Boosting the Bottom Line with Master Data Management

If you haven't heard of master data management (MDM) yet, you will. If you didn't realize that you use master data every day, you do. If you didn't know that MDM can help boost your company's bottom line, it can.

MDM is the process that organizes, unifies, and eliminates duplication of customer, product, and logistical records, as well as other key pieces of information that businesses have to track every day. And it does this across different departments, platforms, and systems. Simply put, master data is the core customer and operational data that gets used in virtually every significant process and transaction that a business conducts.

So what does this mean for an organization in practical terms? MDM enables companies to boost their bottom line by

* reducing the cost of mailings, marketing campaigns, and lead acquisitions
* allowing for faster sales lead processing
* improving the quality of service in customer service departments and call centers
* strengthening sales and marketing functions

Download this informative podcast featuring Lyndsay Wise, senior analyst at Technology Evaluation Centers (TEC), and Anurag Wadehra, vice president of marketing and product management at Siperian, a leading MDM and customer integration solution provider, today. You'll find out more about MDM, including how to get started, what strategies to bring to the table, and all the benefits you can expect.

Click here to download Boosting the Bottom Line with Master Data Management now!

This podcast examines the following questions:

* What is the importance of master data management (MDM) to your organization?
* How can you cut costs through the use of MDM?
* How can MDM help you improve your company's sales and marketing efforts?
* What should you be aware of from a technical point of view before implementing an MDM solution?

Product Lifecycle Management Agility Founded on Innovation

Agile Software and its partners have made it perfectly clear that innovation is the primary theme driving product lifecycle management (PLM). The Agility 2006 Conference audience, drawn from the automotive, electronics and high tech, industrial products, life sciences, and semiconductor industries, got their fill of conceptual and visionary thoughts on innovation, with such keynote speakers as TCG Advisors' Geoffrey Moore, author of Crossing the Chasm; and IDEO's Tom Kelley, author of The Art of Innovation and The Ten Faces of Innovation.

For today's progressive enterprises, who are doing business in a highly competitive environment, innovation is a priority all on its own, and the sheer pace of innovation is as important as the art of innovation. Enterprises need to examine opportunities surrounding product innovation, as well as business process or business model innovation. Agile Software's tag line, "how products happen," is exemplified by the current product development forces of innovation, globalization, and compliance. These forces are coupled with outsourcing and collaboration imperatives that necessitate a high reliance on supply chain flexibility and agility. Enterprise attempts at simultaneous global product launches, aimed at improving time to market, have shown the need for a mastery of the supply chain for successful new product development and introduction (NPDI) execution. How well Agile Software provides tools and processes to meet the challenges of the PLM market and the expanding audience of companies looking for PLM solutions, is largely based on its ability to find synergy between its technology solutions and the market forces.

Opportune Timing

With Dassault Systmes' announcement of its acquisition of MatrixOne, Agile Software now has the advantage of being able to emphasize its unique position as the sole "pure play" PLM vendor (see Acquisition Changes Product Lifecycle Management). Enterprises are now realizing that the velocity and direction of product innovation require a PLM structure. Agile Software has honed its message to a sole focus on PLM, with a commitment to customer's PLM requirements being the primary motivation behind Agile's own PLM innovation. A recent Gartner survey said that global spending on PLM applications rose 13.8 percent (product data management [PDM] and PLM only) from 2001 to 2005. The maturity of innovation models such as product innovation, process innovation, marketing innovation, and integration innovation, will drive more enterprises towards a structured PLM approach

Data Governance

When it comes to compliance, data governance can help your company avoid hefty fines and even jail terms for its senior executives. In terms of customer service, data governance can reduce customer churn while giving your company a decisive competitive edge. And as for supply chain management, data governance can help your company understand what products are selling, what products are in stock, and what products are on the way from suppliers.

And that's just the tip of the iceberg. To find out more about data governance and how it can help your organization excel, listen to Data Governance: Controlling Your Organization's Mission-critical Information. In this informative TEC podcast, analyst Lyndsay Wise chats with Daniel Teachey, DataFlux director of corporate communications, about the benefits, business drivers, and implementation challenges of data governance.

PIM and PLM Origins and Evolution

PIM and PLM have different origins and were designed for different purposes. PIM originated from the need to optimize distribution channels by supplying them with the most current information on products and promotions. PLM, on the other hand, grew from the need to make better products through better management of engineering and design information around the manufacturing process.

Like most software solutions, PIM has evolved along a path on which the most pressing needs are met first. For CPG companies, the highest-priority need is data synchronization. When faced with mandates from their largest retail partners to synchronize product information via EAN/UCCnet, many CPG companies quickly implemented solutions to upload information to the registry.

However, they soon discovered that they did not have all the requested information, or a process for keeping the registry information up-to-date. A long-term PIM strategy requires integration with other systems, workflow, an information repository, and the ability to synchronize and syndicate information to a variety of destinations in multiple formats.

PLM's origin was the need to manage bills of material (BOM) or recipes, manage complex CAD drawings, and consolidate product design information in a centralized repository. To extend that capability, PLM adopted collaborative processes to share design information across the enterprise and with supply chain partners. PLM also added tools to help manage the new product introduction process, including project management to better track project progress through stages and portfolio management, to help target the most profitable products mix available. For more information on the history of PLM and the different aspects of a PLM system, see PLM Coming of Age: ERP Vendors Take Notice and The Many Faces of PLM.

There are a number of best-of-breed PIM players on the market, including FullTilt Solutions, GXS, IBM, SAP, Sterling Commerce, and Velosel. Each has a number of customers using their solutions

The Role of PIM and PLM in the Product Information Supply Chain

By now, most of us understand the concept of the supply chain. This is the conceptual representation of product movement from raw material through manufacturing and distribution to the consumer. It's a problem that we've been working on for years and it is critical that we get it right.

Just as important, but not as evolved, is the product information supply chain where information moves from raw product data through value-adding edits and context setting, to retailers where it can be used to optimize the selling process. The current state of this information supply chain is abysmal. As one executive from a large consumer packaged goods (CPG) manufacturer recently said, "requests for product information scare me because many times we don't know where it exists in our organization, and if we can find it, it is most likely out-of-date".

The solution to the problem is product information management (PIM). A PIM solution would include the ability to organize a company's product information, regardless of location, into a consolidated system of records, and be able to synchronize or distribute that information to any business partners that require it.

Lately, diverse groups have been discussing PIM from the perspective of data synchronization and syndication, product lifecycle management (PLM), and enterprise publishing. Each of these product categories includes the management of product information, but each uses product information for a different operational role.

The term PIM has appeared more frequently lately in the discussion of data synchronization and syndication because of a number of market initiatives that act as catalysts for change. For example, many large retailers, including Wal-Mart, Office Depot, The Home Depot, Albertsons, and Safeway, asked their suppliers to synchronize product data via EAN/UCCnet registry and data synchronization services.

Other catalysts include the Sunrise 2005 initiative that seeks to standardize on a format for global product identification via a new 14-digit code, and the radio frequency identification (RFID) initiatives in place to bring about the rapid adoption of new radio frequency tags on all products, so that they may be more easily tracked through manufacturing and retail environments.

Because of these same initiatives, PLM vendors are also being increasingly asked by their customers to include more commercially-oriented product information in their PLM systems. A few high profile case studies (Procter & Gamble and Heinz are examples) have shown how the data in a PLM system (MatrixOne and Prodika, respectively) can serve as the source of valid, consistent and up-to-date product information for synchronization and syndication to supply chain partners. However, most PLM systems lack a PIM system's ability for secure, trusted synchronization of information to data pools like UCCnet.

Lastly, enterprise publishing's goal is to reduce costs to create and speed deployment of all the product-related information, including user manuals, sales collateral, and web sites, that make up the complete product offering. Enterprise publishing is a fascinating topic, but let's save it as a topic for future articles.

Customer Data Product Strengths

Siperian's strengths are in its ability to match its offerings to an organization's business needs. In addition to offering three distinct hub styles, Siperian centers its offerings on the integration of an organization's CDI initiative with its overall data management strategy. This means that although Siperian focuses on providing solutions for a specific set of data, the vendor places importance on an organization's overall business processes and how its CDI requirements will grow.

Siperian's service-oriented architecture (SOA)-based platform solutions enable organizations to implement the vendor's product offerings more easily than those of vendors that have not adopted SOA standards. Siperian's SOA-framework solutions provide organizations with the ability to integrate multiple applications onto a common platform. Siperian's hubs use additional adapters to leverage SOA and to integrate out of the box with information systems and platforms such as SAP, Oracle, and Siebel. Because many organizations build their information structures based on these three platforms, the natural integration of Siperian's offerings with these products ensures seamless integration.

Siperian delivers out-of-the-box, industry-specific models within the following industries: health and life sciences, financial services, high-tech, manufacturing, and communications and media. Companies in these industries can take advantage of these models, as these models meet many of their requirements out of the box, eliminating the need for excess customization. Siperian's expertise within these industries translates into additional value for the customer, including enhanced features and functionality, additional services, and superior support.

Flexible Customer Data Integration Solution Adapts to Your Business Needs

Customer data integration (CDI) has become one of the buzzwords within the master data management (MDM) industry. Although the concept of creating a single organizational view of the customer is noble and desirable, its value should also be justified by organizations. To implement a customer data hub that only creates a centralized view of an organization's customer-related data does not affect a company's bottom line, unless business units have bought into the initiative and tie it to the organization's strategy. Customer turnover, collections, call centers, and marketing initiatives can be monitored, consolidated, and improved through CDI. However, to ensure successful CDI implementations, solutions should be driven and managed by the business units to ensure buy-in, and to increase the value associated with customer-related data.

In addition to the collaboration and buy-in needed to ensure a successful project, the type of CDI initiative and the architectural style chosen to implement it play important roles in the use and view of customer data. CDI hubs are used differently depending on the way they deliver information to users. It becomes important to choose a style compatible with the organization's current business needs, with the knowledge that these needs will change over time, and that as a result, the CDI architecture may change as well.

An Overview of Siperian's Product Offerings

Siperian is a leading San Mateo, California (US)-based CDI vendor for the health and life sciences industry. The vendor's solutions allow customers to create, consolidate, and present a single view of customer-related data based on their organizations' needs and maturity within their CDI or MDM environments. Siperian's product offerings reflect the business needs of organizations, and provide businesses with the ability to reduce operational costs and improve compliance when implemented in alignment with the organizations' business processes. This occurs through the management of customer-related data by creating a singular view of the customer across the organization, and by providing the appropriate views of that data to business units across the organization, based on their needs.

CDI hubs enable organizations to develop centralized customer data management structures, and to contribute to the ongoing data quality activities required to ensure successful CDI initiatives. Different hub styles, coupled with vendor product offerings, provide organizations with the ability to build and structure their customer information to enhance the customer experience, and to supply employees with the right information when they need it.

Siperian offers three products with differing architectural styles, namely Master Identity, Master Data Management, and Operational Views, to meet the varied requirements of an organization's customers based on the maturity of its CDI environment. These styles provide organizations with different benefits based on the way these organizations choose to apply CDI. Organizations may want a total approach to CDI immediately; that is, to manage their organization-wide CDI and MDM initiatives from the start. However, the implementation of a CDI initiative in stages provides organizations with stronger frameworks to develop and maintain their CDI environments and data quality initiatives over time.

Siperian's Master Identity offers organizations a master reference to link customer-related data across the organization. The Customer-Centric Master Data Management style creates a cross-reference to provide one version of customer data within the organization. This includes the cleansing of data to provide one version of the customer addresses, as well as other information that requires reconciliation across various systems. Customer-Centric Operational Views creates a virtual view of consolidated customer records based on customer transactions.

All three styles provide reliable master data to operational systems such as enterprise resource planning (ERP) and customer relationship management (CRM). Siperian also supports a "consolidation style," which relies on the centralized repository of reliable master data. This centralized repository supports downstream analytical environments, including reporting, analytics, and business intelligence (BI) systems.

Master Identity, through its Master Reference Manager (MRM), identifies entities including customer, product, supplier, etc. Master Identity uses a "registry-style" approach to match and link records from different systems across the organization to create a "golden record." This record creates references based on attributes such as customer number, a combination of phone number and name, and other unique identifiers to link the various records across the organization, creating a central reference area to pool data.

The registry stores data that can be cross-referenced back to the source systems. This hub style may be accessed in real time, and provides read-only access to data as needed. This means that operational data stores are not affected, and that data can be accessed instantaneously across multiple business units, helping users within customer service and marketing departments access the required information. This type of architecture does not allow organizations to add or change data, as the data acts only as a reference point. Therefore, it is not advantageous for point-of-contact users, who are required to update operational systems.

Plant Intelligence as Glue for Dispersed Data

One approach to addressing these challenges is to use plant or manufacturing intelligence systems.

Given the problematized communication between manufacturing execution systems (MES), plant automation, and enterprise applications, a new breed of applications are coming from the likes of former Lighthammer (now part of SAP), Kinaxis (formerly Webplan), Activplant, and Informance. They offer middleware analytical applications called manufacturing intelligence or plant intelligence that target other applications used to generate corporate-wide visibility of key performance indicators (KPI). These plant portal applications consolidate data taken from a wide range of computing sources—from plant floors, enterprise systems, databases, and elsewhere—and organize these data into meaningful, roles-based information, aggregating the data from disparate sources for analysis and reporting. Connections can through extensible markup language (XML), or open database connectivity (ODBC) standards, with communications managed by a protocol layer in the portal's Web server architecture.

Near real time visibility and transactional exchanges have to be created between enterprise applications and the plant floor with appropriate drill-downs to contextualize and understand the impact of specific manufacturing events. These products are applied to critical plant processes, and monitor production and provide the input required for calculating key metrics, such as overall equipment effectiveness (OEE). In order to increase OEE, data generated by equipment in a production line is acquired and aggregated (preferably in automatically, see The Why of Data Collection).

Information is contextualized using business rules and user roles to create and maintain consistent functional and operational relationships between data elements from these disparate sources. For example, these products can demonstrate the relationship between allowed process variables and ranges of time series-based quality and yield data. It can also analyze information by using business rules to transform raw process data into meaningful KPIs. Data can also be filtered for any noise/outliers; visualized with a context-based navigation and drill-down capabilities; and presented or propagated to determine the factors and root cause disturbances that slow production or impact quality. Ultimately plant-level systems allow decisions to be made that will speed up throughput and increase first-run production.

How It Works

Configuring data sources for integration can be done through templates, which is analogous to selecting a printer for an office application. The real trick, however, is in having sound plant-level models, which are frameworks that portray accurate plant-level context and data management, within the application sets. In manufacturing, even small changes to a master plan can create a so-called "reality gap" and these are historically addressed by last-minute panicking and scrambling, all the while, the business protagonists are not always (if ever) conscious of the impact or even the validity of their "educated guess" decisions.

Thus, these new software applications make it possible to model the cascading consequences of anything users do in response to an unplanned event (like a customer doubling an order or a machine breaking down), which in turn, makes it possible to understand how the other, intertwined parts of the user organization and supply chain will be impacted by a change (see Bridging the Reality Gap Between Planning and Execution).

When users have information about unplanned events and how their responses will impact the company, they should have manufacturing intelligence that can guide them through the forking paths of exception-based, decision-making. The value of the plant-level information indeed changes when enterprises use it to support higher-level, strategic, and tactical business processes. For example, data generated for a department supervisor or for management purposes has one value, and the same data used for Sarbanes Oxley Act (SOX) compliance has another (see Attributes of Sarbanes-Oxley Tool Sets). Moreover, the value of quality assurance (QA) information increases substantially when used to support enterprise-wide warranty issues.

Where is Oracle in the Product Lifecycle Management Software Market?

Over the past ten years or so, most enterprise resource planning (ERP) vendors have invested heavily in their product solution suites in order to extend their product portfolio beyond traditional integrated ERP components like financial accounting, human resources (HR), manufacturing resource planning, order management, inventory management, etc. Common application extension segments, generally built on the same technology platform as the ERP modules, include customer relationship management (CRM), supplier relationship management (SRM), supply chain management (SCM), and product lifecycle management (PLM).

At the ERP tier one level, which clearly includes SAP and Oracle, major efforts have been made to ward off the attempts of best-of-breed vendors to exploit revenue opportunities resulting from the gaps left by ERP. However, considerably different approaches have been taken by the two companies. SAP has taken the organic growth through internal development approach to application extensions, which can be time consuming and often results in a late-to-market outcry by clients in need. On the other hand, it often results in a product with the same look-touch-feel and process controls as the traditional ERP components and has better integration touch points. Oracle has taken a somewhat more risky and expensive "acquisition" approach for certain functional areas, as demonstrated by the acquisitions of Siebel for CRM, G-Log for multimodal transportation planning and execution, and Retek for unique retail applications and expertise. PLM, however, seems to be a more difficult puzzle for Oracle to solve. Internal development and commitment to the PLM solution set continues in earnest, while any speculation that their game plan may include a PLM acquisition alternative is just that, speculation.

Oracle PLM 11i.10

Oracle appears to have most of the key elements of a PLM suite. They provide the means for centralized product information, collaboration within and across the extended enterprise for product development, product configuration, and sourcing, as well as visibility and control of product portfolio management (PPM). They also offer a best-in-class Product Information Management (PIM) Data Hub product, and tout its PLM applications as providing the most advanced set of tools based on a single global product set repository. The current Oracle PLM Suite includes the following modules.

* Product Lifecycle Management is the core of the applications suite, with centralized product and component information within a single global catalog for product data management (PDM; items, structures, revisions, issues, change requests, roles, and project issues), as well as intellectual capital. Product change management and issue resolution is also addressed within this core module.

* Oracle CADView-3D provides visualization and mark-up capabilities for two dimensional (2D) and three dimensional (3D) modeling. Documents can have various formats, such as word-processing files, image files, computer-aided design (CAD) 2D or 3D drawing files, and other unstructured data formats.

* Project Management provides project planning, tracking, budgeting, and forecasting capabilities, as well as Project Collaboration software for reporting the project status to all stakeholders. Oracle Projects is integrated with the other relevant Oracle modules to manage projects like financials, HR, CRM, and procurement. It is geared toward new product development introduction (NPDI), with lifecycle phase gate product management. It also has built-in application programming interfaces (API) to Microsoft Project, Primavera, and Artemis, supporting a two-way interchange with desktop scheduling systems.

* Product Portfolio Management enables what-if analysis on product portfolio simulations, priority rankings based on investment, alternative cost and benefit analyses, and idea management.

* Oracle Sourcing integrates negotiation of supplier contracts with effective on-line management of the negotiation process as part of the PLM activities.

* Oracle Configurator manages customer needs with configuration rules for complex products and services as part of the sales cycle.

* Daily Business Intelligence manages the product data repository for analytics.

* Product Data Synchronization provides for Global Data Synchronization Network (GDSN) or Uniform Code Council (UCC)net services.

It’s the Time to Master Your Master Data

Nowadays, many companies are able to automate transactional activities thanks to solutions such as enterprise resource planning (ERP), customer relationship management (CRM), and supply chain management (SCM). However, due to the barriers among various software systems that companies have implemented along the way, and multiple operation locations that require complicated data storage mechanisms, inconsistent master data becomes a critical issue that hampers effective and efficient business operations.

For customer-facing operations, when a customer receives two phone calls from a company–a delivery notification made by a shipment clerk working with a SCM system, and a service follow-up handled by a customer care representative using a CRM system, the customer wants to be addressed as the same person. More importantly, as a company, you don’t want the two departments to contact the same customer as if they were talking with two individuals. What you want is the single version of the truth with respect to your customers.

Besides managing customer master data, product master data is another major area of MDM. The accuracy of product master data needs to be maintained consistently across various departments and branches. This way, when different people refer to a product, they talk about the same thing, with the same information. Without the consistency of product master data, a salesperson may sell a product with a feature that is no longer available due to a design change. This situation is not only embarrassing but also revenue-losing.

The management of product master data is also called product information management (PIM). If you are looking for a PIM solution, you may find Technology Evaluation Centers’ PIM Request for Proposal (RFP) Template helpful (click here to download a free sample).

Although urgent MDM needs mostly come from customer data and product data, MDM initiatives in material master data, supplier master data, and even human resources (HR) master data are also seen.

Boosting the Bottom Line with Master Data Management

If you haven't heard of master data management (MDM) yet, you will. If you didn't realize that you use master data every day, you do. If you didn't know that MDM can help boost your company's bottom line, it can.

MDM is the process that organizes, unifies, and eliminates duplication of customer, product, and logistical records, as well as other key pieces of information that businesses have to track every day. And it does this across different departments, platforms, and systems. Simply put, master data is the core customer and operational data that gets used in virtually every significant process and transaction that a business conducts.

So what does this mean for an organization in practical terms? MDM enables companies to boost their bottom line by

* reducing the cost of mailings, marketing campaigns, and lead acquisitions
* allowing for faster sales lead processing
* improving the quality of service in customer service departments and call centers
* strengthening sales and marketing functions

Download this informative podcast featuring Lyndsay Wise, senior analyst at Technology Evaluation Centers (TEC), and Anurag Wadehra, vice president of marketing and product management at Siperian, a leading MDM and customer integration solution provider, today. You'll find out more about MDM, including how to get started, what strategies to bring to the table, and all the benefits you can expect.