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May 20, 2024
Crucial Steps for a Successful D&A Strategy According to Gartner
In today’s world, a successful data and analytics (D&A) strategy has become crucial for achieving and sustaining business goals. With the rapid advancement of generative artificial intelligence (AI), it’s essential to clearly articulate how data can deliver tangible value to the enterprise and its strategy.
A Data-Driven Vision
According to Gartner, their Data and Analytics Strategy and Operating Model (DASOM) framework highlights key elements for a successful D&A strategy. This model includes a data-driven vision, understanding capabilities and deficits, establishing a delivery model, and achieving stakeholder outcomes.
Defining a Clear Vision and Strategy
The first step is to create a vision and strategy for D&A and AI. It’s essential to understand key business priorities and how data, analytics, and AI assets can generate value. Positioning data as a key enterprise asset and demonstrating its potential for digital transformation is crucial.
Actions to take:
- Research how to craft a modern, actionable D&A strategy that delivers business outcomes.
- Engage in phone consultations to draft an action plan and agree on engagement steps.
- Optimize and select a portfolio of D&A and AI investments by assessing risks, opportunities, and return on investment (ROAR).
Establishing an Operating Framework for a successful D&A Strategy
Next, it is necessary to establish a balanced operating framework. This involves cultivating data and AI literacy among stakeholders, developing data science and advanced analytics capabilities, and leveraging innovations like AI and machine learning to create and sustain business value.
Actions to take:
- Discuss the operating model with experts.
- Attend conferences and join peer communities to exchange methods and tools.
Cultivating Culture and Establishing Governance
The third step is to cultivate a data-driven culture and establish adaptive governance. This includes assessing current data and AI literacy levels, designing training programs, and identifying project opportunities to develop staff.
Actions to take:
- Implement governance initiatives with structured roles, processes, and practices driven by outcomes.
- Identify trends, assess their impact on the enterprise, and harness their value to accelerate initiatives like AI legislation and ethics.
Managing D&A Value
Once the foundations are laid, it is crucial to demonstrate the tangible value of D&A investments and products. Integrating D&A and AI capabilities of digital business platforms and ecosystems to support enterprise growth, speed, and agility is essential.
Actions to take:
- Create a narrative linking D&A and AI initiatives to business outcomes and goals.
- Overcome critical roadblocks by delivering exceptional business outcomes.
Case Study: AstraZeneca
AstraZeneca aimed to transform the discovery and development of new medicines through data, digital, and AI. Gartner collaborated with AstraZeneca to formulate its Data and AI Ethics Vision, guiding principles, and governance framework. This enabled scientists to access analytics-ready data, uncover new insights, and accelerate the delivery of new medicines.
Mission accomplished:
- Unprecedented access to analytics-ready data for scientists.
- Acceleration of the discovery and development of new medicines.
- Faster delivery of potential new medicines to patients.
A successful D&A strategy is essential for transforming businesses and achieving tangible results. By following the key steps outlined by Gartner, companies can create a clear vision, establish a balanced operating framework, cultivate a data-driven culture, manage the value of D&A investments, and continuously refine their strategies in response to emerging trends.
For more insights on D&A strategies and expert advice, visit the [Gartner Data & Analytics page](https://www.gartner.com/en/data-analytics).
