GPS systems have completely changed the way we get from point A to point B. We no longer need to pull out a map for directions, and getting lost is a thing of the past provided your device has enough battery and signal. While we take GPS for granted, there’s a huge amount of data gathered on the backend to provide information on tolls, construction work and traffic jams to give us the best possible route as we need it.
At WalkMe, we see the potential of big data analytics within the workplace to create a “GPS” for employees to navigate through internal systems. Enterprises are increasingly using sophisticated technology for their standard operations, and these provide analytics on what data is being entered. However, we see the future geared towards a larger view of how employees are actually interacting with the software, so companies can better maximize their technology investments and provide teams with the guidance tools to ensure user adoption.
The lifecycle of an employee
Whenever someone joins an organization, the onboarding process is fairly formulaic. One common activity is that he or she will need to create a profile in the company’s HR solution, including their personal details. If a new hire is unfamiliar with the solution, there may be an orientation to familiarize the individual with the technology, as well as additional documentation to help get the employee up to speed.
But there are several challenges with this approach. Firstly, classical training models are typically passive exercises, rather than real-time formats in using the technology. Secondly, training is conducted uniformly, not accounting for an employee’s skills or experience. Finally, research shows that we’re likely to lose 90 percent of new skills within a year when not reinforced.
We can apply a similar situation to other workers. Take using customer relationship management (CRM) solutions for sales and marketing teams, for example. While most employees will be familiar with the basics, is the software being used to its full potential – or are workers unaware of its capabilities? Are all the fields being updated, or is important information omitted within the application? In both cases, the insights derived from the software are only as good as the data entered in.
Forget about forgetting new skills
When one-third of employees quit their jobs after a mere six months, it’s evident that a repeatable and scalable technology is needed to support how workers use various business applications.
Fortunately, big data analytics is at the stage where it can serve as an overlay to assess how employees are engaging with a specific solution. Based on a comprehensive analysis of system use—including assessing details such as employee job title, specific business requirements, and time frame to completion—businesses can uncover the common obstacles to adoption and identify opportunities to improve how to engage users. For example, an organization may realize that the reason why people fail to complete their performance reviews is because they struggle to create professional goals. Or they may find that sales reps aren’t entering prospect deals because they don’t know that they have to select the industry the business is in first.
Additionally, instead of relying on passive forms of training, machine learning can provide contextual guidance on how to use a software. Even if the employee has not encountered the particular software the business has chosen to implement, through recognizing patterns in user behavior, employees can be walked through each step according to their roles and familiarity, reducing the need for IT help desk support and ad hoc training while improving accuracy and productivity.
Automation and the future of work
Big data, combined with machine learning and AI, will enable companies to roll out virtually any solution, and rest assured that their employees are effectively using the technology. Machine learning will discern how to personalize the experience based on an individual’s job title, objectives and familiarity with the application. Meanwhile, big data will allow companies to assess how systems are being used, quantify the improvements, and correlate this to the bottom line. In the near future, AI could bypass these processes to automatically enter the information specific to each user.
We’re on the cusp of embracing the next major disruption to how we work. By analyzing how we engage with the systems and platforms, we will be able to optimize them for better use and better business.