Master Data Management Before or After ERP?



Similar documents
Top Five Reasons Not to Master Your Data in SAP ERP. White Paper

Data Governance for ERP Projects

Master Your Data and Your Business Using Informatica MDM. Ravi Shankar Sr. Director, MDM Product Marketing

Agile Master Data Management A Better Approach than Trial and Error

Building a Business Case for Procure-to-Pay

EMC PERSPECTIVE Enterprise Data Management

Enable Business Agility and Speed Empower your business with proven multidomain master data management (MDM)

HANDLING MASTER DATA OBJECTS DURING AN ERP DATA MIGRATION

HANDLING MASTER DATA OBJECTS DURING AN ERP DATA MIGRATION

Enabling Data Quality

Enterprise Information Management Services Managing Your Company Data Along Its Lifecycle

Data Management Roadmap

Critical Success Factors for Product Information Management (PIM) System Implementation

Data Governance: A Business Value-Driven Approach

The Why, What & How of. Contract Management

Knowledgent White Paper Series. Developing an MDM Strategy WHITE PAPER. Key Components for Success

Evolutionary Multi-Domain MDM and Governance in an Oracle Ecosystem

Next Generation Business Performance Management Solution

The Why, What and How of. Supplier Management. - Part 1 of the Procurement Performance Elevation Series

MRO Master Data Management for Enhanced Maintenance Performance

An RCG White Paper The Data Governance Maturity Model

Operational Excellence for Data Quality

Guidelines For A Successful CRM

SOA Testing Services. Enabling Business Agility and Digital Transformation

HOW TO USE THE DGI DATA GOVERNANCE FRAMEWORK TO CONFIGURE YOUR PROGRAM

Mergers and Acquisitions: The Data Dimension

Analytics Strategy Information Architecture Data Management Analytics Value and Governance Realization

Delivering information-driven excellence

Data Governance: A Business Value-Driven Approach

Office Business Applications (OBA) for Healthcare Organizations. Make better decisions using the tools you already know

Logical Modeling for an Enterprise MDM Initiative

Key Risks IT Channel Partners Must Manage To Succeed In Business

Master Data Management

Transform Your Bank in Measurable Steps

Data Virtualization A Potential Antidote for Big Data Growing Pains

Trends In Data Quality And Business Process Alignment

The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into

A technical paper for Microsoft Dynamics AX users

Purchase Order. Management P2P. Payments & Discounting. The science of procurement. The heart of performance.

Optimizing EDI for Microsoft Dynamics AX

The business owner s guide for replacing accounting software

A discussion of information integration solutions November Deploying a Center of Excellence for data integration.

Buying vs. Building Business Analytics. A decision resource for technology and product teams

CONTENT STORE SURVIVAL GUIDE

Buyers Guide to ERP Business Management Software

Whitepaper Data Governance Roadmap for IT Executives Valeh Nazemoff

04 Executive Summary. 08 What is a BI Strategy. 10 BI Strategy Overview. 24 Getting Started. 28 How SAP Can Help. 33 More Information

Considerations: Mastering Data Modeling for Master Data Domains

Real Estate Lifecycle Management

A new paradigm for EHS information systems: The business case for moving to a managed services solution

Enterprise Data Management for SAP. Gaining competitive advantage with holistic enterprise data management across the data lifecycle

Project Management Office: Seeing the Whole Picture

Portfolio Management 101:

Using Master Data in Business Intelligence

Master Data Management Framework: Begin With an End in Mind

What to Look for When Selecting a Master Data Management Solution

SharePoint Managed Services: How to Make SharePoint Work for You

Applied Business Intelligence. Iakovos Motakis, Ph.D. Director, DW & Decision Support Systems Intrasoft SA

WHITE PAPER The Evolution of the Data Center and the Role of Virtualized Infrastructure and Unified 3D Management

Three Fundamental Techniques To Maximize the Value of Your Enterprise Data

Challenges in the Effective Use of Master Data Management Techniques WHITE PAPER

Master data value, delivered.

This case study walks you through the challenges involved in each step of the MDM initiative as shown in Fig.1 below: Oracle PLM.

IBM Software A Journey to Adaptive MDM

Point of View: FINANCIAL SERVICES DELIVERING BUSINESS VALUE THROUGH ENTERPRISE DATA MANAGEMENT

HP SOA Systinet software

I D C V E N D O R S P O T L I G H T. H yb r i d C l o u d Solutions for ERP

Enterprise Architecture for Communication Service Providers: Aligning Business Goals to IT

The Ultimate Guide to Buying Business Analytics

NCOE whitepaper Master Data Deployment and Management in a Global ERP Implementation

The following is intended to outline our general product direction. It is intended for informational purposes only, and may not be incorporated into

Busting 7 Myths about Master Data Management

Why Professional Services Firms Need an Integrated ERP Solution

Verdantis Material Master Data Management Delivering standardized, de-duplicated & enriched Material Master

World-Renouned Services

Material Master Data Management

Automated Business Intelligence

Informatica Master Data Management

Leveraging BPM Workflows for Accounts Payable Processing BRAD BUKACEK - TEAM LEAD FISHBOWL SOLUTIONS, INC.

Application Services Portfolio

Building the Digital HR Organization. Accenture and SuccessFactors on the changing nature of HR

Transportation Management Systems Solutions:

Turn Your Business Vision into Reality with Microsoft Dynamics NAV

Thriving in the New Normal for Tax Administration

by David Hebert, Managing Director, Oracle Applications, Answerthink and Dr. David Oppenheim, Director, Delivery Services, Answerthink

Enterprise Data Governance

MANAGING USER DATA IN A DIGITAL WORLD

Multi-Domain Master Data Management. Subhash Ramachandran VP, Product Management

Why is Master Data Management getting both Business and IT Attention in Today s Challenging Economic Environment?

Transcription:

Verdantis DATA DRIVEN PERFORMANCE The Million Dollar Question: Master Data Management Before or After ERP?

The Million Dollar Question: Master Data Management Before or After ERP? All organizations taking up this multi-million dollar task of ERP implementation /up gradation find themselves in this tricky situation: When to start thinking about MDM Before the ERP process or after go live? Some also argue on using ERP for MDM - after all MDM is an integral part of ERP offerings. Before jumping to any conclusion it's better to understand the whole concept of ERP first what does it offer? What kind of data it interacts with? Who all work on the new/ up graded application suite? Etc. Interestingly, for most of the companies ERP is a strategy to buy everything from one vendor which is very different from the core idea of bringing all application to a single process/data model. Companies tend to ignore this as sourcing everything from one preferred vendors gives them the liberty to negotiate on the pricing front plus resources are not wasted in integrating different application suites to the core process model. So, should MDM of any value in this process? One word answer, Yes! and optimization requirement. Take for example when we move from one place to another country or city or a new desk for that matter, we start with consolidating our belongings and keeping everything in a structured way so when needed we can find out what's where. Similarly, in any ERP implementation/up gradation involving multiple source systems, locations & languages, Master Data Cleansing & harmonization activity becomes inevitable. In this paper we will discuss why ERP is not the right place to master your data and why MDM is so important whether it's before or after. Also we will have a look at MDM market today and how it's going to shape up in near future. Well, the basic idea is whenever there is any migration activity, there is a data cleansing

Why ERP is not a place to Master your Data? Some people might argue for ERP over MDM. This is not entirely wrong, if all the data is centralized and modeled, managed by single instance of ERP then that organization might not need a separate MDM and governance initiative but data enrichment still becomes mandatory for greater business process efficiencies. However, it rarely happens that a large or even a mid size company runs most of its transactions in one instance of ERP. An effective MDM implementation is one of the few IT initiatives companies can pursue to realize near-immediate business process improvements across many different areas within the enterprise. Many organizations with extensive ERP implementations try to make their enterprise resource planning (ERP) application suite the focus and the basis of their MDM initiatives. It seems like an enticing proposition, given the possibility of capitalizing on existing IT infrastructure, investment, institutional knowledge and so forth. Yet ERP systems are not designed to support master data management, and are simply not the right place to master your data. As a matter of fact, ERP was meant to give a single view of transactional data and not a ERP was meant to give a single view of transactional data and not a single view of business master data. single view of business master data. While its design succeeded in the first part, the latter was implied. ERP in its budding years was not functionally potent to support all users needs. So most, if not all, firms kept on adding other vantage application to their ERP. This leads to the situation where ERP was the core transaction engine but much data existed outside of ERP. With time ERP evolved and built its own vantage applications or acquired those applications, but core process models remained the same as applications were just added to suite and not built on them. So ERP never delivered to its promise of providing single platform, single system, single entry point for all front end, back end, enterprise

Why ERP is not a place to Master your Data? solution. All we built was a large vertical silos of applications with their own data, making the whole concept of Master Data and a single, actionable view of the organization, more complex. So what s wrong with latest versions of ERP solution suite offered by different vendors? Despite all the positives of ERP, flexibility has always been an issue with ERP. Today s complex systems, data structures, architectures need active management of critical master data and ERP doesn t offer the tools to manage that. Specifically, data matching capabilities are too basic. Its search functions might be good at exact match but they are not as strong as the kind of fuzzy searching that is so important in uncovering duplicate entries with subtle differences. Thus it gives the end users the liberty to create new duplicate records bypassing all protocols and there s no way to create a golden copy of master data for use across multiple heterogeneous systems, or to maintain survivorship rules for overlapping data from multiple systems. So, just for recap, top reasons not to master your data in an ERP are: 1. Flexibility is an issue. 2. Data matching capabilities are too basic. 3. ERP products weren't designed for active management of master data. 4. It becomes more difficult to manage data when multiple instances are involved. 5. Its inability to create a workspace between an organization's transactional and analytic systems. Now, consider the scenario where we have more than one ERP instance or different ERPs, each with their own master copy, trying to communicate with each other. Heterogeneous environment is a real occurrence as large corporations grow through mergers and acquisitions. This leads to more confusion as each follow their own taxonomy and architecture to pull data. The siloed approach to data management whereby material data is in one system, vendor data in another, asset data in a third, and so forth, really complicates the integration of processes, data and workflow. For these reasons, spaghetti code for point-to-point integration is, unfortunately, very common today.

Why is MDM necessary, be it before or after? Unlike ERP implementation, where consultants / implementation partners only own the responsibility of defining the business process, an MDM project requires MDM architects to come up with a separate methodology, giving emphasis on identification of technical objects; scenario building; repository needs; taxonomy & workflow analysis; security requirements; user management; design of integration layer; data analysis & migration schemas with respect to identified inbound / outbound systems. Architects need to make sure that they design a unique process, that suits a specific organization and the new master data process has the adoptability to absorb new business & visions to induct new business validations. Contrary to general belief, MDM is not only about consolidation or harmonization of data, it is a process which involves deep understanding of global use of each master, finding out what are the critical attributes at each level, developing master data model, strategizing various processes for each master data client and also redesigning the producer & consumer application for the specific industry. Thus, MDM is more organization specific initiative, while ERP implementation follows MDM is more organization specific initiative, while ERP implementation follows pre-defined consultant mind-set for large scale implementations and rarely turns out to be something that can tackle Master Data requirements specific to your enterprise. pre-defined global / industry specific process standards. Following are the identified specialized areas which need to be tackled by MDM: 1. Integration Capability: When it comes to integration, MDM system can get an upper hand over ERP system anytime. The integration capability of MDM system can provide variety of options to integrate with different kind of systems dealing with different file formats. A leading MDM system in the market today should provide

Why is MDM necessary, be it before or after? a good integration capability to suit custom organizational requirements. 2. Data Governance & Stewardship: It is always recommended to have a data governance team to own the right data, enterprise wide. MDM and this concept complement each other. Through an MDM governance system, you can set up the security access, correct the erroneous data, define the work-flow and act on the notifications and submit a report on the usage of the data. 3. Security control: When you talk about data governance, you must have security at different levels, such as table level, field level. Moreover, when you are dealing with such data entities which need security access globally (e.g. a user from USA should have access to some data which is owned by UK geography etc.). These needs should be taken care at enterprise level rather than at any ERP system. An effective MDM framework needs to be well capable of doing so. 4. Workflow engine: Most of the organizations still do the authorization and the publishing of data through emails. MDM tool should always gets an upper hand over any system in providing strong workflow capabilities with integrated email service solution for notifications. 5. Flexible Data Modeling Capability: MDM system has to be as adaptive as the business process. MDM tool has a flexible data model to quickly prototype and develop. 6. Complementing SOA: MDM forms a base for Service Oriented Architecture. All organizations are moving towards SOA and it makes sense to segregate your master data and have it loosely coupled. MDM needs to have the ability to present enterprise data as services - the next generation business thing! 7. Data Quality Management: This is one of the cruxes of having MDM system in place. Bad data is as good as not having the data at all. The business rules and some processes are always changing in an organization, which in turn impact data quality. MDM tool needs to be capable of handling such dynamics in real time with dedicated quality framework.

Why is MDM necessary, be it before or after? ERP suite Siloed approach to data management Very basic data matching capabilities Flexibility is an issue Niche MDM tool Configurable approval workflow Data Governance and Stewardship Advanced matching using Fuzzy Logic Complements Service Oriented Architecture An optimistic look at MDM market With the economic environment changing continuously companies are looking to differentiate themselves from others in this competitive business age by adding value to their process and reducing cost simultaneously. The MDM market has come of age and continues to evolve & mature at a rapid pace to assist again & again with this requirement. Most of the companies, whether Mid-size or Enterprise, have realized its value and Vendors are trying to make the most out of it. The catch here is one need to catch up with the growing demand, technology and skills needed to pillar an efficient and result-oriented MDM process. Let' take a candid view of how this market has evolved and where it will be in couple of years.

What's fueling the initiative? Despite having a streamlined approach in the inventory management last time, the data slowly or, in most cases, quickly becomes corrupt and data stewards are fighting to maintain it since.irrespective of the current initiative, be it process improvement or ERP implementation / up gradation, most of the companies learn from the mistakes they made in earlier attempts. Despite having a streamlined approach in the inventory management last time, the data slowly or, in most cases, quickly became corrupt and data stewards are fighting to maintain it since. Sounds familiar? Today companies are investing in MDM as a way to allow them to respond quickly to ever- changing market conditions, accelerate product introductions, improve cross-channel and cross-line-of-business sales as well as improve the quality of their business analysis. MDM has been a foundational element in pushing their competitive advantages further. People might ask what's so positive in it. Well, companies are learning that ERP is not the place to master their data and in the process are getting bolder when it comes to managing data as an enterprise asset. They have realized how the poor quality of data has limited their growth in the past and how it is holding them to limit their competitive advantage. This is fueling the MDM market today with global leaders having has much as 77% better value added data that is driving the new enterprise management. Despite having a streamlined approach in the inventory management last time, the data slowly or, in most cases, quickly becomes corrupt and data stewards are fighting to maintain it since.

So, what's the catch? Even though the demand for MDM is ever increasing and the future looks bright, the negative side is that skills needed, to take charge of such an activity, are struggling to keep up. Companies need to be patient when looking to recruit MDM leaders, also should be open to hire new talent from the market and offer attractive incentives to retain it, as retaining internal organizational and relevant domain expertise is essential to the long term success of any data management initiative. Many organizations look to build their MDM team internally but fail miserably as one need to be well versed with the concepts of business requirements like procurement, finance etc., along with data governance, data quality management and data harmonization, to decode the complex master data code. In addition to that we need to know what kind of technology platform one wishes to work on. What tools will our system support? Etc. It's hard to develop an internal resource allocation strategy when you haven't yet determined your technology platform. Next option is ask your technology partners to find the specific talent and resources for a customized MDM initiative. If they have an The trick is to assess the very specific requirements of various kinds of master data and the business value required in such a data, then find technologies specializing in mastering that particular types of data and business challenge. MDM practice and focus, then it makes life easy, else its best to look out for best-of-breed vendors. Although the vendor landscape for MDM software has rapidly matured over the last five years, the talent is still primarily platform-specific. A wide variety of strengths and weaknesses still permeate vendor tools, so finding a resource with specific experience in your technology footprint, while challenging, still makes a big difference.

The road ahead If you are considering an MDM approach to data management in your organization, this is a great time to do so. Tools are stabilizing and reaching the point on the maturity curve where their maturity becomes more evolutionary and less revolutionary. Suites of MDM-related tools offered by the megavendors are filling out. Today challenges are becoming less about the technology and more about the knowledge, domain experts and skills brought to bear in defining, designing, developing, and deploying the solution. As with any evolving market, this is a general trend. Mega vendors offerings will improve, niche products will survive the bubble burst and the less competitive contenders fall. Fewer choices becomes more robust, more tools becomes part of the suite, and this is beneficial for both pricing as well as skill development. MDM and ERP complementing, and not competing with, each other What we need to remember is that the migration of any number of business applications to some fewer business applications won't solve the purpose. We need to understand that MDM and ERP need to coexist as one solution and they cannot & should not replace each other Adoptability of any application in a new routine amplifies when it is a part of the design of the large system migration. A new process is adopted to ensure that post migration the business oriented routines would be established such that master data remains cleansed on an ongoing basis and is actually contributing towards generating greater ROI from organizational initiatives like ERP, Inventory Management, Spend Management, Customer Retention, etc.. We can conclude that if you do ERP first and leave the Master Data for the last part, then you will need to rework a major effort of the

The road ahead implementation process and thus TCOs of the project will rise significantly. Sometimes it so happens that an organization has exhausted all its resources in the ERP implementations and IT doesn't take up MDM as it expects large returns to come from the new and better ERP system without realizing that even the best system need the best data to deliver best results. We need to understand that MDM and ERP need to coexist as one solution and they cannot & should not replace each other. From an investment perspective, it is important to leverage existing technologies such as data quality, extract-transfer-load (ETL) and data integration tools, business process management and workflow along with appropriate data enrichment solutions to harmonize the legacy data, and then put a bolt-on-erp solution for ongoing master data management and governance requirements. Data migration may be the last activity on the dashboard of an ERP project, only because real time data can migrate when the system is about to be working live, but it is a subject to be dealt with much earlier, during the start of the project. It is advised that an organization should plan an explicit MDM work-stream offset by at least a couple of calendar months, Including MDM of the key masters as a part of your business blueprint will ensure that your enterprise derives the maximum real time business benefits of having a new ERP system. ahead of the ERP program. Including MDM of the key masters as a part of your business blueprint will ensure that your enterprise derives the maximum real time business benefits of having a new ERP system. This activity will not only help the ERP users comprehensively but also make the implementation, consolidation or up gradation process streamlined and easier. With these things in mind, you can confidently march forward in providing the organization with the foundational components necessary to build competitive advantage and to be market responsive.

Verdantis DATA DRIVEN PERFORMANCE About Verdantis Verdantis is the first to offer Master Data Management services and solutions that bring real ROI and Business Value by focusing on the business use and application of organizational Master data. Verdantis uniquely offers end-to-end automated ERP MDM solutions driven by our suite of Artificial Intelligence (AI) based solutions and business roles and rules, easily configured to fit enterprise requirements for classification, enrichment, screens, fields, security, attachments, workflow approvals, languages and more. In recent years, many global organizations have taken initiatives to harmonize and manage their master data to ensure the success of their ERP consolidation/upgrade projects. After experiencing sub-optimal results with conventional approaches, an increasing number of Global 2000 companies are opting for Verdantis' cutting-edge automated solutions to ensure success of their MDM initiatives. San Jose Chicago Princeton Ohio Atlanta Paris London Frankfurt Mumbai Leading global companies have chosen Verdantis solutions for the following reasons: u u u u End-to-end automated processes to harmonize & enrich historical master data Ability to ensure ongoing data integrity In-depth domain expertise Ability to handle huge volumes of data in multiple languages NORTH AMERICA 201, Carnegie Center Suite 117 Princeton, NJ 08540 Tel : +1 609 799 5664 Fax : +1 609 799 6047 EUROPE EPJ Business Center, Suite # 418 Mainzer Landstrasse, 27-31 60329 Frankfurt am Main, Germany Tel : +49 (0) 69 27 4015 251 Fax : +49 (0) 69 27 4015 111 ASIA PACIFIC Plot No. GJ 07, Seepz++, Seepz SEZ, Andheri (East), Mumbai, India 400 072. Tel : + 91 22 66407676 Fax : + 91 22 26850580 To learn more about Verdantis, e-mail webmaster@verdantis.com or visit