Business Analytics For Decision Making – Making It Work
Gary Cokins is an internationally recognized expert, speaker, and author in advanced cost management and performance improvement systems. He is the founder of Analytics-Based Performance Management, an advisory firm located in Cary, North Carolina at www.garycokins.com. Gary received a BS degree with honors in Industrial Engineering/Operations Research from Cornell University in 1971. He received his MBA from Northwestern University’s Kellogg School of Management in 1974.
Gary began his career as a strategic planner with FMC’s Link-Belt Division and then served as Financial Controller and Operations Manager. In 1981 Gary began his management consulting career first with Deloitte consulting, and then in 1988 with KPMG consulting. 1992 Gary headed the National Cost Management Consulting Services for Electronic Data Systems (EDS) now part of HP. From 1997 until 2012 Gary was in business development with SAS, a leading provider of enterprise performance management and business analytics and intelligence software.
His two most recent books are Performance Management: Finding the Missing Pieces to Close the Intelligence Gap (ISBN 0-471-57690-5) and Performance Management: Integrating Strategy Execution, Methodologies, Risk, and Analytics (ISBN 978-0-470-44998-1). His most recent book co-authored with Larry Maisel is Predictive Business Analytics (ISBN 978-1-118-17556-9) published by John Wiley & Sons. Mr. Cokins can be contacted at email@example.com.
This presentation focuses on how the finance and accounting function can leverage analytics, especially predictive ones, embedded in their financial reporting, planning, and decision making.
Finance and accounting professionals are typically considered to be very quantitative. They are by nature number-crunchers. But collecting, validating, and reporting data is not the same thing as analyzing the information that can be gleaned from data. Most organizations are drowning in data, but starving for information.
The CFO function is experiencing a shift from beyond financial reporting to dealing with and reporting non-financial information. Finance people are increasingly involved in creating and monitoring performance measurements. But do they know how to identify the appropriate measures? Their task should not be about what can be measured but what should be measured. And don’t stop there. This is not about just monitoring the dials of a scorecard or dashboard, but moving the dials. The decisions involved to improve performance require analytics of all flavors.
Most companies are far from where they want and need to be when it comes to implementing analytics and are still relying on gut feeling, rather than hard data when making decisions. Volatility and complexity are the new normal.
When you step back to see a perspective of importance, financial accounting simply deals with valuation – for example, what is an organization worth if you were to sell it? But managerial accounting is about creating value – its information contributes to management decisions that financial accounting ultimately deals with afterward. Arguably managerial accounting is more important than financial accounting. But the issue does not stop there. An analysis must be added to reporting. How else can the sales and marketing functions determine which types of customers are more attractive to retain, to grow, to win-back, and to acquire? And for the attractive types, what is the optimal level of spending for each customer micro-segment to retain, grow, or acquire them?
What is needed today is the seamless integration of managerial methods such as balanced scorecards, strategy maps, capacity-sensitive driver-based budgets, and rolling financial forecasts, and measuring and managing channel and customer profitability (using activity-based costing principles)? Each one can be amplified by embedding business analytics with them. The methods are collectively intended to align manager and employee behavior and limited resources to focus on the organization’s strategic priorities and objectives and better decision making.
- Learning why business analytics and leveraging Big Data provide a competitive advantage
- Understanding the difference between business intelligence (BI) and business analytics
- How to embed statistics and analytics into enterprise performance management (EPM) methods
- How to differentiate forecasting from predictive modeling
- Learning alternative approaches to accelerating the adoption rate of business analytics
Course Level - Intermediate
Who Should Attend
- Financial officers and controllers
- Managerial and cost accountants
- Financial and business analysts
- Budget managers
- Strategic planners
- Marketing and sales managers
- Supply chain analysts
- Risk managers
- CIO and information technology staff
- Board of Directors
Why Should Attend
Many organizations struggle to answer these types of questions:
- After we properly calculate product, channel, and customer profitability, how can we know what drivers cause higher or lower profits?
- Are we measuring the most valid KPIs? Can we validate them with correlation analysis?
- Can we apply probabilistic variables to calculate the range of financial outcomes?
- How can we validate the selection of cost allocation factors (which are activity drivers used with activity-based costing)?
- How can we improve the accuracy of our forecasts of demand and other variables used for planning, budgeting, rolling financial forecasts, and what if scenarios?