Buying and Planning in Retail - why should you invest?

When it comes to fashion retailing, the most important function is clearly effective planning and buying, whether it is the merchandise financial planning to arrive at the buy budget (OTB – Open to Buy) for the various departments, or the assortment and range building that ensures the business meeting the targets on sales, margins (and markdowns) and inventory across the selling channels (in-store, online, marketplace, wholesale, cross-border or franchise)

In this article, I have outlined the high-level end to end process of retail buying and planning, what challenges are typically faced by the retailers, industry best practices on products and processes and the role of AI and data analytics to make commercial processes more efficient and profitable

Retail merchandise planning typically is at two levels – pre-season and in-season planning.

Assume there are 2 seasons (autumn-winter that runs from July to December, and spring-summer that runs from January to June), so pre-season planning is all about demand planning, how much to buy (OTB or merchandise financial planning), what to buy (assortment planning), when to buy (PO management and supplier collaboration) and how to allocate the range to the stores (range planning). Typically, pre-season planning starts 6-9 months in advance of the start of the season (so let’s say for autumn-winter of 2023, the planning would have started back in Sept 2022)

On the contrary, in-season planning is all about managing the merchandise in-season (during the season) which involves efficient replenishment of stocks to the stores, allocation for the online channels, setting up the right parameters of replenishment like min/max, display qty, shelf capacity, ROS (rate of sale), watermark level/safety stock etc. It also involves consolidation across stores (e.g broken sizes consolidated to form a size profile in a clearance store for better sell-thru) and running down the stock with the right markdowns (often progressive end of season clearances) and still meet the margin, stock and sales targets

In this article, I will highlight the pre-season or demand planning in more details, and will talk about in-season planning in my next

Step 1: Merchandise Financial Planning

First step in the process is getting qualitative and quantitative inputs from various teams (buying, planning, finance, retail and marketing) and deriving the OTB at the class/subclass (sub-category)/week level which is also known as intake planning. This is typically done in an MFP (merchandise financial planning) tool. Most retailers use good old excel for this, but then lose out on the analytical capabilities and a single view of truth of the OTB without an MFP system. Typically the inputs to the merchandise financial planning include

1. Category strategy (e.g focus on denim jackets instead of leather ones, more width of summer dress ranges in bright, bold colors, pastel shades in women’s formal jackets), most of these strategies are driven by competition and trends (EDITED Market is a good product with built in AI engines to collect, track and provide insight on market data based on website scraping, suggest key trends and price points)
2. Location Strategy – How to cluster stores based on various parameters like demographics, purchase parity, ethnicity and other local and regional influences, this will then help in allocating the right range to the right stores for better sell-thru
3. Pricing Strategy (EDITED Price is an useful tool for price planning) – It is very important to formulate the price architecture across categories based on the branding and positioning of the retailer to its customer segments (e.g men’s formal shirts with 3 price points, value at $25, mid-range at $50 and a premium wrinkle free at $75, with an approximate 20-50-30 buy ratio)
4. Sales, stock, margin and markdown targets (derived from the sales budgets at the store/day level, which then gets apportioned to the categories as OTB for the season at the sub-category/week level for the season)

Step 2 – Master Assortment Planning

The 2nd step in the process is the master assortment planning (also known as the buy plan or shopping list) which is all about breaking down the OTB into the number of styles and options (both width and depth) with their preferred attributes, which needs to be bought for the season. Now, this is entirely a planning exercise driven by the planning team (with some inputs from buying) and is NOT at the product level, it is more at the style and option level. This typically is done in an AP tool (assortment planning)

An example of a STYLE is men’s pin-striped formal shirt, and the OPTIONS within that can be the different colors of the stripes or different base colors, next comes SIZE (XS, S, M, L, XL etc.), so every sub-category needs to be planned with a master assortment (in dollars and qty) of the STYLE, OPTIONS and preferred SIZES with detailed product attributes. Much of this is derived from historical data, in terms of which styles/options have performed in the same season last year, or what is the market trend, what kind of supplier offers are there to choose from based on the agreed price points. Here also AI tools like EDITED Market, EDITED Price Intelligence, Bamboo Rose Marketplace are used to merge historical performance data with trends to produce the forecasted BUY PLAN

Step 3 – Placeholder Matching in PLM

Once the BUY PLAN (or MASTER ASSORTMENT) is ready, it then gets integrated to a PLM (product lifecycle management solution, e.g Bamboo Rose PLM, Centric PLM) where there is a process called PHM (placeholder matching). So what is PHM?

In parallel to the master assortment planning, the buyers also start getting inputs on actual products to buy and works with suppliers to induct them into PLM with tech specs, pictures and starts with the sample development process (e.g for private labels) or works with the principal brands (franchise) to induct the available branded SKU’s, which are more like placeholders, because the item is still not selected for buying. Once the master assortment is completed for a category, it is then integrated from AP (assortment planning tool) into PLM to match the agreed style/option with the actual SKU being inducted in PLM (by the buyer), and this is the point in the critical path, where planners and buyers needs to coordinate significantly, as it marries the OPTION with the actual product.

Consider an example, where kids BTS (back to school) planning is done with various categories like shoes, footwear accessories like socks, backpacks, stationaries, lunch boxes and water bottles. For shoes the master assortment proposes 5 styles (leather with laces, leather with velcro, 2 styles of branded sneaker and 1 style in private label sneaker), which can have various options like leather shoes can be black, brown (in 2 shades), sneakers with laces can have 2 shades (off-white and super-white), so all these are planned in AP and interfaced to PLM, and then the actual products in PLM gets placeholder matched based on the style/option level assortment that comes from AP.

Step 4 – Detailed Assortment Planning/Range Planning

The next step in the process is for the selected products to come back to AP, and here the planners start planning the size profiles and the exact qty that needs to be purchased from suppliers, and how the different SKU’s gets allocated and ranged to the stores and e-Com channels, along with other channels like 3rd party marketplace, online exclusives, franchise and wholesale businesses. Both the range and the qty allocation happens in this step, and it is the most critical part of the planning process.

A layover exercise is done (often physically, but planning tools now offers this as a digital selection process) wherein the samples are exhibited to the internal stakeholders (buying, planning, retail, finance, marketing) for any specific inputs on selecting/de-selecting some of these ranges to certain store clusters

Step 5 – Pre-PO and PO creation

Once the final range selection (qty to buy at SKU level and initial allocation to the stores) is done, the next step is the PO creation process, wherein the PO’s are sent to suppliers. Some retailers follow a pre-PO process (during the range planning) to collaborate with suppliers to check their feasibility on the volumes based on the launch dates

As part of the product induction, there are multiple steps starting from showrooming and inspirations (from suppliers and buyers) in products like Bamboo Rose Marketplace, to then loading tech specs of actual products into PLM, out of which the range will get selected in the PHM process, the sampling process (development, fitment, pre-production and production samples), there are tools like CLO 3D that helps in 3D visualization of these samples that saves time and money in shipping the physical samples.

Post the PO creation comes the process of inspections (in-line, mid-line, pre-ship) typically done by 3rd parties (like Bureau Veritas or CFA’s – certified factory auditors who are trained by agencies to do the inspection on behalf of the supplier) and once the shipment is ready, packing list (PL’s) gets created followed by freight booking of liners, container optimization, building the ASN and the final ship-out from the port of dispatch

Challenges in Merchandise Planning

So, what are the typical challenges that are faced by retailers in this process

1. Inconsistent manual paper based and excel sheet-based processes, leading to loss of learnings, knowledge and insights as the team’s churn in planning and buying
2. Planning is more of science and buying an art, and often these 2 teams do not collaborate and end up doing their planning in isolation leading to critical path issues, delays in PO release and subsequent launch in the season (especially the first hits)
3. There are a number of solutions in the market to do both demand and supply planning, but most of them offer siloed solutions (like only replenishment planning or store clustering etc.) and does not cover the entire gamut of merch financials, assortment, range and supply planning (pre-season to in-season) except the large ERP OEM’s like BY (Blue Yonder), Oracle and SAP, and implementing them is not very flexible or agile/fast and takes months and years for retailers to get benefits from
4. Process standardization – Most of the retailers witness a myriad set of variations of the entire pre-season and in-season processes, based on categories and different BU’s which makes it all the more important to standardize (as much as possible within the realms of best practice and practicality), simplify and normalize before looking at planning and buying systems, otherwise it all ends up in large customizations and complexity around rules, measures and workflows
5. Appreciating the fact that all the above processes can happen in parallel and define a critical path based on the product category, sourcing and distribution strategy, rather than following a sequential process that creates an elongated cycle of 6-9 months, which can be optimized (CPO - critical path optimization) further to buy more customer centric ranges closer to the season, that is not only more accurate from choice but also from a quantity perspective

Data Analytics opportunities

The market offers a range of retail solutions in commercial buying and planning, and most of them have got built in data analytics with AI engines around

1. Optimizing prices, promotions and markdowns to maximize margins and achieve the budgeted markdowns and stock covers
2. Size profile optimization – Optimize the intake on size profiles to improve sell-thru and reduce stock covers and EOS markdowns
3. Demand forecasting for continuity lines (which are bought throughout the year, and typically are not specific to a season)
4. Assortment Optimization – Using AI/ML and data analytics, predict the ranges and assortments which can then be used by planners and buyers to further fine tune and select
5. Store clustering - Clustering stores based on demography, ethnicity, fashionability, purchasing parity, weather, geography and other local and regional factors
6. Range and allocation optimization – Optimize the range allocation to store clusters based on various parameters
7. Container and freight optimization – Minimize the number of containers needed to reduce freight costs, also suggest consolidation through CFS stations and the optimum port pair combinations, or suggest the liners based on contracts to reduce spot rate bookings
8. Space Planning and optimization in stores – Identify the right allocation of retail floor space to categories to maximize space productivity (sales or margin per sq.ft per store), which is also termed as macro-planning (as opposed to micro-planning which is more around planogram creation for better visual merchandising and displays)
9. Replenishment Optimization – Optimize the regular replenishment cycle to maximize in-store availability, minimize stock cover and improve full price sell-thru  

Conclusion

In conclusion, merchandise planning and buying is the heart and brain of retail (be it private label, franchise or branded) any format, any category and plays a pivotal role in ensuring the right product mix is bought at the right time, in the right quantity and placed at the right stores for customers. More often this is ignored with the assumption that the tribal knowledge of buyers and planners is good enough, and only realized once churn happens with internal teams and retailers starts losing valuable insights, ends up in lost sales, high markdowns to clear EOS inventory and lost margins. Its time to invest in the right tools and products that digitizes, consolidates, centralizes and optimizes the end to end planning and buying lifecycle