It’s one thing to manage your data; it’s another to gather actionable insights and derive value from your data sets to help your organization flourish. Optimizing data value can help companies deepen their knowledge about their customers, highlight market trends and gaps, and improve customer service throughout the organization.
Data leaders play a critical role in organizations when it comes to maximizing data value: Data is often considered one of the most valuable assets for businesses in the digital age, and its effective management and utilization can have a profound impact on an organization's success.
However, turning data, whether structured or unstructured, into business value is easier said than done.
Ongoing and constant business and technology disruption is putting increased pressure on all business and technology leaders to demonstrate the value of their initiatives quicker than ever before. Additionally, most data and analytics leaders struggle to articulate the value they create for the organization in business terms.
This blog post will discuss the top tips for increasing and communicating the value organizations can create from data and why value optimization has been identified as a trending topic.
The field of data and analytics is increasingly intertwined with business lines to help provide significant benefits to business domains. However, alignment and collaboration with data and analytics teams are needed to ensure data- and analytics-enabled change, organizational agility to respond to change, and connected decision-making. Value optimization from an organization’s data, analytics, and AI portfolio requires an integrated set of value engineering activities and competencies.
Building a value story identifies and articulates stakeholder impact on processes, activities, and decisions from data and analytics initiatives in business terms.
This is needed to get buy-in from business executives and establish how results will be measured across the organization. Getting executive sponsorship also provides the foundational value assumptions needed to prioritize investments in portfolio optimization, data and analytics strategy, and operating model development.
Value stream analysis and design thinking can help identify potential high-value, cross-enterprise options and decisions. Measuring outcomes using outcome-driven metrics that link technical outcomes to business outcomes and adjusting the portfolio as needed ensures the organization realizes the expected value.
Data leaders must show a clear link between data and analytics initiatives and the business outcome improvements to processes, activities, and decisions tied to the organization’s mission-critical priorities. This aligning of data strategy with business strategy ensures that data is not treated as a separate, isolated function but as a valuable asset that is integral to the organization’s success. It helps in setting priorities, resource allocation, and leveraging data to make informed decisions and gain a competitive edge.
It’s important to ensure that the overall organizational data strategy aligns with the business strategy by identifying the specific data needs and requirements to achieve the business objectives. Data leaders should work with business stakeholders to identify data-driven opportunities and create data-driven solutions that support their goals.
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Investments in data and analytics initiatives can yield short-term financial returns in revenue growth, productivity, and cost and risk reduction, but their more significant impact is often on leading indicators of financial outcomes and future value. These financial-influencing benefits can include an increase in the organization’s:
A comprehensive approach to value identification, communication, and option selection is needed to optimize value realization. Discovering and aligning to value streams to deliver data and analytics initiatives maximizes desired business outcomes while efficiently utilizing scarce resources and reducing excess system waste.
Data leaders play a pivotal role in helping organizations unlock the full potential of their data. However, this often requires a strategic approach to data collection, analysis, and utilization, and data leaders are instrumental in driving these efforts within their organizations.
The following steps are crucial for getting started maximizing and optimizing the value data can provide to an organization:
Generating value from data sets is at the top of a general list of priorities identified by data professionals around the world. This value generation and optimization is essential for helping prove the importance of various data initiatives and connecting these findings to the entire company, not just the IT teams.
In the future, value optimization will continue to be a trending topic in the field of big data, and it’s important that CDOs, CDAOs, and data professionals begin to harness the full potential of their data sets to bring value to the entire organization.
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Discover Infonomics, the process of attributing economic significance to information and data and how it can help organizations realize the value customers find in their data. Read more to uncover how to provide best practices to implement data management techniques to help customers navigate their products and services.
