Five Reasons Why Business Automation Initiatives Fail and How to Avoid Them
Learn how Italian Luxury Fashion House Max Mara Successfully Implemented Automation to Decrease Customer Service Resolution Times by 90%
In our constantly evolving business environment, running a business presents plenty of challenges. Increasing customer expectations, gaps in skilled labor and constant digital disruption are driving organizations to turn to automation to enable success. Max Mara, an Italian fashion brand, turned to intelligent automation when they saw their digital sales triple during the pandemic. Using intelligent automation, Max Mara was able to better satisfy their influx of customers. Automation has been shown to have positive effects for many other organizations as well. According to the recent IBM Global AI Adoption Index 2022, which was commissioned by IBM in partnership with Morning Consult, 30% of global IT professionals say employees at their organization are already saving time with new AI and automation software.
Many organizations realize the need to operate in a proactive manner, yet they may struggle to realize the full returns on their investments in automation. It takes many different complex processes to keep a business running — from supply chain management and order processes (i.e., order to cash) to procurement (i.e., procure to pay). These processes are often hindered by bottlenecks or rife with inefficiencies that can slow down response times, increase risk or jeopardize customer satisfaction. Intelligent automation, which is the use of AI, process mining, task mining and robotic process automation (RPA), to streamline and scale decision-making across an organization, can help to reduce those problems.
Intelligent automation simplifies processes, frees up resources and improves operational efficiencies, accelerating the returns on your investment. For organizations looking to implement intelligent automation, process mining is an ideal place to start. Businesses can use data from their key business systems such as Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM) to continuously identify and optimize these processes. This provides the business with a detailed view into how the processes operate, where there are inefficiencies and where intelligent automation can have the greatest impact. That’s why process mining is an ideal starting point.
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IBM has decades of experience working with businesses on their digital transformation journey and we often hear stories of automation initiatives failing to get off the ground. Here are five common reasons why these initiatives fail and how starting with process mining can help avoid these common pitfalls:
- Deploying automation in the dark
- Too often organizations automate broken or poorly executed processes that yield few improvements. Knowing what and what not to automate is the first step to a successful automation plan. Process mining provides full transparency into how your end-to-end processes are actually operating. Data-backed insights derived from organization’s information systems provide business and IT teams a shared view into process inefficiencies, bottlenecks, and deviations.
- Not testing before implementation
- It’s important for an organization to analyze, plan, and prioritize before investing in business automation. Successful implementation requires extensive testing and simulations of revised business processes to help analyze possible bottlenecks and the impact of potential changes. Decisions and prioritization of change initiatives should be driven by ROI projections derived from what-if scenarios analysis/simulations.
- Automating tasks rather than entire processes
- Worker productivity generally improves when repetitive, mundane tasks are automated using tools like RPA. However, such gains often pale in comparison to those obtained by fully modernizing end-to-end employee and customer experiences. Rather than focusing on individual tasks, automation recommendations can identify automation low-hanging fruit and provide a holistic view of the process that includes insights from process mining, task mining, and decision mining.
- Failing to iterate
- Organizations that deploy process reengineering and automation without measuring impact and results typically fail to continuously optimize their processes. Post-deployment monitoring enables an organization to compare process performance against pre-defined key performance indicators (KPI) to ensure projects are operating at an optimal level. A new Insight to Action feature in IBM Process Mining, allows organizations to continuously monitor KPIs and trigger precise, corrective actions when operations stray outside pre-defined thresholds.
- Lack of skills to scale automation
- Today, talent availability is becoming the main adoption risk factor for most businesses that want to implement intelligent automation technologies. Employees with the right set of skills and expertise to work with tools like process mining and RPA are scarce. How can we help those automation builders focus on higher value work like planning and analysis? Insights provided by IBM Process Mining can be used to quickly create RPA automations to speed up development time while enabling you to scale automation across the enterprise.
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At IBM, we’ve seen the benefits of starting with process mining firsthand. Take Italy’s fashion house, Max Mara, for example. Ensuring a satisfying buying experience for customers is a top priority for Max Mara. However, over the course of the pandemic, their digital share of business volume nearly tripled, leading to many potential process issues or bottlenecks. The Max Mara team wanted to understand how they could optimize the post-sales support inquiry process during times of high seasonal demand to eliminate bottlenecks and provide a better customer experience. By using IBM Process Mining, they identified the repetitive parts of the process flow that would benefit from intelligent automation. By simulating these changes, they were able to demonstrate a 90% increase in customer service resolution times, and a 46% reduction in the average cost per resolution.
Max Mara is just one example of the success that organizations can have when they start their intelligent automation journey with process mining. To help make it even easier for organizations to get started quickly, IBM has released its latest version of its process mining software to easily trigger corrective action and tailored automations, accelerate process optimization in the procure-to-pay process, and deploy RPA bots with ease.
IBM Process Mining is available as a stand-alone offering, and as part of the IBM Cloud Pak for Business Automation, to integrate with RPA, Decisions, Workflow, and additional automation technologies. It is part of IBM’s end-to-end portfolio of intelligent automation solutions for business and IT, with many of the solutions developed by IBM Research.
