A Dialogue on Data Transparency with Annette Wright and Dan FischerHeading

From the perspective of Dan Fischer, Strategic Solutions Executive. Response and data governance insights by Annette Wright, Senior Director of Analytics & Governance.

As we wrap up 2019 and look forward to 2020, I wanted to take a moment to reflect on “data” market changes with my colleague Annette Wright, Senior Director of Analytics & Governance, and share some of our observations.

In 2019 we’ve seen a tremendous growth in data literacy across all industries. As the value of data has become increasingly important, this has heightened the need for data governance. Working with our clients on implementing various technologies and data programs, I’ve noticed a stigma with the phrase “data governance.” Managing data has become a necessary corporate function, particularly for companies in highly regulated industries, and for those clients who need better protection of their customer PII data. Regulations such as GDPR and CCPA are good examples of the additional pressure organizations are facing to better manage their most critical asset.

As 2020 begins I will be searching opportunities to change the “data” conversation with my clients; finding new ways to elevate the discussion and focusing on the democratization of the data – making this strategic asset more transparent across each organization. Most of my clients have so much data, they have difficulty knowing how best to use all of this information to improve their products, customer engagement, and achieve their business and financial imperatives. But what data is important? To whom? When? And, why? This is what I mean by transparency – improving an organization’s data literacy – instituting good data management as a business accelerator rather than the perception of a “tax” or constraint.

With that, I wanted to seek Annette’s perspectives on several questions.

Dan: Recapping 2019, how do you feel companies are reacting to the term “data governance?”

Annette:  Well, the good news is that I’m having to explain less often what data governance (DG) is. But that’s also the not-so-good news, as most companies still associate DG initiatives strictly with regulatory requirements.  I’m sure you can see how that association leads to a negative perception for any data program, especially when we are talking with people responsible for the management of a company’s technological architecture.

Dan: So, it sounds like there can be a narrow understanding of DG, and that it spans more than just regulatory requirements. Is the stigma with DG warranted?

Annette:  It certainly didn’t start out that way, but over time the program initiatives that have garnered the most publicity have created that perception. Governance, in and of itself, isn’t negative, but the perceived cost and administrative overhead can certainly slow progress in today’s instant gratification world. Funding is limited, executive patience is thin, and the business wants real results now.

Dan: When you think about changing the conversation and introducing the notion of data transparency over data governance, is that possible?

Annette:  Absolutely. Sometimes rather than trying to change the association and perception of certain terminology, it may be easier to change the words! Data transparency covers far more ground than the current narrower focus that has been tagged to “governance.” Of course, I fully admit we are simply trying to drive the conversation and help companies see the bigger picture – data is still their most valuable asset. Understanding how to control and gain insights is the key to unlocking its potential.

Dan: What do you think is the biggest hurdle companies will face in 2020?

Annette:  Even though data is pervasive throughout any organization, we continue to see reticence among the business stakeholders on creating more systematic management and control of the company’s data. And of course, you can’t change everything at once! Identifying and prioritizing the remediation of key data management risks are always the toughest decisions. But once you make a positive impact in one area, the results begin to reverberate across a company and more demand is generated. Which of course leads to the next hurdle – how to manage data management demand effectively. That is a good problem to have, though!

Dan:  How has Paradigm adjusted its services to create a positive impact for our customers?

Annette:  I think our most effective change is our workshop approach, which we have successfully executed many times this year. We bring both business stakeholders and technology partners together, facilitating a conversation on not only “what” needs to be done in the data management space, but also to make sure everyone understands “why” that work is required.  We’ve both heard people on both sides say things like “I don’t understand technology” or “I don’t know why my business partner has asked for…”  Understanding fosters collaboration across teams and helps qualify and quantify the business benefits of making critical changes.

Annette, thank you for the insights and lively discussion. I’m excited about 2020, particularly as we continue to educate our clients and teams on the value of data transparency and how data governance can be seen as a strategic enabler for these clients to achieve their goals.

Recent Posts

Executive Perspective: Why Securing Your Data is the Key to Winning with AI

As CXOs, we’re all focused on leveraging AI to drive efficiency, innovation, and competitive advantage. The conversation often starts with infrastructure (GPUs, LLMs, and copilots), but let’s be clear: AI doesn’t run on GPUs. It runs on data. And if our data isn’t secure, nothing else matters. Unsecured and unclassified data undermines trust, exposes us to risk, and jeopardizes the very AI strategies we’re betting our futures on. It’s not about chasing the next shiny tool; it’s about building a foundation that allows AI to scale safely, responsibly, and securely.

Quantifying the Value of Data in Financial Services

In the financial services sector, data is a critical asset that drives profitability, risk management, regulatory compliance, and competitive edge. However, measuring its value remains challenging for many CFOs across sectors of the financial services industry regardless of organizational size or country of operations. CFOs rely on accurate data for forecasting, budgeting, and strategic planning. Quality data leads to better decision-making, optimized capital allocation, and swift responses to market changes. It is also vital for risk management, regulatory compliance (e.g., BCBS 239, Basel III, AML/KYC), and avoiding fines and reputational damage. “Fit for Business Use” data also supports customer retention, personalized services, and improved revenue stability. Data-savvy CFOs leverage insights for long-term growth.

AI Starts with Data: Go From Hype to Results

AI continues to dominate the conversation in business. From executive meetings to strategic roadmaps, AI is no longer just a trend but a real driver of transformation. The challenge is that while nearly every organization is talking about AI, very few are prepared to use it in a way that delivers measurable outcomes and lasting impact. The difference between hype and outcomes almost always comes down to two things: the quality of your data and your organization’s readiness to execute.

Exciting Updates from Informatica World: Paradigm Embraces the Future of Agentic AI

The digital landscape is evolving rapidly, and staying ahead means embracing the latest innovations in data management and artificial intelligence. At this year’s Informatica World, Paradigm is thrilled to share the groundbreaking advancements unveiled by Informatica, centered around their latest agentic AI solutions on the Intelligent Data Management Cloud (IDMC) platform.

Modernizing PowerCenter: The IDMC Way – Better, Faster, Cheaper

For many organizations, Informatica PowerCenter has been the workhorse of their data integration for years, even decades, reliably driving ETL processes and populating data warehouses that feed BI reports. However, this longevity often leads to a complex environment that can hinder agility and innovation.

Boost Growth with Data-Driven Hiring for Boutique Consultancies

Consistency is key to a boutique consultancy. Delivering quality services day in and day out, even as client demand fluctuates, relies heavily on having the right talent at the right time. Perhaps one of the largest operational challenges for small and mid-sized consulting firms, though, is matching recruitment cycles with cyclical demand. Without scalable, data-driven talent practices, consultancies can suffer from misaligned capacity, lost revenue streams, and stalled growth.

Strategies for a Successful Journey in Building the Dream Team

In the whirlwind world of project management, the success of a project often hinges on the strength and consistency of the team behind it. Imagine embarking on a journey where building a high-performing project team is not just about assembling a group of skilled individuals; it’s about fostering collaboration, trust, and a shared sense of purpose. Based on my personal experiences, let me take you through this journey with some strategies I use to help you build and lead a high-performing project team.

The Ultimate Guide to AI-Enhanced APIM Analytics for Enterprise Success

Enterprises increasingly rely on Application Programming Interface (API) Management (APIM) to streamline their operations, enhance customer experiences, and drive innovation. Azure API Management is a comprehensive solution enabling organizations to manage, secure, and optimize their APIs efficiently. However, beyond API management, APIM analytics – particularly when integrated with AI and data analytics – empowers senior executives with critical insights for real-time decision-making.

Why PMOs that Leverage Power BI are More Successful

Project Management Offices (PMOs) are increasingly turning to Microsoft Power BI as a game-changing tool to enhance their project management processes. By leveraging data visualization and analytics, PMOs can make informed decisions, streamline reporting, and improve overall project outcomes.