-allocation/distribution of inventory across channels.
Figure 10 line chart displays the 2020 and 2021 monthly trend of sales across sales channels. Management uses this chart to keep track of monthly increase or decrease in sales revenue from each of the different channels (In-store, Online, and Outlet). Departmental managers at Veal can also use this to see which month sales were at highest (July – In-store) or lowest (June – Outlet) as quantities fluctuate. This could be because of seasonal sales or deployed sales strategies targeted to stimulate sales.
Figure 11 clustered bar chart displays 2020 and 2021 sales from various retailers across all three channels. Retailers are: West Gear, Walmart, Sports Direct, Kohl, Foot Locker, and Amazon. The chart shows that West Gear recorded the largest sales amount, with 65% of its sales coming from the In-store channel, followed by Foot Locker, whose sales are distributed evenly across all three channels. This information will alert management to the retailers who account for the bulk of Veal’s sales and serves as a reward tool for proper compensation. In addition, management can gain insight into re-allocating/distributing inventory between retailers with this information.
Figure 12 clustered bar chart displays 2020 and 2021 sales from five regions across all channels. Regions are West, Northeast, Southeast, South, and Midwest. The chart shows that West region churned out the largest sales amount with 39% each of its sales made through the In-store and outlet channels, followed by Northeast region, whose sales (62%) are carried out through its in-store channels. It is worth mentioning that the highest sales retailer (West Gear) is domiciled in West region and second largest retailer, Foot Locker is also domiciled in Northeast region. This information will alert the management to the regions that account for the bulk of Veal’s sales. In addition, management can gain insight into re-allocating/distributing inventory across regions.
4.0 CONCLUSION AND RECOMMENDATION
This study’s essence is to portray as well as address the current state of Veal’s business. Some metrics have been brought to light by The illustrated graphics, which should trigger high-level action on management’s part. Proposals have been put forward to turn the sales performance tide in an upward moving trajectory. To streamline and allocate resources properly, Veal’s focal point in setting up a BI system would point management’s direction to the segment and sub-segment with best-sellers which contributes more to the top-line whilst implementing corrective/stimulating strategies to drive the growth of slow-moving products. In regions with little or no channel sales, suggestions such as promotional activities would be effective in raising awareness, Veal could also adopt a cost leadership stance or differentiate itself from its competitors and explore opportunities to identify and develop new markets for its current products. Furthermore, it is critical for management to ensure that supply chain activities are tailored to meet the needs of the different locations, and that supply chain optimization and distribution network are as efficient as possible so that products are available just in time, in appropriate quantities, and in the needed location. And finally, the deployment of a decision support system widely called “Business Intelligence”. The sole aim of this system is to close the strategic gap between the current performance of Veal and its desired performance by providing Veal with the information it needs to stay ahead. It is therefore recommended to the management of Veal to implement Power BI system as an intelligence tool due to the following reasons: (i) the large volume, variety and velocity of data that it handles, (ii) its advanced data visualization which allows for presentation of diverse types of data, (iii) the in-memory database that supports implementation of real-time dashboards and stores metrics in the background, (iv) the almost real-time data that it provides. By integrating the proposed BI system into Veal’s operation, the efficiency of its business processes will be strengthened, it would allow for provision of useful insights, improve organizational performance and decision making and would create competitive advantage using it. Furthermore, it would support the 'data-based philosophy' style that the chief-decision-makers of Veal adhere to.