The landscape of enterprise organizations continues to evolve, and operational efficiency has become non-negotiable. Achieving operational efficiency is crucial for businesses to remain competitive, reduce costs, streamline processes, and provide quality products and services to customers. In this pursuit, automation tools offer the potential to amplify operational efficiency strategies and empower enterprises to transform the way they work.
Operational efficiency involves optimizing workflows and task execution for greater speed and productivity with direct cost reductions and better use of working capital when supported with automation tools. When operational efficiency is implemented for greatest effect, organizations can reduce the cost of full-time employees, minimize contract work, enhance collaboration between teams, and ensure consistency in output.
To prevent lackluster outcomes, carefully evaluate automation tools for the specific needs and goals of your business. Let’s explore how you can define success, measure impact, and select the right automation tools for improving operational efficiency.
Define Success with Key Performance Indicators
It’s impossible to know how effective any tool is if there are no established expectations for performance. Measuring operational efficiency begins with defining what success looks like. Benchmark where your performance stands now, so you can review against operational efficiency metrics and track progress over time. For example, if your goal is to improve inventory management, you would track inventory turnover ratio, accuracy, stockout rate, and sales over a set period of time to determine if you’re accomplishing that goal.
Not all tools are created equal, and some may excel in specific areas while falling short in others. While considering automation workflows, take a holistic approach and identify automation opportunities across the entire value chain. Conduct thorough research to understand the capabilities of various automation tools and how they may support significant, sustainable improvements by creating synergies between different functions.
A fundamental feature of automation tools is their capability to interact with and generate vast amounts of data. When analyzed properly, this data can extend services associated with products, enable strategic decision-making, and provide opportunities for continuous optimization.
To measure operational efficiency, consider the company’s larger goals and how operational efficiency can help achieve them. Once you have outlined specific, measurable goals, tie them to key performance indicators for operational efficiency. These KPIs will quantify and provide an objective view of how well automation tools are contributing to operational effectiveness.
Steps for Selecting Automation Tools
Having the right tool for the job is essential to any task. Here’s how to make sure you’ve got what you need to effectively pursue your operational efficiency goals.
1. Evaluate existing processes to identify areas for automation.
Resource utilization, production, inventory management, and distribution should be prioritized for enterprise automation. Consider where there are bottlenecks and where waste can be reduced. This is also an ideal opportunity to review which outcomes have high error rates because of fatigue, repetition, or inattention.
2. Consider scalability, flexibility, and integration capabilities.
Many processes can be expedited when they’re not restricted to human scale. Automation tools are well suited to manual data entry and tasks with predictable, set outcomes.
3. Consider organizational maturity.
Start with easily adaptable technologies to establish best practices for operational efficiency. Then assess if your goals require more complex solutions to scale and expand further.
4. Prioritize user-friendliness and minimize training requirements.
This step not only facilitates smoother implementation but also ensures that employees can quickly integrate new technologies into their daily workflows. Both internal and external user-friendliness contribute to the success of an automation tool, making it critical to reduce workload and enhance the overall customer experience.
5. Ensure security, compliance, and regulatory adherence.
Secure data collection must be a priority, and datasets should be accurate for systems to be reliable. Before you rush to decommission legacy systems, ensure new automation tools can maintain industry standards and be implemented with strict adherence to regulatory compliance for data protection, collection, and ethical use of sensitive information.
6. Evaluate vendor support and reputation.
Research technology partners and the automation resources they offer, such as support for maintaining data integrity, data breaches, and monitoring systems for accuracy. Providers’ reputations with clients and competitors will also speak to their credibility.
Automation Tools for Operational Efficiency
Rather than relying fully on a single tool, using a combination of tools to complement one another is often the best way to optimize operational efficiency. These are some low-code technologies and solutions that are frequently used for strategic automation of workflows.
Process Mining
This technology monitors and analyzes processes with data from event logs and related systems. It can use existing data to create a realistic picture of your operational efficiency and visualize how to improve physical workflows and resource allocation.
Effectively, Process Mining identifies the distance between where you are and where you want to be, providing a topographical map of your process executions and functional efficiency, highlighting where to change elevation, reroute pathways, or add new infrastructure.
Robotic Process Automation (RPA)
This software technology uses digital bots to replicate traditionally manual tasks with much greater speed and accuracy. Because these bots follow rules-based programming to emulate human counterparts, they can be implemented for dramatic scalability without fatigue. RPA streamlines time-consuming workflows such as invoice and payment processing, compliance auditing, detecting fraud, scheduling, and forecasting.
Artificial Intelligence (AI)
AI encompasses a range of technologies that interact to simulate the problem-solving capability of the human mind. This technology augments employees’ efforts with intelligent, interactive processing algorithms to forecast and identify patterns in large datasets. This technology takes RPA further for more sophisticated situations such as:
- Managing extensive, document-heavy workflows into a streamlined ecosystem with fewer errors and greater velocity.
- Supporting customer self-service with conversational AI that leverages Natural Language Processing (NLP) and Natural Language Generation (NLG).
- Making real-time decisions for revenue and compliance with actionable, live insights on data.
Machine Learning (ML)
This subset of Artificial Intelligence enables systems to progressively improve understanding and interpretation of data beyond simple programming. Machine Learning improves accuracy as more data is provided, and it enables nuanced insights for innovation, predictions, and acceleration of processes.
This technology can be applied for sales forecasting, fraud detection, medical diagnosis, voice recognition, and Natural Language Processing.
Document Understanding (DU)
This technology within Artificial Intelligence focuses on the processing of unstructured data. It reads documents in any format, including handwritten notes.
These intelligent workflows have significant applications for high-volume processing with minimal review, including contract analysis, compliance documentation, text extraction, and classification of data.
Intelligent Process Automation (IPA)
IPA combines several advanced technologies to automate complex, end-to-end processes that require decision-making and data analysis. Intelligent Processing Automation leverages capabilities such as Robotic Process Automation (RPA), Artificial Intelligence (AI), and Machine Learning (ML) for impressive value to operational efficiency.
Applications for IPA include:
- Automating new account openings and customer onboarding
- Elevating workloads from legacy systems at a reduced cost
- Redacting and validating accounts (e.g., claims processing, legal documents)
- Extracting critical information from unstructured data
- Analyzing sprawling datasets (e.g., shipping routes) for optimization
Purposeful Automation for Unprecedented Efficiency
Strategic selection of automation tools ensures that efforts are focused on the most impactful areas, and the resulting efficiencies are directly tied to desired outcomes. With a clear vision, data-driven metrics, and purposeful automation, enterprises can achieve unprecedented efficiency and gain a competitive edge.
Don’t let your organization fall behind the curve. Learn more in our recent article, “Leveraging Intelligent Automation to Increase Operational Efficiency.”
