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What’s so hard about being a data-driven organization?

Many companies have been trying to become more data-oriented for years, with mixed results. Hard work pays off over time, and winners are distinguished by their persistence, resilience, execution and relentless efforts to use data to make smarter business decisions. But while companies’ desire to be data-driven may not have changed, the circumstances have changed.

       

Today, the biggest challenge for organizations working on a data strategy may not be technical at all. In NewVantage Partners’ latest annual survey tracking the progress of corporate data initiatives, the chief director of data, information and analytics cited cultural change as the most critical factor. This is understandable: being data-driven, after all, is a test of people and organisations’ ability to adapt to change, and to some extent this has been underestimated. Long-established businesses that have enjoyed generations or centuries of success are unlikely to change overnight. Over the past 25 years, the digital transformation of enterprises to adapt to the Internet has been effective. Similarly, the realization of data-driven is also a long-term business transformation that needs to be promoted by enterprises. While much has been achieved in this process, much remains to be done.

       

But while cultural change is not a new issue, two cultural dynamics have shaped corporate activity in the past few years.

       

First, the COVID-19 pandemic and its devastation have reinforced the importance of data, science and facts. Once upon a time, companies may have only paid lip service to the importance of data, but over the past two years it has become clear how important good data can be in making sound, prudent and informed business decisions.

       

Second, self-service is becoming more and more common, and individuals can now consume information and data on demand in their desired way. We live in an era of increasingly fragmented information, which means consumers can choose which news they follow, which social media they want to engage with and which data they want to trust. As a result, consumers of information may be exposed to selectively presented data that supports a wide range of viewpoints. At its most extreme, this has given rise to the concept of “alternative facts”.

       

Finally, there is a structural fact: a lot of data is being generated every day, and it continues to grow at an exponential rate. With its computing power, companies can get accurate answers by crunching huge amounts of data rather than relying on a representative sample.

       

Understanding these trends, and how others are harnessing them, can help us move towards data-driven decision-making.

     

Data-driven roadblocks

       

Three indicators of progress stood out among the participating organizations. First, most organizations still want to achieve data-driven leadership, with only 26.5 percent reporting that they have established one. Second, to be data-driven, organizations need to focus on cultural change. In this year’s survey, 91.9 percent of executives cited cultural barriers as the biggest data-driven barrier. As mentioned earlier, implementing data-driven is not a technical problem, but a human challenge. Finally, organizations are establishing data-driven leadership functions, such as the appointment of chief data and analytics officers, which will lay the foundation for data-driven implementation. However, only 40.2 percent said the role was successful and recognized in their organization.

       

To make matters worse, data-driven tasks are getting harder. Today, enterprises need to process a lot of new data and new data sources, including sensor data, signals, text, images, and other forms of unstructured data. It has recently been suggested that 80 per cent of new data is unstructured, meaning it is not easily collected or quantified. More importantly, companies must recognize that data is a business asset that flows through the organization and should be valued. Data crosses traditional organizational boundaries, often without clear ownership. The fluidity of data increases the complexity of managing this asset to provide continued business value.

       

Moreover, companies face a rapidly emerging problem with the ownership and management of data, using it in a responsible and ethical way. This is also a topic that has been widely discussed and at the center of controversy in recent years, with many articles delving into personal privacy issues and corporate data liability.

Consider Cathy O’Neill’s 2016 book “Algorithmic Hegemony: The Threat and Injustice of Weapons of Math Destruction: How Big Data Increases Inequality and Democracy “); Shoshana Zuboff’s 2019 article, “The Age of Surveillance Capitalism: Fighting for The Future of Humanity on The New Frontier of Power” The Fight for a Human Future at The New Frontier of Power “). Carissa Veliz recently published “Privacy Is Power: Why and How You Can Take Back Control of Your Data” (2021) (” Privacy Is Power: How and Why You Should Take Back Control of Your Data “), And “Why Privacy Matters” (2021) by the law professor Neil Richards.
       

This year’s survey highlights corporate concerns about data ethics and data responsibility: only 21.6 percent of data leaders believe their industry is doing enough to address ethical issues and standards in data and AI.

     

Measures available to the enterprise

       

Building data-driven organizations is a long process that can take years, if not decades. What can organizations and business managers do to accelerate this process? Based on experience, data-driven enterprises have consistently demonstrated qualities that differentiate them from their contemporaries and are driven by the following three driving principles:

       

Think differently. Data leaders recognize that becoming a data-driven organization requires a different way of thinking. Organizations must be prepared to encourage different ways of thinking. There is no shortage of analytical algorithms. But these need to be matched by critical thinking, human judgment and innovative ideas.

       

Fail fast, learn fast. Data leaders understand that individuals and organizations must learn by experience through trial and error. It is said that failure is the foundation of innovation. Companies need to be prepared for faster iterative learning — failing fast, learning fast — in order to gain insight and knowledge ahead of their competitors.

       

Think long term. Data leaders know that data transformation cannot happen overnight. Becoming a data-driven enterprise is a process. French writer Voltaire famously said, “The perfect is the enemy of the good.” Because perfection is almost impossible to achieve. Data-driven organizations recognize that success is achieved through iteration and accumulation. They don’t mind spending a little more time on it, just because they’re more focused on the long term.

       

To remain competitive in the increasingly data-driven 21st century, business managers must learn from the experiences of their predecessors, strive to avoid the pitfalls of the past, and follow the example of companies that have successfully advanced data efforts. At a time when data, science and facts are being challenged, it has never been more important to be a data-driven organization.

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