Richard Trapp

Richard Trapp
Richard Trapp is a Managing Partner and Vice President of Sales and Marketing for Northfield Consulting Group, a provider of strategic data quality consulting services. Mr. Trapp is a highly accomplished Data Quality practitioner and proven business leader with more than 19 years experience in Data Quality, business development and business optimization. Prior to Northfield Consulting Group, he was the director of global data quality for a Fortune 500 provider of business communications solutions and services. During this tenure, he designed and implemented an Enterprise Data Quality Program including organizational design and governance, operating framework and detailed process designs for full suite Data Quality service offerings. He has successfully planned and led numerous Data Quality strategies and initiatives with dozens of core team members and hundreds of extended team members, totaling nearly 500 thousand Data Quality service hours. Recognized as a leading practitioner and thought leader, Richard regularly presents at industry events on the business benefits of Data Quality. He leverages his unique business perspective and Data Quality operations experience to develop and deliver complex, value-driven solutions. Richard is a charter member of the International Association for Information and Data Quality (IAIDQ) and was a member of the team that authored the Information Quality Certified Professional (IQCP) certification examination. He has received a certificate from MIT in “Principles and Foundations of Information Quality”.

A Toast to Informatica’s Marketplace – Here’s to a Long and Healthy Future.

Happy birthday to Informatica Marketplace!

In a brief 3 years, Informatica’s Marketplace has reached several major milestones including the posting of its 1,000th Block (Application or Service) and surpassing 10,000 unique downloads per month. Over that time, the Blocks posted on the Marketplace have marked the onward progress and evolution of the data management industry from multi-domain MDM to in-memory processing to big data, and beyond. In fact, if one was to go back and take snapshots of which Blocks were posted, and when, it would be a sort of “data” time capsule. To me, that’s one of the most compelling features of the Marketplace. In addition to the plentiful and diverse set of offerings the Marketplace Blocks represent, they are continuously evolving to address the ever changing “data” landscape and are reflective of the latest in technological innovation and best practices.

So what can we expect next from the Marketplace? Let me make a prediction. Over the next 3 years, I believe you will see a profound recognition and appreciation for data as a key enabler of significant and real improvements to business performance and operational effectiveness – and this shift will be driven by the business, not IT. The shift is already underway, but to speed it along will require those of us in the industry to continue to move the conversation beyond “it’s foundational”, and more appropriately position “data” as another lever for the achievement of business goals. In order to do that, we will need to speak in terms that resonate with the customer and frame the data discussion in the context of business performance. At the operational level, how are poor data quality and bad data management practices impacting DSO, inventory turns, on-time manufacturing and delivery, revenue recognition and assurance, leverage spend, etc.? From a financial perspective, how do these data related impacts manifest themselves on the balance sheet, income statement, or cash flow statement – and to what degree?  These are the issues that our customers care about, and our solutions and recommendations should be made with these in mind. And since all solution providers are competing for finite corporate wallet share, those of us in the “data” industry will be at a competitive disadvantage if we don’t adapt.  I strongly believe we will get there, and just like the past 3 years this shift will be marked by the continuing evolution of Informatica’s Marketplace.

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When it comes to Data Quality Delivery, the Soft Stuff is the Hard Stuff (Part 6 of 6)

In my previous blog I explored the importance of a firm understanding of commercial packaged applications on data quality success. In this final post, I will examine the benefits of having operational experience as a key enabler of effective data quality delivery. (more…)

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Posted in Big Data, Business Impact / Benefits, Data Governance, Data Quality, Master Data Management, Pervasive Data Quality | Tagged , , , , , | 1 Comment

When It Comes to Data Quality Delivery, the Soft Stuff is the Hard Stuff (Part 5 of 6)

In my last blog post I discussed why an understanding of corporate financial concepts is so important to data quality success. In this blog, I will examine knowledge of commercial enterprise applications as a key enabler of effective data quality delivery.

Packaged applications for ERP, CRM, MRP, HCM, etc. were first introduced decades ago to provide tightly integrated business management functions, standardized processes and streamlined transaction processing. While one can argue whether or not these applications have lived up to all of the hyperbole, the reality is that they have been successful and are here to stay. As these backbone systems continued to evolve and mature, lessons learned from thousands of implementations were incorporated into the model solutions as best practices. These best practices spawned industry standard processes and specialized variants were born (e.g. vertical systems solutions). With the widespread adoption of these solutions, the days of custom building an application to meet the business’s needs have largely disappeared (although exceptions do persist to support specialized needs). (more…)

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When It Comes to Data Quality Delivery, the Soft Stuff Is the Hard Stuff (Part 4 of 6)

In my previous post I emphasized the importance of demonstrated project management fundamentals as a key enabler of effective data quality delivery. In this blog, I will discuss why an understanding of corporate financial concepts is so important to data quality success.

Despite the continued evolution of data management technologies and the growing awareness of the challenges and promises of data quality, business buy-in is still a major barrier to the widespread adoption of data quality as another lever to achieve operational effectiveness. One of the key reasons for limited adoption is a clear linkage between data quality and a business’s performance, which is measured in a myriad of ways from operational metrics to managerial reports to formal KPIs. But, eventually, the enterprise’s performance is summarized in three key financial statements; the income statement, the balance sheet and the cash flow statement. Positioning data quality impacts or improvements in the context of these financial statements begins to “connect the dots” and moves data quality from the abstract to the concrete and from the theoretical to the practical. To illustrate this point, let’s take a look at the impacts and implications of a simple data quality issue like “undeliverable” billing addresses. (more…)

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Posted in Big Data, Business Impact / Benefits, Business/IT Collaboration, Data Governance, Data Quality, Enterprise Data Management, Master Data Management, Operational Efficiency | Tagged , , , , , , , , , | Leave a comment

When It Comes to Data Quality Delivery, the Soft Stuff is the Hard Stuff (Part 3 of 6)

In my previous post I discussed effective stakeholder management and communications as a key enabler of successful data quality delivery. In this blog, I will discuss the importance of demonstrated project management fundamentals.

Large-scale, complex enterprise Data Quality and Data Management efforts are characterized by numerous activities and tasks being performed iteratively by multiple resources, across multiple work streams, with high volume units of work (i.e. dozens of source systems and data objects, hundreds of tables, thousands of data elements, hundreds of thousands of data defects and millions of records). Without the means to effectively define, plan and manage these efforts, success is nearly impossible. (more…)

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Posted in Big Data, Business Impact / Benefits, Data Governance, Data Quality, Enterprise Data Management, Master Data Management, Professional Services | Tagged , , | Leave a comment

When It Comes to Data Quality Delivery, the Soft Stuff is the Hard Stuff (Part 2 of 6)

In my first post I introduced the concepts of hard skills and soft skills in the context of data quality delivery, and I identified 5 soft skills that I think are highly critical to data quality delivery success, and which are typically underestimated; stakeholder management and communications, financial management, project management, commercial applications and operations. In this blog, I will discuss effective stakeholder management and communications as a key enabler of successful data quality delivery. (more…)

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When It Comes to Data Quality Delivery, the Soft Stuff is the Hard Stuff (Part 1 of 6)

I regularly receive questions regarding the types of skills data quality analysts should have in order to be effective. In my experience, regardless of scope, high performing data quality analysts need to possess a well-rounded, balanced skill set – one that marries technical “know how” and aptitude with a solid business understanding and acumen. But, far too often, it seems that undue importance is placed on what I call the data quality “hard skills”, which include; a firm grasp of database concepts, hands on data analysis experience using standard analytical tool sets, expertise with commercial data quality technologies, knowledge of data management best practices and an understanding of the software development life cycle. (more…)

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Making Big Data A Little Smaller

Big Data. The term has certainly caught on and the phenomenon is real. Every nanosecond of every day, more and more data is being created at ever increasing speeds. And since storage has become so economical, both cost and foot print, there are fewer compelling reasons for the enterprise to manage down the size of its databases. In response, new and emerging technologies such as universal database connectivity, complex event processing, connectivity to social network feeds and in-memory processing have been developed to better manage Big Data’s scale. While this is great news for the enterprise, it comes with some challenges in respect to business analytics. (more…)

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If You Build It, Will They Come … If So, For How Long?

I’m sure it’s no surprise to anyone, but there is much talk in the industry today regarding “data” and the management or control of it. To that end, commonly used terms such as Master Data Management (MDM) and Data Governance are sometimes used interchangeably and other times have wildly different definitions and applications. Whether or not the industry should or should not standardize on common terms and definitions is another subject altogether – and one that won’t be resolved any time soon. But, regardless of what it’s called the enterprise’s desire to better manage and control data is a hot topic, and deservedly so. But where does that leave Data Quality? (more…)

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Data Quality is More Than Customer Data

We’re all well aware of the importance of high quality customer data and, perhaps more importantly, the impacts of poor customer data. This heightened awareness is due to many factors, but the main reason is simple, customer data quality resonates with all of us because we can easily relate to it. Why? Because, all of us are “customers” in our daily interactions as consumers – online banking, grocery shopping, Friday night dining out – so we intuitively understand the customer role. In addition, industry white papers, testimonials and Webinars frequently position data quality from a customer perspective. But there’s much more to business than CRM and continuing to “plow that field” may be at the expense of another business area whose problem warrants our attention. (more…)

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