SAP Retail Activity Optimization (RAO) Innovation Project
Summary
The Retail Activity Optimization (RAO) Innovation Project pivoted from its early beginnings of being everything to everyone to a more refined product that focused on providing recommendations to users that enhanced and complimented existing product offerings. This was achieved by returning to discovery research with users to verify areas of greatest pain, time and cost, then rapidly creating and validating concepts with customers to quickly learn what will provide them with the most value, and want them to be part of our pilot program to help us continue to build out the product.
Product: SAP Retail Activity Optimization
Project: Innovation Project
Years: February 2022 - Current
Duration: 7 months
Role: Senior Experience Designer
Problem Space
How can we enhance the existing SAP retail execution software product, where the sales are declining, to overtake the competition and be number one in the market?
The Challenge
Identify activities a Key Account Manager performs throughout their user journey that can be innovated on to provide them value in terms of increased revenue, and create a product that fulfills that mission, measured by purchasing customers.
My Role
Lead a team of 5 UX Designers spread across America, China and Germany, in collaboration with PMs in the same time zones, to understand what has happened in the past, create and validate opportunities for the future, and drive the team in a positive direction aiming toward building a product with clearly defined success metrics.
Eureka Collaboration Model
Discovery
Identify Customers & Personas
Journey Maps
Ideate
Codify Product Vision
Assess
Lab
Empathize
Validate Pain Points
Define Concepts
Demonstrate Concepts
Define Design
Build
Refine Requirements
Code
Test & Deploy
Release & Operate
Monitor
Discovery Phase
Discovery
When I joined the team, Discovery Phase was complete. Customers and personas had been identified and an initial vision for the product was defined. The vision was to create a retail execution product that helped Key Account Managers to 1. recommend the best actions to take to increase revenues from promotions, and 2. allowed them to perform those actions.
However, there was an existing retail execution product in SAP, owned by another business unit, that had the same functionality of part 2. performing actions, but not part 1. recommending actions.
So, we aligned with that business unit and created a roadmap to move forward together, focusing on part 1 and letting them focus on part 2.
Product Vision
I facilitated a card sorting workshop to align on a new vision for our product.
Our new vision became to create an unparalleled recommendation engine that leverages data to connect teams via a modern UI to drive revenue for promotions.
2. Lab Phase
User Journey Validation
Armed with our new vision, we decided to validate the Key Account Manager’s journey and identify actions they perform throughout the journey that cause the greatest pain and take the longest time to accomplish. We found an opportunity in Step 5 and Step 7, where they were spending a lot of time monitoring and analyzing data.
Step 5 - Promotion Sell-In
The Key Account Manager communicates to the Sales Rep which promotions to sell-in prior to execution.
Pain Points:
The KAM doesn’t know which stores are sold in to the promotion until the promotion is being executed in the store.
Therefore, the KAM doesn’t know how much revenue will likely be brought in until the promotion period is over.
And, the KAM doesn’t know if he will meet his targets for the promotion.
Step 7 - Monitor Execution Performance
The Key Account Manager monitors the performance during execution of the promotion in the retail store.
Pain Points:
The Key Account Manager has no real-time visibility into the success of the promotion in a retail store while the promotion is running.
There is little to no communication from Sales Rep to Key Account Manager when an issue occurs in the store during promotion execution.
When an issue does occur, it takes anywhere between 2-8 hours for the Key Account Manager to resolve.
Concept Design and Validation
We created concept designs to solve these greatest pains and validated them with customers.
Promotion Sell-In
We created initial designs that showed a breakdown of the number of stores that have sold in, have not sold in, have not confirmed, or have declined to run the promotion at different periods of time.
After sharing the concept with customers, we received feedback that it was most important to know just how many stores have not yet sold in, and they also wanted to know how they can get those stores to commit to running the promotion.
We made updates to the concept design by just showing stores “not sold in” and including data regarding sell-in potential and expected uplift in revenue, which helped KAMs focus on the important information and gave them a secret weapon when selling to the store.
We landed on a Dashboard Card showing the number of upcoming promotions, which drills into a list of stores with the greatest potential to sell-in the promotion, based on expected uplift in revenue.
By having the data to know which stores to target a promotion to, the KAM can preemptively inform the Sales Rep to visit the store and work with the Store Manager to sell-in the promotion. Thereby increasing the chances of reaching the target revenue goals set.
The Sales Rep can also view the potential sell-in data and expected uplift revenue data on their tablet, to help make the case to sell-in the promotion.
Monitor Execution Performance
Initially, we created a design that showed data submitted by the Sales Rep of compliance activities completed at different times prior to and during the promotion execution in the retail store.
Feedback from customers told us that they were mostly interested in seeing data during execution, not before. Also, they were interested in product sales data, not Sales Rep compliance data, since it would be more meaningful for them to predict the success of the promotion.
We landed on a Dashboard Card showing the current revenue during promotion execution compared to the expected revenue, and predicted recommendations of actions to take when the current revenue drops below a threshold level, for example when the current revenue is very low, it could mean that the stock levels are low, which could be due to either the shelves are not stocked, or the store doesn’t have any stock in the back, or the competitor product is selling better.
Upon further rounds of concept validations, customers confirmed that the new designs would have a potential time-saving of 80%.
3. Build
We are currently in the build phase, where we are usability testing the designs with research participants, and fleshing them out in collaboration with the Development teams.
We are also working at signing customers to pilot the product, and have them continue to co-innovate with us to help us further build out requirements.