DECEMBER - 2020CIOAPPLICATIONS.COM9high value-added products and services. This phenomenon has led to the rise of the data economy and the concept of data monetization. The bigger the ecosystem, the more value it has in the data market. Google, Amazon, Facebook, and recently Alibaba, are leading the game.Visionary companies have understood the business rules of the new world. They have started to consider data as a strategic asset and build their business model around this. Today, technologies have advanced, and data is available to some extent, yet many companies are still struggling to monetize their data, even failing to build up their data assets. The challenges are not only due to the legacy technology but also to the siloed organizational structures and business processes. One example that led to this situation is having prior existence of decentralized and unconnected data analytics projects, which made sense on their own but do not respond to any global strategic plan. Another challenge is the fact that organizations need to understand, data is not used solely for reporting and dashboarding purposes anymore, it is used to create new business models, hence companies face with a need of paradigm shift to create a data-driven culture to turn data assets into a process of creating new products and services. To enable connected, fast, and sharable data, that quickly returns the development investments to the business, old technologies and operational models need to be challenged.Data as a Strategic AssetKnowing the challenges is important but how to tackle them and achieve this transformation to have a competitive advantage and further to monetize data? The key to dealing with these challenges is to consider data as a strategic asset and build a centralized and shared data platform to have a holistic view of data, which will be the crucial factor to extract value, gain competitive advantage and be Data-Driven organization. The ability to set data as a strategic asset on the executive-level can make a difference between winning and losing. This approach will enable to move fast and incrementally to digitize the processes and leverage the data ecosystem, opening up a world of new possibilities. By turning data into an asset, centralizing and profiting from it, many companies would eventually be transformed into a Data-as-a-Service (DaaS) organization. Next to it, organizations also need to build a modern, forward-thinking strategy focused on the data itself, and not only the technology. This includes looking at how to ensure data is never siloed, can be placed in the right place as needed, always available, easily sharable, and can be consumed by both reporting solutions and advanced analytical tools to produce intelligent applications, making sure they are effective at leveraging data to enable value creation.Balanced Data StrategyThe Data-as-a-Service market is moving rapidly into a digital age. At the same time, we are seeing the emergence of connected devices generating a huge amount of data which allows organizations to build their data assets to monetize. To make the most of this incredible opportunity, some companies might go into a trap of executing complete offensive data strategy and neglecting the control of their data assets, which eventually results in failures in their data journeys. For that reason, a balanced data strategy is crucial to make a difference in this journey, in other words, while creating new data products and services, companies should not compromise on establishing a proper data management services, (e.g., data governance, metadata management, security, privacy). Because noisy and incomplete data is a huge hurdle to create effective solutions and data management is needed to preserve and propagate the value of the data.Intelligent BusinessLastly, creating a "collaborative value creation" process that nurtures the on-going collaboration between the business and data organization is a must-have to be successful in the data journey. If you are transforming your traditional data strategy from solely focusing on reports and dashboards (Business Intelligence) into creating new smart business services and/or products utilizing AI/ML that create additional revenue streams for the organization (Intelligent Business), then it is crucial to align data strategy with business strategy and create cross-functional teams enabling the collaboration for success. The challenges are not only due to the legacy technology but also to the siloed organizational structures and business processesTekin Mentes
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