Extending Forecasting and Replenishment Wtih HANA and Mobility

Extending F&R with HANA and Mobility

Roger Roney, Solution Engineer, SAP F&R CoE

© 2012 SAP AG. All rights reserved. 2

Agenda

Overview of an extended system

Mobile In-Store Management on Mobile Devices

Out of shelf detection Concepts

Out of Shelf Detection on mobile devices


Agenda

Extension Architecture

SAP On-Shelf-Availability Overview

Mobile In-Store Inventory Management Overview

Ipad/Iphone Demo


Customer Activity RepositoryFoundation for predictive retail applications

Web Channel

On Shelf Availability

Assortment Planning

Promotion Planning (PMR)

Merchandise Planning

Price Optimization

Markdown Optimization

Loss Prevention Analytics

Partner Solutions

Custom Solutions …

…

Dashboards

Mobile

POS

Financial Planning

Demand Planning

Customer Segmentation

POS Sales Audit

Replenishment& Allocation

CustomerActivity

Repository

Market Data

Demographics

Social Media

Customer

Promotions

Multi-Channel Sales

Merchandise

Pred

ictiv

e A

naly

tics

Retail Analytics Model & KPIs

Assortment

Locations

Click Stream

Mul

tiple

Cha

nnel

s

Inventory

Goods Movements

BW / HANA

…


Inventory Related Applications for Store Users

MasterData

Inventory

Orders

BW on HANA

ERP

POS DM On Shelf Availability

Retail Price

Promotions

In-StoreMIM

SupplyNetwork

SCM

Sales History

…

…

…Loss

Prevention

BOBJ Dashboards

MasterData

SupplyNetwork

Inventory

Orders

F&R

POS

F&R

Open Integration

Non-SAP

Applications for Store Users

On shelf availability analysis warns store personnel about potential out of self situations (mobile app)

In-Store MIM enables the store user to control merchandise and inventory in the stores

F&R store UI provides store users access to centrally created order proposals


Some Statistics

Impact : Inventory & Sales 8% - 15% out of shelf inventory* $69 billion estimated lost sales

Causes: 75% in-store Poor store processes Late and insufficient ordering Incorrect store forecasts

*) Source: D. Corsten/T. Gruen: „On Shelf Availability: An Examination“

**) Source: EPCglobal

The Issue with Out of Shelf Detection


Monitoring the System Inventory is Not Enough

No separate inventories for back room and shelf

2

System Inventory is wrong in most cases:– 65% of all inventory

figures are wrong.2

– Due to

– Theft

– Damage

– Spoilage

– Scanning errors

– Weighting errors

2 A. Raman, N. DeHoratius & Z. Ton, “Execution: The Missing Link in Retail Operations”, California Management Review 43, 136–52 (2004)

System Inventory Cannot be Used to Monitor Shelf Availability


Possible Integration into Business Processes

Analytical

Detection of Out-of-Shelf

Process Optimization

Determination of KPIs

Identification of Process

weaknesses

– Optimization of delivery cycle, pack size, shelf capacity, shelf replenishment …

– Organizational Measures– …


Possible Integration into Business Processes

Out-of-Shelf Detection

Direct Support of Store Processes

Analytical

Operational

– Backroom replenishment– Correction of inventory figures– Ordering– Shelf tidying

– Optimization of delivery cycle, pack size, shelf capacity, shelf replenishment …

– Organizational Measures– …


Measurements and Challenges

Automated Measurements Direct Measurements with technical support

Indirect Measurements by the acts of purchasing

Challenges Application on different selling classes

– Fast Seller– Slow Seller

Recurring variability of the sales level

Consideration of promotions Trend Outlier …


Methods for statistical measurments

Depending on the provided data there are two approaches possible:

1. Analysis on sales- timeseries

a) Sales minimum- limit

b) Maximum period of sequenced zero sales days

t

ymin

t

Nmax


Monitoring the maximum waiting time I

Basis: Series of sales transactions per product, no time aggregation Idea: Frequency analysis of waiting times

determination of a maximum tolerable waiting time tL,max

tL,max can be determined from the probability of exponential distributed waiting timesas a function of average sales per period given a tolerable false alert rate.

t

tL,max

tL

2. Analysis of transactional data- Exceeding of a maximum tolerable waiting time

tL,max

tL,max


Monitoring the maximum waiting time II

Independent of the sales behavior

t

tL tL,max

Ultra Slow Seller

t

tL tL,maxFast Seller

t

tL tL,max

Slow- Seller

Promo


The Algorithm

The Algorithm is the science behind the on shelf availability app. Running on SAP HANA, it analyzes several months of granular T-Log sales data for each product / location

The algorithm sits on Hana, while it accessing the new POS DM on HANA, leveraging in-memory computing power to execute millions of queries constantly

Without NewDB and POSDM on HANA, this kind of number crunching is not possible in a business-useful way


In-Store Applications Overview

Store Associate Application Displays out-of-shelf alerts and a work-list Allows corrections to be done right on the sales floor and in the

back room Updates the rest of the system appropriately

Store Manager Application Displays analytics on out-of-shelf alerts Allows Analysis of alert resolutions on different levels


Store Associate ApplicationOverview

Goal: Displays alerts for products that may have on-shelf availability issues

Store associates in different departments can respond to alerts quickly, and can avoid having to walk throughout the entire store on a daily basis

Store associate can refill his shelf and trigger follow-on activities to prevent potential lost sales

Provides transparency of on-shelf availability situations for regular and promotional products


Manager DashboardOverview

Goal

Provides historical insight into how many products have on shelf availability issues on a weekly, daily and hourly basis

Managers can view details on how store associates resolved each of the on shelf availability issues, and in what time frame

Managers can use this information to optimize resource scheduling, analyze why items are out of shelf, and optimize inventory levels


Mobile In-Store Merchandise and Inventory Management

Mobile In-Store MIM enables store associates to execute core merchandising, inventory and customer service functionality on a mobile device in the aisle

Functionality Inventory/Price/Product Lookup Customer Order Management (COM)/ Order Status Store Ordering Receiving Goods Movement Cycle Counting / Physical Inventory Purchase Order


Mobile In-Store Merchandise and Inventory Management

Mobile In-Store MIM enables store associates to execute core merchandising, inventory and customer service functionality on a mobile device in the aisle

Benefits answer nearly any question a customer might have about inventory, price, and product

details. create an order for home deliver or pickup and includes features such as create customer,

sales order, and order status Receiving functionality provides ability to post receiving and update the inventory instantly. Goods movement can be used by store associates to correct the inventory on the shelf or

transfer products. With Cycle Counting/Physical Inventory store associates can perform counting and ensure

an accurate inventory. Purchase Order allows ordering products from an external or internal vendor, move products

from one store to other, and handle returns. .

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Extending Forecasting and Replenishment Wtih HANA and Mobility