By Joshua Dinneen, President of Strategic Services
In the last blog post in this series, we addressed many of the granular elements vital to achieving successful digital transformation outcomes. In this installment, we’ll examine a key element of your program and your transformation journey: Data.
More Than a Byproduct of Your Business Processing
Organizations use and create data every day in the ordinary course of conducting business. That’s nothing new. However, historically, data was viewed as little more than a byproduct and was written off as something without much intrinsic value. While there may have been some limited post-process reporting or other downstream application needs, those uses were traditionally considered minor or “one-off” uses.
In today’s business environment, data and analytics are increasingly viewed as essential components. Not only do data and analytics form the backbone of business and process models, they can also provide a competitive advantage – one that can be game-changing when leveraged appropriately. In fact, data – sometimes shared between dozens of applications – has become a core component of product structure, decision-making, strategy, and outcomes.
Exponential Increase in the Growth of Data
While organizations are using data in new and expanded ways, the amount of data businesses collect, produce, use, and store has also increased exponentially. In December 2018, IDC announced that data worldwide is expected to grow from 33 zettabytes in 2018 to an astonishing 175 zettabytes (175 trillion gigabytes) by 2025 – a 61 percent growth!
And, data is being produced by more than just traditional network devices. The “Internet of Things” (IoT) has exploded; some estimates claim there will be as many as 125 billion IoT devices by 2030, 75 billion of those consumer devices. That’s more than 10 consumer connected devices for every man, woman, and child currently on Earth. Those estimates may continue to grow rapidly as more manufacturers add online capabilities to their devices.
Unfortunately, not all data is created equal. A significant amount of data in many organizations is considered “dark data.” Simply put, dark data is information that doesn’t hold or produce value. Instead, it ends up costing organizations in the long run, both in the form of increased administration costs and in lost productivity when dark data hampers efforts to extract useful and meaningful data.
Approaching Data Governance Differently in Your Data Transformation
If your organization is using outdated approaches for gathering, maintaining, and managing data, you may find yourself struggling to create – and maintain – a competitive advantage in your industry. When you’re able to create fresh data strategies and protocols designed to match your organization’s current needs, you’ll be better prepared to transform your business technologies to meet your future goals and objectives.
Key elements of data governance include:
Classification and Tagging. Classifying and tagging your data effectively is an essential step in assessing its value, optimizing search efforts, and gathering data efficiently and effectively. Classification and tagging are also an effective means of managing your organization’s dark data, limiting risks and administration expenses.
Policy Development and Enforcement. It’s also essential to develop, implement, and enforce policies for the way your organization will collect, use, distribute, retain, retrieve, and back-up its data. Your policies should also address data expiration and redundancies, as doing so can help limit data disclosure risks.
Data Analytics. You also need a way to locate your data, which is likely spread across multiple platforms and applications, and maintained in multiple places. Your data governance should include analytics that help you map, size, track, and manage data and authorizations effectively.
Machine Learning/AI and Search Context. AI and machine learning technologies facilitate the review of vast amounts of data. Using intelligent technology can help you locate specific information, identify patterns, connections, and relationships. Key AI capabilities include descriptive and predictive analytic tools, which can inform companies about what has happened and what is likely to occur in the future, as well as prescriptive analytic tools, which can suggest action based on underlying information.
Executive Support. For any data governance strategy to be successful, it’s critical that the organization's executive leaders understand and are committed to helping drive needed change.
Knowledgeable Data Management Professionals. You will also need the right people on your team, skilled professionals with proven data management, governance, and specialized tool skills. It is also important to understand that it takes time, patience, and agility to realize optimal data governance.
Is Your Organization Ready to Commit to a Data Governance Strategy?
The type and amount of data your organization uses, and the importance of that data, has changed dramatically. No more just a byproduct, data is now a differentiating asset for organizations. It has also become the subject of increased legal and regulatory scrutiny.
Unless you develop an holistic, well-articulated, and well-managed data governance framework and process, you run the risk of sub-optimizing an extremely valuable business asset, incurring unnecessary operational expenses, and hindering business capabilities. You also increase your risk of violating regulatory requirements.
Many organizations have developed effective data utilization and governance programs by seeking advice from experienced, knowledgeable advisory firms. If you have questions about data governance and its role in your digital transformation, GreenPages can help. We work closely with you to identify your top priorities and risks, and develop cost-effective solutions that protect and better manage your crucial data assets – and your business.
In the next blog in this series, Simon Johnson, GreenPages' SVP of Client Services, will examine the role of technology – the core, underlying factor that will enable you to create a successful and competitive digital transformation program.
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