Change is hard. In an enterprise with multiple stakeholders, hierarchical levels of employees and complex processes, even smaller changes could be highly demanding. Effective change management is needed at all levels to ensure the success of any undertaking.
Implementing Automation across an enterprise is one such challenging task. Even though RPA has been known to provide considerable value to businesses, ineffective change management can significantly reduce the ROI from implementation.
There are multiple factors that have to go right for an enterprise to plan, implement and scale Automation. But the following are known to cause the maximum strife to an organization in its digital transformation journey:
In a McKinsey Global Survey on organizational transformation, it was found that transformation initiatives can achieve a 79% success rate by taking rigorous planned actions and took them to completion. Only 26% of all respondents had reported success rates in the survey. This underlines the need for effective planning when starting a change initiative.
Even well-planned processes in a modern enterprise grow complex over time with user customizations and workarounds. A theoretically simple process of invoice handling also falls prey to potential pitfalls like human error, human bias and incomplete documentation. Extrapolated over the divergent workforce practices and the sheer number of incoming invoices in a large enterprise, even smaller mistakes and biases tend to shipwreck an RPA implementation.
While a well implemented RPA could deliver a significant return on investment for an enterprise, achieving that goal takes equally significant time and effort from everyone involved. Managers tend to underestimate the effort involved and overestimate the expected benefits at the start of a project. This in turn leads to unexpected delays in implementation, additional costs and even decrease in morale of the workforce.
For sales and customer support teams, time spent in working with an automation consultant is time away from reaching their targets. Employees do not take kindly to a decrease in their productive hours during the process mapping phase. Due to these reasons, manual or intrusive process mapping techniques like Process Mining take longer than expected, which in turn delays the full automation implementation. Because of this accuracy gets hit.
Employees are inherently resistant to change. Any change that is not comprehensively planned and backed by exhaustive research and analysis, tends to be met with questions and differing opinions. A full-fledged successful RPA implementation requires whole-hearted support at every level and skepticism means that implementations are not provided with support that is needed.
Most enterprises are not successful in implementing major transformative change. Bain and Company found in a study that 20% of major change efforts fail completely, and only 12% meet their goals. But the good news is that the underlying risks are known and manageable. The solutions recommended by Bain and Company are about getting buy in from the employees and on effective communication and clarity provided by the leadership.
If the answers are so obvious, why are organizations still failing at large scale change management? It is because organizations do not realize they are making these same mistakes. Leaders and employees are prone to all the cognitive biases that afflict other humans as well. This inherent bias is the common denominator in the three factors discussed above.
Thus, for a change initiative to be successful, the first step should be to remove the human bias and errors that arise due to it. An automated, objective and data driven execution will definitely lead to a successful transformation.