In this increasingly complex and interdependent world, challenges arising from global competition is being felt by almost every organization across every industry. These challenges are further accelerated and intensified by the rapid development of big data and analytics. Organizations, and their top executives, who aspire to compete in this data-driven world must generate the most value, and insights, from the massive amounts of data they are collecting each day.
Given the sheer volume of data, the complexity of methodologies, and the evolving face of software technology, it is extraordinarily difficult for organizations to rely on data-driven insights derived from various analytical techniques. Furthermore, it is equally difficult for executives to be supportive of the broader changes needed in the organization to obtain the full rewards from applying advanced analytics to their day-to-day operations and strategies.
While it is understandable that advanced analytics, shrouded in the intricacies of software, mathematics, statistics and analysis, can deter executives from adopting a data-driven culture, it has been documented that top performers are more likely to consider analytics as a key differentiator. These top performers want their business run on data-driven decisions. They want scenarios and simulations that provide immediate guidance on the best actions to take when uncertainties and threats emerge. They want to understand optimal solutions based on sophisticated business parameters and new information as they emerge. They want to take actions quickly and precisely. Therefore, executives must ensure the analytics readiness of their organizations.
Here, we describe three important steps top executives can take to make analytics pay off, and illustrate how the Composable self-service analytics platform can be leveraged to achieve analytics readiness. Whether it is identifying the most profitable marketing channel, the best customer experience, the highest performing investment portfolio or the most efficient business processes, organizations that embrace and adopt these approaches and improve their analytics readiness will be able to become extremely competitive at a global scale.
1. Adopt a data-driven mindset
It is always difficult to bring about change, let alone introduce a new culture. However, analytics readiness requires just that: a data-driven culture embraced by each and every employee in the organization. Decisions based on intuition and experiences need to be pushed aside and replaced by decisions based on an adherence to the scientific method, where hypotheses are continuously generated and tested based on data analysis.
The Composable platform allows employees, across all departments regardless of technical skill level, to become effective data analysts. This fundamentally encourages the collaborative use of data to drive business decisions. Composable’s visual designer is accessible by all, given the platforms modern, intuitive, and easy to use approach for authoring complex dataflows. Dataflow applications and results dashboards can be shared across the organization enabling required collaboration within and across the various lines of business. Finally, as a native cloud app, Composable can be scaled up or down as needed, with no desktop installation required, further lowering the barrier of entry across the enterprise.
2. Start with questions, not data
Advanced data analytics is a means to an end. Ultimately, actionable insights, rather than pristine data sets, beautiful visualizations, or cutting-edge algorithms, are desired. Instead of spending time cleansing data ad nauseam, it is more beneficial to work iteratively from an initial set of questions, at each step inspecting the data and refining the questions, until actionable insights are derived.
Composable is a rapid prototyping platform allowing just-in-time analytics. Users can rapidly create dataflow applications to query the data and refine their methods, exploring the intermediary results at each step along the way. Collaboration is encouraged, allowing for users to work together on dataflow applications and review the results.
3. Use tools with built-in services
Tools with built-in services for analytics, such as trend analysis, forecasting and standardized reporting, helps democratize data analytics. In addition, built-in services for data visualizations and dashboards are making results more understandable and actionable.
Composable DataOps Platform, a full-stack data and analytics platform with built-in services for data orchestration, automation and analytics, accelerates data engineering, preparation and analysis. Built with a composable architecture that enables abstraction and integration of any software or analytical approach, Composable serves as a coherent analytics ecosystem for business users that want to architect data intelligence solutions that leverage disparate data sources, live feeds, and event data regardless of the amount, format or structure of the data.
