Travelers experience it every day—the forecast is calling for terrible weather in a few days…exactly the same time their trip is going to begin. Travelers are then faced with two big decisions: Number one, change travel plans in advance and divert the weather, or number two, do nothing and hope for the best. Regardless of the decision made, the point is that the forecast plays a major role in the decision process of the traveler, just like it should play a major role in the decision process of businesses.
Financial statements, balanced scorecards, and benchmarks are all good methods of tracking the performance of a company over time, but they provide only a snapshot of the organization at a specific point in time which limits insight into the future performance of the organization. Too often, the impact of a change is not felt in an organization until it hits the bottom-line; by this time it is too late. Managers need a way to be proactive into today’s constantly changing environment instead of being reactive to the change around them.
To address this constant problem, companies are turning to predictive analytics. Predictive analytics is the use of a variety of techniques from statistics and data mining that analyze current and historical data to make predictions about future events. Predictive Analytics uses a forward-looking approach to help firms identify the impact of changes before they reach the bottom line, giving managers time to adjust and plan for the future. Predictive models exploit patterns found in historical and transactional data to identify risks and opportunities. Models capture relationships among many factors to allow assessment of risk or potential associated with a particular set of conditions and events. These relationships then guide decision makers to identify and prepare for future events.
Predictive analytics has historically been used in insurance, telecommunications, retail, travel, healthcare, pharmaceuticals and credit scoring. The use of predictive analytics has even crossed into the sports world; Italy’s A.C. Milan uses predictive models and techniques to prevent injuries by collecting and analyzing orthopedic and psychological data from various sources. More and more companies and industries are identifying the need and uses of predictive analytics in their company breaking away from its traditional uses. One emerging area that predictive analytics is being used is the starting point for financial planning and forecasting exercises. For example, companies are using predictive analytics to predict cost on consumption-based recovery items, allowing them to identify the effect of changes in volume forecasts before it hits shared services recovery and the bottom-line.
Predictive analytics deals with extracting relational information from data and using it to predict future trends and behavior patterns. The core of predictive analytics relies on capturing relationships between identifiable variables and predicted variables from past occurrences, and exploiting them to predict future outcomes. To feed an accurate financial planning or forecasting predictive model requires a advanced Strategic Cost Model. Strategic Cost Management (SCM) models identify the activity and cost drivers that link activities to an organization’s products, services, and customers.
Combining a company’s current strategic cost management initiative with the foresight provided by predictive analytics provides managers with a new way to view their costs, enabling them to make better decisions and increase the overall profitability of the firm. Predictive analytics give managers the capability to plan using demand from customers to build budgets bottom-up instead allowing budgets to be set from the top-down. Managers are able to quickly determine the impact of change to an organization and adjust accordingly without waiting to see the impact on the company’s bottom line. Knowing the impact of the change in advance allows managers to better plan and to align resources to forecasted expectations and decrease wasted expense and eliminate unnecessary costs. Finally, providing an interactive dashboard report with key performance indicators directly to managers allows for managers to do their own scenario analysis and minimizes the need for ‘back and forth’ between front-line managers and financial planners or cost modelers.
Predictive analytics allows managers and organizations to be prepared for an uncertain future. They can become proactive with their decisions instead of reactive to the current climate. Just like the traveler who can adjust plans to avoid weather delays, organizations no longer have cross their fingers and hope they can get through the turmoil, they can by using predictive analytics now avoid it all together.