Increase Profits By Localizing Your Markdowns

Over the past 30 years retailers have made a concerted effort to localize assortment and merchandise plans because they recognize that shopper preferences vary across different channels and locations. However, for many retailers these localization efforts have not extended to in-season plan execution.

There is a dichotomy between the common practice of executing enterprise-wide markdown start-date, cadence and discount when contrasted to highly localized pre-season merchandise plans. By reverting to enterprise-wide averages, retailers leave a lot of money on the table by taking "too much too soon" in some stores, resulting in lower profits, and ‘too little too late’ in other stores, resulting in excess inventory.

Given the advances in data analytics and demand based science over the past decade, many retailers are now revisiting the opportunities that markdown optimization presents to resolve this inconsistency. As one retailer states – "no other lever generates free incremental margin like markdown optimization" – because a 3 percent to 5 percent margin improvement goes straight to the bottom line. However, as change has no constituency and overcoming traditional methodologies is always a challenge, implementing a new technology and adapting business processes must be approached with care to ensure that confidence in the system and user adoption are high.

There are several key factors to be considered:
  • Select a proven software solution provider with the best science as a partner
  • Maintain management commitment & engagement throughout the process
  • Pace the implementation & roll-out to organizational bandwidth
  • Integrate technology across all key stakeholders & business processes
  • Continuously refine the process to increase granularity & sophistication
  • Markdown optimization provides a process-driven approach that combines best-in-class demand-based science and predictive analytics with a thoughtful workflow.
This process is designed to minimize markdown spend while maximizing margin, sell-through, inventory value and the velocity of inventory turn for all products - from basic replenishables to seasonal and fashion merchandise.

Optimization uses a combination of data, rules, and science to achieve strategic and financial objectives:
  • Update: Markdowns can be optimized on a weekly cycle or more frequently for products that need to be closely monitored.
  • Adapt: Every time models are updated, recommendations are re-optimized based on the most current data and trends.
  • Identify: When initially identifying markdown candidates, the process supports both event driven markdown item selection and automated item recommendation based on eligibility criteria.
  • Simulate: Optimization simulates every potential scenario for cadence and discount within rules and constraints and then looks at the markdown objective to recommend the most optimal scenario.
  • Prioritize: Prioritizing recommendations within labor and budget constraints as well as evaluating the opportunity cost of delaying a markdown ensures the best marks are selected.
  • Measure: As actual data comes in against forecast and budget data, the system re-runs all the possible scenarios and adapts next step recommendations when necessary to achieve objectives most optimally.
Using a demand-driven process that takes the emotion out of markdown decisions enables retailers to rapidly respond to local shopper behavior and inventory depletion rates and capitalize on the low hanging fruit found beneath the ‘too everywhere’ cover of enterprise-wide markdowns.

Many retailers approach an implementation by selecting a subset of products and/or locations in order to ensure the data is clean, processes are in place and confidence in the solution is established so the balance of the roll-out is smooth and rapid.

A common misconception is that optimization implementations are long and complicated, but this is not the case. Typically, a subset of products/locations can be up and running in 3 to 6 months with full roll-out within 6 to 9 months. Many times initial selections are synchronized to a category review cycle. If a specific class or department is experiencing high levels of markdown spend, they are often a great candidate to tackle first in order to control that spend. Timing the full roll-out to an end of season clearance is also quite common.

The level of granularity in strategies and rules initially implemented also varies from retailer to retailer. Many start by setting them at higher levels and then increase sophistication over time through increased use of simulation and exception-based management. Results demonstrate that simply taking the mark to a local level and automating data collection, rules enforcement and analysis gains an enormous amount of value.

Along with the benefits of localization, other key learnings derived from optimal, non-emotional markdown execution are exemplified in these case studies:

Shallower, earlier marks increase sell-through and profitability
In this retailer example, optimized markdowns in 250 stores were compared to business as usual (BAU) markdowns across the balance of the chain for men’s and women’s branded apparel. BAU took the first mark at 20 percent and a second at 40 percent across the balance of chain at the same cadence. Optimization was driven to a sell-through objective which recommended 4 marks, in some cases starting earlier than BAU, with localized start dates, discounts and frequency.

The variation in results was significant with Sell-through up over 7 percent, Margin up almost 1 percent and the resultant GMROI up 5.6 percent in the optimized stores. Taking shallower marks earlier in the season achieved higher sell-through and profit by giving optimization more inventory and margin to work with at the outset.

Increased granularity and adapting on-the-fly improves profits and limits deeper next step
Another retailer achieved their goal of higher profitability without impacting sell-through for the online liquidation of different colors of boots by increasing the granularity of markdown decisions from the style level to the style/color level. Two colors were chosen for independent optimized discount while the balance of colors had the same markdown plan.

The results showed that increasing granularity and moving the start date up for one boot color cleared inventory more profitably. In addition, while monitoring the event, they modified the initial plan upon determining the 2nd and 3rd marks were not required to clear the inventory. This retailer achieved 5 percent higher margin with negligible impact on sell-through.

Increasing granularity in markdown decisions through localization is proven to drive benefits that cannot possibly be achieved by gut feel, business as usual, or spreadsheets. Optimizing markdowns to local shopper demand provides an opportunity to make merchandise plans an in-season reality by surgically executing exit date, sell-through and inventory plans so assortments remain fresh while still achieving markdown objectives within budget constraints.

Optimization is proven to be an effective tool that enables retailers to make better, more profitable markdown decisions. That being said, it is only a tool and must be supported by people and processes that work in concert to achieve objectives. Choosing the right solution partner that can orchestrate the people, process and technology requirements, facilitate executive team and key stakeholder support, and carefully manage business change are all critical to a successful implementation.

Kathy Beck is senior director of product marketing for Revionics.
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