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The world today is inundated with a remarkable volume of data. The problem: Humans are not equipped to process it all. The solution: the blend of human expertise and technology. Now more than ever, humans and machines have the opportunity to seamlessly work together to create lasting efficiency — especially at work. Deemed the augmented workforce, the integration of humans and technology allows employees to streamline processes and implement more efficiency to drive better outcomes and consistent outputs, all while reducing human error at scale.
The augmented workforce is gathering speed, causing many organizations to reconsider how to plan for future growth, organize work and design jobs. Advancements in technology will only continue to accelerate, and it is up to organizations to embrace and understand the concept of the augmented workforce to reap the benefits and meet the demands of employees.
As more organizations seek to benefit from the augmented workforce, its success is contingent on presenting data and using artificial intelligence in a way that empowers organizations while also gaining employees’ trust. For widespread acceptance, we must strike a balance between leveraging the very best qualities of AI, natural language generation (NLG) and other deep learning technologies, without losing the human touch.
Empowering data to replace repetitive tasks
Storing the copious amounts of data that organizations are bogged down with is no longer a problem and highly skilled data science teams are able to process and analyze it, but where many organizations struggle is actually interpreting what’s valuable and putting it into action. Too often, data science teams “crunch the numbers,” hand off a deck full of “findings” to managers, and say “Here, put this into action!” without much guidance beyond that.
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In an optimized augmented work environment, however, organizations seek to do more than just learn from data, but to actually empower it to make their day-to-day work more efficient. For example, advanced organizations use modern NLG to automate repetitive tasks, like reports that are slow and costly to write but have to be written often.
CEOs and other top executives typically demand reports from various departments, on a weekly or even on-demand basis, detailing performance, market changes and other key data crucial to business successes. Typically, members of the analysis team are tasked with processing the data and typing up the report, but when NLG is plugged into the big data tool, it can act as a last-mile solution to explain the analysis of the data, in an easy-to-read, written narrative.
Turning data into decisions
By automating manual and time-consuming processes through data, organizations across a myriad of industries can transform how their businesses operate as a whole, saving valuable time and allowing employees to focus on more important and strategic work. For instance, financial industry analysts at investment firms and banks spend a great amount of time analyzing incredibly large datasets before drafting detailed written reports that are then used to make business decisions.
In reality, the true value is actually in the comprehensive insights pulled from the data, and everything on the way to those insights is just a waste of time. Augmenting financial reports provides decision-makers with the information they need to drive business while freeing up employees to tackle more productive tasks, as opposed to processing data to get to those key takeaways.
Data drives products to market
An augmented work environment also gets products to market faster, which in some industries can have life-saving implications. Pharmaceutical corporations rely on generating Clinical Study Reports for new drug approval. This tedious process takes weeks or even months. So leading brands like Eli Lilly and others are supplementing the process with NLG, aiming to reduce the time it takes to bring new drugs or vaccines to the market.
NLG has developed far beyond the chatbots of early days and is now able to automate the generation of complex reports at high standards of quality, accuracy and consistency, so that employees can make much better use of their time.
Debunking myths associated with augmentation
In order for employees to effectively utilize automation, organizations must provide the transparency, resources and training needed to understand these technologies. Transparently explaining the augmented workforce will help employees understand their designated roles and provide peace of mind around robots replacing their jobs. Understanding that there may be a learning curve is essential for the overall growth and success of the employees and structure of the organization.
One of the most common myths is that workforces use augmented technologies solely to reduce overhead costs, while workforces are really seeking additional support to streamline processes and put employee productivity at the forefront. Augmentation does not mean replacements, it means reinforcements.
With that, many tend to think that transitioning to an automated workforce is difficult to learn, understand and deploy. However, the benefits can well outweigh any concerns, given proper resources, enough time to retrain, and transparent expectations. It is important to remember that AI technologies are only truly effective when combined with human intelligence.
Emmanuel Walckenaer is CEO of Yseop
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