Business Process Optimization

Process optimization is the discipline of adjusting a process so as to optimize some specified set of parameters without violating some constraint. The most common goals are minimizing cost and maximizing throughput and/or efficiency. This is one of the major quantitative tools in industrial decision making.

When optimizing a process, the goal is to maximize one or more of the process specifications, while keeping all others within their constraints. This can be done by using a process mining tool, discovering the critical activities and bottlenecks, and acting only on them.

Fundamentally, there are three parameters that can be adjusted to affect optimal performance.

They are:

  • Equipment optimization – The first step is to verify that the existing equipment is being used to its fullest advantage by examining operating data to identify equipment bottlenecks.
  • Operating procedures – Operating procedures may vary widely from person-to-person or from shift-to-shift. Automation of the plant can help significantly. But automation will be of no help if the operators take control and run the plant in manual.
  • Control optimization – In a typical processing plant, such as a chemical plant or oil refinery, there are hundreds or even thousands of control loops. Each control loop is responsible for controlling one part of the process, such as maintaining a temperature, level, or flow. If the control loop is not properly designed and tuned, the process runs below its optimum. The process will be more expensive to operate, and equipment will wear out prematurely. For each control loop to run optimally, identification of sensor, valve, and tuning problems is important. It has been well documented that over 35% of control loops typically have problems.

The process of continuously monitoring and optimizing the entire plant is sometimes called performance supervision.

Business Process Optimization

Business Process Optimization is the act of taking your old business processes and optimizing them for efficiency. The general idea is to make it more efficient – the means of doing that, however, can vary a lot.

Most companies today are well aware that their business processes are key to their competitive success. They also know they are central in acquiring new customers, keeping existing customers happy over the long term, all while reducing expense. To that end, the typical company has applied substantial effort to identify and, at a minimum, document their processes. Often the next step is to send the process experts off to analyze and optimize the processes within the company. The benefit of this is that you have the best people looking at improvement across the organization. But there are two key reasons why this approach only has, at best, a short term benefit:

  • These experts have other critical job functions in the company – having them focus on Process Optimization across the company can only be done in short term bursts. This doesn’t achieve the underlying goal of “Continuous Improvement” to gain and maintain the competitive edge.
  • This approach has the effect of making optimizations to all processes. That means the ones that would have the biggest leverage are not easily recognized, and much effort may be spent optimizing processes that aren’t necessarily going to provide the best ROI given the time investment of these key personnel.

So from a corporate oversight perspective, doing some prioritization to determine which processes should be the focus of these efforts is simply the best approach. But how can you be sure you are making informed prioritization decisions?

In parallel, companies often spend considerable time developing elaborate Strategy and Objective models and even often tie compensation to achievement of these objectives. Just like Business Process Optimization, these objectives are typically measured against the competitive landscape with an eye towards new customer acquisition, increasing customer retention and expense reduction. Often, Business Intelligence systems are applied to help with the monitoring of these key performance indicators (“KPIs”) in order to compare results against goals. But with this approach alone, once a KPI measurement is seen to be outside the optimal range, decision makers often have the following limitations:

  • It is often difficult to tell exactly which process is underperforming and therefore where to apply the action plan.
  • It is even more difficult to tell who the best person is to assign to solve the issue.

What often happens is that business intuition is relied upon in generating an action plan to solve the issue. Sometimes this works well, but sometimes even the most knowledgeable decision maker might miss subtleties that would otherwise point directly to the problems.

By creating an Enterprise Model that includes Strategies and Objectives along with the KPIs to measure actual against, in combination with a Processes Landscape (as well as supporting objects like Resources), the KPIs can be integrated into the Process definition and optimization efforts (which includes assignment of Process responsibility). Then dashboards can be created which monitor the actual KPI values to compare against objectives. Now, when a KPI is out of range, it is a simple click to determine which process is causing the issue and who has the responsibility for addressing the issue. The result is that the decision maker has critical information at hand to prioritize the Business Process Optimization efforts to achieve established goals. Note that this method is independent of which processes have been fully automated since many of the critical business processes will always require human intervention. Key advantages of this approach include:

  • Process Optimization efforts and methods (i.e., Six Sigma, Lean, etc.) can be easily tied into the corporate strategies and objectives
  • Issues are shown in the context of the Processes which allows for much quicker analysis of the problems and development of action plans and responsibility assignment
  • Models can be developed at varying levels of depth, allowing for increasingly more granular analysis to pinpoint critical issues
  • KPI goals can be tuned and adjusted with immediate feedback as to what must improve to achieve these new objectives. This means that Continuous Improvement becomes part of the culture and it is always targeted at what is critical
  • Dashboard information can be rolled up based on role in the organization, which allows for the right information in the right hands, at the right time.
What is optimization
Modeling and Optimization

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