application data management - adsotech scandinavia€¦ · · 2017-11-26application data...

Application Data ManagementEmpower business teams to get the data right

Agenda8:30 – 09:00 Breakfast9:00 – 10:15 ADM Introduction

Trends & Data QualityApplication Data Management vs MDMData Ownership

10:15 – 10:30 Coffee10:30 – 11:30 Data Management Organisation (DMO)

Key PeopleGoalsTools

11:30 – 12:30 Lunch12:30 – 13:00 Hands-on Winshuttle Script Development 13:00 – 14:30 Winshuttle Demo14:30 – 15:00 Summary and Questions

DATAis becoming a strategic asset that needs to be managed by the business and not by IT

Trends Impacting Business Today

• Digital Transformation• Internet of Things• Big Data• RPA• Real Time Analytics

Data as a Strategic Asset

Modern Cars Monitor Tyre PressureOil LevelEngine TemperatureWasher FluidMileage

Driver awareness Engine NoiseVibrations of ball bearings

Automation speeds up processes but also puts pressure on data quality

How is dirty data entering the ERP system?

0,00% 10,00% 20,00% 30,00% 40,00% 50,00% 60,00%

Dont Know

None

Other

Innacurate Data

Data entered into incorrect field

Typos

Duplicate Data

Outdated Information (not current)

Spelling Mistakes

Incomplete or missing data

Common data errors in customer/prospect/citizen data

What are the reasons to keep clean data?

0,00% 10,00% 20,00% 30,00% 40,00% 50,00% 60,00% 70,00%

We don't have a data quality strategy

None

Don't know

Other

To help the environment

Reduction of risk /fraud

To crate a single customer view

Compliance with industry /government legislation

To enable more informed decisions

To capitalise onmarket opputunities through customer profiling

Enhancement of customer /citizen satisfaction

Protection of organisation's reputation and brand

Increased efficiency

Cost Savings

Reasons for maintaining high quality records

MDM vs ADM

Both are business-led, IT-enabled discipline whereby an organizations seeks to govern and steward consistent:

- Andrew White, Gartner

MDM• master data across core business processes and systems. In this case, to

keep things simple, master data (is business metadata) are things like “customer” or “product” or “hierarchy” etc.

ADM• application data for use in a specific application or suite of

applications. Application data in this case concerns all the data stored and used by that application or suite.

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• Global and well defined data standards• Lower Frequency of Change

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• Local and less defined data standards• Higher Frequency of Change

Material Master Basic Data

Plant DataRecipeSales Org dataRoutingBOMVendor Info RecordProduction VersionPricing

Warehouse DataUnit of MeasureStorage Bin LocationStorage TypeClassificationForecast ParameterVariant Configurationetc

How to distinguish between MDM and ADM

Data Governance Standards & Policies

Master Data Management

Application Data Management

MDM is the Hub ERP is the Hub

Centralized Decentralized

Select master data All application data

Application neutral Application specific

IT-Driven Business-Driven

ADM

90% ERP Data

MDM10% ERP

Data

ADM is hub-less MDM

Source: Gartner

MDM vs ADM data examples

Master DataShared across many different applications

Material numberDescriptionUnit of Measure

Material VendorCustomer

Application DataUsed only be a specific application

Storage binRoutingsClassificationsForecast parameters

Payment termsInfo recordsPurchasing organization

Customer numberDNS numberNameAddress

Bank detailsInfo recordsSales organization

Vendor numberDNS numberNameAddress

Data Ownership discussions

Customer Data

Supply Chain

Finance Team

Sales/ Marketing Team

Manufacturing

Payment Terms Data ObjectsData Objects

Data Ownership discussionsIf there is not a clearly defined ownership of data, it will probably gradually result in degradation of data.

uality

The MDM organization doesn’t own the data—it governs the data.

MDM

- Validate

- Enter the Data

- Educate?


TrendsData QualityApplication Data Management vs MDM




Who are they? What do they? Why do they do it?

Chief Data OfficerBuild data governance rules &

processes around ERP data

Improved confidence in data and

ability to participate in digital

business

Process ownersImprove data intensive business

processesImprove cycle time & velocity

Business analysts and solution

developers

Rapidly build data management and

data quality apps – batch or real-time

Reduce dependence on strained IT

resources

Data stewards Keep ERP data clean and up-to-date Uninterrupted business operations

Business Users Enter ERP dataAdd real business knowledge into

the ERP

By 2019, 90% of large organizations will have a Chief Data Officer.

CDO Vs CIO

Infrastructure and Applications

CIOCDODevelopment of Enterprise Wide Data

Governace and Stewardship processes

CDO and DMO team

CDO

Development of Enterprise Wide Data


• (RDMS, ERP)

Structured Data

• (data marts or data lakes for analysis)

Semi Structured Data

• (emails, social media web, etc)

Unstructured DataDigital transformation

Big Data Trends

Utilization of information as an asset

CDO and Data Governance

• (RDMS, ERP)

Structured Data

Glossary of Terms

Standards

Rules

CDO



Digital transformation

Big Data Trends


CDO and Data GovernanceGlossary of Terms

• Common Business Terms (Customer, Ship-to Address, Payment Term)

Standards

• Length, format, permissible values, Uniqueness, Name in Database

Rules

• Calculation, Creation, Archiving, Validity, Usage in different applications

CDO



Digital transformation

Big Data Trends


CDO and Data Governance

Data Governance and Data Stewardship

“Data Governance is the process of

implementing policies and procedures that

regulate the creation, updating and deletion of

data assets throughout the enterprise.”

“Data Stewardship is the

enforcement of the established

data governance policies.”

Data Stewardship

Data Stewards do not draft policies, they execute

them

Typically based in business departments

Maybe several Data Stewards in an

organization, each responsible for

certain parts of the Application data as

well as Master Data

Full time responsibility or a part time

responsibility

Data StewardshipTactical data stewardship.

ADM tools are often used to support this activity.

ETL, Data Cleansing based on policies

Operational data stewardship.

ADM tools can often be used in support of these activities.

Ad hoc data management, reporting, and troubleshooting

Strategic data stewardship.

Done at set up of Governance Policies

Analyse Processes and make improvements

Identifying Data Management

Goals

Master Data Maturity

Standardized processes and

platforms

No or few common

processes or

platforms

Organizational focus on master dataTactical Strategic

Tribal

Developmental

Reactive

Established

Optimized

Identifying Data Management Goals

Tribal

Limited set processesVery Ad-hocHandling problems as they arise


Developmental Some rules defined but no real governance to ensure compliance


Reactive Reacting to problems and setting up governance to stop the issue happening again

Data Cleansing in place


Established Governance in place on current processes to ensure data quality

Data Cleansing ongoing


Optimized Governance in place on current processes to ensure data quality

Data Cleansing ongoing

Data Management Team in place to ensure any business changes will also get the correct governance applied

Identifying Data Management

Goals

Master Data Maturity

Standardized processes and

platforms

No or few common

processes or

platforms

Organizational focus on master dataTactical Strategic

Tribal

Developmental

Reactive

Established

Optimized

ADM Technology Solutions

Enterprise Information Management Tools

ETL (Extract Transfer and Load

DQ (Data Quality Tools)

Business Process Management Tools (workflows)

Low code development platforms (Excel based tools)

Analytics and Dashboards

Security and Governance

• New Product introduction 1500 material in a year

Customer Case:Consumer products Manufacturing Company

• 2000 secondary materials and material closing

• 200 people were involved in process

Indirect CostsDirect Costs

Data input:5 and a quarter hours (315 minutes) per new material.

Average time to process new material = 8 weeksAverage time for Material to get ready for Sales Planning = 4-5 weeks

MDM core team needed 3 days in month to report on status material creation

Dirty data: Significant but unmeasured negative impact to operations

Almost same number of materials needed to be closed annually.

Lots of unclosed material in the sytem as it took months to close material manually, some times a year.


Ownership

Initiated, approved and Governed by Supply Chain Organization

Head of Product Master Data - overall responsible of Data Governance

Key users of solution - SAP experts - Part time Data Stewards – for their own area (Warehouse, APO, Purchase, etc. )

Key Users also helped build Governance Rules



PLM –system creates core of SAP-master

data

ADM-solution finds new material number

and automaically starts workflow

Form is sent to all stakeholders to collect

data controlled by workflow

Each participating team creates data

using their own SAP accout.

SAP Material is created. Seperate

notification is send when product is ready

for Sales planning.

Results


0,00% 10,00% 20,00% 30,00% 40,00% 50,00% 60,00% 70,00%


None

Don't know

Other










Cost Savings


Increase efficiency?Reduced workforce involved in process from 200 to 30, which meant 170 could be reassigned to other tasks.

Enhance customer satisfaction?Approx. 300 fields are updated, 85% of these are automatically filled based on form.

Enable more informed decisions?Instant reporting on status of material creation and bottlenecks

Results


0,00% 10,00% 20,00% 30,00% 40,00% 50,00% 60,00% 70,00%


None

Don't know

Other










Cost Savings


Cost/time savings?Reduced errors meant less time correcting errors.No mass mailings as notifications sent to correct teams at the correct time.Approval task for automated closing means materials are closed in one day.

Capitalise on market opportunities?”Ready for Sales” Planning time reduced from 4 weeks to 1 or 2 Weeks


TrendsData QualityApplication Data Management vs MDM




ProactiveReactive

Excel based

Winshuttle

solution

Webforms based

Winshuttle

solution

ProcessOwnership

Centralized

Decentralized

ProcessMaturity

Ill-defined Well-defined

Balancing control, flexibility and speed in Data Management.

Fast and FlexibleSAP Data Management

MDM

Manual

”It is not about one tool being better than the other... We wanted autonomy for the business.”

Winshuttle Overview

MDM HUB[SAP MDG]

OtherApplications

Data

Data

Decisions

Operations

ERP System

Time savings: 80 to 95%Quality Improvement

Process efficiency (50% shortened cycle)Governance

Developer Runner

Record

Map

Run

Benefits of Excel-SAP integration

T-Code T-Code Description Number of Customers Processing time saved by

automation

MM02 Change Material 751 86,5 %

MM01 Create Material 630 88,2 %

XD02 Customer Change 440 79,8 %

VK11 Create Condition Records 408 78,6 %

XK02 Vendor Change 392 86,7 %

XD01 Customer Create 341 93,6 %

XK01 Vendor Create 287 89,9 %

VK12 Change Condition Records 242 77,8 %

KS02 Change Cost Centre 178 74,6 %

KS01 Create Cost Centre 177 94,0 %

Workflow for data collection and approvals

New vendor request

Manager reviews

Upload to SAP

Accounting adds data

Excel based Solutions

Excel based Workflows

Forms based Workflows

Demo

Starting your Winshuttle journey

Installation

• Desktop software

• SAP functional module

Training

• 2-3 days onsite

• Exercises in your system

• Your use cases

Execution

• Launch first solutions

• Expand to new use cases

1 Week

Presented by:

1985

2000

2005

2016

today

Adsotech formed

SAP products

Winshuttle

80+ Winshuttle customers

FinlandSwedenDenmark Norway

6

2

Customers 1600 ww

Thank you [email protected]

application data management - adsotech scandinavia€¦ · · 2017-11-26application data...

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