How to use real-time data to make better, faster decisions

With so much diverse data available, why do so many companies still struggle to embrace the real-time, data-driven decision-making they need to be more agile? One thing is clear: The challenge isn’t solved by technology alone.

“You can’t buy transformation,” says Tom Godden, Principal Technical Evangelist with the Enterprise Strategy team at AWS. “Real change doesn’t come just from new technology—it comes from rethinking your processes, which are enabled by the technology.”

Godden offers three tips to help organizations break down data silos, improve data quality, and overcome other longstanding data challenges to foster a culture of decision-making that drives business agility.

1. Build the foundation for managing data in real-time.

A modern data strategy must emphasize data quality at the source of origin, rather than traditional methods of cleansing and normalizing at the point of consumption. Make sure you have the proper infrastructure, tools, and services in place to capture data from a variety of sources, ensure the quality of the data you’re collecting, and manage it securely, end to end.

The technical underpinnings of a modern data strategy include cloud-based databases, data lakes, and data warehouses; artificial intelligence and machine learning (AI/ML) tools; and analytics. The infrastructure must be supported by a comprehensive plan to manage, access, analyze, and protect data across its entire lifecycle, with fully automated processes and robust integration to make data actionable across the organization.

“It may sound obvious, but if you do not build the right processes to capture all the data, you can’t act on the data,” says Godden.

2. Don’t just democratize data – democratize the decisions based on that data.

Investing in the data management infrastructure, tools, and processes necessary to capture data in real-time through a variety of data feeds and devices is just the first step. If you aren’t simultaneously creating a culture that allows people to act on data, you’re just creating frustration.

To that end, avoid “reporting ghost towns” that require people to stop what they’re doing and access a different tool for insights. Instead, build analytics capabilities directly into their workflows, with context, so they can easily apply the insights to their daily activities.

3. Provide the types of guardrails that spur innovation instead of inhibiting it.

Building automated processes for metadata, including information on data lineage and shelf life, builds confidence in the data. By storing data in its raw or native format, you can apply access policies to individuals without having to modify the data.

This approach ensures more flexibility for how people can use the data they need without compromising the fidelity of the data itself. A data lake can serve as a foundational element of a data unification strategy, providing a single source of truth with supporting policies for real-time provisioning based on permissions.

Agile decision making: How three companies are benefiting from a modern data strategy

Organizations are already capturing the benefits of real-time access to data based on roles and permissions. Here are three examples:

Swimming Australia, the nation’s top governing body for swimming, has long been at the forefront of science. Now, it’s using data to analyze race performance and create bespoke training programs for individual athletes. A data lake unified athlete statistics and metrics in a single location, and AI/ML tools are helping the team tailor training programs and track competitors. Analysts and coaches capture real-time physiological data during training sessions and combine that information with race analysis to determine how to evolve training efforts for individual swimmers. Coaches and athletes can easily track progress in real time from their phones via cloud-based dashboards. Today, with its modern data architecture, the national team can create benchmarking reports in minutes, an innovation that helped make the Australians the most successful relay team in the 2020 Tokyo Olympic games.

Coca-Cola Andina, which produces and distributes products licensed by The Coca-Cola Company within South America, needed a solution to collect all relevant information on the company, its customers, logistics, coverage, and assets within a single accurate source. The answer was a cloud-based data lake, which allowed the company to implement new products and services to customize the different value propositions for its more than 260,000 customers. With all the resources and functionality that the data lake enables, Coca-Cola Andina ensures its partners and customers have access to reliable information for making strategic decisions for the business. Coca-Cola Andina ingested more than 95% of the data from its different areas of interest, which allows it to build excellence reports in just a few minutes and implement advanced analytics. The cloud infrastructure increased productivity of the analysis team by 80%.

Vyaire, a global medical company, needed a way to help its 4,000 employees make better, data-based decisions utilizing both first- and-third-party data. Adopting AWS Data Exchange to find, subscribe to, and use third-party data has made it easier to incorporate data sources into the company’s own data ecosystem, resulting in quicker insights to help teams focus on getting results, not administration. Easy access to third-party data via the AWS Data Exchange catalog has encouraged more experimentation and innovation, giving Vyaire’s leadership confidence that it can meet the changing market for respiratory care products and direct investment in the right area to improve its product portfolio.

Too many organizations continue to be held back from using data effectively to drive all aspects of their business. A modern data strategy will empower teams and individuals, regardless of role or organizational unit, to analyze and use data to make better, faster decisions – enabling the sustainable advantage that comes from business agility.

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