Application Data Management Empower business teams to get the data right

Transcription

1 Application Data Management Empower business teams to get the data right Run by SAP customers

2 Content 1. The beginning Trends impacting business today 2. Data Governance and Data Stewardship 3. MDM versus ADM 4. ADM Technology Capabilities 5. Product demonstrations Winshuttle 6. ADM Adoption in the Enterprise 7. Winshuttle and Adsotech presentation 8. Summary and conclusions 9. Lunch and networking

3 Trends Impacting Business Today Digital transformation Big Data Real time Analytics Data as a Strategic Asset

4 DATA is becoming a strategic asset that needs to be managed by the business and not by IT

5 Importance of Data Management Decisions Operations ERP System 25% Inaccurate or incomplete Data Growth

6 Tax over time Direct Costs Indirect Costs Data Mgt. TAX Delays/ Errors Speed/ Accuracy

7 How is data dirty entering the ERP system? Common data errors in customer/prospect/citizen data Incomplete or missing data Spelling Mistakes Outdated Information (not current) Duplicate Data Typos Data entered into incorrect field Innacurate Data Other None Dont Know 0,00% 10,00% 20,00% 30,00% 40,00% 50,00% 60,00%

8 What are the reasons to keep clean data? Reasons for maintaining high quality records Cost Savings Increased efficiency Protection of organisation's reputation and brand Enhancement of customer /citizen satisfaction To capitalise onmarket opputunities through customer profiling To enable more informed decisions Compliance with industry /government legislation To crate a single customer view Reduction of risk /fraud To help the environment Other Don't know None We don't have a data quality strategy 0,00% 10,00% 20,00% 30,00% 40,00% 50,00% 60,00% 70,00%

9 Data Governance and Data Stewardship 1. Definition of Data Governance and Stewardship 2. The role of the Data Steward 3. Enforcement of Data Governance 4. The role of the CDO 5. Discussion

10 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.

11 Data Governance and Data Stewardship Structured Data (RDMS, ERP) Semi Structured Data (data marts) Unstructured Data ( s, social media web, etc) Glossary 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

12 Data Governance and Data Stewardship Data preparation Data creation Data change Maybe several Data Stewards in an organization, each responsible for certain parts of the Application data as well as Master Data Maybe a full time responsibility or a part time responsibility Typically based in business departments Data Stewards do not draft policies, they execute them If there is not a clearly defined ownership of data, it will probably gradually result in degradation of data quality.

13 Data Governance Enforcement Data Governance Enforcement can be implemented in a variety of ways: Manual enforcement by assigning people to roles such as Data Stewards Built it into ERP systems Reactive Governance Proactive Governance

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

15 Data Governance and Data Stewardship CDO CIO Development of Data Governace and Stewardship processes Infrastructure and Applications

16 Data Governance and Data Stewardship CDO Digital transformation Big Data Trends Enterprise wide governance Utilization of information as an asset

17 Data Governance and Data Stewardship Do you have CDO? Data Stewards? Has the Data Governance been clearly defined? How do you plan to tackle these topics?

18 MDM versus ADM MDM versus ADM Gartner and Wikipedia definitions Trains and buses Discussion about the differences and similarities

19 MDM according to Wikipedia In business, master data management (MDM) comprises the processes, governance, policies, standards and tools that consistently define and manage the critical data of an organization to provide a single point of reference. Enterprise Master Data is the single source of common business data used across all systems, applications, and processes for an entire enterprise (all departments, divisions, companies, and countries).

20 MDM according to Gartner There is a great confusion in the market about what to store and govern in an MDM solution. Too often we hear examples of successful MDM programs drowning in too much data as more and more application data data is moved to the MDM hub since it seemed to provide an effective means to govern data. The reality is that MDM solutions are designed and optimized to work flexibly with any number of applications for which the MDM data model is application neutral. A solution designed and optimized to govern data for a specific, known business application would not be the same indeed it s data model would be identical to the target application. Armed with this knowledge, we see a slow shift and recognition by users that MDM solutions should be used to govern master data outside of and independent of the application - business applications and application data management (ADM) solutions should be used to govern data for known target business applications

21 Managing things Aquatic Animals Amphibians Terrestrial Animals?

22 How to handle Master Data? Master data Application data Transactional data Supplier Vendor Info Record MDM Control/Governance? ERP Speed / Flexibility

23 How to distinguish between MDM and ADM ADM Data Governance Standards & Policies MDM 10% ERP Data 90% ERP Data ADM is hub-less MDM Master Data Management MDM is the Hub Centralized Select master data Application neutral IT-Driven Application Data Management ERP is the Hub Decentralized All application data Application specific Business-Driven Source: Gartner

24 Speed / Flexibility Control

25 MDM vs ADM Both are business-led, IT-enabled discipline whereby an organizations seeks to govern and steward consistent: 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. - Andrew White, Gartner

26 MDM vs ADM data examples Material Customer Vendor Master Data Shared across many different applications Material number Description Unit of Measure Customer number DNS number Name Address Vendor number DNS number Name Address Application Data Used only be a specific application Storage bin Routings Classifications Forecast parameters Bank details Info records Sales organization Payment terms Info records Purchasing organization

27 What is ADM - Conclusion Application data management is a technology-enabled discipline designed to help users govern and steward the application (reference) data required to operate specific business applications, such as CRM, ERP or supply chain planning. Such data may include master data even if there is a separate master data management (MDM) solution. It is implemented within the context of the specific application or suite, so typically it uses the same persistent data and data model. Gartner 2016

28 ADM Technology Capabilities 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

29 Trains and buses

30 Trains PROS Carry more passengers Advanced services (extra luggage, coffee kiosks) CONS Big investment in infrastructure Time-consuming Requires a broad range of specialized skills Can t easily be modified or added to

31 Buses PROS Affordable Implemented immediately Very flexible Can serve all areas of a city Easy to reroute CONS Fewer passengers

32 Long Term Strategy Combo of trains & buses Train line between major hubs Reach outside of the main hubs with network of buses

33 Balancing control, flexibility and speed in Data Management. Centralized MDM Process Ownership Fast and Flexible SAP Data Management Decentralized Manual Ill-defined Process Maturity Well-defined It is not about one tool being better than the other... We wanted autonomy for the business.

34 Winshuttle Usage within ADM Areas Data Management tools for SAP professionals Mass loads and mass changes to SAP application data Mass upload of transactional data Data Cleansing Processes Simplifying the SAP End-User Experience Data Entry Simplification for End-Users Business Process Innovation - Workflows Improve SAP and other business processes Overhaul old legacy MDM, SC, SD, FICO and HR transactional systems

35 Reactive Excel based Winshuttle solution Proactive Excel based process automation Proactive Strategic Webforms based Winshuttle solution

36 Winshuttle Overview Decisions Operations ERP System Data Data Time savings: 80 to 95% Quality Improvement Process efficiency (50% shortened cycle) Governance Other Applications MDM HUB [SAP MDG]

37 Developer Runner Record Map Run

38 Benefits of Excel-SAP integration T-Code T-Code Description Number of Customers Processing time saved by automation MM02 Change Material ,5 % MM01 Create Material ,2 % XD02 Customer Change ,8 % VK11 Create Condition Records ,6 % XK02 Vendor Change ,7 % XD01 Customer Create ,6 % XK01 Vendor Create ,9 % VK12 Change Condition Records ,8 % KS02 Change Cost Centre ,6 % KS01 Create Cost Centre ,0 %

39 Workflow for data collection and approvals Accounting adds data New vendor request Manager reviews Upload to SAP

40 Example of customer who has reduced time for NPI Before Food packaging - 11,000 employees - Revenue: $10 billion Now 28 days for PCR 14 days for PCR Increasing Revenue

41 Master Data-related cost savings ABB in Finland saved more than 6 months during the first six months data cleansing Stora Enso saved several months in the first factories reorganization project Outotec added all of an acquired company's SAP employees data in 2 days

42 Master and Application Data related cost savings Statoil saved in 2016 over hours by using Winshuttle products in various business units (average saving 7300 h/ user per annum)

43 Master Data-related cost savings Days saved vs Transactions processed XD02 - Customer Change VK11 - Create Condition Records VD02 - Customer Change (Sales) IE01 - Create Equipment IL02 - Change Functional Location MM01 - Create Material MM02 - Change Material VK12 - Change Condition Records MM42 - Change Material & ME12 - Change Purchasing Info Record ME11 - Create Purchasing Info Record 0 Transactions Processed H Days Saved H1 2016

44 Master data management time consuming Heavily relied on SAP business analysts Linked scripts for MM01, MM02, CS01, CS02, & CA02 2 hours to 2 minutes

45 GBS Global Data Services productivity trends GBS Customer Data Maintenance GBS Material Data Maintenance Transaction Volume Total Service Cost Transaction Volume Total Service Cost Cost per Transaction Cost per Transaction Customer Data Maintenance Transaction Volume 1 % Total Service Cost -76 % Cost per Transaction -79 % Material Data Maintenance Transaction Volume 45 % Total Service Cost -34 % Cost per Transaction -58 %

46 Demo Excel based Solutions Excel based Workflows Forms based Workflows

47 ADM Adoption in the Enterprise ADM Adoption in the Enterprise ADM Stages and Maturity Key ADM activities and users Customer Case

48 Master Data Market Standardized processes and platforms Mature Optimized Established Master Data Maturity Transitional Reactive Developmental No or few common processes or platforms Tribal Tactical Organizational focus on master data Strategic

49 Organisational maturity Enterprise Workgroup Desktop Tactical/Reactive Organisational focus Strategic/Proactive

50 ADM Vision Key Capabilities & Benefits Who What Benefit Chief Data Officer Process owners Business analysts and solution developers Data stewards Business Users Build data governance rules & processes around ERP data Improve data intensive business processes Rapidly build data management and data quality apps batch or real-time Keep ERP data clean and upto-date Enter ERP data Improved confidence in data and ability to participate in digital business Improve cycle time & velocity Reduce dependence on strained IT resources Uninterrupted business operations Add real business knowledge into the ERP

51 Customer Case: Consumer products Manufacturing Company New Product introduction 1500 material in a year 2000 secondary materials and material closing 200 people were involved in process

52 Customer Case: Consumer products Manufacturing Company Direct Costs Indirect Costs Data input: 5 and a quarter hours (315 minutes) per new material. Average time to process new material = 8 weeks Average 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.

53 Customer Case: Consumer products Manufacturing Company Ownership Data Governance and Data Stewardship Ownership Project was initiated, approved and Governed by Supply Chain Organization. Data related roles Head of Product Master Data department is overall responsible of Data Governance. Most of the Key users of solution are business side SAP experts who are Part time Data Stewards they maintain business rules in solutions data their own area (Warehouse, APO, Purchase, etc. ) that allows automation and eliminates errors. Key user also specified requirements and data model with Adsotech. Project IT run implementation project together with Adsotech. Adsotech developed first solutions, now we are doing knowledge transformation on workflow development and cooperative development for additional material types.

54 Customer Case: Consumer products Manufacturing Company Solution Overview SAP MM DataSteward1 basic Data DataSteward2 DataSteward3 100 % SAP ERP Data DataSteward4 1. PLM system creates core of SAP-master data 2. ADM-solution finds new material number and automaically starts workflow 3. Form is sent to all stakeholders to collect data controlled by workflow 4. Each paticipating team creates data using their own SAP accout. 5. As end result full SAP Material is created. Seperate notification is send when product is ready for Sales planning.

55 Customer Case: Consumer products Manufacturing Company Results Reasons for maintaining high quality records Cost Savings Increased efficiency Protection of organisation's reputation and brand Enhancement of customer /citizen satisfaction To capitalise onmarket opputunities through customer profiling To enable more informed decisions Compliance with industry /government legislation To crate a single customer view Reduction of risk /fraud To help the environment Other Don't know None We don't have a data quality strategy 0,00% 10,00% 20,00% 30,00% 40,00% 50,00% 60,00% 70,00% 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 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

56 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

57 Presented by:

58 today Adsotech formed SAP products Winshuttle 80+ Winshuttle customers

59 Denmark Norway Sweden Finland

60 6 Customers 1600 World wide

61 Thank you Visit winshuttle.com or Adsotech.com for more information.