Journey to Integrated Business Planning with SAP IBP Demand DXC Oxygen.pdf · category development...

© 2020 DXC Technology Company. All rights reserved.

March 5, 2020

Journey to Integrated Business Planning with SAP IBP DemandDelivering a template for better business planning

Denis FranovPrincipal Consultant SCM, DXC Oxygen

March 5, 2020 2© 2020 DXC Technology Company. All rights reserved.

PT_4485a-20

Agenda

1. Introduction – What was the problem?

2. What options were considered?

3. Why SAP Integrated Business Planning

(IBP)?

4. Solution Functionality / Useability

Improvements

5. How has IBP Demand evolved from

APO?

6. Key differences / New features /

Improvements

7. Benefits / Learnings from an IBP for

Demand implementation – What was

achieved?

8. Expected Business Benefits

9. What are the key takeaways about IBP?

10.Key Project Learnings


PT_4485a-20

The problem

• Latest statistical forecasting and demand sensing technology that can

use multiple sources of data to predict most statistically accurate

future forecast

• Flexible time increments and horizons that will allow the demand

planners to view forecasts in easily selectable time periods

• Easy integration with SAP MRP to give supply planning full view of

latest forecast at relevant level of detail

• Ability to input volume and trade spend and complete basic valuation

of key financial metrics to ensure volume meets financial targets

• Offline scenario modelling to facilitate budgets, crop planning,

category development

• A cloud hosted platform supported with quarterly software upgrades

and latest industry best practice updates, algorithms and models.

A leading branded food exporter

came to us with this question…

“How do we bring these

capabilities to our planning

organisation?”

Our answer…

““Implement SAP IBP

for Demand!”


PT_4485a-20

What options were considered?

They looked at numerous

solutions & a detailed

review was performed

which compared… Planning Analytics

Integrated

Business Planning


PT_4485a-20

Why SAP IBP?

Vendors were ranked against

• Functionality

• Security and Applications

Management Module

• Useability

• Vendor Support Structure

• Systems Requirements

• People and Company

Supply Chain Control Tower

Sales & Operations Planning

Demand Inventory Response & Supply

SAP HANA Platform

Vendors were asked to

present to a cross

functional business group

using sample data that had

been provided to them

Based on rankings,

reference visits & further

exploration of the software

capabilities and SAP IBP

was selected as the

solution.

Key factors for selecting IBP

• Overall functionality and maturity of DP

• Integrated workflow

• Detailed time bucket manipulation

• Demand sensing capability

• Extended IBP toolset


PT_4485a-20

© 2020 DXC Technology Company. All rights reserved. March 5, 2020

Solution / Usability Improvements


PT_4485a-20

How has IBP for Demand evolved from APO DP?

• Same core statistical models, plus a number of new more powerful statistical

forecast models

• Fiori Apps for configuration - planning areas, key figures, planning levels,

attributes, etc

• Fiori Apps for creating / editing profiles and other key end user functions

• Key Fiori Apps - Managing Forecast Profiles, Managing Segmentation Rules,

Managing Product Lifecycle, Planning Filters, Application Job Templates,

Application Jobs, Change History Report, Analytics, Dashboards, Alerts, etc.

• Data Cleansing enhanced functionality

• Demand Sensing for more accurate short term forecasting

• ABC/XYZ Segmentation to enable more intuitive product assignment to forecast

models

• Manage Product Lifecycle App for easy Phase in / Phase out and Like Profiles

management

• IBP Excel Add-In front end for a more intuitive user experience for planning

process execution

The key differences, new

features and functionality

Improvements


PT_4485a-20

Web Launchpad – Fiori Apps


PT_4485a-20

Fiori Apps – Manage Forecast Models


PT_4485a-20

IBP Excel Add-In Ribbon

Create

views

Edit

views

Simulate

processes

Manage

master data

Manage

versions Run jobs

Favourites Filters Master

data views

Use

scenarios

All functions at the

user’s fingertips


PT_4485a-20

IBP Excel Planning Views


PT_4485a-20

Master Data WorkbookAll master data types can be included in one master data workbook for ease of master data

access and management


PT_4485a-20

Data Cleansing Tools

Substitute Missing values

It may happen that certain time

series values are missing from the

input data.

Close data gaps that occur due to

lost records or technical issues in the

time series

Outlier Correction

An “outlier” is a value in the historical

data that lies outside the expected

range of values.

Clean the history from outliers such

as one-time events or data entry

errors that affected the sales results.

Promotion Sales Lift Elimination

Historical promotions may be one-

time events or not reflecting future

promotions and have an effect on

the sales history.

Can clean the history of these

promotions i.e. de-promote the data

to create a more accurate history for

new baseline forecasts.


PT_4485a-20

ABC / XYZ Segmentation

Segmentation helps define more specific alerts and

reports, generate more accurate results for demand

planning and inventory planning.

Among others, it allows you to do the following :

• Tailor forecast strategy and inventory optimisation to

characteristics of segments

• Assign more appropriate forecast models to planning objects

• Analyse forecast accuracy by product segments

High volume,

constant demand

High volume, trend

or seasonal

demand

High volume,

random or sporadic

demand

Medium volume,

constant demand

Medium volume,

trend or seasonal

demand

Medium volume,

random or sporadic

demand

Low volume,

constant demand

Low volume, trend

or seasonal

demand

Low volume,

random or sporadic

demand

A

B

C

X Y Z Variance

Usage/

Importance

Characteristics that

the various

combinations of

ABC and XYZ

segments imply


PT_4485a-20

Demand Sensing

What is the difference?

Demand Sensing vs. Classical Statistical Forecasting

Statistical Forecasting Demand Sensing

Basic Principle Forecasting Pattern Recognition

Planning HorizonsComputes a demand plan for the mid to long

term horizon (usually up to 1-2 years)

Computes a demand plan for the short term

horizon (usually 6 weeks)

Planning Cycles Monthly or quarterly cycles, sometimes weekly Weekly and sometimes daily cycles

Historic data UsageSeasonality and trends over a longer term

horizon (e.g. 2 years) are picked up

Short term patterns over the last year.

Seasonality and trends are taken over from the

consensus forecast

Demand Sensing does not replace Statistical Forecasting. It rather extends it.


PT_4485a-20

IBP Integration Requirements Using CPI-DS

• The (CPI-DS) Cloud Platform Integration – Data Services system for

connecting IBP and other systems / data sources for loading data into

IBP and for extracting data

• CPI is a flexible / powerful integration tool enabling mapping and

automated flow of data via extractors

• The graphic shows the types of data transfers executed in the DP

implementation

• ECC master data included: Product, Locations (Plants), Customers,

Currencies, UOM’s, UOM Conversions

• BW data included: Actual Sales history, Customer Product and Product

Location compound master data

• External data included: AC Nielsen scan data loads, Customer Forecast

loaded from customer provided excel files

• Created 30+ batch jobs to trigger the CPI extractors from IBP

• Interfaces: Inbound Master Data = 13, Inbound Key Figures = 11,

Inbound External KF = 6, Outbound to ECC = 6, Outbound to BW = 25

IBP

ECC

BW

External Data

Source

CPI

Master Data

IBP Forecast

Transactional Data

IBP Forecast & Tradespend

Customer Forecast

IBP Dataflow High Level Architecture


PT_4485a-20

IBP for Demand Implementation

• Delivered a standardised process and tools for all business

functions

• Enabled statistical forecasting capability and use

• Provided an understanding of how to develop improved stat

forecasting results through automated model simulation, best

fit model assignment to facilitate ongoing improvement

• Created 12 planning view templates to cover all planning

• Achieved fully automated integration through CPI-DS with

ECC, BW and External data sources

• Utilised all the standard functionality as is out of the box i.e.

Data Cleansing tools, Forecast Models, Segmentation, Forecast

Error Calculation / Lags, NPI / Product Lifecycle Management,

Application jobs, Copy Operators

What was achieved?


PT_4485a-20

Expected Business Benefits

• Address current business issues that lead to poor forecast

accuracy

• Lay the platform to achieve improved forecast accuracy

to drive finished product inventory and other working capital

savings

• Flexibility, responsiveness and transparency

• Real time analysis, scenarios planning, improved financial

planning and budgeting processes

• Deliver improvements in service levels with customers

• Reduction in slow moving & stock write offs

• Less manual tasks


PT_4485a-20

What are the key things to takeaway about IBP?

• Numerous features and benefits over APO DP and other

software in the market

• User interface is completely new!

• Combination of Fiori apps for system management and

reporting

• Excel Add-In for planners with the power of HANA

database

• More visually intuitive tool

• Embed own formulas in the Excel planning

• Cloud hosted system with secure reliable SAP

infrastructure and support from Sydney data centre

• Quarterly updates and IBP is still improving


PT_4485a-20

Key Project Learnings

• Thoughtful definition of planning filters

• Implement statistical forecasting and refine and improve

• Use auto selection of best fit models as a starting point

• Understand the difference between the APO DP CVC design and

the IBP master data design

• Experienced business resource for defining CPI integration

requirements

• Need an experienced SAP Basis resource working with CPI

integration consultant

• Utilise the SAP Best Practices Methodology and tools provided

• Leverage the provided test scripts and processes

• Early user involvement

March 5, 2020 24© 2020 DXC Technology Company. All rights reserved. March 5, 2020 24© 2020 DXC Technology Company. All rights reserved.

PT_4485a-20

Denis Franov

Principal Consultant SCM,

DXC Oxygen

T +61.2.8879.6630

M +61.407.236.843

[email protected]

Journey to Integrated Business Planning with SAP IBP Demand DXC Oxygen.pdf · category development...

Documents

Transcript of Journey to Integrated Business Planning with SAP IBP Demand DXC Oxygen.pdf · category development...