Is Your Data Delivering Actionable Insights?
Data is the lifeblood of a business. The data you collect and use can seriously impact performance. Good data is necessary to produce insights that propel operational excellence, successful change initiatives, effective decision-making, and strategic execution. Generating actionable insights starts with having the right data and processing it to guide management at all levels of your organization.
Many organizations collect huge amounts of data, but they aren’t able to translate them into business insights that support strategy, governance, change management, or operations management. This article offers five things you can do to produce actionable insights.
Learn what people need to know to govern, manage, and deliver effectively.
Develop a business-focused data strategy.
Use data governance to implement data standards and controls.
Integrate your data insight community.
Enable people to explore curated data independently.
Learn what people need to know to govern, manage, and deliver effectively.
Data collection efforts should be based upon prioritized information needs. Put another way, your data collection efforts should be prioritized to answer your most important questions. The questions you need to answer point you toward the kinds of analysis you need to perform and supporting data you need to collect. Data collection and analysis can be expensive. Prioritizing data collection and analysis efforts ensures that you invest where you can get the most bang for the buck.
Different stakeholders are likely to have different questions. Operations staff need to know the volume of work they need to perform, their performance indicators, and how they are doing relative to their targets. Managers will have questions around both individual and group performance as well as cost, quality, and progress measures. Governing individuals need further aggregation of performance across programs, business units, or the entire organization. In addition they need measures to contrast with decision criteria, so they know what steps to take.
2. Develop a business-focused data strategy.
A good strategy aligns organizational priorities and effort around high-value objectives and measurable results. A data strategy can be a powerful resource to focus collaboration between business and technology stakeholders. Developing a data strategy can be a challenging endeavor, though. It will be important to communicate effectively across stakeholder communities to generate awareness of, interest in, and commitment to data strategy development. Without proper representation in the strategic planning efforts, teams may open themselves to executive-level opposition late in the planning process. It is important to engage people who have the authority to define strategy and the influence to develop and sustain commitment.
Strategies to consider:
Harnessing data as a strategic asset. This strategy frames the business commitment to using data strategically. Business units will be challenged to consider and to incorporate strategic outcomes based upon their investment in data and its value delivery to the business and to customers.
Developing a data-savvy workforce. People need to understand the data they have and how to interpret the data. Data literacy has been a foundational element of the federal data strategy, but the need for data literacy isn’t limited to government organizations. Every organization should understand what data they collect, generate, process, store, and use. When it’s time to answer key strategic, management, and operational questions, people need to know what data to use and how to interpret it.
Curate data about and for customers. All too often, organizations focus upon internal measures of execution and outcomes. In recent years, the customer experience movement has drawn attention to the value of customer priorities, preferences, and sentiment. When organizations focus on customer success through high quality customer experiences, they generate higher customer satisfaction, improved trust, and more value.
Make data accessible through application programming interfaces (APIs). Making data available on-demand through digital interfaces empowers people to explore data and to drive innovation. Furthermore, open APIs serve as gateways through which organizations can exchange information across applications and to federate services that drive improved service experiences. Expanding API use and incorporating APIs within federal agency IT strategies is an element of Public Law 115-435, Foundations for Evidence-Based Policymaking Act of 2018, and is incorporated within the federal data strategy. Agencies are required to advance API access and to demonstrate the value open data is providing to government and non-government consumers.
3. Use data governance to implement data standards and controls.
A data governance team can serve as a central authority for the framing of data policies, data rights, and communication across stakeholder communities. The data governance team should consist of business, security, privacy, records management, and technology representatives with sufficient authority to draft and propose data policies. Individuals should understand what data they create, use, manage, and share. Using their knowledge, they can collectively frame consensus-based data policies.
Organizations that maintain a comprehensive data architecture and data catalog will be prepared to support effective data governance. Usually managed within an enterprise architecture program or chief data officer organization, the data team catalogs what data exists within the enterprise and maps data relationships with data sources, business processes, and supporting technologies, such as applications and technology infrastructure.
A data architecture is a highly valuable resource for those interested in how and where data is used. It also provides insight into information technology security requirements driven by the sensitivity of data processed. Data governance teams that leverage an enterprise data architecture’s catalogs and visual data mappings can rationalize, manage, and control standards that protect information while advancing data-driven strategies.
4. Integrate your data insight community.
People act on information that they trust. Fostering trust across your data community begins with recognizing and integrating stakeholder roles, perspectives, and abilities. There are many roles involved with insight generation. Each provides valuable inputs within the information lifecycle. Aligning and integrating the contributions of these roles can help you to deliver trustworthy insights:
Consumer. Delivering data insights is most effective when you know who your information consumers are and what questions they want answered. Customer experience practices, such as capturing the voice of the customer, provide useful ways to learn about what people want and what they value.
Data Steward. Data stewards — the primary creators and users of the data — support the needs of data consumers by ensuring proper and consistent data management and use within the enterprise. Consistent and attentive management are hallmarks for trustworthy – and usable – data. Through the creation of policies, procedures, education, and controls, data stewards ensure that information is collected, interpreted, and communicated consistently using best practices.
Data Analyst. Data on its own is not an insight. Through data analysis and data science, data can be organized, combined, processed, and interpreted to produce information and insights. The analyst prepares data, applied algorithms, and develops visualizations to surface facts, patterns, and associations of interest. Analysts work with technologists to use databases, analytical tools, visualization tools that speed data processing.
Communicator. Information and insights, alone, are seldom enough to trigger action. People are often motivated by the presentation of information to highlight the significance of the data and link the insights to stakeholder interests. Communication experts provide the skills to tell a motivating story – one that drives action from insights.
Data Architect. Getting a handle on data enterprise-wide is a big task. The role of the data architect is to identify data, categorize it, and rationalize the use and flow of data. The data categorizations and big picture views provide people with clues where data comes from, where it goes, who uses it, and how it should be protected.
Technologist. Information technology is the foundation for modern strategic data use. DAta consumers rely upon technology to collect, process, share, and explore information. Technologists select, deploy, and manage information technology that enables people to access and use data – and develop insights – efficiently and consistently. Their involvement is essential to strategic execution in modern business environments.
5. Enable people to explore curated data independently.
When people are able to access data they can generate new discoveries and value through their unique points of view and by combining data with other data sets. Making government data open and discoverable was intended to enable these very same sorts of discoveries and value generation. As mentioned earlier, it’s important to ensure that the meaning and context of provided data is available when shared internally or externally.
Conclusion.
There is no denying that generating data-driven insights takes some investment. Here, I presented five smart ways to invest in insight creation. Start with what people need to know. Create a strategy to establish a vision and set direction. Sets standards and necessary oversight through data governance. Get communities working together that can collect, analyze, and communicate information. Finally, empower people to use data and generate their own insights.
Data-powered technologies are continuously introducing compelling new capabilities, be it through data lakes, analytics dashboards, or artificial intelligence. Establishing the right foundation ensures that you can harness these tools to surface insights that matter.
Peter Wilson is the Founder of Enterprise Insight Solutions. He has more than 30 years of technology and data design, development, delivery, and management experience. Contact us to learn more about how Enterprise Insight Solutions can help you generate insights that matter.