Monthly Archive for January, 2010

Battling today’s global threats

Published on January 27, 2010 in Data Governance and Data Quality. 0 Comments Tags: , , , , , , , , , , .

Do you really know your customers?

Will someone try to defraud your business? Use their account with you to circumvent laws? Threaten your customers? Left to your own devices, it may be difficult to ascertain the true intentions of everyone who wants to be your customer.

To support this initiative, government agencies across the world have created watch lists to help identify individuals who may represent security risks. At the same time, the same governments often require companies to collect, validate and match key information related to a customer’s identity to support the global fight against terrorism, fraud, money-laundering and identity theft.

While anti-money-laundering requirements may only affect financial institutions, the broader requirements impact most every business.  Compliance with the USA Patriot Act, Red Flag Rules, Bank Secrecy Act, HIPAA and Sarbanes-Oxley, for example, all require a more accurate, more in-depth view of your customers.

Data quality is often the first line of defense.  For executives in charge of compliance, poor data can result in the company facing public embarrassment, damage to brand equity, significant fines and even lawsuits. 

Technologies such as Pitney Bowes SpectrumTM help automate the customer screening process with robust matching and scoring mechanisms.  Such solutions consolidate various agency and country lists – providing a single source for matching against both third-party and internal fraud databases.   

In any case, whether your company treats this as a security concern or a compliance issue, your company’s data steward may be the one person best equipped to mitigate the threat.

Data and the CTO Edge

Published on January 27, 2010 in Data Governance, Data Quality, Data Stewardship and Spectrum Technology Platform. 0 Comments Tags: , , , .

IT executives no longer need to be convinced about the high cost of poor data. Most will freely admit that customer records are incomplete, not always consistent, rarely consolidated and frequently contain errors. Each day, however, brings new challenges, new business requirements and time-of-the-essence business demands.

In a recent CTO Edge Corner podcast hosted by Mike Vizard, Jay Bourland from Pitney Bowes Business Insight explains how IT organizations need to bring good data governance practices to bear if they ever want to get a real handle data quality. 

I would like to invite you to take a few minutes this week to listen in as Mike and Jay discuss how some IT execs are dealing with long-overlooked challenges. For example:

  • Juggling access and security. Data becomes more valuable when accessible by more people, but every new approved user represents a threat to data quality and privacy.
  • Responsibilities for data governance. Is it a committee? A person?  Is this an IT function or something everyone needs to be accountable for?
  • Relationship between IT and business units. Where in the process should business users engage IT, and vice versa?  The good news is, effective collaboration is attainable.
  • Organizational roadblocks. Are data profiling, cleansing, updates, governance and integration all managed by the same person on the same schedule? If not, you can still get everyone on the same page.

In addition to these insights, Mike and Jay also touch on the capabilities organizations should look for to achieve the greatest ROI.  If you want to get more practical, you will also want to catch the new 8-minute data quality video from Kit Hamilton that outlines the day-to-day and business challenges and an innovative three-step solution.

10 ways to maximize value of customer data – Part III

Published on January 21, 2010 in Data Quality and Spectrum Technology Platform. 0 Comments Tags: , , , .

In 2010, many business initiatives will bring attention to data quality, as the completeness and integrity of customer information can have a clear impact on near-term profitability.  Previously, we examined how data quality affects marketing and operational efficiency.  Today we focus on compliance and risk management.

8. Risk Management. While companies in the insurance, financial services and healthcare arena may face new regulatory oversight when it comes to risk management, organizations of all sizes will be looking for ways to mitigate risk in these uncertain economic times—especially when it comes to compliance.  Million dollar fines, ongoing lawsuits and damaged reputations are just a few of the costs that can be mitigated when companies have confidence in their customer data.

9. Tax Management. With states and localities dealing with budget pressures themselves, there will be increased scrutiny on how businesses assess, collect and manage tax obligations. Unfortunately, tax jurisdictions change frequently, and jurisdictions are not aligned with ZIP Codes or U.S. census data—so companies will look to specialized applications in order to keep pace with ongoing changes, comply with government requirements and avoid penalties.

10. Fraud Detection. One effect of the recent recession is an increase in fraud. Many companies, including those in the financial services and insurance industries, are looking for ways to integrate fraud detection applications into their core business processes. Here, data standardization, address validation, location intelligence and the ability to match against “watch list” files can greatly reduce risk and exposure.

Whether your organization is looking to pursue one, two or all ten of these strategies, Pitney Bowes offers solutions that can help, including our SpectrumTM Technology Platform.   As we start 2010, think about the ways you can leverage data quality to locate new opportunities, connect with customers and communicate more efficiently.

10 ways to maximize value of customer data – Part II

Published on January 13, 2010 in Data Governance, Data Quality, Data Stewardship and Spectrum Technology Platform. 0 Comments Tags: , , , , .

Like other corporate assets, customer data has measurable value that is integral to achieving strategic objectives. Likewise, the value of data can increase or decrease depending on how effectively you manage this asset over time.  Last week we examined how data quality affects marketing initiatives. Today we look at operational efficiency and in Part III we will examine compliance and risk management.

4. Point-of-Entry Correction. A recent Gartner study estimated that poor data quality cost organizations an average of $8.2 million a year. At that price tag, companies are taking steps to help ensure that “bad data” does not even reach their database. Real-time address validation tools are being integrated at any point where customer data may be entered into the system, including customer service, order processing and Web self-service apps.

5. Data Quality-Data Integration-Data Governance. Analysts from The Data Warehouse Institute have recently identified how organizations can create more value by unifying their data profiling, data integration and data quality initiatives. While the concept seems obvious, in practice these functions have traditionally reported into different teams.  In 2010, look for organizations to overcome the lack of coordination and redundant effort by leveraging new tools to synchronize deliverables across all aspects of data management.

6. Routing and Fleet Management. The increase in online purchasing has created challenges for manufacturers, retailers and shippers who must identify more cost-effective ways to plan distribution networks and manage their fleets. Fortunately, today’s leading data quality solutions provide for the geocoding and spatial analysis necessary to calculate routes, determine points within a boundary and move goods from one point to another at the lowest possible cost.

7. System Optimization. After investing millions in sophisticated CRM and ERP platforms, including Oracle® e-Business Suite, Salesforce.com®, SAP® and Siebel®, over two-thirds of all companies have issues with non-standard data and incomplete information.  Rather than re-invent the wheel, more organizations are increasing the returns on past IT investments by using out-of-the-box “connectors” that extract data, analyze information and provide users the visibility necessary to effectively run their business.

Clearly, the challenges associated with corporate data can overwhelm even the most sophisticated organization as each new system and customer initiative adds new levels of complexity. Solutions like our SpectrumTM Technology Platform complement your existing business platforms, making it easier to improve the quality, accessibility and value of your data assets. Obviously, there are many other ways data quality impacts customer service… how is your company using data more effectively?

10 ways to maximize the value of customer data – Part I

Published on January 7, 2010 in Data Quality and Spectrum Technology Platform. 0 Comments Tags: , , .

This year, a number of business initiatives will bring attention to data quality, as the completeness and integrity of customer information can have a clear impact on near-term profitability. Companies that take steps to improve the quality, integration, accessibility and value of their customer information may realize dividends across these ten initiatives in 2010.  This week, we look at areas that are especially critical for marketing. Next week we’ll look at operational efficiency, compliance and risk management.

1. Customer Onboarding. Given the cost of acquiring new customers, organizations will look to strengthen the quality and effectiveness of their customer onboarding experience. Studies show that getting the first 90 days right may produce greater returns than other comparable investments. In addition to significantly lower attrition rates, in some industries this initial period can account for as much as 70% of all cross-sell activity.

2. Predictive Analytics. CNN recently reported how companies are drowning in data and how gaining meaningful insight can take more effort than ever.  Each week, businesses waste 5.3 hours per employee due to inefficient processes.  It’s no wonder that one of the fastest growing fields involves predictive analytics—technologies that parse, compare and evaluate diverse, disconnected pieces of information in real time so users can make more informed decisions.

3. Postal Savings. While postal rates will not increase in 2010, the US Postal Service will assess fees against companies that do not update addresses when customers move—and that could cost mailers as much as seven cents per piece.  At the same time, new postal discounts are being offered to those who convert address data and mailing specifications into barcodes under the new Intelligent Mail® program.

To be successful, organizations need to find effective ways to deal with long-term issues such as ownership, disparate systems and overall data quality—while being opportunistic when it comes to low-hanging fruit and critical business issues.  Solutions like our SpectrumTM Technology Platform complement your existing business platforms, making it easier to improve the quality, accessibility and value of your data assets.   Obviously, there are many other ways data affects marketing results… what initiatives are critical for your business?