Top 5 Mistakes to Avoid in Assortment Planning

Blogs > Top 5 Mistakes to Avoid in Assortment Planning

Wed Nov 20 2024

Author

Alok Joshi

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Assortment planning for retailers is a complex yet critical function that can significantly impact customer satisfaction and over profitability of a business. Today’s customers are more experienced and have higher expectations, continually demanding more from retailers. With the growth of retail and eCommerce platforms, customers are developing increasingly diverse shopping preferences and behaviours. This makes it more challenging than ever for businesses to meet and satisfy their evolving needs.

Selecting the right assortment needs to consider many factors beyond product selection: Pricing and promotions, inventory management, optimising supply chain operations, and minimising waste to name a few. As a result, organisations frequently struggle to achieve the full potential of their assortment planning processes, leaving gaps in their ability to make informed decisions that respond to market dynamics such as planning for new product launches or deleting / reducing lines that are no longer popular.

In this article, we share the top 5 mistakes that we summarised from our engagements and industry insights, which can undermine the effectiveness of assortment planning in retail, and how to overcome them to maximise success.

Top 5 Mistakes	What it means	How to avoid
1. Too Much on Gut Feeling and Underusing Data	With millions of product-location combinations to assess, overly relying on gut instincts makes it difficult to make the optimal decision. This often leads to product offerings that miss current customer preferences, resulting in lost sales opportunities.	Invest in data and AI/ML tools that can automatically consider customer behavior, sales trends, and product performance. By leveraging AI-driven optimisation, they can make informed decisions that accurately reflect customer demand and improve overall assortment planning.
2. Overlooking Local Preferences and Constraints	Applying a one-size-fits-all assortment strategy across locations and channels ignores unique preferences and practical execution. Each channel, location, and customer has distinct needs.	Go granular. Leverage AI/ML and data to segment the assortment plans, based on forecasted specific demand, ensuring products match the unique demands of every channel, location, and customer.
3. Assortment as a Siloed Process	Treating assortment planning as a standalone function, disconnected from other commercial, supply chain, or operational processes. This siloed approach can result in inefficiencies that don't factor in cost to serve and a lack of alignment between what is promoted and what’s available in each location.	Create a holistic assortment planning system that integrates with end-to-end value chain processes. Aligning assortment planning with promotional strategies and logistical capabilities ensures a smoother execution, improving stock levels and customer satisfaction.
4. Inadequate Forecasting	Many companies rely too heavily on past data, forgetting that past trends don’t always predict future demand. Embedding accurate forecasting into the planning process is crucial for making informed decisions, but technical and capability constraints often prevent businesses from doing so. Even when companies attempt forecasting, many use overly simplistic models that fail to capture complex market dynamics, leading to inaccurate predictions and ineffective assortment strategies.	Invest in advanced forecasting models that use modern AI and machine learning technologies. Additionally, integrating forecasting directly into assortment planning allows companies to make data-driven decisions that anticipate future demand rather than just reacting to past trends. Building internal capabilities or partnering with tech providers can help overcome technical barriers and ensure effective, dynamic forecasting.
5. Not Regularly Reviewing and Updating Assortments	Failing to adapt product assortments regularly can cause retailers to fall behind consumer trends, leading to outdated offerings that don’t meet customer expectations. Sticking to the same assortment can also result in excess inventory or product obsolescence.	Continuously evaluate and update assortments based on evolving consumer preferences and sales performance. This requires building feedback loops that allow for ongoing assessment and adjustments, ensuring that the assortment remains fresh, relevant, and aligned with current demand.

If you’d like to know more about demand forecasting or how jahan.ai can help you, reach out to us on info@jahan.ai and ask for our Retail Assortment Handbook. Or read more about our assortment solution on our website here.

#jahanai #saas #assortmentplanning #ai #retail #productrange

At jahan.ai, we build end-to-end AI twins for retail and supply chain businesses. We take the concept of a digital twin, a virtual replica of business processes, further with advanced AI, which not only mirrors these processes but also automatically optimises them. In this way, we support businesses in driving efficiency, going beyond their potential.

Reach out to jahan.ai to explore how we achieve this or how we can help optimise your business.

#assortment

#jahanrange

Top 5 Mistakes	What it means	How to avoid
1. Too Much on Gut Feeling and Underusing Data	With millions of product-location combinations to assess, overly relying on gut instincts makes it difficult to make the optimal decision. This often leads to product offerings that miss current customer preferences, resulting in lost sales opportunities.	Invest in data and AI/ML tools that can automatically consider customer behavior, sales trends, and product performance. By leveraging AI-driven optimisation, they can make informed decisions that accurately reflect customer demand and improve overall assortment planning.
2. Overlooking Local Preferences and Constraints	Applying a one-size-fits-all assortment strategy across locations and channels ignores unique preferences and practical execution. Each channel, location, and customer has distinct needs.	Go granular. Leverage AI/ML and data to segment the assortment plans, based on forecasted specific demand, ensuring products match the unique demands of every channel, location, and customer.
3. Assortment as a Siloed Process	Treating assortment planning as a standalone function, disconnected from other commercial, supply chain, or operational processes. This siloed approach can result in inefficiencies that don't factor in cost to serve and a lack of alignment between what is promoted and what’s available in each location.	Create a holistic assortment planning system that integrates with end-to-end value chain processes. Aligning assortment planning with promotional strategies and logistical capabilities ensures a smoother execution, improving stock levels and customer satisfaction.
4. Inadequate Forecasting	Many companies rely too heavily on past data, forgetting that past trends don’t always predict future demand. Embedding accurate forecasting into the planning process is crucial for making informed decisions, but technical and capability constraints often prevent businesses from doing so. Even when companies attempt forecasting, many use overly simplistic models that fail to capture complex market dynamics, leading to inaccurate predictions and ineffective assortment strategies.	Invest in advanced forecasting models that use modern AI and machine learning technologies. Additionally, integrating forecasting directly into assortment planning allows companies to make data-driven decisions that anticipate future demand rather than just reacting to past trends. Building internal capabilities or partnering with tech providers can help overcome technical barriers and ensure effective, dynamic forecasting.
5. Not Regularly Reviewing and Updating Assortments	Failing to adapt product assortments regularly can cause retailers to fall behind consumer trends, leading to outdated offerings that don’t meet customer expectations. Sticking to the same assortment can also result in excess inventory or product obsolescence.	Continuously evaluate and update assortments based on evolving consumer preferences and sales performance. This requires building feedback loops that allow for ongoing assessment and adjustments, ensuring that the assortment remains fresh, relevant, and aligned with current demand.

Top 5 Mistakes

What it means

How to avoid

1. Too Much on Gut Feeling and Underusing Data

With millions of product-location combinations to assess, overly relying on gut instincts makes it difficult to make the optimal decision. This often leads to product offerings that miss current customer preferences, resulting in lost sales opportunities.

Invest in data and AI/ML tools that can automatically consider customer behavior, sales trends, and product performance. By leveraging AI-driven optimisation, they can make informed decisions that accurately reflect customer demand and improve overall assortment planning.

2. Overlooking Local Preferences and Constraints

Applying a one-size-fits-all assortment strategy across locations and channels ignores unique preferences and practical execution. Each channel, location, and customer has distinct needs.

Go granular. Leverage AI/ML and data to segment the assortment plans, based on forecasted specific demand, ensuring products match the unique demands of every channel, location, and customer.

3. Assortment as a Siloed Process

Treating assortment planning as a standalone function, disconnected from other commercial, supply chain, or operational processes. This siloed approach can result in inefficiencies that don't factor in cost to serve and a lack of alignment between what is promoted and what’s available in each location.

Create a holistic assortment planning system that integrates with end-to-end value chain processes. Aligning assortment planning with promotional strategies and logistical capabilities ensures a smoother execution, improving stock levels and customer satisfaction.

4. Inadequate Forecasting

Many companies rely too heavily on past data, forgetting that past trends don’t always predict future demand. Embedding accurate forecasting into the planning process is crucial for making informed decisions, but technical and capability constraints often prevent businesses from doing so. Even when companies attempt forecasting, many use overly simplistic models that fail to capture complex market dynamics, leading to inaccurate predictions and ineffective assortment strategies.

Invest in advanced forecasting models that use modern AI and machine learning technologies. Additionally, integrating forecasting directly into assortment planning allows companies to make data-driven decisions that anticipate future demand rather than just reacting to past trends. Building internal capabilities or partnering with tech providers can help overcome technical barriers and ensure effective, dynamic forecasting.

5. Not Regularly Reviewing and Updating Assortments

Failing to adapt product assortments regularly can cause retailers to fall behind consumer trends, leading to outdated offerings that don’t meet customer expectations. Sticking to the same assortment can also result in excess inventory or product obsolescence.

Continuously evaluate and update assortments based on evolving consumer preferences and sales performance. This requires building feedback loops that allow for ongoing assessment and adjustments, ensuring that the assortment remains fresh, relevant, and aligned with current demand.