5 Oct 2022| Blockchain
Driving Employee Engagement with AI
There are hundreds of ways AI and Machine Learning are being applied in today’s companies to drive more employee engagement. From extracting insights from current performance data to automate tedious tasks to eliminating bias and enhancing diversity in the workplace, today’s companies are quietly being revolutionized by the proactive and pragmatic application of AI.
The adoption of Machine Learning and Artificial Intelligence into the boardrooms of the major corporations has given rise to a new era of business leadership, one characterized by accurate and timely decision making, real time execution of key priorities, and increased profitability. This is particularly exciting for smaller companies that have traditionally had trouble achieving top levels of business success due to the “learning curve” associated with the evolution of management principles and business culture.
Companies that are best suited to embrace Machine Learning and AI will most likely be those with the most expertise in working with a wide variety of people, tasks and information. They will also need to be rapidly adapting to changes in labor economics-the gap between demand and supply in labor markets that have been generally flat over the past fifteen years is increasingly narrowing, even in the face of global competition.
Additionally, companies with a strong competitive advantage will enjoy solid returns on investment because they can pass on higher labor costs to their customers. For these reasons, top executives at large companies have spoken candidly about the need to focus on improving employee engagement. If these leaders are to be believed, then we may soon witness a wave of major corporate initiatives centered on solving some of the most fundamental challenges associated with engaging employees and building organizational culture.
Currently, many of the largest companies in the world have been measuring employee engagement through the employment relations function of human resources departments. While this has proved to be an effective way for firms to determine whether or not their workers are satisfied with their jobs, this type of survey does not provide enough details for executives to make informed decisions about engagement levels. For example, it does not indicate what types of activities and relationships within the organization foster greater employee engagement.
This gap is expected to be addressed by newer organizations like ONPASSIVE in the future. These consulting firms are currently collaborating with artificial intelligence technology developers to build new technologies that will allow businesses to determine more specific aspects of employee engagement. In this way, organizations can begin to address problems like low employee participation rates without taking the potentially complicated steps of implementing complex logistical plans.
Companies that can measure and improve their supply chain performance can better anticipate problems before they occur, which can prevent a number of issues such as over-producing or under-utilizing key materials or services. Ultimately, firms that make use of detailed logistics data can reduce the potential impact of policy changes and operational glitches on their businesses, allowing them to better manage their operations and avoid costly mistakes that impact employees.
Organizations can also use detailed logistics information to learn about worker demographics and behavioral patterns. Data from a variety of sources can allow managers to evaluate and create work environments that promote overall engagement. It has been shown that employee turnover rates increase when certain factors are present such as an unhappy work environment. According to Kornblum, A.I. software can be used to collect information from various types of sources, including social networks, online surveys and off-site visits by employees.
To that end, organizations can also use A.I. software to provide an employee survey that collects information on the experiences of new hires. A survey like this can gather information on the types of problems employees have encountered while working at the organization as well as how these problems were handled, the relationships with management and other co-workers, and overall satisfaction with the organization. Kornblum believes that a comprehensive survey can help managers identify areas in need of improvement, as well as provide insight into the reasons why employees leave companies for other opportunities. Measuring organizational burnout and engagement can help managers prevent organizational crisis, such as what happened to Yahoo! recently, or what led Microsoft into the arms of the cloud, according to Schaufeli et al.
It is needless to say that employees make the backbone of any organization. It cannot sustain with a set of unsatisfied employees. With intricate data curation to understand the psych of an employee and improve every experience, AI can bring in a new level of employee engagement. There are various HRMS tools like ONPASSIVE O-Staff that come with special features to address employee concerns and run survey while accumulating data to understand every employee needs. If you are a business and have employees that you depend on then it is a good idea to scale up with a great tool for employee engagement assessment.
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Tags: Technology Artificial Intelligence