Archive for the 'Spectrum Technology Platform' Category

More actionable data

Published on June 8, 2010 in Data Governance, Data Quality, Geocoding and Spectrum Technology Platform. 0 Comments Tags: , , , .

Business users count on high-quality data every moment of every day.  

In practical terms, data needs to be “fit for use”.  That is, you data should add value to your existing operations and help users make better, more accurate decisions in the course of doing business.  For most organizations, ensuring that data is fit for use entails three distinct disciplines. 

  • Traditional data quality: the ability to cleanse, standardize and validate data
  • Location intelligence: the ability to see data in context of location
  • Spatial analysis: the ability to understand the relationship between two or more data points

Today, 70% of all records contain a location element and knowing “where” affects decisions in virtually every aspect of an organization.  Consider:

  • Marketing can gain insights into customer needs and buying habits
  • Insurance underwriters can identify potential risks (such as proximity to a flood zone)
  • Finance teams can assign proper tax jurisdictions
  • Sales managers can develop territories based on true market opportunity
  • Service teams can plan routes to minimize logistics costs
  • Facilities managers can develop optimal network strategies

Location and spatial analysis are so critical, in fact, that organizations are increasingly looking to incorporate geocoding, location intelligence and predictive analytics as part of their core data quality platforms and processes.

This month, Navin Sharma, our Director Global Product Strategy, will share how these market realities play out in the latest release of the Spectrum™ Technology Platform.  This informative webinar will include details on how you can integrate enterprise geocoding, location intelligence and a new geo-confidence model into your core CRM, ERP and legacy systems.  Ideal for data stewards, IT managers and business users, I invite you to register for this Webinar today and get the facts on today’s best practices in data quality, data management and more.

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?

The Four Rings of dPIQ

Published on November 11, 2009 in Data Governance, Data Quality, Data Stewardship and Spectrum Technology Platform. 0 Comments Tags: , , , , , , .

The world probably does not need any more acronyms – especially ones that sound like science fiction movies – but I was particularly impressed with a recent webinar from The Data Warehouse Institute where research analyst Philip Russom talked about dPIQ (pronounced dee-pick).

The idea is that organizations can create more value by unifying data profiling (P), data integration (I) and data quality (Q).  On the one hand, the concept seems so obvious – yet in practice, these functions often report into different teams – each with their own goals and objectives.

When teams work in silos, the lack of coordination often results in redundant efforts – with no synchronization in terms of deliverables or schedules. Russom makes the case as to how data profiling, integration and quality depend on each other.  But more importantly, he provides insight into the iterative and cyclical nature of these disciplines. What he calls “the four rings of dPIQ”.

While you may or may not want to consolidate teams, the real value-add comes from an organization’s ability to coordinate multiple cycles – so that planned updates, changes and improvements to various data management efforts work in concert.  The “four rings” approach can help you understand more about the iterative and overlapping cycles that exist in your company.  If you are in the business of adding value, this webinar could be worth your time.

Managing your data assets

Published on November 11, 2009 in Data Governance, Data Quality and Spectrum Technology Platform. 0 Comments Tags: , , , , , .

There are certain times of the year when we must all put on our financial cap.

As managers of business units and functional groups, we have all become accustomed to the concept of budgeting and planning out expenses for the upcoming year.

Yet there is another financial concept that is often overlooked when it comes to data – and that’s the idea of asset valuation. What is the value of accessible, quality data to your organization?  Can you quantify that value?  More importantly – do you really manage data like an asset?

Your company balance sheet lists current and long-term assets, including inventory, accounts receivable, cash, property and equipment.  But your most important assets – the factors that define who you are and provide for your greatest competitive advantage – are sometimes less obvious. 

Like other corporate assets, data has measurable value that is integral to achieving your strategic objectives.  Likewise, the value of your data can increase or decrease depending on how effectively you manage this asset over time. 

 We’ve recently published a white paper that explores best practices in this area, showcasing where successful managers create environments where data is:

  • accurate and up-to-date
  • accessible and secure
  • usable and well-governed

You may already be looking at next year’s challenges and opportunities from an IT and business owner perspective.  But in today’s environment, it also pays to put on your finance cap as well.

Download this white paper and examine the factors that can maximize the value of your data assets and get a road map for how to increase the return on your investments.

Bigger than the sum of its parts

Published on October 28, 2009 in Data Quality and Spectrum Technology Platform. 0 Comments Tags: , , , , , , .

Filling a gap in intelligence needs

Business intelligence. Predictive analytics. Data mining. Businesses today are truly recognizing the power that lies in their customer data.

The challenge is in harnessing that power, and doing so efficiently.  BeyeNetwork blogger Krish Krishnan captures this issue – particularly as it pertains to the gap in solutions that can help to transform data into actionable information: 

“With market consolidation, companies are left with a mixed bag of solutions and now need to reassess their investments, new market offerings have not reached enough maturity and open source is not accepted yet as enterprise capable in BI. Where we need to go with this situation is to setup an interoperable solution where the vendor consolidation will not impact current investments. There were third party companies that used to offer these kind of solutions and we need a new series of such technologies to be recreated.”

He’s right in some ways: companies that want to better understand their customers have in many cases assembled a hodgepodge of different solutions to address different challenges. As the sources of those solutions thrive and consolidate (or wither and disappear), companies that have acquired them are left with a collection of parts built in silos that are condemned to stay in silos unless they find an “interoperable” solution to enable those parts to work in concert.

However, there are solutions providers, including Pitney Bowes Business Insight, who’ve recognized this issue and have been working steadily to create options – such as the Pitney Bowes Spectrum™ Technology Platform – to address this very issue.

Rather than sending companies back to “square one”, solutions like Spectrum work in tandem with companies’ core data quality platforms. Spectrum is designed to facilitate improvements in customer data quality, and augment/assess data for a range of purposes, from Enterprise Tax Management to Global Sentry Watchlist Monitoring to Enterprise Routing for Fleet Logistics. It also provides data quality connectors for SAP and Siebel – again, enabling companies to make the most of the systems they may already have.

We agree with Krish and the others who tout the need for solutions that can grow and change with the companies they serve – and help to provide the tools for enterprise-wide business intelligence and predictive analytics.  Today’s leading-edge data and software technologies should continue to grow and change to address those specific needs.

To learn how a common data enrichment and management platform can support needs across your entire enterprise, you can read more about our Spectrum™ Technology Platform.

Announcing the Pitney Bowes Spectrum™ Technology Platform

Published on August 19, 2009 in Spectrum Technology Platform. 1 Comment Tags: , , , , , , , , , .

In the next few weeks and months, you will be hearing a great deal about the Pitney Bowes Spectrum™ Technology Platform. This represents a renaming of our enterprise data quality and location intelligence solutions formerly called Customer Data Quality (CDQ) Platform. The new name will be used beginning with the next release. If you are currently using any of the Customer Data Quality Platform Modules, this new name will not require anything from you.

Next month, you will be hearing about our 6.0 release which further expands the capabilities of our enterprise data quality solution. This release will use our new naming and be called Pitney Bowes Spectrum™ Technology Platform 6.0.

The new name was created to clarify exactly what we offer. Essentially, we are using the name Pitney Bowes Spectrum™ Technology Platform as we reference the SOA plaform in its entirety. We then grouped modules together to create five core function areas, illustrated in this diagram.

This new module alignment is very flexible. We will continue to be the only vendor to offer functionality in modular fashion. In addition, we will now bundle modules into packages for those customers who desire it.

Below are some frequently asked questions. We welcome additional questions or comments.

Frequently Asked Questions

 

Do I have to uninstall CDQ Platform to install Pitney Bowes Spectrum™ Technology Platform?

Nothing about the Pitney Bowes Spectrum™ Technology Platform naming requires you to install or uninstall anything.

 

What about the modules?

As stated above, we are keeping the modules.  It is the preference of our customers and therefore will continue to be how we offer our solution.  The module names will not change. 

 

Does this new name change the frequency or format of database updates?

No.  This will not be changed due to the new naming.

 

Will I still find the databases in the same place on the support site?

Yes.

 

Do I have to upgrade to the new Spectrum release, or can I stay on CDQ Platform 5.7?

You can stay on v5.7, but we highly recommend you move to Pitney Bowes Spectrum™ Technology Platform as soon as possible so you can take advantage of the great new features we have added.

 

Will the programs I’ve already written with the CDQ API still work?

Yes. And that is true for all available APIs.

 

What do you mean by ‘Technology Platform’? What new features does that give me?

The Pitney Bowes Spectrum™ Technology Platform refers to the overall set of solutions and the actual SOA platform.  The features that are on the existing Customer Data Quality Platform are the same as those on the Pitney Bowes Spectrum™ Technology Platform.