Con2012 salmon impact_of_sap_hana_revolutionary_changes_for_sap_controlling_data

© 2012 ERP Corp. All rights reserved.

The Impact of SAP® HANA: Revolutionary Changes for Your SAP Controlling Data

Janet Salmon

SAP AG

Topics

• Introduction• SAP HANA – The Basics• Profitability Analysis• Overhead Management• Production Cost Analysis• Material Ledger• SAP HANA – Next Steps• Summary

SAP HANA: Breakthrough Innovation with In-Memory Computing

Benefits• Gain Real-Time – know it when it happens

• Go Deeper – ask any question on any data

• Act Broadly – manage large volumes of data

• Run Faster – analyze at the speed of thought

• Get Flexibility – eliminate pre-fabrication requirements

In-memory computing is a technology that analyzes massive quantities of data in local memory so that the results of complex analyses and transactions are available at your fingertips and business decisions can be executed without delay.

Your Controlling Data…

• Large data volumes• Reports require tens of thousands of

records to be read and aggregated

• Process performance• Reports take several hours to complete

impacting close times

• Speed of analysis and reporting• Difficult to make relevant finance

available to managers within adequate time frame

• Poor productivity • Laborious and time consuming

reconciliation processes at period close

Big Data : What the Experts Say...

Worldwide digital content will double in 18 months, and every 18 months thereafter.

IDC

VELOCITY

In 2005, mankind created 150 Exabyte of information. In 2011, 1,200 Exabyte’s will be created.

The Economist

VOLUME VARIETY80% of enterprise data will be unstructured spanning traditional and non--traditional sources.

Gartner

ERP Data

Cos

ts

Profitability

Spe

ed

Velocity

Transactions

Opp

ortu

nitie

s

Revenues

Reports

Em

ails

Planning

Analysis

MobileP

eriod

-end

closin

g

Topics


SAP HANA – The Basics

SAP HANA is used as second database to accelerate existing applications

• SAP HANA serves as secondary database for SAP ERP or SAP CRM

• Data is replicated / written into In-Memory in real time for secondary storage

• User interface remains unchanged to ensure non disruptive acceleration

• Application is accelerated by reading the data directly from the In-Memory database

SAP HANA

Read

SAPBusiness

Suite

SAP UI

Traditional DB

In-Mem

ory

Computing Engine

Data Modeling

Replicate

SAP HANA – The Landscape

Database Table

ERP System

ABAP-Program

write

Copy ofDatabase Table

HANA DBre

ad

HANA DB is maintained as secondary DB in ERP and connected as RFC connection

Table replicationor line-wise inserts

Accelerated read

Reading from SAP HANA – An Example Data Selection

HANA DB TablesERP DB Tables

Configuration for ERP Accelerators in SAP ERP

• Monitoring of and configuration for ERP accelerators (transaction HDBC):

• Overview of available accelerators• Central configuration of secondary DB

connection• Activation of secondary DB for individual

applications• By user• By report / transaction

• Availability and status of secondary DB• Overview of replicated tables by

accelerator scenario

Topics


Profitability Analysis: Drill-Down Reports

CO-PA Accelerator – Allocations via Reference Data

• Assessments of cost center expenses into CO-PA are accelerated if receiver tracing factor for reference data is variable.

• In this example the Sales Quantities per Receiver will be read from SAP HANA to determine how the cost center expenses are to be allocated.

Transactions:

KEU1 (definition)

KEU5 (execution)

CO-PA Accelerator – Top-Down Distribution

• Example: allocate overhead marketing cost to products according to billing quantity per product

Value field as reference base for allocation

Allocate to product

For any customer, company code …

Value field to be allocated

Transaction KE28

ERP w/o HANA(production Hardware)

ERP with HANA (test installation)

Acceleration factor vs. ERP

EBIT with commodity sales – initial report

280 sec 7 sec(DB 2,8 sec)

40

EBIT with commodity sales – drilldown by alphacode


124

Cost allocation – initial report


9

Cost allocation – drilldown by sending cost center


37

Profitability Analysis: Customer Data

CO-PA Accelerator - How it Works

Periodic Update

CO-PA Read-interface

SDFI

OMPC

OBJCRM

…

CE4

CE3

CO-PA Interface

ERP-Reporting & BW -Upload

Costcenter-allocation

Top-Down-distribution

Segment Level

Line Items

K81K81.1

K81CO-PA

Line Items

K81K81.3

Customer-definedAggregation

Levels

CE2CE1

Initial Build

In Memory DB

Classic DB

„Best Choice of Source“

Add Delta

In-memory database is used as secondary database to accelerate data selection in all CO-PA processes.


Topics

Controlling Accelerator

DB Table

ERP System

Investment Programs

write

Line items

HANA DB

read

Table replication

SAP BO BI 4.0

Overhead Orders

Cost Center Accounting

Accelerated read

Accelerated ERP Reporting and In-Memory Based Partner Object Reporting Display Actual Cost Line Items for Cost Centers

and Orders Display Plan Cost Line Items for Cost Centers and

Orders

Accelerated overhead and accrual calculation

Active Availability Control Monitor

New Line Item Browser

To leverage the speed of HANA accelerated CO Line Item Browsers are provided: Cost center actual line

items KSB1N (replacing KSB1)

Cost center plan line items KSBPN (replacing KSBP)

Order actual line items KOB1N (replacing KOB1)

Order plan line items KOBPN (replacing KOBP)

Functions of New Line Item Report

Display single document

Values are aggregated by shown characteristics. Here: Cost Element

One-click access to predefined Layouts

Direct navigation between cost center groups and cost centers

Extended Selection Options

• The speed of HANA allows more freedom in selection of data

• Any field in the line item can be selected, where the old transactions would finish with a timeout for non key fields

• New Feature: Postings by partner and source object

• Examples: • Show me the aggregated value of the debits my

cost centers received from the IT department• Show me the postings to my project that were

initiated by payroll in Brazil.

Accelerated Overhead Calculation & Accrual Calculation

Actual Overhead Calculation: Project/WBS Element/Network CJ44

Financial Statement Plan/Actual Comparison CJ45

Plan Overhead Calculation: Project/WBS CJ46

Plan Overhead Calculation: Projects/WBS Elements (collectively) CJ47

Actual Overhead Calculation: Product Cost Collector CO42

Actual Overhead Calculation: Production/Process Orders CO43

Actual Overhead Calculation: Business Process CPZI

Plan Overhead Calculation: Business Process CPZP

Actual Overhead Calculation: Order KGI2

Actual Overhead Calculation: Internal/maintenance orders KGI4

Plan Overhead Calculation: Internal/maintenance orders KGP4

Plan Overhead Calculation: Order KGP2

Actual Overhead Calculation: Cost Object (individually) KKPZ

Actual Overhead Calculation: Cost Object (collectively) KKPJ

Actual Overhead Calculation: Cost Centers/Activity Types KSI4

Plan Overhead Calculation: Cost Centers/Activity Types KSP4

Actual Overhead Calculation: Sales Orders VA44

Runtime improvement: Programs will typically only need

half the time

Actual Accrual Calculation for Cost Centers KSA3

Calculate Cost Center Actual Accrual Costs: Initial Screen

KSA4

Plan Accrual Calculation for Cost Centers KSA8

Runtime improvement: The runtime may typically

decrease by a factor 2

Investment Programs Monitor

With this new function the speed of HANA enables comparison of relevant budget values and assigned values of all orders or WBS elements for an investment program (or to a sub-tree of an investment program) in real time.

Topics


Production Cost Analysis

Accelerated ERP Reporting

• Accelerates all CO-PC drill-down reports

(SAP and customer specific)

• Accelerates POWER Lists and Crystal

Reports

Responsibility Reporting on HANA

• Cost center and activity reporting as

additional dimension for responsibility

reporting

SAP BO BI 4.0

DB Table

ERP System

write

HANA DB

read

Production Cost Reports

Responsibility Reporting

Transactional data Master data

(for HANA-based reporting)

Accelerated read

Transactional data replicated via

datasourcetable replication for

master data

Production Cost Analysis in HANA Studio

26

Production Cost Analysis: Raw Data in SAP HANA

© SAP 2007 / Page 27

Production Cost Analysis: First Data Analysis

© SAP 2007 / Page 28

Production Cost Analysis – ERP Reports

• Acceleration of drill-down reports by reading from SAP HANA

• On-the-fly summarization means that data collection run (Transaction KKRV) is no longer needed during period close

• On-the-fly summarization means that there are no aggregate records in the database

• Transaction KKBC_HOE will be migrated to SAP HANA later

Production Cost Analysis – New Reports (1)

• Use Business Object Explorer for Responsibility Reporting

• Responsibility reporting determines the cost center at which variances occurred

• New analysis of variances by activity type

Sub second access

Ad hoc drill down

Cost center based view

Product based view

Product based view

Production Cost Analysis – New Reports (2)

• Use SAP Business Objects Analysis Client for Management Reporting

• Drill-Down Using Familiar Pivot Table

Product based view

Topics


Material Ledger Accelerator

• Material Ledger Reporting

• Drill down Reporting for ML

• Virtual Info Provider for ML Reporting

with SAP BO BI 4.0 tools

• Accelerated Material Price Analysis

• Material Ledger Period End Closing • Accelerated costing runs

• Accelerated BW extraction

DB Table

ERP System

write

HANA DB

read

SAP BO BI 4.0

Material Ledger /Actual Costing

Monthly aggregated reporting data

Closing Documents

Accelerated read

Table replication

Material Ledger Reporting

CKM3 - Single Material

KKML0 – Aggregated Drilldown Reporting

Reporting Using Virtual InfoProvider

ERP DB Tables

ERP System

write

HANA DB

rea

d

SAP BO BI 4.0

Virtual InfoProvider(incl. Authority

Check)

HANA DB Tables

Accelerated read

Table replication

Selection Step:

Select CKMLPP

Performance Measurements for Costing Run

Post Closing:

Join MLHD x MLIT x MLPP

Select CKMLPP 54,7%

Select MLIT 50,9%

Resulting Code Changes

• Replicate content of relevant tables to HANA• Change program to read data from HANA

HANA

Costing Run ERP w/o HANA(production Hardware)

ERP with HANA (test

installation)

Acceleration factor vs. ERP

Selection 45 minutes 10 minutes 4,5

Post Closing 75 minutes 27 minutes 2,7

Improvements in Costing Run

Relevant Database Tables

Material Data:Table Content # Fields # Keys Typical Count To be

replicatedCKMLHD Header data by material / plant 18 1 2.5 Mio -

CKMLPP Collected quantity data and status by material and period

39 5 60 Mio yes

CKMLCR currency-dependent data by material, period and currency

56 6 120 Mio -

ML Document Data:Table Content # Fields # Keys Typical Count To be

replicatedMLHD Header data by material ledger document 21 1 45 Mio yes

MLIT Control data by document item 43 3 250 Mio yes

MLPP Additional Info per item 23 5 270 Mio yes

MLCR Values and quantities by Item

Acceleration of Selection Step

• Materials have to selected by plant and by status in CKMLPP from millions of entries. It is difficult to achieve good performance with the CKMLPP keys.• When CKMLPP can be read from HANA the step can be

accelerated by a factor of 3 in a typical customer case• There are 2 variants

• Asynchronous replication: CKMLPP will be replicated / HANA by a designated program

• Ongoing replication via the LT replicator

• The first variant will be used as a start. In the long run he synchronous replication makes much more sense, because otherwise the replication step will add a new step in the period end closing process.

To be replicated: CKMLPP

Acceleration of Posting Step

• Performance tests showed that the post closing step spends a large amount of the runtime reading ML documents that were written in the previous steps of the settlement. Join on MLIT x MLPP x MLHD (> 50% of Runtime)

• Reading from HANA accelerated the step by a factor of 2 to 3.

To be replicated: MLHD, MLPP, MLIT

Topics


Bring Side-by-Side to Suite on HANA

Read

SAPBusiness

Suite

SAP UI

Traditional DB

ReplicationSAP HANA

SAP HANA

SAPBusiness

Suite

SAP UISide by Side On HANA

DB Migration

In-Memory Benefits for SAP Business Suite:

In-Memory Computing for SAP Business Suite

Improved business processes

Reduced complexity:OLAP and OLTP in one system

Performance

Productivity

Flexibility

SAP HANA

Agility: Less code, less customizing, better

supportability, …

Topics


Resources

• Janet Salmon, Controlling with SAP – Practical Guide• ISBN: 978-1-59229-392-6• http://www.sap-press.com/products/Controlling-with-SAP-

%E2%80%94-Practical-Guide.html• Vanda Reis, Actual Costing with the SAP Material Ledger

• ISBN: 978-1-59229-378-0 • http://www.sap-press.com/products/Actual-Costing-with-the-

SAP-Material-Ledger.html• Rapid Deployment Solutions for SAP HANA

• http://www.sap.com/solutions/rapid-deployment/hana-erp-profitability-analyis/index.epx

• http://www.sap.com/solutions/rapid-deployment/hana-erp-financial-reporting/index.epx

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Five Key Ideas

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• SAP HANA provides innovation through in-memory computing• Data is replicated from SAP ERP to SAP HANA in near real-time• SAP ERP transactions read data from SAP HANA

• Alternatively you can use SAP Business Objects reporting tools to display the data

• Accelerators are available for Profitability Analysis, Overhead Management, Production Cost Analysis and the Material Ledger

• SAP plans to extend the approach to cover SAP ERP, bringing OLAP and OLTP into a single system and optimizing where possible

Questions

• Now:• Ask questions now for immediate answers

• Later:• [email protected]

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Q&A

Disclaimer

SAP®, R/3, mySAP, mySAP.com, xApps, xApp, SAP NetWeaver®, Duet®, PartnerEdge, and other SAP® products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of SAP AG in Germany and in several other countries all over the world. All other product and service names mentioned are the trademarks of their respective companies. ERP Corp is neither owned nor controlled by SAP.

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