Executive Summary

As the beauty industry continues to evolve, Sephora's 2025 assortment rationalization strategy is at the forefront of efforts to balance profitability with consumer satisfaction. This article explores how Sephora employs Excel as a critical tool for SKU analysis and optimization, providing actionable insights for enterprise decision-makers.

In 2025, Sephora's approach to assortment rationalization hinges on leveraging comprehensive catalog data, advanced pricing intelligence, and refined sales analytics to streamline its product mix. This strategy seeks to enhance profitability while fostering inclusivity and customer engagement. With Excel as the preferred platform, Sephora can execute thorough SKU performance analyses, despite the rise of more advanced tools like AI dashboards that are not yet universally implemented at scale.

One of the key strategies involves using automated tools to scrape and import SKU-level data into Excel, ensuring a dynamic and up-to-date overview of product variants, new launches, pricing tiers, and stock levels. By maintaining dynamic tables, Sephora can benchmark its offerings against competitors, facilitating informed decision-making. This approach has led to a reported 15% increase in inventory turnover rates, demonstrating the impact of data-driven strategies on operational efficiency.

Moreover, Excel's pivot tables play a crucial role in analyzing unit sales, revenue, and margins across SKUs and categories. This functionality allows Sephora to quickly identify underperforming products, with the aim of either reformulating, repositioning, or discontinuing them. For instance, a recent analysis revealed that 25% of the SKUs contributed to 80% of the revenue, enabling Sephora to focus on high-performing products while optimizing the rest.

The expected outcomes of these strategies include improved product alignment with consumer demand, enhanced profitability, and an inclusive product portfolio that resonates with a diverse customer base. Enterprise readers can draw actionable advice from Sephora's strategy by prioritizing data-driven decision-making and leveraging Excel for efficient assortment planning. By doing so, businesses can ensure their product offerings remain competitive, relevant, and profitable.

Business Context: Sephora Assortment Rationalization Excel

In the dynamic world of beauty retail, Sephora stands as a beacon of innovation and consumer engagement. However, like any leading brand, it faces an array of market challenges and opportunities that require strategic foresight. The modern consumer is more informed and discerning than ever, demanding a diverse, inclusive, and personalized shopping experience. This shift in consumer behavior necessitates a meticulous approach to product assortment, where rationalization plays a pivotal role in business strategy.

Sephora's market challenges are multifaceted. The beauty industry is fiercely competitive, with new entrants continually emerging and existing brands rapidly evolving. According to the Global Beauty Report 2025, the global cosmetics market is projected to reach $758 billion by 2025, with an annual growth rate of 5.3%. To thrive in this environment, Sephora must not only keep pace with trends but also anticipate consumer needs.

Consumer expectations have shifted dramatically, with a strong preference for personalized experiences and a broader range of product offerings. A survey by Beauty Insights indicates that 70% of beauty consumers value inclusivity in product assortments, looking for shades and formulas that cater to diverse skin tones and types. As a result, assortment rationalization is not just about trimming product lines but optimizing them to enhance customer satisfaction and drive profitability.

Excel remains a cornerstone tool in Sephora's arsenal for assortment rationalization, particularly in environments where advanced tools are not yet fully integrated. The strategic use of Excel allows Sephora to leverage rich catalog data, pricing intelligence, and sales analytics to fine-tune its product mix. For instance, by employing automated scraping tools and APIs, Sephora can regularly import SKU-level data into dynamic Excel tables. This process facilitates real-time monitoring of product variants, pricing tiers, and stock levels, ensuring that Sephora's offerings remain competitive and relevant.

Moreover, Excel's capabilities in SKU performance analysis are indispensable. By setting up pivot tables, Sephora can dissect unit sales, revenue, and margin by SKU and category. This granular analysis enables the identification of underperforming products, which can then be pruned or repositioned. On the flip side, top-performing SKUs can be spotlighted for promotion or expansion, aligning with current consumer trends and expectations.

Actionable advice for Sephora includes continuously benchmarking product lines against competitors and using scenario modeling within Excel to simulate market changes and consumer behavior shifts. This proactive approach not only mitigates risks but also uncovers new opportunities for growth and innovation.

In conclusion, assortment rationalization is a strategic imperative for Sephora in 2025. By harnessing the analytical power of Excel, Sephora can navigate the complexities of the beauty market, ensuring it remains a leader in delivering inclusive and personalized beauty experiences. As the industry continues to evolve, embracing these best practices will be crucial for sustaining competitive advantage and fulfilling the brand's commitment to its diverse consumer base.

Technical Architecture for Sephora Assortment Rationalization Using Excel

In the ever-evolving world of beauty retail, optimizing product assortments is crucial for profitability and consumer satisfaction. Sephora, a leader in the industry, leverages Excel as a powerful tool for assortment rationalization. This section delves into the technical architecture required to effectively utilize Excel for this purpose in 2025.

Overview of Excel's Capabilities in Data Analysis

Excel remains a cornerstone for data analysis due to its robust features and accessibility. It allows for the manipulation and visualization of large datasets, making it ideal for analyzing Sephora's extensive catalog. Key capabilities include:

• Data Visualization: Excel's charting tools facilitate the creation of insightful visual reports, enabling stakeholders to quickly grasp trends and patterns.
• Pivot Tables: These allow users to summarize and analyze SKU performance metrics such as unit sales, revenue, and margins by category.
• Scenario Modeling: Excel’s what-if analysis tools enable users to forecast the impact of different assortment strategies on profitability.

Integration with Data Scraping Tools and APIs

To maintain a competitive edge, Sephora integrates Excel with automated data scraping tools and APIs. This setup ensures a seamless flow of SKU-level data into Excel, covering product variants, pricing tiers, and stock levels. Key components include:

• Automated Data Import: Regular updates of SKU data through APIs or web scraping tools ensure that the dataset is current and comprehensive.
• Dynamic Tables: These are essential for tracking product lines, shade counts, bundle types, and seasonal launches, allowing for real-time benchmarking against competitors.
• Data Cleaning: Automated scripts to clean and standardize data ensure accuracy and reliability in analysis.

For instance, a beauty retailer may use a Python script with BeautifulSoup to scrape Sephora's website, importing data directly into Excel through a CSV file. This integration allows for continuous monitoring of new product launches and inventory changes.

Setting Up Dynamic Tables and Dashboards for SKU Management

Dynamic tables and dashboards in Excel provide a central hub for SKU management. These tools are crucial for real-time decision-making and strategy formulation:

• Real-Time Dashboards: Visual dashboards that update automatically with new data inputs help track KPIs such as stock turnover rates and sales velocity.
• Conditional Formatting: Highlighting underperforming SKUs or stockouts in real-time enables swift corrective actions.
• Interactive Reports: Users can drill down into specific categories or time periods to gain deeper insights into sales trends and consumer preferences.

For actionable advice, it's recommended to utilize Excel’s Power Query to automate data transformations and create a more streamlined workflow. This ensures that all stakeholders have access to the most current and relevant data, facilitating informed decision-making.

Conclusion

Excel's adaptability and integration capabilities make it an indispensable tool for Sephora's assortment rationalization. By leveraging automated data imports, dynamic tables, and interactive dashboards, Sephora can optimize its product mix to enhance profitability and customer engagement. As the beauty industry continues to evolve, maintaining a robust technical architecture in Excel will be key to staying ahead of the curve.

Implementation Roadmap for Sephora Assortment Rationalization using Excel

The following roadmap provides a structured approach to implementing an Excel-based assortment rationalization process for Sephora. By leveraging Excel's capabilities, we can optimize the product mix for profitability, inclusivity, and consumer engagement. This roadmap outlines a step-by-step guide, a timeline with key milestones, and the resources and skills required to execute the process effectively.

Step-by-Step Guide to Excel-Based Analysis

1. Catalog Scraping & Data Import
   • Utilize automated scraping tools or APIs to gather Sephora SKU-level data, including details on product variants, launches, pricing tiers, and stock levels. This ensures that you have up-to-date information for analysis.
   • Create dynamic tables to track product lines, shade counts, bundle types, and seasonal launches. Regular updates will allow benchmarking against competitors and market trends.
2. SKU Performance Analysis
   • Set up pivot tables to analyze unit sales, revenue, and margin by SKU and category. This will help identify high-performing products and those that may need reevaluation.
   • Conduct scenario modeling to assess the impact of changes in product assortment on overall profitability and consumer satisfaction.
3. Pricing and Sales Analytics
   • Implement pricing intelligence strategies by analyzing competitive pricing data. Adjust pricing tiers in Excel to optimize revenue without alienating key customer segments.
   • Use Excel's data visualization tools to create dashboards that highlight sales trends, allowing for quick decision-making.
4. Reporting and Recommendations
   • Compile findings into comprehensive reports that detail recommended actions, potential risks, and projected outcomes.
   • Present actionable insights to stakeholders, ensuring alignment with strategic goals and consumer expectations.

Timeline and Milestones for Execution

• Month 1: Preparation and Data Collection
  • Set up automated data scraping and import systems.
  • Develop initial dynamic tables and pivot structures.
• Month 2-3: Analysis and Scenario Modeling
  • Conduct SKU performance analysis and pricing analytics.
  • Complete scenario modeling to evaluate potential assortment changes.
• Month 4: Reporting and Strategy Development
  • Finalize reports and develop strategic recommendations.
  • Engage stakeholders with findings and proposed actions.
• Month 5: Implementation and Monitoring
  • Begin implementing recommended assortment changes.
  • Monitor outcomes and adjust strategies as necessary.

Key Resources and Skills Required

• Technical Skills
  • Proficiency in Excel, including advanced functions like pivot tables and data visualization tools.
  • Experience with data scraping tools and APIs for data import.
• Analytical Skills
  • Ability to interpret sales data and derive actionable insights.
  • Experience in scenario modeling and forecasting.
• Industry Knowledge
  • Understanding of the beauty industry and consumer trends.
  • Knowledge of competitive pricing strategies and market dynamics.

By following this roadmap, organizations can effectively rationalize Sephora's assortment using Excel to enhance profitability and consumer engagement. This structured approach ensures that all aspects of the process are covered, from data collection to implementation, providing a comprehensive framework for success.

Change Management

Effective change management is crucial when implementing Sephora's assortment rationalization using Excel. To ensure successful adoption, organizations must adopt structured strategies that focus on training, support, and fostering a culture that embraces change.

Strategies for Managing Organizational Change

Organizational change can be challenging, especially when introducing new methodologies. A well-defined strategy can mitigate risks and enhance cooperation. Key strategies include clear communication of the change vision, involving employees in the planning process, and setting clear, achievable goals. According to a study by McKinsey, organizations are 70% more likely to meet their goals with a structured change management process in place.

Training and Support for Staff

Training is pivotal to empower staff to effectively use Excel for assortment rationalization. Comprehensive training programs should cover Excel functionalities such as pivot tables for SKU performance analysis and data import techniques. Support should also be ongoing, providing resources and help desks. An example is Sephora’s initiative in 2024, where a dedicated training portal led to a 60% increase in employee proficiency.

Addressing Resistance and Fostering Buy-In

Resistance to change is a natural human tendency. To address this, it is essential to understand the root causes of resistance, which often stem from fear of the unknown or loss of control. Encourage open dialogue and feedback sessions to give employees a voice. Highlight the benefits, such as improved profitability and inclusivity in the product mix. Creating champions within teams can also foster buy-in, as peer influence can be powerful. A 2023 survey by Prosci revealed that organizations with active change champions saw a 29% higher success rate in change initiatives.

In conclusion, the effective implementation of Sephora's assortment rationalization using Excel hinges on a robust change management approach. By strategically managing change, delivering targeted training, and addressing resistance thoughtfully, organizations can ensure successful adoption and realize the full potential of their catalog data and analytics capabilities.

ROI Analysis: Unveiling the Financial Impact of Sephora's Assortment Rationalization

Sephora's strategic approach to assortment rationalization, utilizing Excel as a primary tool, offers a compelling case for improving profitability through data-driven decisions. This analysis will explore methods for calculating Return on Investment (ROI), illustrate the financial impact through case examples, and weigh the long-term benefits against the short-term costs.

Methods for Calculating ROI

Calculating ROI on assortment rationalization requires a comprehensive understanding of cost savings and revenue enhancement. Sephora leverages Excel to perform scenario modeling, focusing on:

• Cost Reduction: By identifying underperforming SKUs, Sephora can eliminate or consolidate them, reducing inventory carrying costs and freeing up capital.
• Revenue Enhancement: Enhanced product mix optimization aligns offerings with consumer demand, driving increased sales volume and margin per SKU.
• Efficiency Gains: Automating data imports and analysis in Excel reduces labor costs associated with manual data management and decision-making processes.

Case Examples of Financial Impact

Consider a scenario where Sephora rationalizes its lipstick product range. Initial analysis reveals that 20% of SKUs contribute to 80% of sales (a Pareto principle application). By focusing on the top-performing SKUs, Sephora can:

• Achieve a 15% reduction in inventory costs, translating to substantial savings annually.
• Increase overall margin by 5% through strategic pricing adjustments.

In another example, a seasonal product line revamp resulted in a 10% rise in quarterly sales, showcasing the profound impact of timely assortment adjustments.

Long-term Benefits vs. Short-term Costs

While the immediate costs of implementing assortment rationalization—such as data management systems and personnel training—are notable, the long-term benefits are compelling:

• Enhanced Consumer Engagement: A well-curated assortment improves the shopping experience, fostering brand loyalty and repeat purchases.
• Increased Market Responsiveness: Quick adaptation to market trends ensures that Sephora can capitalize on emerging consumer preferences.
• Sustainable Growth: Consistent refinement of the product mix supports sustainable revenue growth and profitability.

In conclusion, Sephora's utilization of Excel for assortment rationalization offers a robust framework for achieving significant ROI. By aligning products with customer preferences and optimizing the supply chain, Sephora not only enhances its financial performance but also positions itself as a market leader in customer satisfaction and innovation.

Risk Mitigation in Sephora Assortment Rationalization Using Excel

Assortment rationalization at Sephora involves careful analysis and restructuring of product offerings to enhance profitability, inclusivity, and consumer engagement. However, the process carries inherent risks that can impact business outcomes if not managed effectively. This section outlines the potential risks associated with assortment changes and Excel usage, along with strategies to mitigate these risks and prepare contingency plans.

Identification of Potential Risks

Key risks in assortment rationalization include:

• Data Integrity Issues: Errors in data importation or manipulation within Excel can lead to inaccurate analyses, causing misguided decision-making.
• Consumer Backlash: Removing popular products may lead to dissatisfaction among loyal customers.
• Market Misalignment: Poor alignment of product mix with consumer demand may result in missed sales opportunities.

Strategies to Mitigate Risks

• Enhanced Data Validation: Implement rigorous data validation protocols by using Excel’s data validation tools to ensure accuracy. Leveraging advanced Excel functions like VLOOKUP or INDEX/MATCH can cross-reference data for consistency.
• Customer Feedback Loop: Use surveys and social media monitoring to gauge consumer preferences continuously. This real-time feedback should inform product retention or phasing out decisions.
• Scenario Analysis: Utilize Excel’s scenario modeling features to simulate various rationalization outcomes. This helps anticipate potential customer reactions and financial impacts, allowing for more informed decision-making.

Contingency Planning

Having a robust contingency plan is crucial in mitigating risks effectively:

• Diversified Product Offerings: Maintain a balance between core products and new launches to cushion the impact of any individual product’s underperformance.
• Backup Data Systems: Establish redundant systems and regular backups to protect against data loss. Cloud-based backups can ensure quick recovery and continuity.
• Agility in Operations: Develop flexible supply chain and inventory management practices to quickly adapt to shifts in consumer demand and minimize stockouts or surplus.

In conclusion, while the rationalization process at Sephora using Excel holds potential for streamlined operations and enhanced consumer satisfaction, acknowledging the risks and implementing strategic mitigation plans are essential. By enhancing data integrity, engaging with consumers, and planning for contingencies, Sephora can ensure a smooth transition towards optimal product assortments.

Governance

The success of Sephora's assortment rationalization using Excel hinges on a robust governance framework. This section outlines the key elements of governance, including establishing roles and responsibilities, ensuring data governance and compliance, and setting up effective monitoring and reporting mechanisms. By putting these structures in place, Sephora can optimize its product mix for profitability and consumer engagement.

Establishing Roles and Responsibilities

To effectively manage the assortment rationalization process, it is essential to establish clear roles and responsibilities. A dedicated team should be formed, comprising data analysts, category managers, and IT specialists, each with defined roles. Data analysts will focus on importing and analyzing SKU-level data using Excel, while category managers will interpret the insights to inform product decisions. IT specialists ensure the technical infrastructure supports seamless data import and processing.

Statistics from a 2025 study indicate that organizations with clearly defined roles are 30% more likely to meet their product assortment goals on schedule. Sephora can leverage this insight by assigning team leads responsible for specific product categories, ensuring accountability and streamlined decision-making processes.

Data Governance and Compliance

Effective data governance is critical to maintaining the integrity and accuracy of the data used in assortment rationalization. Sephora should implement strict data governance policies that outline how data is collected, stored, and accessed. Compliance with data privacy laws, such as GDPR, is paramount, especially when dealing with consumer data.

Actionable advice includes conducting regular audits of data processes and ensuring that all team members are trained in data compliance requirements. Establishing a data stewardship role can further enhance governance by overseeing data quality and compliance protocols.

Monitoring and Reporting Mechanisms

Continuous monitoring and timely reporting are vital components of effective governance. Sephora should leverage Excel's capabilities to set up automated reporting dashboards that track key performance indicators (KPIs) such as SKU performance, inventory levels, and sales trends.

For example, using Excel's pivot tables and charts, the team can create intuitive reports that provide real-time insights into product performance. These reports can be shared with stakeholders to facilitate agile decision-making. Additionally, setting up alerts for anomalies in sales data can help identify issues early and adjust strategies accordingly.

To ensure continuous improvement, Sephora should establish a feedback loop where team members regularly review outcomes and refine processes. This iterative approach not only enhances decision-making but also fosters a culture of continuous learning and adaptation.

By implementing these governance structures, Sephora can ensure that its assortment rationalization efforts are well-managed, compliant, and aligned with its strategic goals, ultimately driving both profitability and consumer satisfaction.

Metrics & KPIs

In the dynamic world of Sephora's assortment rationalization, measuring success through precise metrics and KPIs is pivotal. The use of Excel as a primary analytical tool offers an accessible and powerful platform for decision-making. Here, we delve into the key performance indicators, setting benchmarks, and achieving continuous improvement in the Sephora context.

Key Performance Indicators for Measuring Success

Effective assortment rationalization requires a comprehensive set of KPIs to gauge performance. Core metrics include unit sales, revenue growth, and profit margins by SKU and category. Excel's pivot tables facilitate the analysis of these metrics by offering a detailed breakdown of sales data, allowing quick identification of high-performing products.

Additionally, inventory turnover ratio and stock-to-sales ratio are crucial. These indicators help in managing inventory efficiently by assessing how frequently stock is replenished and sold, directly affecting profitability. According to industry benchmarks, an optimized inventory turnover rate ranges between 5 and 10 times annually.

Setting Targets and Benchmarks

Establishing clear targets and benchmarks is essential for guiding strategic decisions. For Sephora, setting realistic goals in Excel involves historical data analysis and competitive benchmarking. For example, a 5% increase in SKU-level revenue or a 10% improvement in margin year-over-year can serve as tangible targets.

Leverage Excel to track progress against these targets by implementing conditional formatting and goal-seeking analysis. This allows for visual representation of achievements and offers a data-driven approach to adjusting tactics as needed.

Continuous Improvement through Data

Continuous improvement is at the heart of successful assortment rationalization. To achieve this, regularly update Excel models with the latest data using automated scraping tools or APIs. This ensures that decision-making is based on the most current information available.

Employ scenario modeling to test various assortment strategies, identifying the optimal mix for profitability and consumer engagement. For instance, simulate the impact of expanding a popular product line against reducing underperforming SKUs, aiming for a balanced and inclusive assortment.

Remember, the goal is to foster an iterative process where insights from data lead to actionable adjustments, enhancing the product mix continuously. As demonstrated by a leading beauty retailer, integrating timely sales analytics led to a 15% increase in overall profitability.

By focusing on these key metrics and KPIs, and through diligent use of Excel's capabilities, Sephora can optimize its product assortment to meet consumer demands and achieve sustainable growth.

Vendor Comparison: Excel vs. Other BI Tools

In the realm of assortment rationalization, Excel remains a steadfast tool notably due to its accessibility and versatility. However, as the landscape of business intelligence (BI) tools expands, it’s crucial to compare Excel with other platforms such as Tableau, Power BI, and Looker, particularly for Sephora’s intricate needs in 2025.

Excel

Excel's enduring popularity is attributed to its robust functionalities for data manipulation, pivot tables, and scenario modeling. In scenarios where dynamic reports and quick data manipulation are needed, Excel shines. For instance, it supports SKU performance analysis by easily incorporating data on unit sales and revenue, which is paramount for Sephora’s SKU rationalization.

Other BI Tools

Tableau and Power BI offer advanced data visualization and real-time dashboard capabilities, making them ideal for larger datasets and complex visual analysis. Tableau's strength lies in its intuitive drag-and-drop interface, allowing users to create intricate visual representations of data trends, which can be more engaging than Excel's charts. Power BI, backed by Microsoft, integrates seamlessly with other Microsoft products, offering strong data connectivity and sharing features.

Looker, now part of Google Cloud, excels in providing powerful data exploration capabilities. It’s particularly suited for teams that need to embed analytics directly into workflows, offering seamless integration with Google’s ecosystem.

Pros and Cons

• Excel: Pros include its widespread use and flexibility; cons encompass limitations in handling very large datasets and collaborative features.
• Tableau: Pros are rich data visualization and ease of use; cons are the cost and a steeper learning curve.
• Power BI: Pros include cost-effectiveness and powerful data integration; cons involve limited on-premises capability.
• Looker: Pros are seamless integration with Google services and advanced analytics; cons include high cost and dependence on SQL for detailed analysis.

Recommendations

For enterprises like Sephora, the choice between these tools should be guided by specific needs:

• If budget and simplicity are key, Excel remains a valuable option, especially for its familiarity and simplicity in catalog data import and SKU analysis.
• For visually driven insights and larger teams, Tableau or Power BI is recommended, especially with their enhanced collaborative features.
• For enterprises deeply integrated within Google’s ecosystem, Looker offers an unmatched blend of analytics and integration.

Conclusion

The strategic rationalization of Sephora's assortment using Excel is crucial for maintaining a balance between profitability, inclusivity, and consumer engagement. As outlined in this article, leveraging Excel's capabilities for catalog scraping, SKU performance analysis, and competitive benchmarking provides a robust framework for optimizing Sephora's product mix. By regularly importing SKU-level data via automated tools or APIs, Sephora can maintain up-to-date records on product variants and pricing, enabling dynamic decision-making.

One of the standout insights from our exploration is the power of Excel pivot tables in analyzing unit sales, revenue, and margin by SKU and category. This analytical approach allows Sephora to swiftly identify underperforming products, focusing resources on high-margin and high-demand items. In 2025, while advanced AI dashboards have become available, Excel remains a reliable and accessible tool for detailed scenario modeling and actionable reporting in environments where such technologies are not universally accessible.

Looking ahead, Sephora's assortment strategy can benefit from further integration of advanced data analytics and machine learning algorithms. By harnessing these technologies alongside Excel, Sephora could enhance its predictive capabilities, better forecast market trends, and refine its product offerings. However, the core principles of thorough data collection and precise analysis, as facilitated by Excel, will continue to be foundational to its success.

In conclusion, Excel plays a pivotal role in Sephora's assortment rationalization strategy. It not only provides the necessary tools for detailed analysis but also offers a platform for continuous innovation in product management. As Sephora moves forward, maintaining a commitment to data-driven decision-making will ensure it remains at the forefront of the beauty industry, delighting customers with a carefully curated selection that meets diverse needs and preferences.

Frequently Asked Questions

Assortment rationalization involves analyzing and adjusting product offerings to optimize sales, profitability, and customer engagement. At Sephora, this means balancing inclusivity and exclusivity with data-driven decisions.

How can Excel be used for assortment rationalization?

Excel remains a powerful tool for assortment rationalization through its robust functionalities like pivot tables and scenario modeling. Set up dynamic tables to track product lines and launches. Use pivot tables to analyze unit sales, revenue, and margins by SKU and category.

Why is SKU performance analysis important?

SKU performance analysis helps identify top-performing products and those that need reconsideration. By examining unit sales, revenue, and margin, decisions can be made to either promote, revise, or discontinue certain products, ultimately enhancing profitability.

How can I import Sephora's product data into Excel?

Utilize automated scraping tools or APIs to import SKU-level data, including product variants and pricing tiers. Keeping a dynamic data set allows for accurate benchmarking against competitors and aids in strategic planning.

What are the benefits of using Excel over more advanced tools?

While advanced tools like AI dashboards offer more automation, Excel provides flexibility and accessibility, making it ideal for environments where such tools aren't scalable. Excel allows for highly customizable analysis and reporting to enhance decision-making.

Any tips for successful assortment rationalization?

Focus on data accuracy and regular updates. Leverage sales analytics to understand consumer preferences and adapt your product mix. Remember, a well-rationalized assortment leads to increased profitability and customer satisfaction.