How To Build A Predictive Business Analytics Foundation

In a recent Q&A for Business Finance, I introduced the concept of Predictive Business Analytics (PBA) as the skills, technologies, tools and processes for continuous analysis of past business performance to gain forward-looking insight and drive business decisions and actions.

PBA focuses on developing new insights and understanding business performance based on extensive use of data, statistical and quantitative analysis, explanatory and predictive modeling and fact-based management as input for human decisions—or as input to drive fully automated decisions.

These past several years of economic turbulence have provided excellent examples of the importance and benefits to be realized by organizations that developed a workable PBA process. Many have used it to anticipate and guide its operations to productive outcomes. Conversely, it also demonstrated the consequences of omitting or not adequately developing a relevant predictive business analytics process.

A 2009 survey by PricewaterhouseCoopers of over 400 senior financial leaders in both public and private sectors found that these high performing companies outperformed low performers by 54 percent in several key categories including shareholder returns and profitability and were 43 percent more effective in turning analytics into a competitive advantage.

Now that we know what it is and what are some of its benefits, the next step is to define how we go about implementing PBA. It has been my experience that an effective way to get started is to adhere to a set of principles that can guide its development and deployment:

• Demonstrate a Strong Cause-and-Effect Relationship. In order to be able to predict outcomes, it is important to measure and monitor what drivers or events most likely causes the outcome(s) to occur.
• Contain a Balanced Set of Financial, Non-Financial, Internal and External Measures. Too often management reporting is concentrated on internally focused financial results, like net income, and less on the non-financial activity that have a financial impact or externally driven metrics that show how the marketplace views the organization.
• Be Relevant, Reliable and Timely. PBA should be provided to users when, where, and how they need it. Analytics should be relevant to the business, industry or function. It must have the right level of timeliness and reliability to the critical issues being addressed. In other words, it is "fit for purpose".
• Ensure Data Integrity. Data integrity is of paramount importance and should be supported by an organization's ability to establish data standards and data quality practices, which is the foundation for a trusted and accepted PBA.
• Be Accessible and Well-Organized. For PBA to contribute to managerial decisions and actions, it needs to be easily accessible using tools and technologies that are "user-friendly" and organized in a way that reflects the business model.
• Integrate into the Management Process. Predictive business analytics and forward looking performance measures should be tied to accountabilities, linked to operating results and performance, and be an integral part of the management review process.
• Drive Behaviors and Results. PBA should highlight those measures that foster desired behaviors of the organization such as innovation, team work, collaboration and risk taking. Accordingly, it is important that PBA is tied to reward and recognition processes.

The primary purpose of PBA is to identify how the future might look and what subsequent actions need to be taken. It is a continuous process to cultivate managerial and operational decision-making that affect future financial and operating results and facilitate strategy execution.

Several uses of this process include updating forecasts of projected results given current state; evaluating changes to current strategies and operating plans (deviations) and adopting corrective actions (gap closing); sharing expectations among interdependent groups or entities; looking around "the curve" with an eye towards actions and changes; and approximating results based on changes in business drivers to provide a broad palette of alternative actions for discussion and decision among responsible managers.

PBA supports an organization's need for a capability to anticipate future events, forecast their possible outcomes, and select actions and decisions that affect its business results, operational capabilities, response to changing market and industry dynamics, and its recruitment and retention of critical people, skills, and competencies. The use of predictive business analytics can be illustrated as an example from a consumer finance company.

A consumer finance company monitors its outstanding credit card balances across several key internal and external attributes. Internal attributes include aging of balances, level of repayments relative to minimums due, geographies and demographics, to name a few; in addition, external attributes include employment rates, unemployment insurance claims and credit scores. These attributes or "drivers" form the foundation of an organization's ability to apply PBA to its business model and to convert its insight into a series of decisions and actions. Several critical elements are necessary to make this process relevant, namely:

• Information Quality: ensuring the data is trustworthy and the relationships are causal and consistent;
• Tools and Access to the Information: making sure the formats graphic are intuitive and the information is easily and rapidly accessible;
• Operating Processes: to capture, validate, distribute, and analyze relevant data for establishing performance insights and facilitating decisions at the designated levels of accountability;
• Skilled Individuals: making sure they are knowledgeable and informed about the strategic or operational results and their implications; that they can process what happened and why it is happening and whether this is an anomaly or if it is a trend;
• Credible Management Processes: ensuring these foundations are in place to raise awareness and determine actions and decisions and a process to monitor and measure the effectiveness of these actions.

Larry Maisel is the managing partner at consulting firm DecisionVu and a leader in the field of strategy and performance management. He is a regular contributor to Business Finance.

Thanks to Larry Maisel / Penton Media, Inc. / Business Finance Mag
http://businessfinancemag.com/article/how-build-predictive-business-analytics-foundation-0523