Gartner, Inc.‘s recently identified ‘Automation Strategy Rethink’ as the #1 digital infrastructure trend that leaders must start preparing for to support digital transformation in 2020. In recent years, Gartner states they have detected a significant range of automation maturity, with most organizations automating to some level and many attempting to refocus staff on higher-value tasks. However, automation investments are often made without an overall, long-term automation strategy in mind. This is not surprising as many executives have been under pressure to ‘quickly implement’, and a marketed benefit of Intelligent Automation (IA) is speed to market (a bot can be up and running in a few weeks). As we move into 2020, applying process standardization and improvement to IA will enable the transformational benefits organizations are yearning for beyond the incremental gains currently achieved through pilots and localized efforts.
Research has shown that companies who see the greatest success with IA are those that started with process standardization, improvement, or redesign. Rather than starting with the technology and looking for processes to automate, it’s more efficient in the long-run to start by examining and optimizing the process first, as part of an automation strategy. Organizations need to standardize first, then improve, and lastly automate. Once a process is standardized and improved, IA tools (such as OCR & RPA) can be more efficiently and effectively utilized. Unfortunately, most organization’s IA deployments focus exclusively on the “as-is” process, with no review or enhancement of the current process steps that are to be automated. Consequently, they may achieve modest savings but will most likely miss out on opportunities to significantly reimagine processes and deliver transformation to the organization. Worse yet, organizations may spend more time and money on maintaining the IA infrastructure in the long-term for a small short-term gain.
Taking the time to develop and maintain well-managed processes also helps to build a data-backed business case that supports IA beyond the typical buzzword appeal. By working with business process experts to standardize, challenge, and improve the process in order to best apply IA, we have seen not only significant rewards and a decrease in errors and risk.
Some of the major reasons why process standardization mapping, analysis, and redesign work are essential to a highly effective IA strategy include:
- Some processes are overly complex to begin with (i.e. they fall into the extra-processing section of the eight wastes in Lean). They often involve unnecessary steps that should be eliminated before IA is implemented.
- There are built-in checkpoints for processes previously performed by human workers that are no longer needed with IA. IA doesn’t generally make mistakes and therefore doesn’t require additional checks. Finding what doesn’t add value to any process and eliminating it can help a process run even smoother, whether it’s done by a human or a robot.
- The degree of process knowledge, understanding, and/or documentation may be lacking. Many businesses have an unmanaged collection of standard operating procedures, but they are often inadequately documented and out of date. Workers may also follow their own understanding of best practices and process execution varies by worker.
- Most IA tool implementation involve defining and standardizing business rules. In many cases, business rules haven’t been updated in quite some time and don’t make sense in the current business environment. Existing business rules are often undocumented and human workers execute based on their individual knowledge of the business.
- The effectiveness of IA is not always measurable because relevant process metrics haven’t been created. IA, when fully deployed, should bring benefits beyond hours saved.
- IA can also streamline the data environment. Legacy operational processes often involve multiple back-and-forth access to various systems. Often times with the use of IA the process could extract all the required information at once.
- RPA-based process design can restore some useful steps at nominal cost. This is one of the often-overlooked aspects of automation. Some organizations have eliminated steps from processes that add value because the necessary resources to perform them weren’t available.
Viewing IA as one of several options for improvement, rather than in isolation, is the key to a successful digital transformation. While redesigning processes as part of implementing IA can increase the time and cost of the overall initiative, the return on investment can be as great or greater when compared to IA implementations with no process review. Plus, you may find quick improvements that do not require any technology to support. As leaders rethink their automation strategies in 2020, process standardization and improvement should be a key tenant to ensure IA longevity and a sustainable return on investment (ROI).