3/9/2024 0 Comments Cio 90 day plan templateExternal regulators demand certifications and scrutiny to ensure compliance with standards. The organization itself has hurdles to overcome: diversification of customer base, changing business priorities, and infrastructure and scalability concerns. Expanding these data sources and creating channels where data can be translated into actionable insights is a fundamental part of a data-driven culture. Organizations invest heavily in research to identify who their customers are, what their needs are, and how they differ by region and culture. Bear in mind that the ultimate stakeholder is the customer. Successful data leaders hit the ground to build a data-driven culture by identifying stakeholder needs and responding to them with data-driven decisions. Executives are reshaping their organizations to become more data-oriented, but the vast majority still point to culture as the greatest challenge in becoming a data-driven organization. How a strategy is defined is up to leadership, but how well it is executed is often a function of company culture. With the global economy in a period of stagflation (stagnation and inflation), the ability of business leaders to extract value from data could be a deciding factor in how well a company weathers the storm. This is important not only to promote growth and accelerate innovation but to build resilience during periods of austerity. Today’s data leaders are seeing these AI trends play out in real-time and are adapting their enterprises to take advantage of what AI can offer for data-driven decisions and strategies. The same distinctions exist for generative versus predictive AI. Additionally, not all MLOps stacks are created equal - AI working with unstructured data requires different pipelines than those working with structured data. ![]() This also holds true if they want to improve model training, deployment, and monitoring. As the role of AI grows within an organization, data leaders will need a more robust foundational toolset if they want to identify which features of their data provide signal (a process known as feature engineering). ![]() Similarly, powerful AI needs DevOps and MLOps tooling to support it. A full-stack approach to ETL (extracting, transforming and loading) data, creating data lakes and lakehouses and de-siloing data architectures can give companies a real competitive edge. ![]() Companies that can invest in their data infrastructure will be able to more successfully capitalize on emerging AI techniques. Read more: 8 Tech Investors Share Predictions for 2023Ī sophisticated AI model requires a modern data stack. Techniques such as generative AI - capable of creating rather than simply predicting - has a fast-growing number of use cases. While most companies expect to adopt AI technologies, many data leaders are looking even further ahead to more advanced forms of artificial intelligence. The data leader is aware of the importance of aligning data and AI strategies to better serve the organization’s overall mission.Ī 2022 survey revealed that over half of the data executives surveyed expect AI to become “critical” to multiple facets of their business by 2025. The key is to recognize where emerging trends and company needs intersect, and then create a roadmap to fulfill short- and long-term needs with technology that provides a competitive advantage. Young organizations often struggle to create meaningful data strategies. But while the role of the data leader is still often shared, a data leader’s acumen and approach for data-driven decisions can be adopted by many leaders to have a significant impact on revenue and growth.Įvery enterprise and business case is unique, but today’s data leaders have established a set of best practices to chart the digital pathway to profitability: This is especially the case at early-stage companies too small to have this position. In the current resource-stretched climate, the CTO, CIO, or CxO often wears the data leader’s hat. Regardless of title, CxOs of young and established organizations realize their ability to make excellent data-driven decisions is a must to achieve the company’s business goals. ![]() For existing data leaders, it’s prudent to take a step back at least once a year, think about the business with fresh eyes and ask: What would a new data leader try to address in the next 90 days? For newly hired data leaders, the first 90 days are crucial.
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