Project management

Four Paths to Automation Project Management Success


A recent roundtable revealed ways organizations can overcome automation project management challenges.

OpenOcean General Partner Tom Henriksson Identifies Four Ways Automation Experts Have Succeeded in Project Management

When companies embark on an automation program, the path to successful implementation is far from certain. Indeed, according to Ernst & Young, approximately 30-50% of robotic process automation projects worldwide will fail.

While every business will go its own way with automation, there are several common barriers that stand in the way of automation project management success that cut across industries. Without a doubt, technical issues remain a regular cause of automation projects going off the rails. However, in many cases the problem with automation is not technical, but rather a failure to see the big picture.

The lack of strategic focus, defined impact, and clear long-term goals for any automation project inevitably hampers progress. This situation is often compounded by projects that get off to a bad start due to a lack of understanding of business processes and an unclear perspective on the specific goals of automation.

Many companies also find it difficult to manage change and bring employees with them. By focusing on the task itself rather than the associated business benefits, teams fail to build a compelling business case for the automation project, which has a huge impact on stakeholder sign-up and wider company employees.

Given such a list of hurdles, the prospect of starting an automation program can be daunting. I chaired an OpenOcean roundtable on the topic of AI in automation, with thought leaders and pioneers from across the industry. Participants had a wide range of suggestions on how to successfully implement AI in automation, a reflection in part due to the complex range of factors that underpin every successful automation program. Given the key points that have emerged, there is a clear roadmap for businesses to follow in order to avoid obstacles, build a long-term business case, and establish an enabling environment for automation and the AI.

1. Build a good internal foundation

The best AI and ML in automation programs rely on a good internal foundation. It should start with rigorous work on the part of the business to clarify potential use cases, match the technology to business reality, and engage with important stakeholders during the planning process. Many AI companies have matured their technical application and purpose, but are still in the early stages when it comes to establishing valuable and relevant use cases to target and often lack broader engagement. stakeholders.

The financial sector is a good example of good practice. Thanks to internal changes in the industry, particularly around product standardization, companies have been able to rapidly deploy automation projects across the industry. Investing in AI and ML is not enough: focus on connecting technology to reality and business goals.

2. Understanding the process is essential

Having a fundamental understanding of the relationship between problem and outcome is essential for automation success. Process mining is one of the best options a business has to speed up this process. Leyla Delic, former CIDO at Coca Cola İçecek, eloquently describes process mining as a “CT scan of your processes”, taking stock and ensuring that the automation you want to implement actually solves the problems of the business. With Process Mining, one should expect to have to go in and try blindly at first, learn what works, and only then expand and evolve to get real results.

A recent Forrester report found that 61% of executive decision makers use or plan to use process mining to streamline their operations. Building a detailed, end-to-end understanding of processes provides the foundation needed to move from siled specific task automation to more holistic process automation, resulting in tangible impact. With the most advanced tools available today, one can even understand real-time knowledge worker activities and processes across teams and tools in real time, and receive automatic recommendations on how to improve work.

3. Move from siled apps to platform integration

One of the major benefits of implementing AI and automation in the workplace is increasing productivity, streamlining processes, and unleashing important capabilities of human workers. Having too many different systems and services not communicating with each other creates the opposite effect on productivity that AI and automation aim to achieve. To achieve AI-based work orchestration, we need to break down the silos between applications.

The industry is currently experiencing what PD Singh, VP of Software Products at SambaNova, calls the “diffusion effect” – the rush of companies to capitalize on market interest after one company has shaken up the market, leaving them with an array of similar platforms. The direction of travel must be towards an integrated enterprise and a more holistic orchestration of tasks, processes and resources. This will require AI integration to support optimal orchestration, and could be achieved by integrating these capabilities into a single end-to-end platform or through what Gartner calls a composable platform architecture approach. .

4. Establishing clear automation and AI ROI will help technology scale

John Hill, CEO of Silico, described the significance of the “differences between the change that has happened and the change that would have happened compared to if you had done nothing”. This distinction is essential to enlighten an organization on the return on investment of automation.

Figuring out how to measure automation ROI is not a process that needs to be rushed. Investing this time early on allows an organization to take a focused approach to initiating and scaling the project, with full buy-in from all stakeholders, which will benefit the entire business.

At the same time, organizations should remember that no automation project is without risk. You will not be able to predict all results at first. But by being willing to fail and learn from their mistakes, organizations can move a project forward incrementally and chart the best path to more holistic automation.

The Path to Automation Success

Automation has enormous potential to transform businesses. Yet too many companies are still held back by recurring project management issues that prevent them from realizing these benefits. While far from a complete guide, these pointers should serve as a foundation for a business to defy the odds and come up with an automation program designed for long-term success. Businesses need to go beyond just setting up automation, but also integrate ML and AI to bring intelligence to an integrated platform if they want to benefit from maximum added value.

Written by Tom Henriksson, General Partner at open ocean

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