Capacity-planning-feature-OverIT

Capacity planning

Build smart, data-driven plans that anticipate demand and optimize resource allocation using historical data and predictive insights!

Operations managers and planners are hardwired to think ahead, anticipating future challenges. This approach entails preparing for predictable peaks, addressing fluctuating demands, and gearing up for unexpected disruptions. The key to navigate these complexities lies in effective capacity planning, which ensures the efficient allocation of resources, optimized performance, cost control, and sustained organizational resilience.

Challenges

The planning of maintenance and operational activities on linear assets such as electric grids or gas pipes demands diligent coordination and foresight. These assets undergo a range of activities throughout the year, including routine inspections, scheduled upgrades, and other recurring tasks, that can be subject to unforeseen disruptions, due to sudden changes in weather conditions, equipment failure, and emergencies.

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This could be the case of a utility company facing increased demand for repair crews during summer storms, while also struggling to complete scheduled transformer maintenance prior to peak power consumption periods.
Whenever the planning process relies on traditional tools like excel files or sheets, complications may add up. In fact, such an approach is prone to generating errors, inefficiencies, and time losses.
For instance, manual data entry and update is tedious and often leads to inconsistencies or mistakes, such as misallocated resources or missed deadlines. Poor planning is likely to increase the risk of overstaffing or understaffing, which ultimately results in higher costs and can lead to operational delays that could disrupt critical services or cause service outages.

Solutions

This is where capacity planning comes into play. The new feature combines historical data and predictive insights to create a detailed, data-driven plan that anticipates demand and forecasts future needs, ensuring that the right resources are available at the right time. Moreover, whenever dealing with ongoing changes, the system allows for automatic re-planning, enabling managers to adjust the plan in real time without having to re-run the entire scheduling process manually.

Data-driven planning

Operations managers can review historical activity data from previous years, such as routine maintenance schedules. This data helps identify recurring resource and task demands, providing a solid foundation for the planning process. For instance, trend analysis helps managers to predict periods when certain tasks will require the greatest effort in terms of manpower. Additionally, the system considers the specific skills required for each type of task and its categorization (e.g., maintenance, repairs, inspections).

Skill-based allocation

Each task gets mapped with the greatest accuracy, based on its priority (critical tasks are scheduled first), required skills (expertise is what rules the assignment of a technician to a specific task). This could be the case for tasks in mountainous areas, that might require technicians trained for rugged terrain and vehicles equipped for challenging weather conditions.

Real-time simulations

Operations managers can create “what-if” simulations for potential expansion projects, unforeseen events, or emergency scenarios, such as a major storm or sudden equipment failure. These simulations help estimate workloads and prove strategic in testing the flexibility of resource allocation, preparing the company for unexpected peaks in demand. Let’s assume, for example, that a major storm is approaching: the tool is capable of simulating the need for additional repair crews, thus allowing managers to adjust their workforce plans in advance. Additionally, the system supports managers in comparing different scenarios to identify the most effective one based on pending tasks and available resources. 

Identifying any potential gaps between available capacity and planned / expected demand

The system will clearly display visual alerts whenever capacity falls below planned demand, enabling managers to quickly identify areas at risk. This proactive approach translates into timely decisions to optimize resources, plan capacity increases, or explore alternative solutions.

Workload analysis

Managers can assign higher weights to tasks that are critical at a given time of the year, ensuring they are prioritized at the exact right moment. Conversely, less time-sensitive tasks are given lower weights and are scheduled in periods of reduced demand.

Benefits

Enhancing resource optimization
Increasing cost efficiency
Improving decision-making through data-driven insights
Streamlining the planning process
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