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How to maximize resource effectiveness with analytics


Analytics can transform your business. I shared with you how to transform customer retention and marketing with analytics. This time I’d like to share with you how to use the power of analytics and Decision Management to allocate constrained resources and to give you a competitive edge.

How to maximize resource effectiveness with analytics

Organizations are under constant pressure to improve the efficiency and effectiveness of their operations. Budget and headcount restrictions are common place. In this environment you must focus on maximizing the resources you have by rethinking traditional process and workflows to be more efficient. What are currently complicated and resource-heavy processes are often in actuality simple processes that have been over complicated by poor decision management. You can streamline processes by finding the decisions where many manual steps are required to process data.

There are three steps to transforming resource allocation.

Step One: Decision-driven Data Integration

The backbone of analytically based decision making is integrating the data required to make a particular decision. Many organizations have data scattered across multiple sources and implement processes to manually integrate and aggregate this data. Much of this data has only ever been considered from a financial perspective. Resources are directly wasted on these processes and indirectly wasted because decisions based on assumptions and habit rather than data.

Decision Management Edge: Begin with the decision instead of the data. Many data integration efforts flounder because they attempt to integrated data without a purpose.

Step Two: Focus on High Value Decisions, automate the rest

With the data integrated, the opportunities for cost reduction abound. Business rule management systems can streamline basics like alerts that align to business objectives. But moreover, they can act automatically on some or all of their transactions using this information. Business rules can easily express the regulations and policies that need to be applied, allowing 80% or more, sometimes up to 95%, of transactions to be automated. Resources can now focus on high value decisions and have the time they need to use their data to make better ones. The combination of business rules-based automation of day-to-day transactions and analytics to minimize the exceptions to those rules, streamlines processes and the resources needed. Business rules automation makes it easier to apply resources and analytics where they can be most effective.

Decision Management Edge:  Organizations that consider business rules and analytics as a pair automate more routine manual decision making and focus human decision-makers where they make the most difference.

Step Three: Proactive value creation

Instead of waiting for something to go wrong and then spending money and resources to fix it, organizations can identify much cheaper preventative steps. They can apply resources to the prevention of problems not their cure. Predictions can be of fraud, of natural disasters or other problems, of equipment failure and much more. A rich, integrated history of what has happened in the past can provide the data needed to produce these kinds of models. Predictive modeling techniques use this data to turn uncertainty about the future into usable probabilities. Instead of being taken by surprise, because they are unable to predict when a problem will occur, organizations can estimate how likely each kind of problem is to occur in time to act. By analytically deriving where risk truly exists, organizations can focus resources where they will create the most value.

Decision Management Edge:  Using predictive analytics to detect problematic trends and estimate future risk avoids pay-and-chase fraud investigations and allows resources to be assigned to the next best case, maximizing the value of your resources.

Each step builds value – making data-driven decisions improves efficiency, streamlining processes by automating decisions frees up resources for higher value work and using predictive analytics lets you assign resources where they will make the most difference. Companies and government agencies are already using these approaches to transform resource allocation and drive value to their bottom line. This is not a future vision but a practical way to make improvement today. And Decision Management gives you the edge in quicker realized value of analytics implementations.

These insights come from the collective wisdom of over 50 organizations that have transformed their business using analytics. These organizations tackled core business issues like customer retention, marketing, service delivery, operations and customer centricity, in industries as varied as Telecommunications, Retail, Healthcare, Education, Government and Banking.


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