BUSINESS TRANSFORMATION
Optimising resource allocation in business process models
With the increasing importance of improving business process models, companies strive to analyse running instances within processes to take immediate administrative action when problems arise. Predictive monitoring of business process models has received much attention in this context. It is intended to improve business processes by providing timely information that enables proactive and corrective action (time remaining, potential risk, performance metrics, upcoming events for running instances, etc.). Companies have adopted various strategies to foresee such data based on statistics, annotated transition systems, and machine learning algorithms.
What is resource optimization in business process models?
The process of management strategy or practice to improve employee competence, output, and performance within a project-based organisation is called resource optimisation. Achieving these goals involves planning, forecasting, allocating, and scheduling available resources and using them intelligently to meet organisational goals. Resources include people, equipment, facilities, finances, and more.
The critical resource optimisation goal is to exploit employee potentiality and develop business productivity. Resource managers use a variety of techniques to optimise the workforce and balance schedules, such as:
- Resource levelling
- Resource smoothing
- Modelling and simulation
- Inverse Resource Allocation
Top Resource Optimisation Techniques in Business Process Models
Since you know why resource optimisation is important, now the question is, how do you do that?
Here are the key resource optimisation techniques that companies and digital agencies can consider:
- Resource smoothing
- Resource levelling
- Modelling and simulation
- Reverse resource allocation
Project managers use resource smoothing techniques when time constraints are at the forefront. Resource smoothing, or time-bound planning, ensure that requirements stay within budget and do not exceed the resources allocated to the project. Project managers need to assess resource workloads to see how they can ensure that project deliverables are delivered on time.
As a project manager, you may find your project needs to progress according to a plan due to resource constraints. In these cases, you need to find ways to adapt to the situation so that the project outcome is not compromised.
Resource levelling involves adjustments made to start and finish dates for project completion with a specified amount of resources. This technique helps managers find the right balance between demand and available supply for a particular resource, reducing employee burnout. Resource levelling techniques help project managers assign tasks to the right resources, usually skilled resources familiar with the task.
Modelling and simulation help administrators create multiple scenarios in a sandbox environment. Managers can then analyse and compare the results of each scenario to select the most appropriate resource plan and prioritise projects. It prevents potential bottlenecks and protects profit margins.
Suppose you have a pipeline project with a certain probability of being approved. In such instances, managers can create different combinations of resources, alter usage, assess the impact on project schedules and budgets, and select the best possible results before applying them to resource planning.
The reverse resource allocation method can be used with the two techniques above but requires a different approach. This technique works in reverse, so work backward through your schedule, starting with the last or most important task. This technique works if your project has a deadline or you must complete important tasks on time. For example, if a task on the critical path has a project that requires an expert, assign the task so that the business expert can work on the specified project on that particular day.
The human factor in optimising resource allocation in business process models
Another level of complexity arises from the human factor involved in determining the length of individual tasks. It is well known that when our boss asks how long it will take us to complete a particular task, we tend to demand significantly more time than is strictly necessary to protect ourselves. It is exacerbated by multitasking (the tendency to do more than one thing simultaneously). Multitasking is great for computers but counterproductive for the human mind. At last, there is the effect of the student syndrome. It means that you always put it off until the last minute whenever you have more time to do something.
Role of AI (Artificial Intelligence) in resource allocation
With the help of AI, businesses can optimise resource allocation applications and strategies. It can improve efficiency, enhance decision-making, and high-cost savings. AI helps the business in predictive analysis, which uses machine learning algorithms and historical data. It allows organisations to foresee future demands, resource requirements, and trends and make informed decisions to distribute their resources efficiently. AI can predict customer demand, reduce waste, improve customer satisfaction, and increase sales.
AI also assists in intelligent automation to streamline different tasks and procedures. AI can automate daily tasks like report generation, inquiries for customer service, and data entry. It enhances employee efficiency, retention, and satisfaction as they can concentrate on more high-value and complex tasks.
Conclusion
Resource optimisation enables companies to maximise employee potential and improve efficiency in business process models. Infosys BPM’s digital transformation process can help with the above techniques to allocate resources to the right projects to ensure optimal utilisation and increase engagement and productivity. Plus, paired with the right resource management software, it can ensure profitability and sustainability.
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