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The SHS Group are an SME company with

a very diverse and complex operating

model. The company has implemented a

highly integrated end to end solution with an

ECC, CRM, BI / IP, Portal footprint.

BW solution viewed as a burden rather than

an integral part of the SAP solution…

SAP User Group 19th Oct 2010

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• Formed in 1975

• Privately owned

• Group Turnover 2008 500 million Euro

• Group employs 800+ people

• Core geographical areas:

United Kingdom

Republic Of Ireland

Background

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The Core Business

The Company operates in the FMCG sector and provides a

strong financial base and central resource for ten

successful businesses operating in four distinct areas:

• Brand Ownership

• Sales & Marketing

• Corporate Services

• Manufacturing

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SHS Group - Companies

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SHS Business Model / SAP Landscape

Plan Sales /

Promotions

Capture

Orders

Deliver From

Stock

Report /

Analyse /

Re-plan

InvoiceSettle

Promotions

IP CRM ECC BI IP

Trade Promotion Management

Portal / Electronic Trading Platform

Brand Owner Portfolio

Market understanding

Brand development

Sales and promotion

Logistics

Financial settlement

Analysis / feedback

Impulse /

Convenience

Multiples

On-Trade

• 380 BW Users

• 23 BW Reports

• Business Critical

• Brand Owner relevant

• 25 IP Reports

• Forecasting & Planning

• Daily Loads from:

• ECC (Actuals)

• CRM (Promotions & Forecasts)

BW Infrastructure

• Loss of credibility – No faith in BW, increase in

offline/non BW reporting

• Reporting Runtimes – As the amount of data

increased, so did the report runtimes

• Data Loading – The daily load amounts stayed the

same, but the time taken for the updates to complete

was constantly increasing

• Tablespace – constantly having to increase table

space volumes month on month

• Inherited Bad Practice – Lack of housekeeping, cube

design, lack of Data Store Object’s

BW – Issues & Challenges

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Plan for resolution of issues was created based on Best Practice

Strategy recommended by De Villiers Walton

Split in to two separate phases of work

Phase 1 – Best Practice Strategy

Phase 2 – InfoCube Redesign

B.I. Performance

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B.I. Performance

Phase 1 – Best Practice Strategy

• Aggregates

• Compression

• Scheduled Jobs – PSA / Change Log / Compression

• Process chains updated and reordered for better data loading

• Deletion of dormant InfoCubes / Queries

Reduced data usage from 98%

capacity to 64%

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B.I. Performance – Aggregates

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B.I. Performance – Compression

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B.I. Performance – Process Chains

Clear Out PSA

Clear Out Change Logs

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Phase 2 - InfoCube Redesign

Multiproviders – Ensuring that all cubes have a multiprovider over them

SAP_INFOCUBE_DESIGNS – 9 InfoCubes identified for redesign

Redesign – change of cube structure/storing of data

Indexing – Indexes added to improve performance of InfoCube

Partitioning – Cubes partitioned by fiscal periods

InfoCubes by Year – Each cube designed to hold one fiscal year only

Report movement from InfoCube to multiprovider

Reloading of data to redesigned InfoCube

BW Performance – Phase II

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B.I. Performance – MultiProviders

B.I. Performance – SAP_INFOCUBE_DESIGNS

Shows the database tables of an InfoCube, the number of records in

these tables and the ratio of the dimension table size to the Fact table

size.

If dimension tables are too large then they can cause badly performing

table joins on database level. As the data volume grows and the data

allocation changes over the time, this check should be executed

regularly.

When loading transaction data, IDs have to be generated in the

dimension table for the entries. If you do have a large dimension, this

number range operation can negatively affect performance.

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B.I. Performance – Indexing

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B.I. Performance – Partitioning

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B.I. Performance – Partitioning

Increased query performance

Average query runtime down from 20 secs to 5 secs

Average database call time down from 12.5 to 3 secs

Examples,

Sales v Budget report 15 secs down to 5 secs

Gross Margin reports 30 secs down to 3 secs

Debtors Analysis 60 secs down to 6 secs

Increased tablespace capacity – was 98% usage, now 60% usage

Improved data load time – Recent load of a cube took 60 hours, after cube redesign was down to 6 hours (excess 20 million record – highly customised)

User Acceptance – Improved performance leading to satisfied users running reports quickly and efficiently - now getting the data they want in a timely manner.

BW Performance – Benefits Realised

BW Performance – Benefits Realised

Accuracy – “One version of the truth” – reduction in offline reporting,

reversion back to centralised report structure. Business is now

benefiting from quick and accurate reporting.

Credibility – No longer a question over the availability or the accuracy

of the data. People can now rely on their reports being there and

being accurate

Downtime – Outages now restricted to unforeseen errors (often

caused by end users). Outage resolution a lot faster due to the

increase of system performance, full weekends no longer required for

reloads.