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  • Writer's pictureAnantaya Pornwichianwong

Data Strategy: The Tool for Unlocking the Power of Data



We believe that nowadays, Big Data has become common ground for all businesses, and it is a crucial step in their digital transformation. However, unlocking the full potential of data is impossible without an effective data strategy.


In this article, Sertis would like to introduce you to a data strategy: why it matters, how it benefits businesses, and what are the key components for designing an effective data strategy.


What is a Data Strategy?


A data strategy is a long-term plan for the utilization of data within an organization. It is designed to comprehensively control and guide data utilization across the organization, encompassing aspects such as data collection, storage, analysis, and utilization. Additionally, it involves defining tools and technologies, establishing data governance frameworks, and providing training for stakeholders. The objective of this process is to achieve the most effective data strategy aligned with the organization's business goals.





Why is a Data Strategy Essential for Businesses?


In today's business landscape, vast amounts of data circulate within operations daily, including customer data, operational data, and external data. Data can be an invaluable asset, but only if we can extract insights hidden within it. To achieve this, proper data management and utilization that align with the business's nature are essential.


These insights can be significantly useful for helping businesses make informed decisions and guiding them toward directions that generate profits and growth. This is precisely why businesses planning to leverage their data need a comprehensive and accurate data strategy.


How Does a Data Strategy Benefit Businesses?


  1. Enable informed, data-driven decision-making for accurate and effective choices.

  2. Eliminate errors by implementing quality assurance measures based on data for all processes.

  3. Increase operational efficiency by utilizing data to understand overall processes and identify areas for improvement.

  4. Reduce costs by identifying unnecessary and excessive expenses through data analysis.

  5. Enhance the likelihood of success in various aspects, such as new product launches, based on data insights.

  6. Further leverage data to develop technologies that reduce workload and enhance business operations, such as machine learning and generative AI models.





Key Pillars for Designing a Data Strategy:


  • People: Define the stakeholders and their roles and responsibilities.

  • Process: Define the processes that interact with data, including data policies, standards, and procedures.

  • Data: Define a data format and architecture that aligns with business objectives.

  • Technology: Define technologies and platforms for data analytics, focusing on scalability and expansion.


How to Design a Data Strategy:


  1. Assess:


Assess the organization's current state and benchmark it against industry-leading practices.


  1. Business Discovery:


Identify improvement opportunities and business values generated from a data strategy and data utilization. This includes boosting sales, saving resources, and optimizing operations by defining clear objectives for data utilization and associated teams, aligning them with business goals, and determining tangible KPIs.


  1. Future-proof Solution:


Define a detailed state covering all relevant aspects to design the data strategy that balances cost and value, and achieves desirable outcomes both now and in the future, including the following aspects:


  • Data Governance: Define effective data management policies, including data collection, cleansing, and security, to ensure that all data in the organization is of high quality, ready-to-use, and transparent.

  • Data Architecture: Design a data architecture covering data collection, processing, and utilization, by selecting technologies and platforms that suit the organization's data needs, such as choosing cloud storage and data warehouses, as well as customizing data pipelines.

  • Data Tools: Select appropriate tools for data collection, transfer, analysis, visualization, and dashboards. The choice of tools should align with the objectives and ensure efficiency and security.

  • People and Skills: An effective data strategy prioritizes people. All teams should be properly prepared for and adapt to becoming a data-driven organization. Training and support teams are required for a smooth transition.


  1. Actionable Outcomes:


Develop initiatives that can be immediately implemented to provide tangible and immediate benefits, thus motivating continual compliance.





What Should We Do Next?


After a data strategy is ready to be implemented, there are three key things to proceed with:


  • Design the Action Plan: Leverage your ready-to-use data by designing a detailed action plan for each area. Include clear timeframes and KPIs to track progress.

  • Invest in Technologies and Tools: Upgrading technologies and tools may be necessary during implementation to increase efficiency. Optimize your investment by focusing on functionalities that directly support your data strategy.

  • Track and Improve: Continuously track data utilization within the organization. Analyze results and make improvements to adapt to changes and ensure maximum efficiency.


Designing a data strategy is a complex task, requiring significant resources, time, expertise, and foresight. Collaborating with industry experts is another option for businesses seeking to ensure the efficiency of their data strategy.


Sertis is a leading data and AI solution provider offering one-stop service. We collaborate with our customers to design and develop customized data strategies that meet their unique business needs. We equip businesses with a robust data foundation, empowering them to unlock substantial value from their data.


Learn more about Sertis' solutions at https://www.sertiscorp.com/solutions

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