Business toautomation Initiatives and investments will increase sharply in 2023 and beyond, fueled by the potential of AI and hyper-automation to transform business models and create additional business value.
It is well understood that automation solutions can perform a wide range of activities to streamline processes by automating manual tasks. Proven benefits for businesses that adopt automation capabilities include the ability to transform the business to improve productivity, deliver services faster, reduce operating expenses, and eliminate costly errors.
It also boosts employee morale by eliminating mundane and repetitive tasks and allowing more focus on improving customer engagement and providing capacity for more complex work. As a result, and with the emergence of new technologies, automation use cases are expanding into new industries and a wide variety of business areas.
However, companies seem to have lost focus on what it means to be automated. Worryingly, in a world where customer experience and service delivery is a key differentiator, many companies are unable to provide accurate, real-time insight into the performance of their processes.
The original premise of business process management (BPM) was to allow companies to automate processes to give visibility to processes, but even large companies seem to have lost their way.
Businesses have gotten too mechanical about automation, without a clear automation journey and end state in mind. At the end of the day, the big picture is serving customers better, and the fact that companies don’t measure how well customer-facing processes are performing is surprising.
In addition, there is evidence that companies have not achieved the expected benefit from their historical automation initiatives. Barriers that have created challenges must be removed for future initiatives to be truly successful. In this article, we highlight some of these barriers and provide guidance for removing or mitigating the associated risk.
inherited barriers
Despite all the available technology and modernization efforts in recent years, many organizations still have multiple legacy systems and old components in their environments. Data integration with these systems is a common business challenge that cannot always be solved in a cost-effective manner. The latter creates a barrier to implementing advanced automation solutions and limits profit and value outcomes.
We have found that clear requirements and an up-to-date data architecture help identify potential challenges. When data formats and process steps are not structured or well defined, process and task mining can be used to help discover those processes and more accurately assess the “as is” state while clearly defining the structure of the process. required data.
Software Automation Journey
Most companies have a wide range of software solutions from a multitude of vendors. These vendor solutions have different automation strategies and journeys. For example, a software vendor might identify gaps in their offerings and acquire new tools and capabilities, for example, an ERP vendor will acquire an RPA (robotic process automation) and process mining tool to make their suite more complete. Similarly, most software vendors are investing heavily in AI to make their tools smarter and more efficient, and to stay relevant.
This industry consolidation creates complexity for companies implementing automation solutions. It is important for a company to consider the automation strategies of its solution providers in order to create a clear automation provider strategy, that is, a single or multi-vendor strategy. This strategy will guide the approach to selecting hyperautomation vendors that will provide the various tool sets, eg RPA, BPMS, OCR, AI, ML, process and task mining.
preferred practice
The complexity of automation can result from a lack of structure. The nature of automation means that it is geared toward clearly defined data formats, steps, and results. Adding unstructured data or process variation to the mix adds further complexity.
Automation preferred practices should be guided through a formal or informal automation center of excellence. These practices provide governance and control and ensure that a consistent approach to automation is taken. Automation preferred practices should be regularly reviewed and evaluated to identify new and updated practices. This will help ensure that companies’ automation strategy can be future-proof.
The fallacy of the application and the cloud
A component of most companies’ digital transformation journeys is building one or more mobile apps and providing additional digital channels to engage with their customers. There is a belief that these apps/channels automate existing business processes. This is a fallacy.
Similarly, due to large-scale migration to the cloud, companies have a perception that because their automation tools are on-premises, they are no longer relevant. Companies are also investing in SaaS applications to replace the legacy system, but they make the mistake of trying to automate all their processes in SaaS solutions, which is doomed to fail. The complexity of trying to do this creates an endless cycle of change.
We do not recommend that companies not deploy applications or move to the cloud, but the automation path and strategy should be restructured to balance and align with these changes.
Automation maturity
Companies are not always aware of where they are in terms of automation maturity. Automation is an evolution, and measuring maturity, benefits, and value is an ongoing, fact-based exercise. Companies are not always clear about what they need to automate. There is often a focus on solutions rather than value drivers:
- RPA came along and short-circuited the evolution of automation. Companies began to automate tasks and processes without fact-based analysis;
- Some industries skipped a few steps because they were lagging behind in automation. The selection of solutions drove the process;
- RPA vendors directly engaged with the business;
- these independent initiatives are not sustainable and now require the involvement of IT;
- A degree of Fomo emerged, driven by the media and vendors.
A key reason for this is that it can be difficult to gauge automation maturity and identify opportunities. The lack of understanding and adoption of process mining and how you can solve this problem is a key challenge. Process mining tools have reached a high level of maturity and are a proven solution for assessing maturity and identifying opportunities.
In summary
To get the most out of automation, companies need to gauge the maturity of their processes and automation investments by looking at the right metrics. They need to consider customer experience and service delivery priorities and plan their automation initiatives accordingly.
They must also understand their current technology environments and be clear about how automation solutions will be sustainably integrated.
The value that can be derived from hyperautomation is significant, but requires a clear understanding of the automation journey and strategy.
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