Corporate Performance Management world in moving from the analysis of past and present - which was the focus of BI all along - to future predictive analytics. The new tools of simulation and complex algorithms are helping the leading edge performers! So how are the companies doing it? Here is a useful article:
Most companies focus on the past and present simply because that's all their technology allows them to do. BI tools generally provide little or no insight into the future. And in the quest to supercharge results and embrace business performance management (BPM), that's simply not good enough.
That's why many organizations are turning to predictive analytics. Predictive analytics capabilities, which are being incorporated into software products that generally fall into the categories of BI or BPM, allow an organization to run highly detailed simulations and develop appropriate strategies to execute throughout operational areas as well as within the finance function.
Here's how predictive analytics works. An application scans data sets and examines patterns that relate to successes and failures. Then, if sales dip below a prescribed threshold or the company exceeds its budget, the software not only pinpoints the specific problem, it sifts through the data to find contributing factors. Once the system identifies key issues, it analyzes an ongoing stream of operational and transactional data to provide alerts and insights.
Using a graphical dashboard, a predictive analytics application displays the probable impact of various scenarios. Not only does the software track how KPIs mesh with other metrics, they show how all these factors drive business processes. As a result, it's possible to notify managers about emerging issues and problems early on so that they can make quick adjustments. No less important: The system ensures that all managers abide by the same set of standards, and it can suggest a course of action based on previous circumstances and results.
The article also gives five ways to tie Predictive Analytics to BPM:
Identify key metrics. Finance and other departments must determine which metrics and key performance indicators to analyze. The number usually falls between 5 and 15 and encompasses diverse metrics ranging from days sales outstanding to scientific data used for oil exploration.
Build a BPM model. Success depends on developing a sound business model that incorporates data, rules, formulas, workflow and other factors. It's also necessary to build templates so that line managers and others can view relevant data and act on it as needed.
Integrate applications. Analytics tools and BPM software must integrate with core systems, such as enterprise resource planning (ERP), material resource planning (MRP) and customer relationship management (CRM). Data must flow into the analytics application in order to produce valid results. This might translate into investments in middleware and programming.
Train executives and managers. Without training, even the best predictive analytics system is likely to go astray. Decision-makers must understand how to view dashboards and act on data in a timely and effective manner.
Monitor data and act on it. Finance can play a key role in understanding data sets -- particularly financial information related to BPM -- and putting analytics to use. It can also help other departments make data actionable.
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