Data analytics has played a key role in business management and continuous improvement in recent years. We’ve already discussed 10 Ways Data Analytics Can Improve Your Company, so now let’s talk about how data analytics will change in the coming year.
“Analytics has become a great way of finding the best talent and improving recruitment and hiring processes,” said HNM Systems Managing Director Kristin Schaer. “We are now able to find great candidates using new tools such as behavioral and cognitive assessments and interview results. By analyzing the behavioral drives of employees and organizations we can find the factors of behavior and why employees stay or leave an organization.”
Here are 4 ways that data analytics are expected to change in 2019, and how your company can use it to continue growing.
- Privacy Concerns. It will continue growing as a major issue within data analytics. In May 2018, the European Union passed new data protection rules. It is expected for more countries to continue adding regulations and fines to protect data and be transparent about data collection. Make sure that you are being transparent about which data is being collected from your website.
- Competition based in Customer Experience. In the past, companies have competed in price, quality, services, etc. but now they will be competing on customer experience. Using data analytics in this capacity can help your company track and predict consumer behavior.
- Customized Analytics. Data analytics are moving away from data analytics dashboards that have limited functionality and standard sets of metrics, which are used to collect large amounts of data. Companies are turning toward embedded analytics dashboards, which deliver metrics and insights based on user queries. This will give you a much more detailed analysis.
- Shortage of Data Analyzers Worsens. The field of data analytics is growing at a faster pace than there are people joining the workforce. This has caused delays in the development of more data analytics. This expected to give way for more self-service analytics tools to account for the labor deficiency.