Five Reasons Why Business Automation Initiatives Fail and How to Avoid Them

Five reasons why business automation initiatives fail and how to avoid them

By Dinesh Nirmal | IBM General Manager, Data, AI and Automation

October 13, 2022

learn how Italian luxury fashion a house Max Mara successful Implemented automation to reduce customer service resolution times by 90%

In our ever-evolving business environment, running a business presents many challenges. Rising customer expectations, talent shortages, and ongoing digital disruption are driving organizations to turn to automation to thrive. Max Mara, an Italian fashion brand, turned to intelligent automation when they saw their digital sales triple during the pandemic. Smart automation enabled Max Mara to better serve the flow of customers. It has been shown that automation has positive effects for many other organizations as well. According to the latest 2022 IBM Global AI Adoption Index, commissioned by IBM in partnership with Morning Consult, 30% of global IT professionals say employees are already saving time at their organization with new AI and automation software.

Many companies recognize the need to be proactive, but may struggle to realize the full return on their automation investment. There are many different complex processes required to keep a business running – from supply chain management and ordering processes (ie order to cash) to procurement (ie procure to pay). These processes are often hampered by bottlenecks or are fraught with inefficiencies that can slow response times, increase risk, or jeopardize customer satisfaction. Intelligent automation, meaning the use of AI, process mining, task mining, and robotic process automation (RPA) to streamline and scale decision-making across an organization can help reduce these problems.

Intelligent automation simplifies processes, frees up resources and improves operational efficiencies, giving you a faster return on your investment. For companies looking to implement intelligent automation, Process Mining is an ideal place to start. Organizations 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 gives the organization a detailed view of how processes are performing, where there are inefficiencies, and where intelligent automation can have the greatest impact. That is why Process Mining is an ideal starting point.

IBM has decades of experience working with companies on their digital transformation journey, and we often hear stories of automation initiatives that just don’t take off. 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 companies automate flawed or poorly executed processes that yield few improvements. Know what and what not Automation is the first step to a successful automation plan. Process mining offers full transparency how your end-to-end processes actually work. Data-driven insights from the organization’s information systems provide business and IT teams with a shared view of process inefficiencies, bottlenecks and deviations.

• Don’t test before implementation
  • It is important for a company to analyze, plan and prioritize before investing in business automation. Successful implementation requires extensive testing and simulations of revised business processes to analyze possible bottlenecks and the impact of potential changes. Decisions and prioritization of change initiatives should be based on ROI projections derived from analysis/simulations of what-if scenarios.

• Automate tasks instead of entire processes
  
  • Employee productivity generally improves when repetitive, mundane tasks are automated with tools like RPA. However, such gains often pale in comparison to those achieved by completely modernizing end-to-end employee and customer experiences. Instead of concentrating on individual tasks, Automation Recommendations can identify low-hanging fruits of automation and provide a holistic view of the process that includes insights from process mining, task mining, and decision mining.

• Error while iterating
  
  • Companies that use process reengineering and automation without measuring the impact and results typically fail to continuously optimize their processes. Post-deployment monitoring allows an organization to benchmark process performance against predefined Key Performance Indicators (KPI) to ensure projects are running at optimal levels. A new insight into action Feature in IBM Process Mining enables organizations to continuously monitor KPIs and trigger precise corrective actions when operations breach pre-defined thresholds.

• Lack of automation scaling skills
  • Today, talent availability is becoming the main risk factor for adoption for most companies looking to implement intelligent automation technologies. Employees with the right skills and expertise to work with tools like process mining and RPA are scarce. How can we help these automation developers focus on higher-value tasks like planning and analysis? The insights provided by IBM Process Mining can be used to quickly create RPA automations to reduce development time while scaling automation across the enterprise.

At IBM, we’ve seen firsthand the benefits of getting into process mining. Take Italy’s fashion house Max Mara, for example. Ensuring customers have a satisfying shopping experience is a top priority for Max Mara. However, over the course of the pandemic, their digital share of business volume has nearly tripled, leading to many potential process issues or bottlenecks. The Max Mara team wanted to understand how they could streamline the post-sales support request process during times of high seasonal demand to eliminate bottlenecks and provide a better customer experience. Using IBM Process Mining, they identified the repetitive parts of the process flow that would benefit from intelligent automation. By simulating these changes, they demonstrated a 90 percent increase in customer service resolution times and a 46 percent reduction in average cost per resolution.

Max Mara is just one example of the success companies can have by starting their intelligent automation journey with Process Mining. To make it even easier for companies to get started quickly, IBM has released the latest version of its process mining software, which makes it easy to trigger corrective actions and custom automations, accelerate process optimization in the procure-to-pay process, and deploy RPA bots Ease.

IBM Process Mining is available as a standalone offering and as part of the IBM Cloud Pak for Business Automation for integration with RPA, Decisions, workflow and other 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.

For more information about IBM Process Mining and how it can help an organization accelerate automation, join our webinar on November 2, 2022.