The Power of Data Differentiators: How to Use Them to Your Advantage

In today's data-driven world, businesses need to be able to identify and leverage their data differentiators in order to stay competitive. But what exactly are data differentiators, and how can you use them to your advantage? This guide will provide a comprehensive overview of data differentiators and offer tips for identifying and using them effectively.

"The Data Differentiator" is a term used to describe the importance of data in creating a competitive advantage for organizations. It involves designing a data strategy, building a robust architecture, and delivering governed data across the organization.

According to a Forbes Insights and KPMG report, data, and analytics capability ranks the highest of CEOs' top five investment priorities today. However, faith in the data businesses rely upon is low. As a result, improving data quality is a critical differentiator to business success.

What does it take to be data-driven?

Being data-driven means using data to inform decision-making and strategy across an organization. To be data-driven, an organization needs to have a data strategy, a robust data architecture, and governed data delivered across the organization. Therefore, the first step in becoming data-driven is to recognize the need to focus on data and analytics capability.

According to the Forbes Insights and KPMG "2016 Global CEO Outlook," data and analytics capability rank the highest of CEOs' top five investment priorities today.

To be data-driven, an organization needs to have accurate and timely data. Accuracy means that the data is correct, such as addresses that guarantee mail will be deliverable or transaction data that adequately reflects a customer's purchase history. Timeliness means the data is fresh and reflects the most up-to-date information, such as a customer's new address.

Data-driven culture starts at the top. Companies with data-driven solid cultures tend to have top managers who set an expectation that decisions must be anchored in data. They lead by example and use data to inform their decision-making. Companies need to choose metrics with care and cunning to create a data-driven culture. They need to grant universal access to just a few critical measures at a time instead of grand but slow programs to reorganize all their data. Improving data quality is a crucial differentiator to business success. As businesses attempt to prepare for transformational technologies like autonomous vehicles, artificial intelligence, and the Internet of Things (IoT), many find themselves grappling with the complexities of data and analytics. The role data plays in enabling these future technologies is critical.

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What are data differentiators?

Data differentiators are unique characteristics or attributes of a business's data that set it apart from competitors. These can include the type of data collected, the sources of the data, the quality of the data, and the insights that can be derived from it. By identifying and leveraging these differentiators, businesses can gain a competitive edge and make more informed decisions.

Data differentiators are becoming increasingly important in today's data-driven business landscape. With so much data available, it can be difficult for businesses to stand out and make sense of it all. By identifying their unique data differentiators, businesses can better understand their customers, competitors, and market trends. For example, a company that collects data from a variety of sources, including social media, customer surveys, and sales data, may have a more comprehensive view of their customers than a competitor that only collects sales data. Similarly, a business that invests in high-quality data cleaning and analysis may be able to uncover insights that their competitors miss. Ultimately, data differentiators can help businesses make more informed decisions, improve their products and services, and stay ahead of the competition.

How to identify your business's data differentiators?

To identify your business's data differentiators, start by analyzing your data and comparing it to your competitors. Look for unique characteristics or attributes that set your data apart, such as the sources of your data, the quality of your data, or the insights that can be derived from it. You can also conduct market research to understand what your customers value most about your data and how it compares to your competitors. Once you have identified your data differentiators, use them to your advantage by highlighting them in your marketing materials and using them to inform your business decisions.

One way to identify your business's data differentiators is to conduct a thorough analysis of your data. Look for patterns or trends that are unique to your business, such as data sources that your competitors don't have access to, or data quality that is superior to your competitors. You can also look for insights that can be derived from your data that are not available from your competitors.

What does it take?

Several critical components need to be in place to be a data-driven organization.

1. A cohesive and comprehensive data strategy that applies across the organization is required. This strategy should encompass technology and automation, including artificial intelligence (AI), culture, governance, cybersecurity, data privacy, skills, and other components.
2. A robust data architecture must be built to deliver governed data across the organization.
3. Data quality is critical to business success, and improving data quality is a crucial differentiator.
4. A data-driven culture needs to be established, starting from the organization's top. Top managers need to set an expectation that decisions must be anchored in data, and they need to lead by example.
5. Metrics need to be chosen with care and craftiness.
6. . Sixthly, data literacy needs to be improved across the organization.
7. Data must be democratized, with universal access to critical measures at a time.
8. Data needs to be used to drive innovation and transformation.
9. Data governance must be established to ensure data is managed effectively and securely.
10. Finally, a data-driven organization needs to be agile and adaptable, able to respond quickly to changing circumstances.

How to use data differentiators to improve your marketing strategy?

Data differentiators can be a powerful tool in improving your marketing strategy. By highlighting the unique characteristics of your data, you can differentiate yourself from your competitors and attract new customers. For example, if your data is particularly accurate or comprehensive, you can use that as a selling point in your marketing materials. You can also use your data differentiators to inform your marketing decisions, such as which channels to focus on or which messaging resonates best with your target audience. By leveraging your data differentiators, you can gain a competitive edge and drive business growth.

One way to use data differentiators is to showcase them in your marketing materials. For example, if your data is more up-to-date than your competitors, you can highlight that fact in your advertising. This can be particularly effective if you are targeting customers who need the most current information, such as those in the healthcare or financial industries. Another way to use data differentiators is to inform your marketing decisions. For example, if your data shows that your target audience is most active on social media, you can focus your marketing efforts on those channels. By using your data to inform your marketing decisions, you can ensure that your messaging is resonating with your target audience and driving business growth. Overall, data differentiators can be a powerful tool in improving your marketing strategy and gaining a competitive edge in your industry.

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Key Components

A comprehensive data strategy is essential for modern businesses to manage, secure, and use data effectively. A successful data strategy should include six key components: data, tools, people, processes, documentation and auditing, and culture.

1. The first component is data, which involves identifying what data a business has, where it is stored, and who can use it.
2. The second component is tools, which include data catalogs, data management tools, and data visualization tools.
3. The third component is people, which involves identifying the roles and responsibilities of individuals who manage and use data.
4. The fourth component is processing, which includes data integration, labeling, storage, security, sharing, and selling.
5. The fifth component is documentation and auditing, which involves documenting data processes and auditing data quality.
6. The sixth component is culture, which involves creating a data-driven culture that values data as a strategic asset.

Developing a data strategy begins with identifying the business's goals and evaluating the problems within the data environment. The data strategy should be comprehensive and involve broad involvement and support to ensure data is managed well. Metadata can be used to identify and manage unstructured data, and implementing and maintaining a data security program is critical to developing a successful data strategy. A data-driven enterprise requires having a cohesive, comprehensive data strategy that applies across the organization and encompasses technology, culture, governance, cybersecurity, data privacy, skills, and other components. A data strategy allows companies to solve data management challenges by making data accessible and shared in a way that meets business needs and supports both IT teams and business users.

How to leverage data differentiators to gain a competitive advantage?

To leverage data differentiators effectively, start by identifying what sets your data apart from your competitors. This could be anything from the accuracy of your data to the breadth of your coverage. Once you have identified your data differentiators, use them to inform your marketing strategy. For example, if your data is particularly accurate, you could focus on targeting customers who value accuracy and precision. You could also use your data differentiators to create targeted messaging that speaks directly to your audience's needs and interests. By leveraging your data differentiators, you can differentiate yourself from your competitors and attract new customers, ultimately driving business growth.

One way to leverage data differentiators is to use them to inform your product development strategy. For example, if your data is particularly comprehensive, you could use it to develop new products or services that address gaps in the market. You could also use your data to identify new market opportunities and target customers who are underserved by your competitors. By leveraging your data differentiators in this way, you can create a competitive advantage that sets you apart from your competitors and drives growth for your business. Ultimately, the key to leveraging data differentiators is to understand what sets your data apart and use it to inform your marketing and product development strategies.

How to measure the success of your data differentiators?

Measuring the success of your data differentiators is crucial to understanding their impact on your business. One way to do this is to track metrics such as customer acquisition, retention, and engagement rates. If you notice an increase in these metrics after implementing your data differentiators, it's a good sign that they are resonating with your audience. You can also conduct surveys or focus groups to gather feedback directly from your customers about what they value most about your data. This information can help you refine your data differentiators and continue to improve your marketing strategy. Remember, the key to success with data differentiators is to constantly monitor and adapt your approach based on the needs and preferences of your target audience.

Another way to measure the success of your data differentiators is to track their impact on your bottom line. Look at metrics such as revenue, profit margins, and customer lifetime value to see if your data differentiators are driving business growth. You can also analyze your sales data to see if there are any patterns or trends that can be attributed to your data differentiators. For example, if you offer personalized product recommendations based on customer data, you may see an increase in sales of those recommended products.

Conclusion

A test-and-learn mindset is essential when constructing a data architecture to drive innovation. Experimentation with different components and concepts can help identify the right level of architectural sophistication. Collaboration between data stewards, engineers, and modelers is also crucial. Establishing data "tribes" can help achieve end-to-end data management. Flexibility is another essential aspect of modern data architecture. A modern data architecture should proactively be designed with scalability and elasticity, anticipating complex data needs. It should be able to accommodate new solutions that come on the market and change with the tools and platforms put into place to handle data.

Finally, data privacy and access governance are significant challenges in modern data platforms. Managing privacy controls and access governance across the entire stack is crucial. A modern metadata solution that is fast, flexible, and scalable is also necessary.

In summary, building a modern data architecture with a data differentiator in mind requires a focus on data quality, experimentation, collaboration, flexibility, and data governance. It should be designed proactively with scalability and elasticity in mind and be able to accommodate new solutions that come on the market. Managing privacy controls and access governance across the entire stack is also crucial.

Our data experts here at ExterNetworks can help you navigate, let's talk.