Five key points for continuous improvement in the life-cycle of processes

Five key points for continuous improvement in the life-cycle of processes:

Nowadays it is essential that companies adopt a continuous-improvement methodology that will support a sustainable and profitable business model. This is particularly important in the changing, competitive environment firms now find themselves faced with.

For this methodology to be effective, the company's processes need to be seen as a lever for analyzing and optimizing the way the firm works. The simple fact of modeling and analyzing processes (inputs, outputs, participants, activities, information flows, etc.) makes it possible to identify points where improvements can be made (bottlenecks, downtime, unequal distribution of work, etc.).

Moreover, when processes are well understood it is easier to determine who will be affected by the changes associated with improvements, which in turn makes it easier to introduce and communicate such changes. In other words, we are talking about using processes as the basis for knowledge and change management.

Polymita Technologies recommends that the following key points for continuous improvement in the life-cycle of processes be taken into account before initiating any project that involves process automation and management.

1. Organize an interdisciplinary team of key people in the company. Bring together business users and technical users.

Knowledge of processes tends to be held by different individuals who participate in different ways, whether as suppliers or clients, as executors or in a supporting role with respect to execution.

Processes are not confined to any specific area: they tend rather to be transversal in nature.

If a process is to be analyzed correctly, all relevant information needs to be available, including both business information and technical information. On the basis of this broad perspective it is possible to identify all the key factors: What initiates the process? What must be obtained? What areas/people participate? What steps need to be taken? What rules define the pathway to be followed? What IT applications are used? What is the information flow? What indicators have to be taken into account?

It is vital to get all participants talking the same language to ensure that they will end up pursuing the same objectives. This will reduce the gap that tends to develop between the interests of those with a business focus and those more oriented to technical issues. If this type of approach is taken, it will be possible to properly identify, understand and reach a consensus on all processes.

2. Analyze and model correctly by performing simulations and making estimates using a tool that is integrated with your process execution engine or allows results to be exported.

After defining who needs to provide information, the next step is to model and analyze the process. A range of different tools can be considered for modeling, from basic Office tools such as PowerPoint to more specialized software such as Visio, or tools like Aris and Adonis that are designed specifically for use at this stage. Using a notation like BPMN can make it easier to establish a shared language for all participants.

Coordinating different working groups is an effective way to obtain and organize the necessary information. This step provides access to the flow that represents the process and to all of the information needed to correctly analyze it.

If information about times and costs is also available and the tool used for modeling allows for it, simulations of various scenarios can also be carried out to determine how effectiveness and efficiency are impacted as we move from the process “AS IS” to a hypothetical process “TO BE.”

If the tool utilized also offers documentation functionalities, it will be possible to export different formats (HTML, DOC, XPDL, etc.) that can be used to generate documentation about the process. This documentation can then be published on an intranet, for example. It will also be possible to feed the information about the flow to an execution engine, a step that guarantees a significant improvement in the process and its standardization.

3. Import the model to the execution engine; performance of tests and measurements, detection and correction; integration with systems and execution; documentation.

When the model is imported to an execution engine, it brings with it all the logic underlying the process (roles, steps, actions, etc.). At this point all the elements needed to automate the process are in place. These include dynamic assignment rules, the data to be handled, business rules to be taken into account when automating certain decisions, integrations to be tackled for the exchange of information with other necessary applications, and alarms and indicators that will be used to control the process.

The more tasks can be carried out by means of configuration without the need for programming, the easier it will be to go on applying the concept of continuous improvement thanks to the flexibility and responsiveness that can be deployed to deal with changes on a continuous basis.

Tests need to be carried out to check that the flow is well established with respect to participants, the flow of information to be handled, and the steps to be taken.

4. Monitoring and auditing processes; analysis of the information generated with working groups.

Automation brings major benefits on two levels. On the one hand, it facilitates the work of process participants who will always know what they need to do, when and how to do it, and what information to use. On the other hand it gives managers the information they need to make optimal fact-based decisions.

When this information is used correctly and shared with all stakeholders, it will generate suggestions concerning changes that can be made to improve the process and facilitate its adaptation to evolving needs.

Greater access to information about the overall behavior of the process and the instances executed will provide a basis for better decisions. The easier it is to access such information, the more appropriate the resulting decisions will be.

5. Adapting the original models to the results obtained.

Based on the knowledge that will be available simply as a result of having modeled and analyzed the process, and given the complete control possible thanks to automation (indicators, traceability, etc.), it will be easy to decide what needs to be changed to make improvements. The next step will therefore be to adapt the original model by implementing any improvements that have been defined.

A good approach is to identify various possible improvements and then prioritize them based on a cost-benefit analysis, bearing in mind that automation is bound to reduce the cost of implementing changes.

Applying these five principles while effectively managing knowledge and change will ensure success when it comes to managing the life-cycle of processes.

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Domingo García Caro
Polymita Technologies
info@polymita.com

09-07-2008