The Data Value Chain

The data value chain is a conceptual framework utilized in data science that describes where data sources are identified, ingested, processed, stored, analyzed and finally utilized by enterprises to add value. Volumes of information are spread across an organization. The significance of this value chain is in discovering those areas of the business that require additional intelligence and then creating a process to transform the raw data housed across the organization into usable insights. By intersecting data with analytics, this point in time data transforms into powerful and actionable intelligence that has the ability to unify disparate business practices and empower decision makers.

The value chain we described above can be applied to all types of data. The value extracted from the identified data is applied from the application-centric view, primarily focused on functional units that fulfill well-defined business purposes.

Primary Data Characteristics

As we review the data via the data chain discussed above, three primary attributes are contemplated—Quality, Usability, and Intelligence. Each feature is multi-dimensional in character and includes distinct but related facets, each critical to users and decision-makers.

Quality : This attribute focuses on providing an accurate data scope that provides enough information to review for the topic of interest. It also ensures timely receipt of the data to complete required actions and decisions.

: This attribute focuses on providing an accurate data scope that provides enough information to review for the topic of interest. It also ensures timely receipt of the data to complete required actions and decisions. Usability : The extent to which data is inclusively presented. It includes the ease with which data can be processed and the degree of data consistency across multiple sources.

: The extent to which data is inclusively presented. It includes the ease with which data can be processed and the degree of data consistency across multiple sources. Intelligence: This attribute includes identifying demand patterns, different trending models, and recommendations for better decisions.

Utilizing Data for Improved Intelligence & Business Value

Data Analytics eliminates the need to be a tarot card reader by providing proven statistics and insights to keep your enterprise ahead in the competition. Here are a few areas where data science can make a significant impact:

Improved customer segmentation : Data is critical to understanding who your customers are and how to drive increased sales and higher customer satisfaction. Access to data can drive decision making around target markets of focus (geographies, cross and upselling, new ventures) as well as provide the foundation to develop additional strategies and optimize promotions to reach your optimal consumer.

: Data is critical to understanding who your customers are and how to drive increased sales and higher customer satisfaction. Access to data can drive decision making around target markets of focus (geographies, cross and upselling, new ventures) as well as provide the foundation to develop additional strategies and optimize promotions to reach your optimal consumer. Optimized supply chain : Data can help you understand which products or services are performing better in the market and which aren’t meeting expectations. As an example, having access to data that shows a particular product is in high demand during a specific time of the year, provides the foresight to increase inventory just in time to meet this rising demand. Data, when wielded at the right time, is the path to significant profits.

: Data can help you understand which products or services are performing better in the market and which aren’t meeting expectations. As an example, having access to data that shows a particular product is in high demand during a specific time of the year, provides the foresight to increase inventory just in time to meet this rising demand. Data, when wielded at the right time, is the path to significant profits. Enhanced market knowledge for better positioning : A thorough understanding of the market, competitors, and recent trends are critical in devising profitable go-to-market strategies. This data can ensure your enterprise initiatives are aligned with the market and help mitigate any risk through early identification. For example, market data on performance management practices can be utilized by an enterprise to help convince investors and key stakeholders you are well positioned for continued financing of your future operations/business. By keeping a pulse on your ecosystem, you can better ensure your enterprise remains a top player.

: A thorough understanding of the market, competitors, and recent trends are critical in devising profitable go-to-market strategies. This data can ensure your enterprise initiatives are aligned with the market and help mitigate any risk through early identification. For example, market data on performance management practices can be utilized by an enterprise to help convince investors and key stakeholders you are well positioned for continued financing of your future operations/business. By keeping a pulse on your ecosystem, you can better ensure your enterprise remains a top player. Optimized internal processes for reduced costs : Data analytics can be utilized to improve existing business processes and operations across the organization in customer acquisition, customer retention, operations, manufacturing, application/product development and more providing far-reaching efficiencies and cost savings.

: Data analytics can be utilized to improve existing business processes and operations across the organization in customer acquisition, customer retention, operations, manufacturing, application/product development and more providing far-reaching efficiencies and cost savings. New business models: Data insights can provide visibility to new avenues for business growth/expansion – via new products, services, or business models. Data can empower enterprises to better understand customer needs and as a result, build applications and services better customized to meet the demands of the target audience.

Conclusion

Data insights are an essential ingredient for businesses to pivot, compete and grow. Combining effective data with the right strategy will provide operational impact and financial rewards.

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