|
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.
Top
|
