Richard Trapp
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…)
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…)
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…)
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…)
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…)
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…)
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…)
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…)
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…)
Nothing Sells Data Quality, Like Data Quality Success
A few weeks ago, I was privy to a very active blog topic regarding CxOs and why they don’t “get” Data Quality and its value proposition. It attracted dozens of responses from a multitude of perspectives. Much of the dialogue was in regard to getting senior leadership’s initial buy-in and support but it got me thinking… even if you are fortunate enough to get the go ahead, how do you take this one opportunity and parlay it into a string of opportunities? (more…)
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