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How to Improve Efficiency In A Business: Optimising FTE Capacity Levels with Process Simulation
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How to Improve Efficiency In A Business: Optimising FTE Capacity Levels with Process Simulation

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Many companies exhibit significant fluctuations in demand, particularly those in retail, hospitality, and healthcare. However, McKinsey shows that common corporate functions such as customer service and delivery exhibit the same problem across industries: meeting customer expectations without holding expensive excess capacity. Companies walking this tightrope will benefit from faster processes, better customer satisfaction, increased revenue and lower costs. However, companies will leave revenue on the table when moving too far off the optimum or face lower margins. 

This blog illustrates how Silico’s Business Process Simulation platform can be used to develop a Digital Twin of business processes that can forecast staffing requirements and will show you how to improve efficiency in a business, optimising your FTE capacity levels.

The Value and Impact of Good Capacity Management

A company’s operational goals should support its strategic business objectives. For example, some businesses pursue cost-leadership strategies, while others strive to differentiate, for instance, through superior customer service. Effective capacity management can support either strategy or even contribute to differentiation while lowering costs through numerous benefits:

  • Employee satisfaction: Good capacity management ensures that employees are neither underutilised nor overworked. They are engaged in their jobs without getting burned out, challenged and interested but not overstretched.
  • Employee turnover: With greater employee satisfaction comes reduced turnover. This decreases a company’s hiring and onboarding costs and supports its cost leadership strategy. Moreover, reducing employee turnover also maintains the specialised knowledge of employees in a business required to differentiate.
  • Productivity improvements: With greater satisfaction and engagement in their roles, productivity and business efficiency increase, just as it does when knowledge is maintained, and existing employees spend less time hiring and training new ones.
  • Revenue improvements: With sufficient capacity, customers are serviced within their service level agreements or other acceptable timeframes, improving customer satisfaction, retention, and long-term revenue. Improving the capacity of, for example, an order-to-cash process also improves revenue directly by ensuring that orders are delivered as quickly as possible to move revenue and cash flow forwards.
  • Cost reductions: Removing excess capacity ensures your organisation achieves the above benefits at minimal excess capacity, idle time, and costs.

Supporting Capacity Management using Digital Twins and BPS

The central task of capacity management is matching processing capacity to fluctuating demand levels. Business Process Simulation can simulate Digital Twins of your processes in forward-looking scenarios in five steps to optimise your FTE capacity levels:

  1. Model the as-is process: Firstly, BPS creates a Digital Twin of the process for which a company wants to optimise capacity levels. In a series of blog posts, we have shown how quickly and easily Process Twins can be developed based on existing resources such as process maps. An advanced BPS platform like Silico can automate this process by importing, for example, process maps or mining outputs to create the structure of a Digital Twin of your process.
  1. Understand the current state of the process: Once we have the structure of the process right, we need to quantify it by setting input values. Those inputs include variables like the manual handling times for activities and tasks. They also include the current queues and backlogs at each process step. The higher these queues are and the earlier they are in the process, the higher the capacity required to get a new case done in a target time - assuming FIFO, first-in-first-out. Such backlogs are often ignored in simple forecasting with Excel spreadsheets, leading to improved capacity management using simulations. With data integrations to your existing systems, Silico’s BPS platform can update your Digital Twin with those data points in real-time and without manual effort.
  1. Develop scenarios: Once your Digital Twin is developed and set up to reflect the current state of the process, your decision-makers create forward-looking scenario planning models. For example, what growth rates are the sales team expecting over the next six months? Are we expecting seasonal factors such as holidays to affect demand over our forecasting period? Because we cannot predict the future accurately, it is important to explore many scenarios and their consequences for capacity requirements.
  1. Forecast demand: Good Business Process Simulation does not just cover your focal process but extends beyond it, for example, to reflect the case volume likely to emerge in the forward-looking scenarios. Take forecasting capacity in an order-to-cash process; reflecting the order-to-cash process itself and the influences on new orders is critical. These may be the orders in your sales funnel, your marketing activities, or opportunities in your lead-to-order process. Modelling the structure of these and how the scenario inputs affect case volumes allows BPS to forecast future case volumes.
  1. Identify capacity requirements: Based on the current backlogs and queues, forward-looking scenarios and resulting demand forecasts, capacity requirements can be identified that match your specific business requirements. For example, capacity can be optimised to minimise excess capacity costs, complete a new case within a target lead time, or balance those two goals appropriately for your company. Depending on your business priorities, BPS allows you to ensure your processes support your strategic business objectives.

Capacity Management as Part of your Transformation Journey

Transforming processes and their resulting capacity requirements and management are tightly linked, and both coexist in a circular feedback loop. 

Past transformation activities influence today’s capacity requirements as they determine what is currently in the process and how productive employees are. Therefore, the first two steps to managing capacity using BPS are reflecting the structure of your process and capturing variables about it. Using Digital Twins operationally, for example, for capacity management, ensures that you put your company on a path from process to operational and business excellence.

However, operators and process owners may also trigger new improvement cycles based on their capacity requirements. For example, if we expect growing order volumes, capacity requirements may exceed budgets, and process improvements are required to achieve more with the same FTE resources. A Digital Twin of the process can inform when to engage transformation and improvement teams. The transformation team can then use the Digital Twin to ensure their process improvement activities have maximal benefit in minimal time.

Ensure your Process can Support your Strategy!

Make sure your company optimises the capacity of your processes to support your strategic business objectives. Silico can build Digital Twins of your processes in as little as 4 weeks and show you how to unlock cost savings, as well as revenue improvements, employee satisfaction and customer experience improvements with minimal effort, time, and costs.

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