Merchandise Optimisation – Lecture 2 Review

This set of flashcards covers the key concepts, processes, metrics and technology trends from Lecture 2 on Merchandise Optimisation, enabling practice for exams or reviews.

What are the five learning objectives highlighted for this lecture?

Understand the merchandise planning process; understand merchandise classification and organisation; understand the importance of merchandise controls; know ways to measure merchandise productivity performance; know how retail technology helps in merchandise planning.

What is the first step in the merchandise planning process?

Forecast category sales.

Name three later steps in the merchandise planning process after buying merchandise.

Allocate merchandise to stores; monitor and evaluate performance; make adjustments.

Define “merchandise management.”

The process by which a retailer offers the right quantity of the right merchandise, in the right place, at the right time to meet financial goals.

List the five planning units used to organise merchandise.

Merchandise group, department, classification, category, SKU.

What is a ‘category’ in retail merchandising?

A group of products or services that consumers perceive as complementary or substitutes in satisfying a specific need.

Give two examples of category roles.

Destination category and seasonal category (others: routine, convenience).

Which two broad types of merchandise‐management planning systems are identified?

Staple merchandise planning systems and fashion merchandise planning systems.

How is a staple merchandise category characterised?

Continuous demand over an extended time period.

Mention two controllable factors used when forecasting staple merchandise sales.

Operating hours and special promotions (also prices, placement of merchandise).

Name two typical information sources for forecasting fashion merchandise.

Market research and fashion trend services (others: previous sales data, vendor input, focus groups, in-depth interviews).

What does an assortment plan outline?

The selection of products to be offered by a retailer within a specific category or department, covering variety (breadth) and assortment (depth).

State two factors that influence the development of an assortment plan.

Retail strategy and GMROI (others: complementary merchandise, effects on buying behaviour, physical store characteristics).

What is a model stock plan?

A projection of the exact number of each SKU that should be available in each store based on the assortment plan.

Define ‘product availability.’

The percentage of demand for a particular SKU that is satisfied.

In inventory management reports, what is the ‘order point’?

The inventory level below which the quantity should not fall or the item risks being out of stock before the next order arrives.

What is a merchandise budget plan for fashion goods?

A dollar plan that specifies how much merchandise needs to be delivered each month, based on sales forecasts, discounts and desired GMROI.

Explain ‘open-to-buy’ (OTB).

The dollar amount a buyer still has available to spend on merchandise for a given period without exceeding planned purchases.

Provide the basic OTB arithmetic statement.

OTB = Planned purchases – (purchases received + on-order + customer returns + transfer-in – transfer-out – returns to vendor).

What does GMROI stand for and what does it measure?

Gross Margin Return On Inventory Investment; it measures the relationship between gross margin dollars and the average inventory investment at cost.

How is inventory turnover defined?

The number of times inventory is sold and replaced during a specific period, usually a year.

Give one formula for inventory turnover using retail values.

Inventory turnover = Net sales ÷ Average inventory at retail.

Name two approaches to improve inventory turnover.

Reduce the number of categories/SKUs/items; buy merchandise more frequently in smaller quantities.

What is algorithmic merchandising optimisation?

Using algorithms to decide which items to display, stock, price and promote across channels to maximise sales, margin, inventory efficiency and customer satisfaction.

List two retail functions supported by AI and machine learning, according to the lecture.

Demand planning & forecasting, and dynamic price optimisation (others: personalised marketing, chatbots, product catalog management, in-store operations).

How do AI-powered recommendation engines help retailers?

By analysing customer data to generate personalised product recommendations, targeted campaigns and tailored promotions.

What retail problem do smart shelves and video analytics address?

They provide insights into shopper behaviour for queue management, stock replenishment, product placement and optimising store layout.

Explain ‘datafication’ in retail.

The use of retail data analytics combined from multiple channels to gain insights for personalisation, product management, price optimisation and operational efficiency.