01 Dec, 2020 | Blogs
A perfect business process is vital for the success of a company. However, having a perfect process is easier said than done. Most organizations are prone to broken business processes, which cost huge losses in terms of time and money. Moreover, identifying the exact problem is also a challenge and doesn’t include a sure-shot formula. Therefore, in this article, let’s look at process improvement as a methodology or a framework that enhances both efficiency and productivity.
What is Process Improvement?
Process improvement is a business practice to identify, analyze, and improve existing business processes. It is a trusted methodology to optimize performance, follow best practice standards, improve quality, and enhance the user and customer experiences. Process improvement goes by several names, including business process management (BPM), business process improvement (BPI), business process re-engineering, continual improvement process (CIP), etc. Irrespective of the nomenclature, the end goal is the same: reduce or eliminate errors, increase productivity, and streamline efficiency.
Process Improvement Techniques
Process improvement includes several techniques, each of which has a unique way to pinpoint process issues, fix them, and measure the success or failure of the implemented changes. They are selected based on the needs of the company. For instance, some methodology focuses on lean process improvement techniques while others help businesses visually map out workflows. Let’s look at the five most popular process improvement frameworks:
One of the most popular frameworks, Kaizen ensures continuous improvement by focusing heavily on lean and agile practices. Kaizen stresses enhancing quality, productivity, and efficiency by making small changes in daily work aimed at fostering a culture that prevents errors from happening.
Born out of Kaizen and Lean methodologies, the 5S model, as the name suggests, includes five main steps: Sort, Straighten, Shine, Standardize, and Sustain. The 5S model is used to create consistency in process improvement and standardize it.
Six Sigma is another popular methodology that involves two broad steps to break down process improvement. It uses karate belt ranks to pull up workers, starting with the Green Belt until the highest, Black Belt. Six Sigma comprises two approaches: DMAIC and DMADV. DMAIC has the following steps: defining, measuring, analyzing, improving, and controlling, while DMADV includes defining, measuring, analyzing, designing, and verifying.
To get employees, leadership, and business units on the same page, Kanban is used for process workflow visualization. It is a popular tool that incorporates and promotes lean process improvement.
Similar to Kanban, process mapping is another workflow visualization method that helps organizations create a plan to improve processes. It is also called Process Flowchart, Process Chart, Functional Flowchart, and Process Model. This framework aims to create a flow diagram that provides critical information about a process workflow from the beginning to the end.
Role of Automation
The advent of digital transformation technologies has made automation an integral part of process improvement. That is because automation provides one of the easiest ways to improve efficiency and productivity by eliminating manual work and lowering human error.
Robotic process automation (RPA) is being heralded as the next big thing in process improvement. RPA is a computer-coded bot that captures and interprets applications for various activities such as processing transactions, manipulating data, triggering responses, and interacting with other legacy systems. It differs from traditional systemic automation since the bot can replicate human actions by running through the processes and communicating with other applications.
Difference between RPA and Excel Macros
While RPA aims to improve processes by reducing human involvement, its implementation must be focused, since it delivers maximum benefits to processes with two main characteristics. These characteristics are structured data and the type of tasks (complex or simple).
Processes with structured data and simple tasks such as insurance claims processing, customer account management, and client data migration are ideal candidates for RPA. In the case of complex tasks and unstructured data, cognitive RPA is deployed to handle complex business rules with several escalation pathways. Cognitive bots use learning algorithms to continuously learn and adapt to multiple inputs.
Some functions and areas where RPA can be implemented are finance and accounting, human resources, banking, insurance, healthcare, retail, and telecom. Common process improvements that are automated through RPA are automated email responses, accounts reconciliations, categorizing helpdesk tickets, online order processing, data transferring between systems, and payroll management.