Giveaway: https://www.tradepub.com/free/w_wile941/
Download: w_wile941.pdf
Offered Free by: Wiley
What if you could future-proof your business strategy using the same AI and analytics frameworks that top consulting firms charge thousands to teach? Strategic Analytics: Towards AI-based Strategy Planning, 2nd Edition is a comprehensive digital resource normally priced at $100, and it is available at absolutely no cost for a limited time. Whether you are a seasoned strategist or just beginning to explore data-driven decision making, this eBook delivers a rare blend of academic rigor and real-world applicability that is hard to find in a single volume.
Key features
- AI-driven strategic frameworks: Explore modern approaches that integrate machine learning and predictive analytics directly into classical strategy models.
- Updated second edition content: Benefit from revised chapters that reflect the latest developments in artificial intelligence and its growing role in corporate planning.
- Actionable planning tools: Move beyond theory with structured templates and step-by-step methodologies you can apply immediately in your organization.
- Cross-industry applicability: The frameworks are designed to work across sectors including finance, healthcare, retail, and technology.
- Data interpretation guidance: Learn how to read, clean, and translate complex datasets into strategic decisions that stakeholders can understand and act on.
- Competitive positioning insights: Discover how AI can sharpen your understanding of market dynamics and rival behavior to give your business a measurable edge.
- Accessible language for mixed audiences: Written to serve both quantitative analysts and business leaders who may not have a deep technical background.
Who is it for
This eBook is a strong fit for a wide range of professionals and learners. Business strategists and consultants will find the AI frameworks immediately useful for client engagements and internal planning cycles. Data analysts and business intelligence professionals looking to elevate their role from reporting to strategic advising will gain concrete language and models to bridge that gap. MBA students and academic researchers benefit from the structured, citation-worthy approach to combining analytics with strategy theory. C-suite executives and senior managers who want a working understanding of how AI tools inform long-range planning, without needing a data science degree, will appreciate the accessible tone and practical focus.
How it compares
- Competing on Analytics by Thomas Davenport and Jeanne Harris: This well-known business book focuses on how organizations build analytical cultures and competitive advantage through data, but it predates the current AI wave and does not address machine learning-based strategy tools in depth.
- AI Superpowers by Kai-Fu Lee: A widely read macro-level look at AI competition between the US and China, it is better suited to policy and big-picture thinking than to hands-on strategy planning for individual organizations.
- Prediction Machines by Ajay Agrawal, Joshua Gans, and Avi Goldfarb: An economics-focused examination of AI as a prediction tool, it is intellectually rigorous but lighter on direct strategy frameworks and planning templates.
- The AI Advantage by Thomas Davenport: A practitioner-oriented guide to deploying AI in business, it covers implementation well but leans more toward operations and technology adoption than toward strategic planning methodology.
Strategic Analytics: Towards AI-based Strategy Planning, 2nd Edition occupies a distinct space by combining structured analytical frameworks with forward-looking AI strategy content in one focused volume. It is the best pick for analysts, strategists, and managers who want a single, practical resource they can apply directly to planning workflows rather than a broad survey of the AI landscape.