It’s no secret that managing data efficiently is critical to a company’s success. Today, with the large quantities of data that businesses collect, this has become a major challenge, fueling the demand for outsourced solutions like data entry and cleansing, document scanning, and more. However, reports say that while many companies realize that data is a strategic asset, they fail to achieve their data management goals. According to experts, this is possible only if you have a data strategy.
So, what exactly is a data strategy, and why is it important?
Data Strategy Defined
A data strategy is a long-term plan that guides organizations on how to get the most out their data. According to Gartner,”A data strategy is a highly dynamic process employed to support the acquisition, organization, analysis, and delivery of data in support of business objectives”.
A data strategy will help organizations:
- Understand how use data intelligently in practice
- Clarify top data priorities
- Develop a plan to understand the type of data they need, where to obtain that data, and how to store and analyze that data
With a proper data strategy, your company can create an attainable plan for the future.
However, reports say that most organizations lack a stable data strategy. A Forbes article reported that studies across many industries show that:
- Generally, less than 50 percent of an organization’s structured data is actively used for decision making
- Less than 1% of its unstructured data is analyzed or used at all
- Over 70% of employees have access to data they should not, and
- Most analysts spend time on just discovering and preparing data
- Data breaches are common
- Companies’ data technology cannot keep up with demands
Without a proper strategy for organizing, governing, analyzing, and deploying their data, organizations cannot leverage and protect their assets.
Importance of a Proper Data Strategy
With a coherent data strategy, you company can achieve many goals that are central to its operations:
- Overcome data management challenges: Common data management challenges that organizations face include data silos, data duplication, inefficient internal data flow, and poor clarity around data priorities. A proper data strategy can help them overcome these challenges.
- Make intelligent use of data and improve decision making – Data management strategies such as data cleansing services will allow organizations to obtain refined data. With clean data, organizations can ensure better data analytics and make accurate decisions to improve financial performance and profitability.
- Anticipate and mitigate risks that can compromise data security – A Thought Lab report reveals that in 2021, the average number of cyberattacks and data breaches increased by 15.1% from the previous year. A proper data strategy will allow organizations to prevent unauthorized access to data and plans all operations carefully to enhance the integrity and security of information at all times. This includes using analytics to detect and counter fraud and build systems that safeguard data. By improving data security, an effective data strategy boosts regulatory compliance.
- Identify and leverage business opportunities – With a data strategy, organizations can evaluate market trends and identify new business opportunities, driven by a better understanding of the customers’ behavior, competitors, weaknesses, and strengths. This will allow them to implement strategies to boost growth.
- Improve the customer experience and boost competitive advantage – Analyzing customer behavior is a crucial element in business development. A data strategy can help organizations identify customer segments, where they shop and what motivates them to buy. Once businesses have this information, they can personalize the customer experience, improve customer satisfaction and loyalty, and gain new customers, which can all add up to increased RoI
Companies need to devise a data strategy to meet their specific goals.
Key Components of a Data Strategy
Data priorities differ among businesses based on their goals. Here are the key components of a data strategy as defined by experts:
- Tools: Data catalog tools and data management tools are necessary to implement a data strategy. With data catalog tools, IT teams and other users can obtain an inventory of available data, identify the data they need, and use the information to map data and business operations. Data management tools are used to organize, process, and analyze a company’s data. IT teams also utilize business intelligence (BI) tools or software to collect, process, analyze, and visualize large volumes of past, current, and future data and prepare reports.
- Data analytics techniques: Advanced data analytics techniques include data visualization, predictive analytics, text analytics, sentiment analysis and cluster analysis. When appropriately deployed, data analytics techniques can help companies better understand their customers, predict their behavior and choices, and offer product recommendations and personalize the consumer experience.
- Data review: A data strategy should have a review process to evaluate and improve existing data management systems and data strategy.
- Collaboration: Collaborative tools such as video conferencing, chat and file sharing are crucial for engagement among team members and externally.
- Documentation: All strategic goals and the underlying data strategy must be documented. As techtarget. com explains this will allow companies to answer questions about the plan, data, tools, etc., as to what is appropriate, what is approved, the purpose, and the governance policy.
- Human resources: Having the right people to create and implement your data strategy is crucial for success. For this, organizations consider IT professionals, data scientists and engineers, people with analytic skills, data architects, database administrators and other data management professionals.
Regardless of all these recommendations, success with your data strategy depends on having clean, accurate, well-maintained data that is secure and ready for use. Business processing outsourcing companies play an important role in this context. They help companies manage their data processing tasks and take advantage of emerging technologies like automation, machine learning, artificial intelligence and the Internet of Things to implement effective data strategies.
Finally, keep in mind that, while it is important to have the right systems and tools in place to implement your data strategy, make sure to prioritize security and ensure compliance with relevant regulations and laws.
