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How to Drive Organic Innovation Through Automation and Process

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The conversation around using AI and automation as a means to free up employees for higher-level work is not a new one. However, the pandemic’s effects have brought to light how the failure to automate daily, repetitive tasks can hinder more than a workforce’s mind space. That monotonous work takes away the physical ability to execute on strategic, business-building work. Now more than ever is the time for further organic innovation and implementation of AI technologies to automate the mundane so we can focus on profitable sustenance.

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The pandemic is pushing business leaders from all industries around the world to re-imagine and deploy how to best use their employees and tech stacks. The workforce and workplace have both changed drastically this year and creativity has taken a backseat to sustainability and survival. To move forward, companies must optimize their processes and, where possible, invest in organic innovation of automated solutions to enable employees to focus time, and now limited energy, on doing what they came to their company to do – create innovative solutions that push beyond current boundaries or barriers of their industry.

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Empowerment Through Automation

Every enterprise department has tasks that could be automated but it’s not a one and done process.

Deciding where, when and what to automate requires an understanding of the unique needs of a company’s workforce. In this case, empowerment can only begin when employees are given a voice and stake in how automation decisions are made and implemented.

To best understand the landscape, feedback must be solicited across the organization with employees prioritizing their biggest pain points and which daily processes and workloads are causing the most drain on their time. Sourcing this feedback and insight will uncover where an enterprise’s specific goals and strategies can be achieved and strengthened by automation.

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For example, one of the challenges in many organizations has been the complexity of data pipelines caused by the number of technologies involved in the 4 stages of the data lifecycle – ingest, store, process, analyze.

The mix of technologies involved causes inefficient automation siloes.

Business users are often frustrated with the time to realize value from data analytics initiatives. Focus needs to be on enabling the integration, automation and orchestration of complex data pipelines spanning real-time, event-driven and time-based processes, across multiple data, application and infrastructure technologies – all running in production, at scale and with governance.

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After identifying where the automation is needed most, whether by department, team or company-wide, the next step is not only a matter of selecting the tools required for automation but also building a framework for implementation, employee training and the metrics and key performance indicators (KPIs) you’ll measure to gauge success.

A recommended best practice is to identify2-3 use cases that are estimated to offer the highest business value, automate these rapidly to deliver value, and use the positively impacted employees as change agents to drive a broader transformation across the organization.

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Organic Innovation and Empowerment through Process

Once automated solutions are implemented and more employee mind space and time is available for higher-level, strategic work, it’s important to ensure the increased creative freedom isn’t wasted. New processes to guide shifting priorities and initiatives need to be set in motion as new automation technologies are implemented. Over the course of my career, I have developed and tested a 6-step process that we’ve come to use to empower people to explore their ideas beyond a brainstorm and a brief. It starts with idea presentation/selection, then validation. From there we focus on proof of concept followed by proof of value, then comes commercialization and finally product organization.

Employees should be supported in seeing their ideas through and given the chance to prove the value of their concepts with data. A truly modern organization isn’t hiring someone to simply execute on existing ideas, they hire them to challenge old methods, improve strategies and innovate in new ways. That’s not possible without processes that provide sufficient room to test theories and see what can succeed.

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