Most retailers have, with reasonable success, adopted optimization solutions for pricing and promotions. Very few have successfully implemented merchandising solutions and even fewer have successfully extended these solutions to core functions such as assortment and space planning. While there can be any number of reasons contributing to the slower adoption rate, the underlying issue has always been the resistance shown by the user community toward using such solutions.
Anybody who has worked in merchandising will tell you that there are two pieces to merchandising:
- The art piece, that decides how to merchandise items so as to appeal to the customer to ensure the purchase decision is made at the right time and
- The science piece, that decides what and how many items to keep, thereby focusing on efficient operations.
The key challenges include the following:
- Misaligned incentives
- Resistance from ‘power’ users
- Optimization engine is a black box
- Myth that optimization solution adoption will lead to leaner workforce
- Manipulating the solution to provide similar recommendations (without changing the results)
- Insufficient and incorrect data, resulting in inaccurate results
- Inflexibility in the solution to deal with last-minute changes
- Flying blind, based on results, without understanding the underlying assumptions
- Not building the analytics competency in the merchandising organization sufficiently
In this white paper, we attempt to explain the most common and key challenges encountered by leading retailers when adopting merchandise optimization solutions. We hope to create awareness among the stakeholders in these organizations and assist them in avoiding and / or overcoming these challenges.
Some of the challenges listed above are similar in nature to most automation and computerization adoption challenges. Yet, these seemingly simple challenges are where the complexity lies - as our brains tend to focus on solving difficult challenges without paying much attention to the simplest challenges. By grouping these commonly-seen problems, retail organizations can understand the issues that could derail the implementation of optimization solutions.