Automation technologies also offer new possibilities for the employee experience, making it easier to interact with complex systems through a natural interface. For example, at this stage companies may begin using chatbots, which are powered by natural language processing technologies and able to understand intent, to transform the end user experience.
Also at this stage of the journey, some employees’ work is beginning to change, especially jobs that include repetitive, data-based transactional work. In many cases, this work is the least fulfilling part of their jobs, and automation presents opportunities for employees to focus on more value-add work. It is important that companies recognize these changes and incorporate learning opportunities to support shifting roles.
At the next stage, intelligent predictions and insights are widely used to inform decision-making and planning. Leaders, managers, and frontline employees all become adept at using intelligence to augment their daily decision-making, infusing it throughout everything they do.
Also at this stage, machine learning techniques use colossal amounts of data to underpin predictions and create simulations, opening up entirely new possibilities for data-driven decision-making. They make these predictions and simulations so cost-effective and accessible that they can be more widely used than ever before.
Natural language technologies also play a big role in bringing advanced analytics to every employee by democratizing access to data and empowering employees to make augmented decisions. Instead of having to learn complex query languages and data interrogation tools, at this stage natural language interfaces allow employees to ask simple questions to achieve complex data science. For example, “How does the weather impact sales in our stores?” or “Which managers have the best track record for developing strong employees?”
Intelligent analytics and predictions are being used to incorporate larger and more diverse data sets from which to make decisions. Cloud computing power, along with intelligent algorithms and advanced analytics platforms that can fully harness it, allow data from multiple systems to be combined to generate predictions and spot patterns that previously would have remained hidden.
At this stage, companies should be investing in developing data and intelligence literacy skills across the employee base. As a business deploys augmented decision-making, and as every employee starts to become skilled at using data as part of his or her daily work, the organization starts to transform from within.