Automation, at its core, refers to “the technology by which a process or procedure is performed with minimal human assistance.” The essence of automation lies in creating systems that can operate independently, executing tasks with precision and speed that often exceed human capabilities. In today’s rapidly evolving technological landscape, automation has become a cornerstone of modern business operations, revolutionizing industries across the globe and enabling them to achieve their business goals more effectively.
As automation adoption grows rapidly, we now see companies shifting towards positioning automation as a mindset. The “Automation Mindset” is a strategic approach that emphasizes using automation to streamline processes, enhance efficiency, and minimize manual intervention. This mindset involves identifying repetitive tasks that can be automated, leveraging tools and technologies to implement these automations, and continuously seeking opportunities to improve and expand automation capabilities within an organization.
For instance, in the context of Workato, automation is used to integrate various systems, manage workflows, and ensure that business processes are efficient and error-free. This involves creating automated workflows to handle tasks such as sales order processing, ticket management, and data synchronization across different platforms. Adopting an automation mindset helps organizations drive efficiency, effectiveness, and much more.
For example, Slack uses automation to assign tickets based on agent skills and availability within an internal helpdesk tool where employees can raise issues, streamline incident management, monitor newly signed documents, create purchase requisitions, approve invoices, onboard employees, and more.
Broadcom, the semiconductor and infrastructure software giant, is also a great example of a company with an automation mindset. They have built automation across their entire business, including employee onboarding and offboarding, new hire setups, IT service management, and massive automation investments to improve employee experience.
The Automation Value
As mentioned earlier, the automation mindset is a concept embraced by many companies today, largely due to the enormous value they gain from automation. As we focus on the impact of automation, it’s a good opportunity to summarize its main benefits and values:
- Increased Productivity – Automation enables greater output with the same or fewer inputs, such as labor, time, and materials. It often reduces manual labor, manual data entry, and human error.
For example, Broadcom has accelerated their onboarding process by 16 times, decreased emails and calls by 15 times, and increased productivity by 12 times. - Enhanced Quality – Automation consistently produces high-quality outputs with minimal variability, reducing the likelihood of human error and ensuring that products and services meet rigorous standards.
Cloudorizon, for example, enhanced their invoicing process by automating it, making it faster with higher accuracy and fewer errors caused by manual data entry. - Cost Reduction – Automation lowers operational costs by replacing or augmenting human labor, reducing errors, and optimizing resource usage.
For instance, Grab used automation for its IT team, saving over 3,000 man-hours and reducing IT time by 200+ hours weekly. - Increased Data Accuracy – Automation ensures precision and correctness in data inputs and outputs, enhancing the reliability and integrity of data used in decision-making processes.
SurveyMonkey automated their customer feedback analysis to improve accuracy, leading to better insights for improving their customer experience strategies. - Consistency in Data Processing – Automation ensures uniform application of rules and procedures across data inputs, resulting in standardized and repeatable outputs.
SentinelOne uses automation to ensure data consistency between systems, including partner systems, leading to faster transaction processing with fewer errors and better data consistency across platforms. - Improved Customer Service and Experience – Automation enhances how customers interact with a company’s services, leading to higher satisfaction and loyalty.
Flexport, for instance, uses automation for customer support ticket handling, improving response times and leading to a 15% increase in customer satisfaction.
Rapid7 used automation to ensure knowledge articles are up-to-date, resulting in a 12.6% case deflection rate, saving time for both engineers and customers, and enhancing overall customer satisfaction. - Operational Visibility and Control – Automation provides real-time monitoring, management, and response capabilities, often through automated reporting, notifications, and logging. This results in better decision-making, quicker response to issues, and overall improved operational efficiency.
Instructure, for example, uses automation to create QBR reports, improving report quality and timeliness, which leads to better decision-making and customer satisfaction.
Riskified uses automation to allow users to create their own reports, saving 1,500 hours per month on report creation by the Ops team, reducing operational costs by 60%, and reducing SLA from 48 hours to 20 minutes. - Risk Reduction and Compliance – Automation minimizes potential risks and ensures adherence to regulatory and organizational standards. This is achieved through automations that focus on policy enforcement, real-time monitoring, audit trails, regulatory reporting, data security, and incident response.
HSBC uses automation for anti-money laundering (AML) checks by integrating customer data with third-party compliance databases, while Bank of America automates the collection and organization of data required for financial audits. - Flexibility and Scalability – Automation ensures that systems can adapt to changing needs and grow alongside the business without significant overhauls or disruptions. Flexibility refers to the ability of a system or process to adapt to varying conditions, requirements, and environments. In the context of automation, this includes adaptability, customization, and user empowerment. Scalability refers to the capacity of a system to handle increasing amounts of work or to expand to accommodate growth. From an automation perspective, this includes performance, resource management, future-proofing, and cost-effectiveness.
When combined, flexibility and scalability provide a robust foundation for business growth and innovation, ensuring business agility, operational efficiency, risk mitigation, and customer satisfaction.
Shopify, for example, used automation to handle increased traffic and transactions during peak shopping seasons without performance degradation, while Goldman Sachs used automation to manage a growing number of transactions and customer accounts without compromising security or performance.
Jeff Wilke, former CEO of Worldwide Consumer at Amazon, summed it up well:
“Automation has allowed us to scale our operations efficiently and meet the growing demands of our customers. By automating repetitive tasks, we’ve been able to focus on innovation and improving the customer experience.”
The Automation Value Across Different Business Units
Now that we have established the value of automation, it is important to note that the automation mindset involves not only recognizing this value but also ensuring its implementation across all business functions. We do this by exploring automation opportunities within the company, and as mentioned earlier, there are many just waiting to be uncovered.
In this section, we’ll go over some automation use cases by business unit and demonstrate how different processes can be automated for each type of unit within our business. The following includes the business unit (BU), the use case, a description, and the potential value. This list is by no means exhaustive—it’s just a taste of what’s possible.
IT Use Cases
- Self-Service Provisioning with Approvals: Automate employees’ apps and hardware requests, including necessary approvals.
Value: Saves manual labor and reduces provisioning time. - Identity Access Management: Automate user identity management and access permissions.
Value: Enhances security by ensuring timely updates and reduces IT staff workload. - Ticket Management and Routing: Automate the creation, routing, and updating of IT support tickets.
Value: Improves issue resolution time and ensures timely handling.
Finance Use Cases
- Automated Invoicing: Automate the process of verifying and paying invoices to streamline submission, approval, and payment processes.
Value: Reduces invoice verification time, enhances productivity, reduces errors, and ensures timely payments, improving cash flow. - Automated Financial Reporting: Automate the collection and consolidation of financial data for reporting purposes.
Value: Increases report accuracy, reduces manual effort, improves data consistency, and supports better decision-making. - Expense Management: Automate the logging, submission, and approval of expenses.
Value: Streamlines expense management, reduces time, and enhances compliance.
Customer Support Use Cases
- Customer Feedback Collection: Automate sending out surveys and collecting feedback after support interactions.
Value: Provides valuable insights into customer satisfaction and areas for improvement without manual effort. - Escalation Management: Automate escalations for tickets that require higher-level intervention.
Value: Ensures critical issues are promptly addressed, improving resolution times and customer trust. - Automated Knowledge Base Updates: Automatically update and maintain the knowledge base with solutions to common problems based on resolved tickets.
Value: Ensures customers and support agents have access to the most up-to-date information, reducing the number of repeat inquiries.
Sales Use Cases
- Automated Quotes and Proposals Generation: Automatically generate quotes and proposals using predefined templates and customer data.
Value: Reduces time spent on manual document creation, ensures consistency and accuracy. - Contract Management: Automate the creation, approval, and tracking of sales contracts.
Value: Streamlines contract management, reduces delays, and ensures compliance. - Renewal and Upsell Opportunities: Automatically identify and notify about renewal and upsell opportunities based on customer purchase history and usage data.
Value: Maximizes revenue, ensures timely renewals, and identifies potential upsell opportunities.
Account Management Use Cases
- Customer Onboarding: Automate onboarding for new customers, including sending welcome emails and introductory resources.
Value: Enhances customer experience by providing timely and consistent information, leading to better product adoption and satisfaction. - Automated Data Entry: Automate the entry and updating of customer data based on interactions and transactions.
Value: Reduces manual data entry tasks, frees up time for customer-facing tasks, and minimizes administrative work. - Automated Deck Generation: Automatically gather and organize relevant data, images, and content from various sources to create professional presentation decks (e.g., QBR, EBR).
Value: Saves significant time and effort in deck preparation, ensuring consistency and accuracy while allowing employees to focus on more strategic tasks.
HR Use Cases
- Employee Onboarding: Automate the entire onboarding process, including document collection, account creation, and equipment provisioning.
Value: Ensures a smooth and efficient onboarding experience, reduces manual effort, and improves new hire satisfaction. - Payroll Processing: Automate payroll calculations, approvals, and disbursements.
Value: Reduces errors, saves time, and ensures employees are paid accurately and on time. - Performance Management: Automate the collection and analysis of performance data and schedule performance reviews.
Value: Provides timely insights into employee performance, enabling better management decisions and employee development.
Revenue Operations (Rev Ops) Use Cases
- Deal Desk Automation: Automate deal desk processes, including approvals, pricing, and contract management.
Value: Speeds up deal finalization and ensures compliance with pricing and discount policies. - Churn Detection: Automate identification and notification of churn risks based on customer usage data and engagement metrics.
Value: Ensures proactive management of at-risk accounts, maximizing customer retention. - Automated Revenue Forecasting: Automate the collection, integration, and analysis of sales data from various sources to generate accurate revenue forecasts.
Value: Enhances the accuracy and timeliness of revenue predictions, enabling better financial planning and decision-making.
Marketing Use Cases
- Customer Segmentation: Automate customer segmentation based on behavior, demographics, and engagement data.
Value: Enables personalized and effective marketing strategies by targeting the right audience. - Social Media Management: Automate the scheduling, posting, and monitoring of social media content across multiple platforms.
Value: Enhances social media presence and engagement while freeing up time for strategic activities. - Event Management: Automate the planning, promotion, and follow-up processes for marketing events and webinars.
Value: Streamlines event logistics and improves attendee engagement and follow-up.
The importance of Measuring the Automation Impact
As we’ve explored, the value of automation is far-reaching, extending across various business units and significantly enhancing efficiency, accuracy, and overall performance.
The examples provided demonstrate how automation can be tailored to meet the unique needs of each department, reinforcing the importance of a comprehensive and strategic approach. However, recognizing and implementing automation is just the beginning. To fully realize the potential of these initiatives, it’s crucial to understand their impact.
Measuring the impact of automation is essential for several reasons, providing a comprehensive understanding of how automation initiatives contribute to an organization’s overall success.
Firstly, understanding Return on Investment (ROI) is critical. By measuring the financial returns of automation organizations can determine whether the costs of implementation and maintenance are justified by the savings and additional revenue generated through increased efficiency, productivity, and reduced errors. This financial analysis helps to validate the economic viability of automation investments.
Secondly, it is vital for ensuring alignment with strategic goals. Automation initiatives must support broader organizational objectives, such as improving customer satisfaction, increasing market share, or enhancing operational efficiency. By measuring impact, organizations can ensure that their automation efforts are not only effective but also strategically aligned with their long-term vision.
Additionally, measuring automation’s impact helps in identifying and mitigating potential risks. Automation can introduce new risks, such as cybersecurity vulnerabilities, system failures, or unintended consequences that could disrupt operations. Ongoing assessment allows organizations to proactively address these risks, ensuring the reliability and security of automated processes.
Another important aspect is assessing workforce implications. Automation can significantly impact employment, skill requirements, and overall employee satisfaction. By measuring these effects, organizations can manage transitions more effectively, providing necessary reskilling and upskilling opportunities to support their workforce through the changes automation brings.
Finally, measuring impact is crucial for driving continuous improvement. The data gathered from these assessments provide valuable insights that inform future automation projects, resource allocation, and strategic planning. This evidence-based approach ensures that automation efforts are continuously refined and aligned with the organization’s long-term objectives, leading to sustained success.
By diligently measuring the impact of automation, organizations can maximize their return on investment, ensure alignment with strategic goals, mitigate risks, support their workforce, and drive continuous improvement in their automation initiatives.
Automation Key Performance Indicators (KPIs)
Automation Impact measurement is done by using Key Performance Indicators (KPIs). These KPIs provide insights into how automation influences various aspects of an organization’s operations.
Those KPIs are heavily connected to the automation value we discussed, and this section we’ll be covering how they translate to measurable KPIs, their definitions, key metrics, and methods to effectively measure them.
1. Process Efficiency
Process Efficiency assesses how well a process functions after automation. Key metrics include Cycle Time (the time taken to complete a process) and Throughput (the number of units processed within a given timeframe). To measure these, compare the cycle times and throughput before and after automation, and use process mining tools to analyze workflow data and identify any bottlenecks.
2. Error Rate Reduction
This KPI measures the reduction in errors post-automation. Important metrics are the Error Rate (number of errors) and Error Corrections (time spent correcting errors). To track this, log errors before and after automation and use quality assurance tools to analyze the data for improvements.
3. Cost Savings
Cost Savings measures the financial benefits derived from automation. Metrics include Operational Costs (costs associated with manual processes) and Return on Investment (ROI). Calculate reductions in labor, material, and overhead costs post-automation, and track ROI using financial analysis tools over time.
4. Scalability
Scalability evaluates how well automated processes can scale. Metrics include Volume Handling Capacity and System Performance (response times and throughput under varying loads). To measure scalability, collect data on system capacity and monitor performance under different workloads.
5. Compliance and Risk Management
This KPI measures how well automation supports compliance and mitigates risks. Key metrics include Compliance Rate (adherence to regulatory standards) and Risk Incidents (number of incidents post-automation). Use compliance monitoring tools and conduct risk assessments to measure this KPI.
6. User Satisfaction
User Satisfaction gauges how content users are with automated processes. Metrics include User Feedback Scores and Adoption Rates. To measure this, conduct surveys, collect feedback, and track adoption rates through usage analytics.
7. Time to Market
Time to Market measures how quickly automation allows processes to deliver results. Metrics include Development Cycle Time and Time to Delivery. Use project management tools to compare development and delivery times before and after automation.
8. Quality Improvement
This KPI assesses the impact of automation on output quality. Key metrics are Quality Scores and Customer Satisfaction. Measure quality through regular assessments and gather customer feedback via surveys.
9. Productivity Increase
Productivity Increase measures the boost in productivity due to automation. Metrics include Output per Employee and Task Completion Rate. Track these metrics before and after automation using workforce analytics tools.
10. Employee Engagement
Employee Engagement evaluates the impact of automation on employee satisfaction and retention. Key metrics include Employee Satisfaction Scores and Turnover Rate. Conduct regular surveys and track turnover rates to measure this KPI.
By measuring these KPIs, organizations can make data-driven decisions to optimize processes, reduce costs, improve quality, and enhance overall efficiency, ensuring that automation initiatives align with strategic goals and foster a positive work environment.
Unlocking the Power of Automation: Key KPIs to Measure Success
In the journey toward maximizing the benefits of automation, understanding and measuring its impact is crucial. To truly unlock the power of automation, organizations must focus on specific Key Performance Indicators (KPIs) that provide a clear picture of how automation is driving efficiency, reducing costs, and improving overall performance. In this section, we will explore essential KPIs that serve as benchmarks for success in automation initiatives. By defining each KPI and offering practical methods for measurement, we aim to equip you with the tools needed to assess and optimize your automation efforts, ensuring they deliver tangible value to your organization.
Manual Work Reduction
The Manual Work Reduction KPI measures the hours saved over a specific period (such as a week, month, or year) by automating tasks that were previously done manually. This metric is a direct reflection of how much time is freed up for employees to focus on more strategic tasks, rather than repetitive data entry and processing.
The calculation assumes that employees typically spend between 10% and 25% of their time on manual tasks. The number of employees involved and the time period being measured are also crucial to determining the total hours saved (Gartner, “Hype Cycle for Digital Workplace Infrastructure and Operations, 2020).
For the calculation, consider a company with 500 employees, where each employee spends around 10% of their workweek (approximately 4 hours) on manual tasks.
Over a month, the hours saved can be calculated as follows:
Hours saved per month = 4 hours/week × 4 weeks/month × 500 employees = 8,000 hours saved per month.
Error Reduction
This KPI quantifies the hours saved by reducing errors that occur due to manual data entry. Automating data entry processes not only improves accuracy but also significantly cuts down the time spent correcting mistakes.
On average, companies spend about 12 hours per week correcting data entry errors. This figure can vary depending on the specific teams involved, such as Sales or Revenue Operations, where the error correction time may be higher but the number of employees affected is smaller (MJ Consulting, “12 Signs That You Could Improve Your Processes.”, 2023).
Using a conservative estimate, if employees spend 6 hours per week correcting errors, and the company has 500 employees:
Hours saved per month = 6 hours/week × 4 weeks/month × 500 employees = 12,000 Hours saved per month.
Time Reduction in Integration Development
This KPI measures the time saved in developing integrations by using automated processes. Integration development can be time-consuming, especially when dealing with multiple applications. Automation can significantly reduce this time, allowing faster implementation and smoother operations.
Integration development times are categorized based on complexity – simple, medium, and complex.
It’s assumed that 30% of integrations are simple, 40% are medium, and 30% are complex.
We will be basing our calculation on this table, demonstrating the estimated effort in hours required for integration development using workato against developing it from scratch by coding it.
The assumptions for development effort for this KPI are backed by data from “The Costs of Building and Maintaining a Custom API” by The Republic (2020) and McKinsey’s “Top Trends in Tech.” (2022),
The workato data is based on customer evidence from customer interviews.
| Complexity | Workato | Code |
| Simple | 6-8 | 10-50 |
| Medium | 10-20 | 50-200 |
| High | 20-40 | 200-500 |
For the calculation, we’ll use the median for each category (i.e. – for simple code integration we’ll use 30, for medium Workato integration we’ll use 25).
We’ll multiple each category by the assumed complexity percentage.
Our calculation will be for 100 connected applications, so we’ll assume 30 simple, 40 medium and 30 high.
Here is the calculation:
- Code development:
Total hours = (30×30) + (125×40) + (350×30) = 15,590 hours. - Workato automation:
Total hours =( 7×30) + (15×40) + (30×30) = 1,710 hours.
The hours saved through automation would be: 15,590 – 1,710 = 13,800 hours saved for 100 apps.
Time Reduction in Automation Development
This KPI measures the time companies spend on developing automations. The goal is to reduce this time significantly by using advanced automation platforms, which speeds up the delivery of automated solutions
Automation development times are categorized based on complexity -simple, medium, and complex.
It’s assumed that 30% of integrations are simple, 40% are medium, and 30% are complex.
We will be basing our calculation on this table, demonstrating the estimated effort in hours required for automation development using workato against developing it from scratch by coding it. The assumptions for development effort for this KPI are backed by data from McKinsey (“Cracking the complexity code in embedded systems development”, 2022), as the workato data is based on customers’ evidence in Workato community G2 reviews.
| Complexity | Workato | Code |
| Simple | 2-8 | 40-100 |
| Medium | 8-20 | 100-300 |
| High | 20-50 | 300-600 |
For the calculation, we’ll use the median for each category (i.e. – for medium code automation we’ll use 200, for high Workato automation we’ll use 35). We’ll multiple each category by the assumed complexity percentage.
Our calculation will be for 100 automations, so we’ll assume 30 simple, 40 medium and 30 high.
Here is the calculation:
- Code development:
Total hours = (30×70) + (200×40) + (450×30) = 23,600 hours. - Workato automation:
Total hours =( 5×30) + (14×40) + (35×30) =1,760 hours.
The hours saved through automation would be: 23,600 – 1,760 = 21,840 hours saved for 100 automations.
Development Team Headcount Reduction
The Development Team Headcount Reduction KPI estimates the number of employees that a company saves by using Integration Platform as a Service (IPaaS) for automation, rather than employing additional developers.
It’s estimated that one employee is required for every 50 automations. Additionally, the average salary of a developer in the United States is approximately $10,000 per month (Jooble, for integration developers in the US).
For a company with 150 medium-to-complex automations, 150/50 means 3 developers saved, monthly savings is 3 times $10,000, meaning $30,000 monthly saved per month.
Customer/Employee CSAT Improvement
Customer Satisfaction (CSAT) and Employee Satisfaction (CSAT) KPIs measure the improvement in satisfaction levels among customers and employees, respectively, after the implementation of automation. These metrics provide insights into how automation enhances overall experience and engagement.
The improvement in satisfaction is gauged by comparing CSAT scores before and after automation.
The data for this KPI is collected through customer and employee surveys conducted before and after the implementation of automation.
If the CSAT score improves from 3.8 to 4.4 after automation, the percentage improvement can be calculated as:
CSAT Improvement = (4.4 / 3.8−1) × 100% = ~16% improvement.
This highlights a significant boost in satisfaction levels, attributed to the benefits of automation.
Compliance Score Improvement
This KPI measures the degree to which an organization’s adherence to regulatory requirements improves after automation. A higher compliance score reflects better alignment with industry standards and internal policies, reducing the risk of legal and ethical violations.
Compliance scores are compared before and after the implementation of automation to assess the impact, and are typically obtained from internal or external compliance reports.
If the compliance score increases from 7.7 to 9.1 after automation, the improvement is calculated as: Improvement = (9.1 / 7.7−1)×100% = ~18% improvement.
This demonstrates a notable enhancement in the company’s compliance standing, thanks to automation.
Improved Coordination
Improved Coordination measures how effectively automation enhances coordination among development teams. By automating notifications, task creation, and data capture, teams can significantly reduce the time wasted on poor coordination.
The calculation assumes team members need to be notified of key milestones and tasks, data should be automatically captured and disseminated to relevant team members and Improved coordination can save up to 30% of the time previously lost due to inefficiencies (McKinsey, ” Mapping the value of employee collaboration”, 2021).
For the calculation, we should estimate an average dev project (in hours), multiply by number of projects a year and then reduce 20% (as a conservative estimation).
For example, let’s assume that an average project takes 700 hours, and we have 8 projects a year.
700 × 8 = 5,600 hours. 5,600 × 20% = 1,120 hours saved by improving project coordination.
This KPI underscores the importance of streamlined communication and coordination in maximizing project efficiency.
SLA Improvement
SLA Improvement tracks enhancements in service level agreements, focusing on faster, more efficient, and more reliable service delivery that meets or exceeds customer expectations.
The calculation compares SLA before and after automation, as improvements can be quantified in terms of time saved, money saved, or percentage improvement.
The data is gathered from relevant applications such as CRM systems, Jira, and Freshdesk to reflect SLA measurement before and after automation deployment.
For the calculation, let’s take “case resolution time” for a contact center with 20 agents, and assume we have 90 minutes measured before automation deployment and 45 minutes measured after automation deployment, meaning we saved 45 minutes for case resolution.
We can safely say that we improved 50% improvement on SLA by 50%, and saved 900 minutes (45 × 20), that translates to 15 hours (900/60) per day.
This KPI shows the direct impact of automation on enhancing service efficiency and customer satisfaction.
Scalable Solutions
Scalable Solutions refer to the ability of an organization to efficiently grow and adapt its systems in response to increasing demands without significant changes to infrastructure or the need for additional hires.
The calculation is based on the following assumptions: moving to cloud-based solutions can reduce hardware costs by 50%, automation can lead to up to 30% savings on unused or redundant software and improved operational efficiency through automation can reduce labor costs by 20%-30% (Gartner, “Best Practices for Cloud Cost Management”, 2021; Gartner, “Driving Business Performance With Strategic Cost Optimization”, 2021).
For a company spending $2 million on software licensing, with a 30% reduction through automation:
$2,000,000 × 30% = $600,000 saved on software licensing.
This KPI highlights the cost savings and efficiency gains possible through scalable, automated solutions.
Invoice Automation
Invoice Automation refers to the use of automation technologies to streamline the process of generating, processing, and managing invoices. This KPI measures the efficiency gains and cost reductions achieved by minimizing manual intervention in invoicing, thereby increasing accuracy and processing speed.
According to the Institute of Finance and Management (IOFM), the average cost to process an invoice manually ranges from $12 to $30. By automating this process, the cost is significantly reduced to between $3 and $6 per invoice, translating to a savings of $9 to $24 per invoice, which is a reduction of 75%-80%.
McKinsey & Company reports that organizations using invoice automation have achieved an average processing cost of $2.74 per invoice, compared to $15.96 for companies not using automation, reflecting a reduction of 82%.
To calculate the total savings from invoice automation, we should use the following formula: Total Spend on Invoice Processing × Savings per Invoice.
For instance, if a company processes 10,000 invoices annually and automation reduces the cost by $12 per invoice, the total savings would be:
10,000 invoices × $12 = $120,000 saved annually.
This calculation highlights the significant cost-saving potential of invoice automation, making it a vital KPI for businesses focused on optimizing their financial operations.
In the second part of this section, we will shift our focus from in-depth analysis to a high-level overview of additional KPIs that are essential for understanding the broader impact of automation. While these KPIs may not require detailed scrutiny, they still play a vital role in providing a comprehensive view of how automation contributes to the overall success of your organization. By highlighting these metrics, we aim to offer a balanced perspective that captures both the immediate and long-term benefits of your automation initiatives.
Reduce Customer Acquisition Costs – this KPI measures the effectiveness of automation in reducing the costs associated with acquiring new customers. Automation enables more targeted and personalized marketing campaigns, which can lower overall marketing expenses while increasing conversion rates.
McKinsey (“The value of robotic process automation: An interview with Professor Leslie Willcocks”, 2017) found that personalized marketing automation can reduce customer acquisition costs by as much as 50%.
Customer Service & Customer Retention – this KPI assesses the impact of automation on customer service efficiency and customer retention rates. By automating customer service processes and personalizing marketing efforts, companies can reduce costs and improve customer loyalty.
A case study by Bain (“Intelligent Automation: Getting Employees to Embrace the Bots”, 2020) revealed that a retail company implementing automated customer service and personalized marketing campaigns saw a 20% reduction in customer service costs and a 15% increase in customer retention, resulting in annual savings of over $500,000.
Customer Service Costs – this KPI tracks the reduction in labor costs associated with customer service due to automation. Automation can handle routine inquiries and tasks, reducing the need for large customer service teams.
McKinsey (“The value of robotic process automation: An interview with Professor Leslie Willcocks”, 2017) reports that companies using automation for customer service can reduce labor costs by up to 30%.
Improve Data Accuracy and Consistency – this KPI measures the improvement in data accuracy and consistency achieved through automation. Accurate data is critical for compliance and reporting, particularly in financial institutions.
According to Bain (“Intelligent Automation: Getting Employees to Embrace the Bots”, 2020), automation can reduce compliance costs by up to 30% and significantly improve data accuracy, saving substantial amounts in fines and remediation efforts.
Consistent Data Standards – this KPI evaluates the role of automation in enforcing consistent data standards and validation rules, which are crucial for maintaining high data quality.
Bain (“Intelligent Automation: Getting Employees to Embrace the Bots”, 2020) reports that maintaining consistent data standards through automation can reduce costs associated with poor data quality, which can account for up to 20% of a company’s revenue.
Reduce Security Breach Costs – this KPI measures the potential reduction in costs associated with security breaches by implementing predictive analytics and other automation tools.
Gartner (2024) indicates that predictive analytics through automation can help avoid costly breaches and reduce breach costs by up to 50%.
Reduce Audit Costs – this KPI assesses the reduction in audit costs as a result of automation. Automating audit processes can improve efficiency and better allocate resources.
McKinsey (“The value of robotic process automation: An interview with Professor Leslie Willcocks”, 2017) states that audit automation can reduce overall audit costs by 30%.
Reduce Hiring Time – this KPI measures the reduction in time-to-hire achieved through recruitment automation, which can lead to significant cost savings and faster onboarding of productive employees.
Bain (“Intelligent Automation: Getting Employees to Embrace the Bots”, 2020) notes that recruitment automation can cut the average time-to-hire by up to 50%, and McKinsey (“The value of robotic process automation: An interview with Professor Leslie Willcocks”, 2017) adds that it can reduce recruitment costs by 30% to 40%.
Reduce Benefits Administration Costs – this KPI tracks the cost savings achieved through the automation of benefits administration, which streamlines the management of employee benefits.
Bain (“Intelligent Automation: Getting Employees to Embrace the Bots”, 2020) estimates that automating benefits administration can lead to savings of 20% to 30% in benefits administration costs.
IT Operations – this KPI measures the impact of automation on IT operations, particularly in areas such as license management, where automation can reduce manual intervention and errors.
A Gartner survey (2022) revealed that 80% of executives believe automation can be applied to any business decision, including IT operations, leading to faster provisioning and deprovisioning processes.
Provisioning and Deprovisioning – this KPI evaluates the reduction in manual labor associated with licenses provisioning and deprovisioning, leading to lower administrative costs.
A Forrester Total Economic Impact Study (2020) found that automating these processes can reduce administrative costs by 50%.
License Optimization – this KPI tracks the efficiency of automation in identifying and reallocating underutilized software licenses, ensuring that companies only pay for what they use.
The State of ITAM Report (2023) indicates that automation can reduce licensing costs by up to 30%.
Inventory Management Cost Reduction – this KPI measures the cost savings achieved in inventory management through automation, which optimizes processes and reduces waste.
Deloitte’s research (“Automation with intelligence“, 2023) shows that automation can achieve an average cost reduction of 31% over three years in inventory management.
Sales Uplift – this KPI tracks the increase in sales potential resulting from the implementation of sales automation.
McKinsey (“Sales automation: The key to boosting revenue and reducing costs”, 2020) reports that sales automation can uplift sales potential by up to 10%.
In conclusion, when it comes to measuring the impact of automation, it’s essential to shift the focus from the cost of implementing automation to the savings and benefits it delivers. The true value of automation lies in how effectively it addresses inefficiencies, reduces errors, and enhances productivity across an organization. By concentrating on the substantial savings generated through reduced manual labor, fewer errors, and streamlined processes, businesses can better appreciate the long-term return on investment. Measuring these impacts through key performance indicators allows organizations to quantify the tangible benefits of automation, ensuring that the focus remains on the significant value gained rather than just the initial costs. This approach not only justifies the investment in automation but also highlights its critical role in driving sustainable business success.
