Business Process Management is a Journey, not a One-Time Project.
Business processes underpin business capabilities, a progressive organization should always take process improvement and optimization as a journey, not a one-time project, in order to build competitive advantage, however, how to select the right process to improve?
Selecting processes to improve should be based on organization goals, strategy, and KPIs. How far is your current process performance from targeted KPIs? Hopefully, the KPIs you selected are important to your customer. Dollars available to improve a process may be another consideration. So business process management should be well aligned to realize the organization's goals & objectives and should focus on targeting the KPI’s / SLAs that the organization wants to achieve.
Potential to simplify a complex process is a consideration, but process complexity is usually not a high consideration in deciding which processes to improve. One can use a phased implementation approach if there are too many numbers of steps. The process complexity and simplifying the process should be owned by business analyst/process modeler & designers. Please remember how a high-level process map at the enterprise level is analyzed will drive the structural complexity of the various decomposed processes at a various level of your organization. You may consider the following complexity parameters for the BPM implementation
1) Process steps complexity: Number of process steps involved
2). Process Flow complexity: number of splits, joins, loops
3). Human steps complexity: Front-end logic, back-end validation
4). Business rule integrations: BPMS rules, external rule engine, routing, rerouting, escalation handling
5). System integrations: Interfaces with the external application, point to point integrations, number of elements, data element mappings
6). Process exceptions handling: rollback, rollback within exceptions
7). Leveraging reusable components: Sub flows, business factions
8). Requirement complexity: Transactional and process related dashboards
9). Others complexity: Audit details, Payload information, Timer Logs, Managing human intervention steps from the side the organization needs
1) Process steps complexity: Number of process steps involved
2). Process Flow complexity: number of splits, joins, loops
3). Human steps complexity: Front-end logic, back-end validation
4). Business rule integrations: BPMS rules, external rule engine, routing, rerouting, escalation handling
5). System integrations: Interfaces with the external application, point to point integrations, number of elements, data element mappings
6). Process exceptions handling: rollback, rollback within exceptions
7). Leveraging reusable components: Sub flows, business factions
8). Requirement complexity: Transactional and process related dashboards
9). Others complexity: Audit details, Payload information, Timer Logs, Managing human intervention steps from the side the organization needs
Measurement in the complexity of business processes really spins off at a structural level: Other factors are not really parameters for the computing complexity of business processes at an organization level. Other aspects only come into during process design and implementation level but process complexity is complicated during process map analysis, laying out enterprise process diagrams and high-level process modeling. The process improvement approach should start with organization goals and then drill down to the process. Process complexity should be discussed once the processes have already been selected for improvements
1). Converting more real-life process charts into graphs. As mathematical theory like graph theory is one of the important techniques for measuring the structural complexity of a business process
2). Gaining long-term experience on the values of the complexity measures for real-life graphs, to establish the scale of the measures and enable comparison of the difference
3). Devising validation methods for the complexity measures and applying them. Implementing the algorithm to compute the complexity index (CI)
4). Investigating and validating the use of the restrictiveness estimator (RT) to cyclic process graphs. Further development of using the number of distinct trees (T) as a complexity measure
5). The relationship between size and complexity: should a complexity measure be independent of size and how can this be accomplished?
6). Using weighted arcs to represent the difficulty of information, material and control flow, possibly taking into account the media and the possibility of crossing organizational boundaries or geographical distances
7) Implementation of the best complexity measure or a set of complexity measures in a process modeling software, allowing quick and easy analysis of the complexity of different processes
Consider the "level of automation possible within the Business Process, as an additional parameter once the processes for improvement are identified: Not all activities within a process can be automated but automation certainly makes the process more repeatable and predictable. Make analytics upon how the complexity of the business process can be defined or measured with the level of automation since one of the major objectives/vision of implementing business process is automating all possible nonhuman tasks to enhance process throughput.
1) The level of automation may complicate the integration/interfacing based on the technology stack used but should not drive structural complexity of the organizational business processes.
1). Converting more real-life process charts into graphs. As mathematical theory like graph theory is one of the important techniques for measuring the structural complexity of a business process
2). Gaining long-term experience on the values of the complexity measures for real-life graphs, to establish the scale of the measures and enable comparison of the difference
3). Devising validation methods for the complexity measures and applying them. Implementing the algorithm to compute the complexity index (CI)
4). Investigating and validating the use of the restrictiveness estimator (RT) to cyclic process graphs. Further development of using the number of distinct trees (T) as a complexity measure
5). The relationship between size and complexity: should a complexity measure be independent of size and how can this be accomplished?
6). Using weighted arcs to represent the difficulty of information, material and control flow, possibly taking into account the media and the possibility of crossing organizational boundaries or geographical distances
7) Implementation of the best complexity measure or a set of complexity measures in a process modeling software, allowing quick and easy analysis of the complexity of different processes
Consider the "level of automation possible within the Business Process, as an additional parameter once the processes for improvement are identified: Not all activities within a process can be automated but automation certainly makes the process more repeatable and predictable. Make analytics upon how the complexity of the business process can be defined or measured with the level of automation since one of the major objectives/vision of implementing business process is automating all possible nonhuman tasks to enhance process throughput.
1) The level of automation may complicate the integration/interfacing based on the technology stack used but should not drive structural complexity of the organizational business processes.
2) The level of automation can decide efficiency: Once you have identified the list of processes for improvement, it cannot be used to solely determine the complexity but can be used to determine the processes where maximum efficiency can be gained.
3) The level of automation can play a role in choosing the right process for improvement and yield high ROI.
Not suggesting that it can be used solely to define the complexity of the process. Therefore, selecting a process to improve should be based on the business goal and priority, automation, complexity, etc are also considered factors. You may perhaps consider the emergent process, which is inherently "complex" due to their collaborative, knowledge-intensive nature. These are processes you may only be able to map at a high level of abstraction. But for effectiveness in process improvement, always put the focus on targeting the KPI’s / SLAs that the organization wants to achieve.
Not suggesting that it can be used solely to define the complexity of the process. Therefore, selecting a process to improve should be based on the business goal and priority, automation, complexity, etc are also considered factors. You may perhaps consider the emergent process, which is inherently "complex" due to their collaborative, knowledge-intensive nature. These are processes you may only be able to map at a high level of abstraction. But for effectiveness in process improvement, always put the focus on targeting the KPI’s / SLAs that the organization wants to achieve.
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