Partial book profile
Predictive Business Analytics
A practitioner's guide to building and deploying a predictive business analytics (PBA) capability that turns historical data into forward-looking, fact-based decisions to gain sustainable competitive advantage.
The full book profile is not available yet.
What it’s about
Predictive Business Analytics argues that the next competitive edge for organizations lies not in more data but in the disciplined, forward-looking analysis of the right business drivers that have a strong cause-and-effect relationship to financial and operational outcomes. Written by two seasoned management consultants (co-developers of the balanced scorecard and activity-based costing thought leaders), the book distinguishes PBA from business intelligence, predictive analytics, and enterprise performance management, then lays out seven guiding principles, a maturity model, a step-by-step framework for developing and deploying a PBA function, and real-world case studies from MetLife and the biopharmaceutical industry. It shows how to integrate PBA with performance scorecards, predictive/marginal-expense accounting, and driver-based budgeting and rolling forecasts, while candidly addressing the true obstacles—not technology, but human resistance to change, culture, and leadership. Readers learn how to move their organizations from reacting to the past toward anticipating and shaping the future, replacing gut feel and intuition with evidence-based, probabilistic decision making.
The through-line
- Who it’s for
- A business leader, manager, or analyst who wants to make faster, smarter, fact-based decisions and gain a sustainable competitive edge for their organization.
- The problem
- The organization is drowning in data but starving for actionable, forward-looking insight to guide decisions. Leaders fear making wrong or confused decisions, relying on gut feel while competitors pull ahead.
- The plan
- Assess your organization's analytics maturity and adopt a change management process.
- Establish seven guiding principles and gain organizational concurrence.
- Develop a PBA framework: design the process, build the model, and capture data.
- Deploy the function with a performance measurement system, KPIs, and management reviews.
- Integrate PBA with accounting, budgeting, and rolling forecasts.
- The payoff
- The organization anticipates events, forecasts outcomes, and proactively selects the best actions. · Decisions become fact-based, faster, and probabilistic rather than intuitive. · Leaders out-think, outsmart, and out-execute competitors and achieve sustainable performance.
See our guide
Related profiles we’ve built
- A Practical Guide To Conjoint Analysis →
- Analytics at Work: Smarter Decisions, Better Results →
- Big Data: A Revolution That Will Transform How We Live, Work, and Think →
- Big Data_ A Very Short Introduction (Very Short Introductions) →
- Business Adventures →
- Business Intelligence Guidebook: From Data Integration to Analytics →
- Data Mining for Business Analytics: Concepts, Techniques, and Applications →
- Data Warehouse and Data Mining →
Additional reading
- The Balanced Scorecard: Translating Strategy into Action · Robert S. Kaplan and David P. Norton
The book presents the Balanced Scorecard methodology, which is described as a key tool for performance management and a central component of an effective PBA deployment.
- Why Smart Executives Fail · Sydney Finkelstein
The book's explanation for corporate failure—flaws in executive reasoning and culture rather than lack of intelligence—is used to build the case for why fact-based PBA is necessary to mitigate risk.
Featured in these guides
- Practice Business Intelligence & Data Science →Cited source
Co-cited books
- Alteryx Designer The Definitive Guide (Fifth Early Release) · Joshua Burkhow
- Analytics at work smarter decisions, better results · Davenport, Thomas H., 1954-, Harris etc.
- Operations Research for Social Good A Practitioners Introduction Using SAS® and Python
- Business Intelligence and Big Data Business Intelligence and Big Data Drivers of Organizational Success
- Data Analytics for Business Lessons for Sales, Marketing, and Strategy
- Cultural Analytics
- Competing on analytics the new science of winning · Davenport, Thomas H., 1954- author, Harris etc.
- The Definitive Guide to DAX Mastering the semantic model expression language for Microsoft Power BI, Fabric, and Excel Third… · Alberto Ferrari, Marco Russo