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December 5, 2002

Business Process Intelligence

BI and business process management technologies are converging to create value beyond the sum of their parts

by Mark Smith

The business environment today demands that your organization redouble its efforts to improve the efficiency of processes that have a positive impact on financial performance. Fortunately, the capability to be much more responsive to business events is now available, enabling you to eliminate bottlenecks in the decision-making process.

For example, the ability to continuously measure and monitor a business process is now economically and technically possible through years of technological advancements in application integration and servers, business rules and workflow, business intelligence (BI), and process management software. Specifically, the developing convergence of BI and business process management (BPM) software is enabling business process intelligence (BPI): the application of BI-oriented performance-driven management to business processes. Instead of simply automating business processes — as they've done for years — forward-thinking organizations are beginning to realize that gaining intelligence about such processes will guide business and IT investments that can result in reduced costs and higher ROI.

Consider the example of a computer technology retailer looking to drive more efficiency in its customer order-to-fulfillment processes to align revenue and service level goals. Recent analysis suggests that fulfillment targets are down by 10 percent, customer satisfaction is down by 15 percent, and out-of-stocked items are up 15 percent, which is probably contributing to a 5 percent revenue decline. The retailer has no systematic method of examining these processes to link and monitor activities among order, finance, inventory, warehouse, and distribution functions. To effectively respond to bottlenecks through notifications that can drive action and inform customers about order delays, the retailer has to find a way to drive more efficiency through measuring and monitoring activities.

Fusing Performance Management into Processes

There's a lot of noise in the marketplace about corporate, business, and enterprise performance management. Regardless of the term used, the ability to apply performance management principles to daily operations — to optimize overall efficiency, continuously improve quality, and assign value to tangible and intangible assets — is now the ultimate goal of most large business organizations. The question is, how can your organization transform its existing, transaction-oriented information architecture into a performance management network? (See Figure 1.)

The most important aspect of this network is the ability to continuously manage performance at all three decision levels, not just measure historical performance. Just looking in your rearview mirror and examining the past won't help you optimize your future efforts and align your resources accordingly. The network links the three decision levels — strategic, tactical, and operational — to the information and user requirements that enable synchronization of efforts to reach a common set of goals. At the strategic level, executives outline strategies and goals. At the tactical level, management in the business units sets direction for their organizations, so that at the operational level individuals can take the right actions.

Unfortunately, most technology investments in this area have diverged, resulting in a web of inconsistent, silo systems and resulting metrics that have no relationship to one another for measuring and monitoring performance. However, a positive aspect of the industry direction toward performance management is the emerging consensus that the fractured, transactional infrastructure typical of most organizations has reached its limit and isn't useful for managing performance across business processes. Furthermore, it's now widely understood that the "business process" — defined as a set of interrelated tasks linked to an activity that spans functional boundaries — should be the most significant focus for organizations, because it can provide value at both incremental and evolutionary levels.

It's a given that a business process is a continuous loop that can be systematically linked and automated. The challenge is deciding where, when, and how you should automate those tasks to ensure that your IT investments are aligned to reap the greatest benefit.

Driving Intelligence into Processes

Several efforts are required to meet those goals. First, you'll need to prioritize process-level improvements through measuring, monitoring, and linking to functional and organizational goals. This goal is critical; automating tasks in a certain set of activities may not have the positive impact you desire if interdependencies allow gains in one area to be eliminated by other tasks.

The next step toward addressing these challenges is to apply a performance management methodology focused on the business process, which will help ensure that performance can be assessed and aligned in the right areas. For example, using the "understand-optimize-align" DecisionCycle methodology, here's how you would define the necessary functional requirements to achieve performance management goals and BPI:

1. To understand your business processes, create a business process model that can represent a set of business activities each linked to a set of individual tasks. This model is also supported by the definition of business rules and logic, which bind activities with business process. Then you need to bring real-time and non-real-time data together and flow it into the process model. Consequently, you can execute process measurement by applying analytics to the process model and generating meaningful performance metrics. Using our example from the introduction, in this step, the retail company would create a business process model that defines the order-to-fulfillment process that could be used for measuring performance of activities in a single context.

2. To optimize your business processes, apply automated and manual methods to leveraging information and analytics for performance improvement. Several technologies and approaches are available for applying sophisticated algorithms and models to provide a forecast and plan. You should then have a method to collaborate and share insights and knowledge on process-level metrics, which can then manifest into a set of performance metrics that transform into operational task recommendations for optimizing performance and actions. This step could enable you to collaborate and develop a plan that examines alternative approaches to improve performance.