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4 Steps to Achieving Your Process Improvement Goals with Silico
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4 Steps to Achieving Your Process Improvement Goals with Silico

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Introduction

There is no doubt that businesses see process improvement as an essential focal point. Companies that implement process improvement initiatives see an average of 30% improvement in key performance indicators such as cost, quality, speed and customer satisfaction. Therefore, monitoring process improvement is critical to sustaining process change and course-correcting where necessary in your organisation.

In a study by the Management Consulting Group, organisations that successfully implemented process improvement initiatives saw an average increase in revenue of 18%. In this blog, we will explain ‘what is business process improvement’, take you through the benefits of improving your processes, and discuss the importance of correct process improvement implementation. We will explore the popular tools and methodologies used for process improvement and explain how Silico can help you achieve and exceed your process improvement goals. 

What is business process improvement? 

Gartner defines Continuous Process Improvement as:

“A methodology for improving production, driven by formal metrics and measurement programs, including methodology upgrades”

There are many ways to achieve process improvement. For example, it could involve increasing an existing process's efficiency by reorganising its steps' order more efficiently. It can also include adding or removing stages of the process via a digital transformation. Digital Transformation can involve automating certain process steps with technologies such as Robotic Process Automation (RPA). 

What are the benefits of using process improvement?

The benefits derived from process improvement differ depending on the type of process being improved and the method used for the process improvement. For example, increasing the speed of an order-to-cash process will help improve a business’s cash flow and, subsequently, customer satisfaction. Automating parts of a procure-to-pay process will likely reduce costs and result in a more resilient supply chain. Whereas, increasing the efficiency and effectiveness of a car assembly line will result in lower costs, fewer product defects, increased customer satisfaction and increased profits in the short and long term.

However, if successful and conducted strategically, all process improvement initiatives will help improve the organisation's efficiency, which boosts long-term profits and market share. However, deciding which processes to focus on, and which improvements to make is far from obvious. That is where Silico, the Business Process Simulation tool comes in. 

Popular tools and methodologies for process improvement 

Many methods and SaaS tools exist to spur businesses towards process improvement. Below are just a few of those:

Six Sigma: Uses data and empirical and statistical tools to analyse deficiencies and drive improvements, particularly in the manufacturing industry. 

Lean: Where the focus is to reduce waste and use the fewest resources to achieve the end product. 

Agile: Developed among software development teams, the agile approach involves bringing cross-functional teams together to work in short production cycles called sprints to improve or add technology features and functions to enhance a business processes.

Theory of Constraints: Enables managers to identify the most significant constraint currently blocking improvements or organisational objectives and then focus on process improvement until that constraint is no longer an obstacle.

While these methods can help identify specific ways to improve processes, they do not offer a validated or scientific way to evaluate which specific combination of process improvements will deliver the highest ROI for specific KPIs. Silico can help you to remove this obstacle.

How can Silico help you achieve your process improvement goals?

Approximately 70% of process improvement initiatives fail to achieve their desired results, often due to a lack of efficient or proper planning or support from senior management. Silico offers these teams a way to create Digital Twins of Processes (or “Process Twin”), which allow them to simulate process improvements before enacting them in reality. This allows the team to choose the combination of process improvements that will deliver the highest ROI. After this transformation stage, the Process Twin can also be used to foresee issues with the process ahead of time, and allocate resources accordingly. 

Above: an example of a Process Twin of a simple order delivery process, run under a scenario with and without partial automation of the “order reviewing” stage

A dashboard of the previously mentioned model, which provides decision-makers a way to see the ROI of automation under different scenarios for order volume and staff availability.

You can read more about our Process Digital Twins and their evolution in this Teiss article.

Here are the 4 steps to process improvement with Silico:

  1. Creating a Process Twin of the As-Is process (optional)

Some process improvement teams may start by creating a Process Twin of the As-Is process. This helps them to demonstrate the need for process improvement. Suppose a team was to build a Process Twin of an Order to Cash process. They could simulate how growing order volume will increase the need for FTEs or process efficiencies if certain KPIs are to be met. 

  1. Creating unlimited numbers of To-Be processes 

Once the need for a process improvement has been identified, the Process Twin can be adapted to show how specific changes to the process will impact the KPIs resulting from the process. For example, teams could simulate how introducing a particular ERP system might reduce processing times and the number of FTEs needed for the process, or how removing/adding specific steps to the process might affect backlogs. Crucially, Process Twins allow you to evaluate these changes from an end-to-end perspective. For example, automating one step of a process will help reduce backlogs and lead times, or if it will simply shift a backlog from one step to another. 

  1. Monitoring the implementation of the chosen process

Once the process changes with the highest ROI have been chosen, the Process Twin can then serve as a blueprint for how the implementation of those changes is expected to go. This is given from the perspective of changes in certain KPIs (such as revenue or lead time, for a given order volume) and intermediary variables (such as backlogs). By integrating the Process Twin with live feeds of data from relevant databases (such as ERP or CRM systems), process owners can identify where the implementation is going off track. The Process Twin can then simulate different corrective actions, to help identify the right one.

  1. Simulating recurring management decisions

The Process Twin continues to deliver value long after the transformation and implementation stage. With a Digital Twin of the Process, process owners can simulate how, for example, projected order volume will impact the resources (staff, etc,) required to manage the process and maintain KPIs at a certain level. They can also use Silico’s optimisation feature to identify the optimal allocation of resources along the different steps of a process so that KPIs are achieved as efficiently as possible. 

Conclusion

Business process improvement initiatives are essential in today’s hyper-competitive marketplace. While there are plenty of methods for identifying ways to improve a process until now there has not been a way to scientifically evaluate which process improvements will deliver the best results. This has now changed. By creating a Digital Twin of a process, process improvement teams can evaluate which process improvement initiative will deliver the highest ROI. Having this evidence-based framework for decision-making not only leads to the best possible decision, but it also fosters buy-in from stakeholders, which becomes essential for the implementation stage. Beyond transformations, Silico’s Process Twins can also help process owners to manage the new To-Be process in the most efficient way possible, getting foresight of capacity constraints and allocating resources in the most efficient way possible. 

A study by the Institute for Healthcare Improvement found that hospitals that implemented process improvement initiatives saw an average reduction of 30% in hospital-acquired infections, 50% reduction in patient falls, and 40% reduction in medical errors. This highlights the importance of process improvement initiatives and the cruciality of proper implementation, with next-level process simulation technologies like Silico. The action of process improvement and creation of Process Digital Twins in Hospitals is being catapulted into a new era, with initiatives led by people like Silico and Strasys to optimise processes in Hospitals with Digital Twin technology.

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