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How Much Does Bad Data Cost Your Business?

Bad data is bad for business. Ovum Research reported that poor quality data is costing businesses at least 30% of revenues. Never before have business leaders across a broad range of roles recognized the importance of using high quality information to drive business success. Leaders in functions ranging from marketing and sales to risk management and compliance have invested in world-class applications, six sigma processes, and the most advanced predictive analytics. So why are you not seeing more return on that investment? Simply put, if your business-critical data is a mess, the rest doesn’t matter.

Dennis Moore explains the implications of using inaccurate, inconsistent and disconnected data and the value business leaders can gain by mastering it.

Dennis Moore explains the impact of using accurate, consistent and connected data and the value business leaders can gain through master data management (MDM).

Not all business leaders know there’s a better way to manage their business-critical data. So, I asked Dennis Moore, the senior vice president and general manager of Informatica’s MDM business, who clocked hundreds of thousands of airline miles last year visiting business leaders around the world, to talk about the impact of using accurate, consistent and connected data and the value business leaders can gain through master data management (MDM).

Q. Why are business leaders focusing on business-critical data now?
A. Leaders have always cared about their business-critical data, the master data on which their enterprises depend most — their customers, suppliers, the products they sell, the locations where they do business, the assets they manage, the employees who make the business perform. Leaders see the value of having a clear picture, or “best version of the truth,” describing these “master data” entities. But, this is hard to come by with competing priorities, mergers and acquisitions and siloed systems.

As companies grow, business leaders start realizing there is a huge gap between what they do know and what they should know about their customers, suppliers, products, assets and employees. Even worse,  most businesses have lost their ability to understand the relationships between business-critical data so they can improve business outcomes. Line of business leaders have been asking questions such as:

  • How can we optimize sales across channels when we don’t know which customers bought which products from which stores, sites or suppliers?
  • How can we quickly execute a recall when we don’t know which supplier delivered a defective part to which factory and where those products are now?
  • How can we accelerate time-to-market for a new drug, when we don’t know which researcher at which site used which combination of compounds on which patients?
  • How can we meet regulatory reporting deadlines, when we don’t know which model of a product we manufactured in which lot on which date?

Q. What is the crux of the problem?
A. The crux of the problem is that as businesses grow, their business-critical data becomes fragmented. There is no big picture because it’s scattered across applications, including on premise applications (such as SAP, Oracle and PeopleSoft) and cloud applications (such as Salesforce, Marketo, and Workday). But it gets worse. Business-critical data changes all the time. For example,

  • a customer moves, changes jobs, gets married, or changes their purchasing habits;
  • a suppliers moves, goes bankrupt or acquires a competitor;
  • you discontinue a product or launch a new one; or
  • you onboard a new asset or retire an old one.

As all this change occurs, business-critical data becomes inconsistent, and no one knows which application has the most up-to-date information. This costs companies money. It saps productivity and forces people to do a lot of manual work outside their best-in-class processes and world-class applications. One question I always ask business leaders is, “Do you know how much bad data is costing your business?”

Q. What can business leaders do to deal with this issue?
A. First, find out where bad data is having the most significant impact on the business. It’s not hard – just about any employee can share stories of how bad data led to a lost sale, an extra “truck roll,” lost leverage with suppliers, or a customer service problem. From the call center to the annual board planning meeting, bad data results in sub-optimal decisions and lost opportunities. Work with your line of business partners to reach a common understanding of where an improvement can really make a difference. Bad master data is everywhere, but bad master data that has material costs to the business is a much more pressing and constrained problem. Don’t try to boil the ocean or bring a full-blown data governance maturity level 5 approach to your organization if it’s not already seeing success from better data!

Second, focus on the applications and processes used to create, share, and use master data. Many times, some training, a tweak to a process, or a new interface can be created between systems, resulting in very significant improvements for the users without major IT work or process changes.

Lastly, look for a technology that is purpose-built to deal with this problem.  Master data management (MDM) helps companies better manage business-critical data in a central location on an ongoing basis and then share that “best version of the truth” with all on premise and cloud applications that need it.

Master data management (MDM) helps manage business-critical customer data and creates the total customer relationship view across functions, product lines and regions, which CRM promised but never delivered.

Master data management (MDM) helps manage business-critical customer data and creates the total customer relationship view across functions, product lines and regions, which CRM promised but never delivered.

Let’s use customer data as an example. If valuable customer data is located in applications such as Salesforce, Marketo, Seibel CRM, and SAP, MDM brings together all the business-critical data, the core that’s the same across all those applications, and creates the “best version of the truth.” It also creates the total customer relationship view across functions, product lines and regions, which CRM promised but never delivered.

MDM then shares that “mastered” customer data and the total customer relationship view with the applications that want it. MDM can be used to master the relationships between customers, such as legal entity hierarchies. This helps sales and customer service staff be more productive, while also improving legal compliance and management decision making. Advanced MDM products can also manage relationships across different types of master data. For example, advanced MDM enables you to relate an employee to a project to a contract to an asset to a commission plan. This ensures accurate and timely billing, effective expense management, managed supplier spend, and even improved workforce deployment.

When your sales team has the best possible customer information in Salesforce and the finance team has the best possible customer information in SAP, no one wastes time pulling together spreadsheets of information outside of their world-class applications. Your global workforce doesn’t waste time trying to investigate whether Jacqueline Geiger in one system and Jakki Geiger in another system is one or two customers, sending multiple bills and marketing offers at high cost in postage and customer satisfaction. All employees who have access to mastered customer information can be confident they have the best possible customer information available across the organization to do their jobs. And with the most advanced and intelligent data platform, all this information can be secured so only the authorized employees, partners, and systems have access.

Q. Which industries stand to gain the most from mastering their data?
A. In every industry there is some transformation going on that’s driving the need to know people, places and things better. Take insurance for example. Similar to the transformation in the travel industry that reduced the need for travel agents, the insurance industry is experiencing a shift from the agent/broker model to a more direct model. Traditional insurance companies now have an urgent need to know their customers so they can better serve them across all channels and across multiple lines of business.

In other industries, there is an urgent need to get a lot better at supply-chain management or to accelerate new product introductions  to compete better with an emerging rival. Business leaders are starting to make the connection between transformation failures and a more critical need for the best possible data, particularly in industries undergoing rapid transformation, or with rapidly changing regulatory requirements.

Q. Which business functions seem most interested in mastering their business-critical data?
A. It varies by industry, but there are three common threads that seem to span most industries:

Business leaders are starting to make the connection between transformation failures and bad data.

Business leaders are starting to make the connection between transformation failures and a more critical need for the best possible data.

  • MDM can help the marketing team optimize the cross-sell and up-sell process with high quality data about customers, their households or company hierarchies, the products and services they have purchased through various channels, and the interactions their organizations have had with these customers.
  • MDM can help the procurement team optimize strategic sourcing including supplier spend management and supplier risk management with high quality data about suppliers, company hierarchies,  contracts and the products they supply.
  • MDM can help the compliance teams manage all the business-critical data they need to create regulatory reports on time without burning the midnight oil.

Q. How is the use of MDM evolving?
A. When MDM technology was first introduced a decade ago, it was used as a filter. It cleaned up business-critical data on its way to the data warehouse so you’d have clean, consistent, and connected information (“conformed dimensions”) for reporting. Now business leaders are investing in MDM technology to ensure that all of their global employees have access to high quality business-critical data across all applications. They believe high quality data is mission-critical to their operations. High quality data is viewed as the the lifeblood of the company and will enable the next frontier of innovation.

Second, many companies mastered data in only one or two domains (customer and product), and used separate MDM systems for each. One system was dedicated to mastering customer data. You may recall the term Customer Data Integration (CDI). Another system was dedicated to mastering product data. Because the two systems were in silos and business-critical data about customers and products wasn’t connected, they delivered limited business value. Since that time, business leaders have questioned this approach because business problems don’t contain themselves to one type of data, such as customer or product, and many of the benefits of mastering data come from mastering other domains including supplier, chart of accounts, employee and other master or reference data shared across systems.

The relationships between data matter to the business. Knowing what customer bought from which store or site is more valuable than just knowing your customer. The business insights you can gain from these relationships is limitless. Over 90% of our customers last year bought MDM because they wanted to master multiple types of data. Our customers value having all types of business-critical data in one system to deliver clean, consistent and connected data to their applications to fuel business success.

One last evolution we’re seeing a lot involves the types and numbers of systems connecting to the master data management system. In the past, there were a small number of operational systems pushing data through the MDM system into a data warehouse used for analytical purposes. Today, we have customers with hundreds of operational systems communicating with each other via an MDM system that has just a few milliseconds to respond, and which must maintain the highest levels of availability and reliability of any system in the enterprise. For example, one major retailer manages all customer information in the MDM system, using the master data to drive real-time recommendations as well as a level of customer service in every interaction that remains the envy of their industry.

Q. Dennis, why should business leaders consider attending MDM Day?
A. Business leaders should consider attending MDM Day at InformaticaWorld 2014 on Monday, May 12, 2014. You can hear first-hand the business value companies are gaining by using clean, consistent and connected information in their operations. We’re excited to have fantastic customers who are willing to share their stories and lessons learned. We have presenters from St. Jude Medical, Citrix, Quintiles and Crestline Geiger and panelists from Thomson Reuters, Accenture, EMC, Jones Lang Lasalle, Wipro, Deloitte, AutoTrader Group, McAfee-Intel, Abbvie, Infoverity, Capgemini, and Informatica among others.

Last year’s Las Vegas event, and the events we held in London, New York and Sao Paolo were extremely well received. This year’s event is packed with even more customer sessions and opportunities to learn and to influence our product road map. MDM Day is one day before InformaticaWorld and is included in the cost of your InformaticaWorld registration. We’d love to see you there!

See the MDM Day Agenda.

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Posted in Business Impact / Benefits, Business/IT Collaboration, Customers, Data Quality, Informatica World 2014, Master Data Management | Tagged , , , , , , , , , , , , , , , , , , | Leave a comment

Customer Data Management – Time for a Reboot?

I have been developing two ideas for customer data management: entities vs. roles and differentiation. In the last post I suggested that customer is not a data type, but rather a role that can be played by some core entity in some context, with some set of characteristics assigned to that role within that context. (more…)

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Customer Data Forum Off To A Great Start Featuring MDM

We launched a coast-to-coast Customer Data Forum road show with visits to Atlanta and Washington, D.C., that attracted business and IT professionals interested in using master data management (MDM) to attract and retain customers.

From the business side, our guests consisted of analysts, sales operations personnel, and business liaisons to IT, while the IT side was represented by enterprise and data architects, IT directors, and business intelligence and data warehousing professionals. In Washington, about half the audience was from public sector and government agencies. (more…)

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Posted in Data Governance, Data Integration, Data Integration Platform, Data Quality, Data Services, Data Warehousing, Enterprise Data Management, Identity Resolution, Informatica Events, Master Data Management, Partners, Pervasive Data Quality, Profiling, Public Sector, Scorecarding | Tagged , , , , , , , , , , , , , , , , , | Leave a comment

Do You Trust Your Data?

Recently I was talking to a prospective customer who shared some challenges they faced recently– they had asked five people for a report and had gotten five different answers. Unfortunately, this is not an uncommon situation. In fact, at times it seems as though making business decisions and managing business processes is a bit like using an “origami fortune teller” — you hope you get the right answer, but you’re really leaving your fate to chance.

(more…)

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Posted in Business Impact / Benefits, Business/IT Collaboration, CIO, Customer Acquisition & Retention, Customer Services, Customers, Data Governance, Data Integration, Data Integration Platform, Data Quality, Enterprise Data Management, Uncategorized | Tagged , , , , , , , , , , | Leave a comment

Data Quality And The Customer Life Cycle

One of the sections in my recent Informatica-sponsored paper on Understanding the Financial Value of Data Quality Improvement looked at impacts associated with customer retention. Once the company has acquired a customer, there is an expectation that steps will be taken to ensure that the customer’s business is retained, and this means not only encouraging the customer to continue doing business with the company, but to take the proper steps to prevent the customer from purchasing products of services from any competitors as well. There are a number of techniques employed for customer retention, most of which rely on high quality information about the customer as well as deep visibility into that customer’s relationship and history of interactions. (more…)

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Posted in Customer Acquisition & Retention, Customers, Data Governance, Data Quality | Tagged , , , , | Leave a comment