The recent rise of big data has resulted in the transformation of traditional business methods. No longer do organizations rely on data obtained from external sources. They use advanced computing techniques, advanced software applications, and sophisticated analytic capabilities to collect, organize, analyze and act on this wealth of data. Big data analytics allows users access to previously unthinkable insights, allowing them to make decisions that would have been too risky or time-consuming just a few years ago.
As organizations become more data-driven, they need to leverage all the information they have gathered effectively. The significant data phenomenon has created a new need for talent agencies. This is because human capital – specifically highly talented but less visible talents – are becoming increasingly important. As technology improves and organizations require more data to make informed decisions, agencies need to develop tools to capture and leverage the hidden talent within their client’s pool. To be successful, talent buying must take place on the platform of big data.
Talent agencies are currently leveraging the power of three technologies to increase their effectiveness:
First, they are developing an intelligent agent platform that streamlines finding and hiring the most effective talent. Real-time data feeds allow agencies to view jobs in a fraction of the time it takes traditional recruitment processes to conduct. The platform streamlines the screening process by focusing on an organization’s kind of candidate and skills. It also facilitates the sourcing and recruiting process, cutting costs and wasted opportunities.
The second platform for the agency is their internally hosted dashboard:
The dashboards, developed internally by the agency, allow them to view and monitor the talent market quickly. In one place, the organization can manage hundreds of job opportunities at one time. They can also quickly identify which jobs are not staffed and why. The platform makes it possible to share internal and external data with key decision-makers and help them gain a competitive advantage by improving the quality of their hiring decision. This enables them to make informed decisions regarding their staffing.
Companies have started deploying big analytics solutions because they have realized the strategic importance of big data for business decisions. Today, businesses use big data analytics to understand consumer behavior, understand competitor strategies, and gain a competitive advantage. These days, big data analytics drives business outcomes by improving productivity, reducing the cost of doing business, reducing vendor risk, and giving companies greater customer insight. In short, big data analytics is changing the way business is done.
The third application of big data analytics in the supply chain:
Today, companies use big data analytics to understand their supply chains and build better ones. Supply chain involves the entire life cycle of goods produced in the business. It starts with the design of products and ends with delivery. At every stage, new technologies and strategies are employed to streamline operations, improve productivity, reduce waste, and cut costs. By enabling companies to address problems in their supply chains, big data and contextual intelligence can help them improve productivity, reduce costs, reduce cycle times, and increase profits.
Another application of big data analytics and its impact on business activities is global customer optimization (GCO). GCO allows a company to combine data from all critical elements in the supply chain to more efficiently make decisions about specific products. For example, in the manufacturing and assembly process, a company can use data on worker productivity, part count, and material costs to improving their overall efficiency. They can also take this a step further by applying this information to sales and service activities to realize faster, better, and more accurate projections of customer satisfaction and customer demand. Global customer optimization involves using big data and its associated tools to improve company performance as it applies to all aspects of its business.
Perhaps one of the most exciting uses of big data and its impact on decision-making is its ability to drive efficiencies across the organization. Companies use these tools to analyze data, make informed decisions, visualize the data and its implications for performance, and facilitate collaboration across the business.
Conclusion
Data visualizations tool companies such as ONPASSIVE and more enable organizations to view jobs, teams, and tasks on a map to more effectively see where they are doing things when they’re doing them and what they’re doing daily. When data visualizations are applied to decision-making, it’s known as “behavioral dashboards.” Using this tool, a company can reveal which employees are wasting time, performing inefficiently, and causing productivity issues with quality.
We at Onpassive Digital are work towards making Data Analytics and Big Data available to all the businesses and help them in achieving their maximum reach and realizing goals.