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Inefficient workflows, tool sprawl, lack of visibility — three terms that can keep business leaders up at night.
Stagnant processes spur a chain of negative consequences, from wasted resources to low-quality outputs and loss of consumer trust.
But companies can prevent dispersed and ineffective processes by taking an honest look at where workflows fail — and pivoting.
Here, learn how to implement process improvement initiatives, and find out how Scribe’s Workflow AI can help you pinpoint and automate efficiency-driving change.
What is process improvement?
Process improvement implies analyzing the efficiency of current workflows and changing them as needed. The goal is to identify potential bottlenecks or quality issues and refine processes, streamlining work and driving better outcomes.
Process improvement hails from the manufacturing world, but now, other environments like IT, HR, business operations, finance, customer service, and supply chain implement these practices.
Key benefits of process improvement
Organizations that perform systemic process improvements save time and resources. They also achieve better customer satisfaction.
Improving your organization’s reputation, resource use, and outcomes are convincing reasons enough to implement process improvements. But this best practice is crucial for contemporary organizations for a few more reasons, as well.
Today, with the constant advent of new digital tools, companies have the opportunity to scale at lightning speed. But businesses must be agile enough to correctly adopt new technologies, powering up business processes, and staying on par with (or, better yet, ahead of) the competition.
Before introducing new technologies, like AI automation, companies should already have highly functional workflows that these tools can support. Trying to layer automation on top of a broken process is wasted effort. Instead, start by improving the underlying workflow.
Process improvement (especially with a boost from AI analytics tools) also helps businesses make better decisions. When organizations collect information on current processes, they can suggest data-driven — instead of intuition-based — plans and pivots.
How to get started with business process improvement
Companies that don’t perform process improvements fall behind. They can’t successfully implement new technology or reasonably keep up with organizations that are constantly leveling up.
Become one of those ever-improving, always-ahead-of-the-curve businesses with the following few steps.
1. Identify high-impact workflows
First, assess your current workflows, identifying the most high-impact ones, as you’ll build your improvement efforts around them. Often, these are the workflows that have a significant effect on business outcomes and imply the involvement of various stakeholders and departments. For example, major IT development projects are high-impact workflows.
Need a guide to get started? A SIPOC template can help. In this visualization, you map high-level business workflows, identifying suppliers, inputs, processes, outputs, and customers (or end users). You can also use Scribe Optimize to identify high-impact processes for you; this tool provides data-based insights on where you can be more efficient, so you don’t have to guess.
2. Capture and map current processes
Once you’ve pinpointed the companies’ most essential workflows, map all the existing processes within them. For example, a fulfillment workflow contains processes like invoicing and payment processing. An onboarding workflow comprises steps like data entry and employee training.
The more attention to detail in this stage, the better. Never assume that a process doesn’t need review because it’s small or seemingly unimportant. In order to spot areas of improvement, you need the most comprehensive process view possible. You can speed up and increase the accuracy of this step with Scribe. With AI-driven analytics, Scribe maps processes for you and shows you where to prioritize improvements.
4. Analyze bottlenecks and root causes
Identify the slowest parts of the processes you’ve mapped. Some organizations think of this step in terms of the Theory of Constraints (TOC) — that is, finding the roadblock that limits workflow. Constraints or slow steps are your bottlenecks — places where work stalls before being able to move forward.
Then, pinpoint the root causes of these setbacks. Commonly, bottlenecks stem from lengthy approval processes, unwieldy information hand-offs, and inefficient tools or tech.
Take the guesswork out of identifying slow processes and root causes by leveraging AI analytics. Scribe highlights bottlenecks and provides data-driven insights on the root causes.
5. Design and implement improvement plans
After identifying process setbacks and causes, you’re ready to suggest potential solutions. If using Scribe’s Workflow AI, you already have a leg up. This tool gathers real-time data on potential bottlenecks and generates AI-driven recommendations for process changes.
However you go about creating process improvement initiatives, one thing is true: All of your decision-making should be based on data, not on instincts. In other words, run the numbers. How much time will your fulfillment team save by automating invoices or upgrading to faster tools? What is the value-add of the projected changes for the organization in the short and long term?
Once you have a clear, well-researched path forward, implement your new processes. Ensure that leaders and employees are clear on changes and have adequate training for using any new tools or workflows. This way, they can help, not hinder, process improvement projects.
6. Measure impact and iterate
After you streamline processes, monitor progress. Leverage analytic tools, like Scribe’s Workflow AI, to track KPIs, outlining improvements or issues with the new process implementation. Workflow AI consistently measures data, like how long team members spend using a certain application or how often they must jump between tools to complete a single task, giving you clear metrics on how work really happens.
New processes may not be perfect at first, and iteration is normal. When you use Workflow AI, you’ll be able to quickly pinpoint any issues in implementation and leverage the tool’s data-based insights to shift course.
7. Build a culture of continuous process improvement
Process improvement isn’t just procedural; it’s cultural. Train leaders and team members on continually looking for ways to optimize processes. Introduce them to the Kaizen method—the Japanese business philosophy of continual process improvement—or Total Quality Management (TQM), which invites employees at all levels to suggest changes to better meet customer needs and boost output quality.
Fostering a culture of continuous improvement means encouraging a safe environment for people to speak up. Leadership should actively listen to employees’ concerns on where processes stagnate, ready and willing to implement changes.
Common process improvement methods
Several key process improvement techniques originated in the manufacturing sphere but apply to all types of business models, including contemporary digital ones. Here’s more on some of the most popular frameworks.
- Lean: Lean, or just-in-time production, focuses on reducing waste driven by mistakes, overproduction, long wait times, low productivity, and poor inventory management, among other inefficiencies. Organizations performing lean manufacturing or production aim to spend resources only on value-added activities and constantly analyze workflows to spot wasteful processes.
- Six Sigma: Six Sigma is a manufacturing quality control initiative that applies well to intangible products, as well. This methodology aims to reduce variations (a.k.a. defects) in end products using two improvement initiatives: DMAIC (define, measure, analyze, improve, control) for existing processes and DMADV (define, measure, analyze, design, verify) for new processes.
- PDCA (Plan-Do-Check-Act): The PDCA cycle is an iterative process improvement methodology, comprising four steps. Businesses plan a change, execute it, monitor its effectiveness, and implement changes as needed.
How Scribe simplifies process improvement
Scribe’s Workflow AI is your partner in problem-solving, leveraging artificial intelligence to help teams gather, analyze, and optimize processes automatically and quickly. Workflow AI helps you:
- Gain visibility: Through process mining, task mining, and workflow mining, Workflow AI captures data on how work really happens. Process mining gathers system record information (i.e., from your CRM), task mining tracks individual user activity (like clicks and micro-steps), and workflow mining maps how work moves between tools. Analyzing this data, Workflow AI pinpoints and surfaces process inefficiencies.
- Prioritize with data: Workflow AI helps strategize solutions for the most urgent process changes, maximizing impact.
- Drive actionable change: Workflow AI harnesses the power of artificial intelligence to suggest process improvements. And it constantly reviews the efficiency of these new processes, iteratively suggesting further changes.
Common mistakes and how to avoid them
Process improvements can lead to a boost in operational excellence, but only when performed with intention and strategy. The following are a few key pitfalls to avoid, ensuring your process analyses actually result in improvements.
- Introducing tech too soon: Automation won’t be able to do much if workflows are broken. Uncover and improve bottlenecks on high-impact processes before introducing automated tools. Scribe’s Workflow AI finds clunky workflows, tells you what’s causing them, and suggests improvements—-allowing you to quickly transform inefficiencies. Then, you can implement automation, speeding up work even further.
- Not taking feedback from team members: Data gives great insights, but so do people. Stakeholders in current business processes have first-hand knowledge of how work really plays out, and can provide valuable feedback on inefficiencies.
- Not monitoring progress: Often, positive change is the result of several iterations of an improved process. Companies must monitor the success of new processes and switch course as needed.
What’s the difference between process improvement and automation?
Process improvement refers to optimizing workflows, removing bottlenecks, and maximizing time and resources. Automation is a technological tool for organizations to successfully run process improvement initiatives. These AI tools streamline redundant, time-consuming work—like automating payroll processing.
How often should teams revisit their workflows?
Constantly. Process improvement is an iterative process. Use Workflow AI to continually monitor for inefficiencies and implement changes.
What metrics should I track to measure improvement?
Track KPIs for resources (like time or funds saved), quality (like customer and employee satisfaction), and operations (like productivity or error rates).
Can AI tools fully replace traditional process mapping?
No. Organizations still rely on human input. Team members have valuable first-hand process feedback from their on-the-job experience that can shape positive change. Business leaders leverage data to make informed process improvements, and employees integrate these shifts into their daily tasks.
