This document discusses how prescriptive analytics can be used to increase sales and margins. It provides examples of how prescriptive analytics can identify issues from data and provide specific actions to resolve them. Prescriptive analytics empowers employees by delivering smart tasks to take action on problems. It then tracks whether the actions were completed and their impact. Prescriptive analytics creates value by identifying controllable factors that impact future performance and offering actionable opportunities to deliver strong results.
5. IMAGE AREA
7.5” h x 7.4”w
Prescriptive analytics
creates value
5
Impacting future performance
by identifying controllable
factors and providing actionable
opportunities that deliver stellar
results
6. WE LIVE IN A CULTURE OF
LIQUID EXPECTATIONS
WHERE EACH NEW AND AMAZING EXPERIENCE
BECOMES THE STANDARD TO WHICH ALL
OTHERS A RE COMPARED
“IF I CAN PAY SEAMLESSLY WHEN I
TAKE AN UBER, WHY ISN’T IT THE
SAME WHEN I PURCHASE MY
GROCERIES?”
8. Seth’s Background –
25+ years in Retail
From startup and single store to Fortune 10 retailers
Unique blend of leadership in Retail Operations, IT,
Human Resources, Asset Protection, Safety…
Data centric, problem-solving, collaborative geek
Soccer Loft
9. • Today, we're the largest consumer co-op in the country with more
than 18 million members, over 13,000 employees and 158 stores in 37 states
and the District of Columbia.
• For the fifth year in a row, all our stores, distribution centers
and headquarters were powered 100 percent by renewable energy. Since
2008, our demand for energy has grown only 4 percent while sales have
grown 78 percent.
• Added more than 1 million new members, bringing the co-op's total
membership to more than 18 million.
• We gave back more than 70 percent of our profits in 2018 to employees,
members and nonprofit partners.
• REI has been on the "Fortune 100 Best Companies to Work For" list
for 21 straight years–that's every year the list has been out.
• Total revenue $2.78 billion in 2018, a 6 percent increase from 2017
REI's core purpose:
to inspire, educate and outfit for a lifetime of
outdoor adventure and stewardship, for all.
12. Leveraging
prescriptive analytics
to scale
• Putting the customer first
• The more data you feed it, the better it works
• Empowering employees with smart tasks
• Importance of actionability
• Feedback loop
• Quantify results
14. What can I use Prescriptive analytics for?
• Inventory Accuracy – facilitate accuracy and efficiency
• **39% customers leaving a store without purchase due to out of stocks
• Lost product, Quality issues, Pricing issues
• Customer Satisfaction
• Sentiment analysis, More staff on salesfloor, Payroll allocation, Store
hour compliance
• Cooler/Freezer preventative maintance
• Drive sales & improve margins
• Identifies missed sales opportunities – how much money is being lost
due to out of stocks
• Optimize labor allocation
• Faster identification of damages and quality issues – reduces returns
and refunds and increases the likelihood of vendor credit
• Fraud and compliance
• Identify non-compliance to age restricted products
• Anywhere you have data that should be actioned upon to improve results
**Zebra Global Shopper Survey data
15. How it is different?
• Business facing self-serve analytics
• “Push” the issue to the correct end user to
resolve
• Tell the user exactly what action to take to
resolve the issue
• Track the completion of delivered actions
• Instant feedback loop on success or failure
• Quantify the issue in dollars and track success
16. Example: Phantom Inventory
• Store number 4,836 used to sell the blue large
Patagonia insulated vest at a rate of 6 per
week
• The inventory system states they have 8 in
stock
• All their “peer” stores with the same weather
conditions cluster are still selling at their
normal rates
• To date this week, this store hasn't sold any
• Today, without prescriptive analytics, how do
you see this?
• What is the problem?
• Who can solve this?
• How should they solve it?
17. • Prescriptive analytics: used when action is needed on data
• This is bottom up problem solving
• Multiple divisions should use it for action taking
• Answering the 4 questions:
• What? Where? How? And What to do?
Actionable Takeaways from this session:
Identify behaviors that are impacting the customer
Data; Why: Helps to Identify unique behaviors and reduce false positives: How: find a solution provider that is format agnostic, utilize the rawest data you have. They should have data scientists capable of working with it.
Smart tasks: don’t give a number and tell your team to figure it out
Actionability – use language that is simple and unique to your retailer
Use this visual to showcase how many corrective actions could take place by one aggregated number.
Said differently, if you send the same issue to 500 stores to resolve without clear direction on how to solve it, you will get at least 500 ways to solve it. How many of them were correct?
e.g. inventory accuracy is dropping in your store on your apparel
This is one of the ways prescriptive analytics is different… Bottom up problem solving
Inventory Accuracy
Lost Product example
Pricing example - Use POS data to analyze every item in every store every day for price modifies on the same item across multiple stores
Quality Example - Use POS data to analyze every item every day and look for products that are starting to be returned at a higher rate then that products own return history
Sentiment analysis (online reviews, ratings, etc.) to determine customer pain points/general perceptions of business
Identify quality issues before they impact too many customers
Put employees back on the sales floor, versus reading reports in the back room
Increase delivery efficiency and accuracy to ensure e-commerce customers receive their orders on time
Seth can give the Kite endcap example from Target days