PCM System Attributes

SAP's recent acquisition of the former catalog management vendor A2i and IBM's acquisition of the former product information management (PIM) vendor Trigo might indicate some enterprise-wide product content management (PCM) approaches of the mainstream enterprise platform and enterprise applications or enterprise resource planning (ERP) vendors, as their responses to the need for an effective master data management (MDM) system to the widespread challenges of sprinkled data integration from multiple systems, physical locations, and diverse trading partners. Thus, PCM and PIM would be the core parts of MDM solutions that will manage any kind of master data and be seamlessly integrated into a customer's existing enterprise architecture, ideally eliminating all data duplication and making centralized customer, supplier, or product information available to other applications across the organization.

SAP, IBM, and like mainstream enterprise vendors need to solve the problems inherent to data residing in disparate systems, as enterprises are becoming painfully aware of the need to clean up their structured data and unstructured content acts to capitalize on more important efforts like regulatory compliance, globalization, demand aggregation, and supply chain streamlining, to name some. To that end, these enterprise vendors have to provide the ability to also integrate emerging radio frequency identification (RFID) data into their software, as well as full support for web services-based provisioning and consumption of data and processes.

Yet, the all-encompassing content management solution is still in the ever-evolving design stage, as vendors try to piece together comprehensive systems. Therefore, there seems to be a proliferation (and subsequent confusion about) of the pertinent terms and acronyms like enterprise content management (ECM), product content management (PCM), catalog management, product information management (PIM), records management (RM), product data management (PDM), enterprise data repositories (EDR), document management (DM), knowledge management (KM), web content management (WCM), digital asset management (DAM), enterprise information management (EIM), digital rights management (DRM), document imaging, workflow management (WM) or business process management (BPM), and many more.

Generally speaking, PCM (sometimes also called PIM) refers to a system for managing all types of information about finished products, and it is a further evolutionary step of catalog content management backed up with a workflow management. This is however different from ECM, which focuses more on document management and other unstructured editorial and web content, whereas PCM is more granular around individual data elements and focuses on highly structured product content. ECM encompasses many of the above-cited technologies used to capture, manage, store, preserve, and deliver content and documents related to organizational processes. In other words, it allows the management of an organization's unstructured information (e.g., e-mails, photos, spreadsheets, documents, etc.), wherever that information exists—stored in repositories, shuttled across networks, and managed over the course of its existence or life cycle.

This is part one of a three-part note.

Part two will present background information and lessons learned.

Part Three will address challenges. 

Coming back to managing structured, alphanumeric information, a PIM or PCM solution would include the ability to organize a company's product information, regardless of location, into a consolidated system of record, and be able to synchronize or distribute that information to any business partners that require it. Yet, true PCM should mean more than just the centralized repository to eliminate data duplication with a limited nugget of functionality; rather, this repository must be capable of storing all product information, while the system must be more than a point solution or an island, since it must also offer high-performance access to that information, and it must include tightly integrated functionality that can be used to drive all crucial enterprise initiatives.

First and foremost, the PCM should revolve around a single centralized repository of product information. It should be the "system of record" for all non-transactional product information and organizational intelligence about products, and eliminate data duplication and system redundancy across the enterprise. In effect, it should be the "ERP for product information" containing not only "rich product content", but also other types of related information, such as supplier information, as well as one or more supplier-specific sub-records of sourcing information for each product that allows the PCM to simultaneously drive both sell-side and buy-side initiatives. In other words, the rich product content managed by the PCM must be much more than simply transactional data about each product from the ERP or product master file (e.g., a part number, a description, and a price).

This brings us to the notion of enterprise publishing (where some PCM systems will overlap with ECM), which aims at reducing 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. In fact, rich product content must comprise all of the non-transactional product information within an organization, such as detailed parametric data on product specifications; merchandising text, high resolution images, drawings, diagrams, and portable data formats (PDF) for various marketing and publishing requirements; a classification scheme for organizing the products into a searchable taxonomy of categories and subcategories with category-specific attributes; product relationships to represent selling relationships (such as up-sells, cross-sells, and accessories) and structural relationships (such as assemblies, kits, and bundles); parts usage information; and finally, various product-specific services for leveraging the rich product content such as hotspots information for illustrated parts catalogs without the need for a separate system.

The term PIM has appeared more frequently lately in the discussion of global data synchronization (GDS) 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, Target, Albertsons, and Safeway have mandated their suppliers to synchronize product data via European article number (EAN)/UCCnet registry and data synchronization services. Other catalysts would include the Sunrise 2005 initiative that seeks to standardize on a format for global product identification via a new 14-digit code, and the 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.

A full-fledged PCM system should additionally have no predetermined notion of the repository structure itself, but rather offer a fully flexible schema that can be tailored to meet the specific requirements of each enterprise and each vertical industry, and that can change over time. The PCM must be more than just a simple database application or end-user application, and more than just a standalone point solution that addresses a single functional requirement (such as UCCnet synchronization, paper print or web-based publishing, or illustrated parts catalogs). Rather, it must be a completely open system with both graphical user interface (GUI) tools for end users and multi-platform application programming interfaces (API) for programmatic access (e.g., Java 2 Enterprise Edition [J2EE], Microsoft .NET, eXtensible Markup Language [XML], web services, and simple object access protocol [SOAP]), supporting both content authoring and runtime searching, and providing a horizontal platform for building best-of-breed vertical solutions.

The like PCM system must also support all the leading middleware application stacks so that it can leverage and integrate with web application servers (WAS), enterprise application integration (EAI) and portal servers. Also, rather than a fixed web-based user interface, it should provide a flexible presentation layer that can be completely customized and tailored to particular organizational requirements and various vertical markets needs.

Finally, the PCM should be able to unify and harmonize product information stored within repositories across the enterprise, creating "a single copy of the truth" regardless of where the data resides. That is to say, the PCM must act as a centralized "hub" that plugs PCM functionality and high-performance access to highly-structured product information into all enterprise initiatives, not only at the user level but also at the enterprise integration level, for plug-and-play coordination with other extended-ERP solutions, such as customer relationship management (CRM), product lifecycle management (PLM), supplier relationship management (SRM) and supply chain management (SCM), where the vendors with broad offering like SAP or Oracle should be glad to oblige their users. 

Based on the above discussion, a proper PCM system, such as the one acquired by SAP, should have the following attributes:

  * Powerful product content aggregation and cleansing, management and editing of product information, since the proper PCM system should do more than store data that used to reside in another system. Instead, it must include powerful and extensive capabilities for loading, restructuring, cleansing, normalizing, and transforming source data from a variety of electronic sources, including text, Microsoft Excel, Microsoft Access, structured query language (SQL), and XML for both flat files and relational data.

  * Classification into a taxonomy with category-specific attributes, since not only must the proper PCM systems have a completely flexible schema, it must also support multiple classification schemes, user-defined taxonomy hierarchies of arbitrary depth with category-specific attributes, multiple simultaneous taxonomies, and drag-and-drop taxonomy editing capabilities that allow the taxonomy of the fully populated repository to be completely restructured and refined over time.

  * Intelligent image management, since many systems can easily store an image as a binary large object (BLOB). By contrast, the proper PCM system must support intelligent image management with an understanding of all of the leading image formats, the ability to automatically transform images for different publishing purposes, and optimized high-performance image access and efficient image caching.

  * Integrated high-performance product search engine, since search mechanisms offered by traditional systems are not precise enough for searching product information. The full-fledged PCM system must hence include a fully integrated multidimensional search engine that is optimized for product search, with support not only for drill-down, parametric, and keyword search, but also units or measurement search, partial or contains search, and other types of search. To that end, there should be the ability to let customers search for goods without knowing product codes, that is, in a "No part number, no problem" manner.

  * Performance acceleration, with scalability up to millions of products, since traditional enterprise applications, such as ERP or CRM, are not optimized for heavy search and access loads. Similarly, a traditional relational database management system (DBMS) is slow on typical searches against large repositories, so relying on the "naked" DBMS is also a problem. Not to mention that databases have not been architected well to manage large, binary objects, since rows, columns, and SQL access are not suited for managing object like frames of a video or pages of a document. Therefore, a proper PCM system must have a self-optimizing performance acceleration layer that is able to quickly serve up product information to users and other enterprise applications.

Most catalog solutions are simple database applications that layer a thin veneer of functionality over SQL and they rely on SQL for all access to the data, wherebyy SQL works well with retrieving a single record from among thousands or even millions. Yet, to retrieve, for example, several thousand records from among a few million, and to limit across all of the different dimensions of the search for users to only see valid selections and valid values, that requires a multi-table join. 

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?

 


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Podcast Transcript

Hi, and welcome to TEC Radio. My name is Lyndsay Wise, and I am the senior research analyst for business intelligence [BI] and performance management here at Technology Evaluation Centers. Today I have [with me] Anurag Wadehra, the vice president of marketing and product management at Siperian. Siperian is a leading master data management [MDM] and customer integration solution provider. I will be discussing with Anurag what the importance of master data management is, and how organizations can use MDM solutions to improve their sales and marketing efforts, and how MDM can affect the bottom line and increase profitability within an organization.

LW: What is MDM?

AW: That's a very interesting question, Lyndsay. Today, there's a lot of coverage of master data management, and essentially what it is, is a management of a certain kind of data. It is a data that defines the core business descriptions of customers, products, locations, and other key entities that [businesses] have to track. That's a very simple way of saying that master data management is managing your key business entities.

LW: How do organizations use master data? Can you give us an example?

AW: What's interesting about master data and the management of it, and the use of it in companies is that nobody uses it exclusively. Nobody wakes up and says, "I'm going to use master data today." It gets consumed in every business process and every business transaction. Let me give you an example. If you go to the bank and withdraw 10 dollars from an [automatic teller machine] ATM, in that transaction is implied who you are: what's your name,... your account number,... your address,... your location. Those aspects of the transaction are attributes of master data, and they get used, derived, or accessed during that transaction. And that's true for other business processes that involve customers, products, the relationship among customers and products, or other classes of what is called master data. So, in a nutshell, master data gets used in virtually every significant business process and transaction.

LW: How can MDM actually help a company improve its sales and marketing efforts?

AW: That's a very tricky question because companies have been trying to improve their business performance, including their sales and marketing processes, for a very long time. And for sales and marketing, companies have been trying to reduce the cost of mailings, cost of marketing, to different segments of their customers.

In sales, the cost of acquiring the leads and processing the leads … is an area of focus for many companies to improve their effectiveness. Master data is critical because very often the reason why costs are very high is because companies do not have good control over their master data. And therefore by controlling the quality and reliability, and very often, very simply, the definition of master data around customer product accounts, companies can significantly improve the business performance and business processes associated around this data.

Perhaps an example will help. If you consider a mailing that is sent to 10 million customers by a large bank announcing either a credit card offer or some other product offer, a significant amount of money can be spent on incorrect addresses, incorrect duplicate names, similar names, multiple mailings sent to the same household, very often not recognizing that spouses might actually belong to the same institutions as customers.

All of these issues result directly in higher cost and lower profitability. The root cause of many of the problems I've just described was poor quality of master data, lack of understanding of the relationships among master data.... By improving the quality and control of master data, you can improve directly the bottom line of your sales and marketing processes by reducing the cost of mailings, by improving the quality of services at call centers, and by improving the time it takes to process leads for sales. 

LW: What kind of strategies should organizations use to help them implement MDM?

AW: So, what we've discovered is that a lot of companies understand the importance of high quality master data and the management of it, yet struggle with getting started because master data is so pervasive and is part of every major transaction and business process. Therefore, our recommendation has been that you start by looking at one specific business problem, such as cost of marketing, or high cost of sales, or improving customer service levels, and then drill down within that problem to the root cause of high costs, and very often those are driven by poor quality of master data.

By limiting the business problem, you are trying to attack and [narrow] in on the master data issues in that area. You can actually implement a solution rather quickly, very often within 60 days or less. And therefore you can start getting the benefit of having fixed the master data issue in one particular business area, such as marketing or sales, very quickly.

That's what we advocate. Don't try to boil the ocean. Don't try to attack master data across the entire enterprise in a single project. Identify a business problem that is very contained, and solve the problem by implementing a solution for master data. The dark side of that approach is that if you solve the problem and then go on to address a different problem—let's say, with product data—and now you implement a completely different solution for that, how do you make sure that all these solutions are actually, in fact, connected, because your common definition of a customer for marketing needs to be the same common definition of customer for, let's say, tracking products that are being shipped to the customer.

Connecting the master data solutions and making sure that all the master data solutions in the company are based on a common set of definitions is a very important consideration as you attack master data problems.

LW: In your previous question beforehand about sales and marketing, you actually did mention some of the challenges that customers face when they are trying to implement or use master data management solutions for their sales and marketing efforts. But can you also describe some of the challenges that customers face who don't use MDM, either additionally within sales and marketing or other areas of the organization?

AW: I think what has happened is that people who don't think that master data management is a new problem that needs to be addressed in a new way, usually end up having to address the problem in the old way.

Let me give you an example of that. A lot of companies might say, “I have a CRM system,” whatever the back office application they have purchased for managing sales leads, or “I have a call center application,” whatever system they might use to train their customer service reps to take the calls and support them. They might believe that those systems are adequate for providing a coherent view of the customers—their addresses, their locations—and that might be true for just that narrow process. However, business processes and customer processes span across sales and marketing and support. So, it's very important that the customer service rep knows that a sales call has been made to this customer the day before, or what state of marketing offer might have been sent out two days before.