Digital technologies such as RPA, iBPMS, AI, and process mining can be used together to improve the success rate of digital transformation initiatives. However, businesses must have clear plans in place to successfully deploy Intelligent Automation.
There has been a lot of talk about what IDC refers to as intelligent process automation and what Gartner refers to as hyper-automation. These terms apply to the combined implementation of emerging technologies such as robotic process automation (RPA), intelligent business process management suites (iBPMS), artificial intelligence, process mining, and so on in both cases.
Digital transformation is a difficult task. Moreover, the success rate of digital transformation initiatives is low, with only around 30% of such initiatives succeeding, as per a 2020 BCG report. Integration of emerging technology may be the key to achieving greater performance. As a result, it’s not shocking that many vendors have pushed this theme. However, no digital transformation strategy can be successful unless a company has appropriate technology deployment strategies in place.
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Strategies for Successfully Deploying Intelligent Automation
Despite the fact that strategy is more important to digital success than technology alone, many businesses lack a digital strategy. That’s partly due to a long history of rushing to a technological solution — sometimes only one tool for the sole use of one department — rather than establishing the context necessary to recognize business opportunities. The specifics of the company’s strategy must drive digital, and strategy must be guided by customer experience.
It’s no longer just about products and competitors when it comes to developing a strategy. Complementary services and network effects must also be considered, which also necessitates changes in business models, revenue sources, and how end-to-end processes operate. The digital strategy must be led from the top. By prioritizing strategy over digital technology, businesses should consider what is required to scale RPA and machine learning.
The Need for Collaboration
Transformation attempts suffer when teams do not collaborate. Around 75 percent of 1,500 global senior and C-level executives saw business functions competing against one another rather than collaborating on digitization initiatives, according to a recent survey. Because of this lack of collaboration, 64 percent of businesses have failed to see revenue growth from their digital investments. When departments don’t collaborate, it’s difficult to concentrate on customer service and end-to-end process success.
While cross-team coordination can seem easy in principle, it is difficult in practice since teams responsible for specific skills, such as process improvement and customer service, are often located in different areas of the company and report to different executives. Furthermore, customer service teams use a different approach than process management teams, which can make collaboration challenging. Due to the proprietary platforms that vendors have worked to create, collaboration between vendors faces similar challenges.
Many companies undervalue implementation skills such as change management, leaving many executives and IT departments unprepared for this critical stage of the phase. When it comes to change management, it’s all too common for it to be confined to stakeholder analysis and a communication strategy.
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A new mindset is needed to shift management focus from a conventional static, hierarchical view of business to a customer-centric, agile, business process-based view of output. Instead of focusing solely on what is good for the business, leaders should consider what is best for consumers. Leaders must also turn their focus on what is best for the company as a whole. And, rather than focusing on implementing a single discrete technology for the benefit of a single department, business leaders should consider deploying Intelligent Automation in an integrated, agile fashion for the benefit of the entire organization.