Resource Allocation Optimisation - How to optimise your Resource Allocation Using Business Process Simulation

Introduction

Dynamically allocating resources, such as FTE capacity and available budgets, profoundly impacts companies’ performance. McKinsey identified that companies who are optimally allocating resources achieve shareholder returns a third higher than those who reallocated less. Over 20 years, such return differences make agile reallocators worth more than twice as much as their rigid counterparts. Yet, despite the importance of allocating resources to where they are needed, many executives struggle to identify the optimal use of limited resources. With the benefits of resource allocation optimisation in mind, this blog describes how Business Process Simulation (BPS) with Digital Twins can ensure that your company uses resources optimally.

The Importance of Resource Allocation

In a previous blog post, we discussed how BPS and Digital Twins of processes can quantify capacity requirements in five simple steps, ensuring your processes can cope with the expected case volumes. Ideally, companies are adequately resourced to cope with demand. However, companies may be possible in practice. For example, companies may be constrained by budgets or need more lead time to mobilise additional resources. Therefore, reallocating existing resources is imperative.

A vast majority of senior executives understand this resource allocation importance intuitively. In a McKinsey survey, 83% identified resource allocation as the most critical managerial lever to accelerate company growth. When resources are constrained, being able to shift them between regions, products, markets, or projects can unlock capacity for growing segments while avoiding costly idle time in others.

Resource allocation becomes even more important in economic downturns when budgets are trimmed, and increased uncertainty prevents significant investments. Using limited resources efficiently and effectively reduces waste and costs, can drive revenue and customer satisfaction, and, thereby, mitigate the impact of an economic downturn. The best reallocators may even use a downturn or crisis to invest in growth opportunities at lower prices to maximise their ROI.

Overcoming Resource Allocation Challenges with BPS

Despite many executives agreeing that resource allocation is a critical driver of performance, they need support to make and implement decisions based on data, facts, and logic. BPS is a method to produce Digital Twins of processes that users can simulate to make decisions including optimal resource allocation.

In many organisations, budget discussions are not based on a new assessment of requirements but on the past year’s budget. Instead of using previous budgets as an anchor, Digital Twins can identify the resources required to achieve processes’ objectives based on their current state and forward-looking expectations, such as process changes and case volumes. Thereby, decision-makers can identify budget requirements for future circumstances, not repeat past decisions.

Teams’ incentives and overconfidence also hinder some organisations from allocating budgets appropriately. Sales teams can be, for example, notoriously optimistic about their forecasts. Similarly, managers responsible for products or segments may be protective of their budget and employees. Imagine allocating employees to teams, activities, or tasks in an order-to-cash process. Taking optimistic forecasts at face value may lead to the overallocation of budgets to the process or certain activities at the expense of others. Digital Twins with advanced simulation capabilities allow decision-makers to experiment with multiple scenarios, such as different volume forecasts, and identify their impact on the optimal resource allocation.

Similarly, BPS twins can connect multiple processes to build a Digital Twin of the Enterprise (DTE). For example, opportunities in a lead-to-order process may inform capacity decisions in an order-to-cash process by providing a more realistic forecast of volumes based on the current pipeline. Decision-makers can counteract overconfidence biases by connecting processes and experimenting with various scenarios.

Decision-makers may also struggle to adapt to changing circumstances as they emerge. While companies may run an annual and quarterly budgeting process that triggers resource (re)allocations, those processes are long and drawn out. Moreover, decision-makers may need more scope to react to ad-hoc changes or can only do so after long decision-making processes. Often, such decision-making processes involve instructing a team of analysts to collect data from numerous sources and teams, build new models of the business based on it, analyse different scenarios, and report their findings in a meeting weeks later. With a Digital Twin of their business, all the data needed to make decisions and experiment with different scenarios are available straight away, short-circuiting the decision-making process and ensuring they can react to changes faster than their competitors.

‍

Examples of Resource Allocation Using BPS and Digital Twins

Depending on the process and the other elements of the business that a Digital Twin represents, BPS can aid resource allocation optimisation in many cases. Some examples among many other (interrelated) use cases, include:

• Ensuring sufficient capacity across your different teams and allocating budget over them most effectively. For instance, as part of capacity planning over the next quarter.
• Allocating employees or FTE capacity to activities and tasks in a process to maximise throughput.
• Simulate business resources to generate forward-looking analytics through AI-powered ‘what if’ scenarios that demonstrate the impact of changes to individual processes on the organisation, as demonstrated by the work Silico conducts in partnership with Arcwide.
• Optimising healthcare processes, clinical pathways, and capacity levels to help services run more effectively and reliably, and achieve better patient outcomes, as Silico does in partnership with Strasys.
• Allocate resources, including limited budgets and transformation team capacity, over the process improvements with the highest ROI.
• Optimise the capital tied up in, for example, inventories to free up budget for other projects and required resources and manage supply chains better.

Maximise Your KPIs with Better Budget Allocation

Don’t just be among the companies that double their value by reallocating more resources - ensure you allocate resources optimally using Business Process Simulation and Digital Twins to outperform your competitors. Start making data-driven decisions that optimise your resource allocation to maximise KPIs! With Silico as your partner, you can get there in as little as 4 weeks.