Data Analytics is the New Industry Standard

Place Stock in Good Data

Playing the stock market has made and lost many fortunes. It is not enough that one simply buys any or all stock to make money; it is important to buy good stock in order to capitalize on an investment.

Data are the stock shares of an organization; good data is a sound investment. Just because one can collect all data does not mean that one should collect all data. It is essential that one collect the good data in order to capitalize on the learning process.

When data is collected in mass quantities, a learning and development department runs the risk of using worthless, unusable data that costs valuable time and resources. Defining good data is best left in the hands of able professionals such as the consultants from a managed learning services provider like VisionCor. A skilled consultant can objectively separate good data from bad data. The right data in the right hands serves as a catalyst for achieving organization objectives.

Eliminate Bad Data

While good data is the catalyst to faster growth and achievement, bad data can cripple and make stagnant any growth whatsoever. The industry has evolved in such a way that organizations are relying on data analytics, learning analytics, and business analytics in order to connect and streamline processes within their organization. Employing these analyses informs the business intelligence that allows an organization to achieve goals more quickly, oftentimes outpacing other, similar organizations that do not employ such practices. An evolving industry should produce evolving standards within business practice. Those standards are determined by the need and output of each organization.

Learning and development teams often struggle to provide quantitative data regarding training programs because of they are using all available data rather than the good data that will best inform practice. Need and output are the best informants in that process. If data cannot answer these questions, then it should be discarded. If a team is struggling to assess data regarding its usefulness, then a managed learning services provider such as VisionCor can provide a consultant to seamlessly enter the process and determine what data serves to inform the needs and outputs of an organization.

What, How, and Why of Data for Learning Analytics

VisionCor professionals look to analyze data according to the science of business intelligence, which answers the what and how of a practice. This analysis would determine if there were gaps in knowledge and skills, if there are steps necessary in a chain of work, or if there are weaknesses in learning management system capabilities. It would also determine how such examples could be adjusted or solved. While the what and how is important in having a good understanding of current processes, the understanding cannot be complete until determining why these processes should be changed or remain as they are in the future.

For this reason, VisionCor professionals look to analyze data according to the science of business analytics and learning analytics in order to determine the why of a practice.  It is not enough to know what and how something should be done. Knowing why something is done leads to a deeper understanding of the pulse of an organization. Knowing specific needs and why it affects output as it does ensures a faster track toward business output and an understanding of the components of the organization that allow for it to be further fine-tuned within an industry that continues to evolve.

Good Data, Good Company

If good data is placed in the hands of a skilled designer, then nothing but good can come from using it. Good data will shape a strong, attractive company profile with a clear corporate goal, specific and clear-cut training goals, and a realistic, obtainable return on investment. This part of the process is the ending point of analysis, though.

When data is used to analyze organizational processes, it keeps this process running in a cycle in order to keep a close guard on the strength and life cycle of a company. The company profile that was initially constructed will provide in-depth information that informs how an organization keeps and defines objectives, risk management, and other critical organizational skills and operations. A good data farmer will know how to tie every piece of data to the components of the company and the essential tenets of the corporate profile. Good data nourishes and strengthens the profile of a company that knows how to evolve and grow in today’s market.

Good data informs the data and learning analytics that provide quick solutions to education and training programs. If one is new to the standard of learning analytics, then Part 1 of this introduction is a good place to start. Part 2 is a good look at how learning analytics will work within an organization. Of course, nothing beats a cursory consultation with a managed learning services provider such as VisionCor. Now is the best time to cut wasted time, money, and inefficient training and education from the organizational process. Now is the time to capitalize on company strengths and identities in order to create defined objectives and efficient processes. Now is the time to employ learning systems thinking in order to best use current resources to a stronger corporate profile and output.