07 Feb The Importance of a Data & AI Analytics Strategy
What is a Data & AI Analytics Strategy?
Want to learn how a data and AI analytics strategy could help your business? At InfoCentric, we’ve been delivering strategy and advisory services for over 13 years, partnering with major banks, retailers, insurers, government, and utilities to develop pragmatic, AI-enabled data strategies.
A data and AI analytics strategy helps businesses unlock the full potential of their data by integrating AI-driven solutions like machine learning and predictive analytics. This strategy creates a target environment and roadmap to achieve business outcomes, ensuring AI capabilities drive smarter decisions and greater operational efficiencies. Collaboration with key business and technology stakeholders ensures alignment with business goals, IT strategy, and AI governance.
Why is a Data Analytics Strategy Important?
An effective strategy helps our clients set clear, goal-oriented objectives when implementing data and AI analytics solutions. Incorporating AI allows organisations to enhance forecasting, automate decision-making, and optimise operations.
Our approach provides a practical target state, including AI-powered analytics, automation capabilities, and the required infrastructure. We also articulate pragmatic and phased initiatives in the roadmap to ensure smooth AI adoption whilst managing risks and maximising business value.
The InfoCentric Data Analytics Strategy
Our strategy helps you plan the necessary steps to meet your business objectives. While every business has unique needs, our proven methodology ensures an efficient, AI-integrated approach that delivers measurable results.
Business vision
We start by discussing your strategic vision and objectives. Through workshops, we identify business-led use cases and refine these into data and AI capabilities, aligning the strategy with your goals for data-driven and AI-powered decision-making.
Environmental analysis & assessment
We explore different aspects of your organisation by:
- Conducting interviews and workshops with key stakeholders
- Gathering intelligence on your business and technical requirements
- Using our data analytics maturity models to assess your current data, analytics, and AI capabilities.
This helps us identify opportunities for enhancing your data environment with AI solutions like machine learning and predictive analytics.
Your ideal future
We combine insights from the analysis and your strategic vision to design a realistic future state for your organisation, integrating AI-driven capabilities such as scalable data architecture optimised for AI workloads, AI-powered automation, and the necessary skills for AI innovation.
Strategic recommendations
We provide tailored strategies to help you transition to an AI-powered data environment. These include AI platforms, cloud solutions, and governance frameworks that ensure ethical AI use.
Your roadmap to success
After selecting a strategy, we create a clear, practical roadmap for implementing AI and analytics solutions. This includes timelines, technology enhancements, and AI model lifecycle management to ensure ongoing performance and compliance.
Investment and Cost Analysis
We offer phased cost estimates for implementing and operating your AI-powered data analytics environment.
A compelling benefits case
Through proven and refined methods, we quantify the potential value of your data and AI assets, demonstrating the impact of AI-driven automation, predictive analytics, and real-time decision-making. This helps ensure your investment in AI technologies delivers significant value.
The starting point for unlocking the power of data and AI analytics is developing a clear strategy. By integrating AI into your data analytics approach, you can drive automation, smarter decisions, and transformative business outcomes.
Learn More:
Your Guide to Data Modernisation Strategy
5 Things That Are Holding You Back From Being A “Data Driven Organisation”
Our Information Management Maturity Assessment: The Basics