Using data insights to manage client expectations
by Sachin Rathi in General
In today’s world Data is the new Oil. Across most industries data has become a precious entity with organizations collecting data to support and drive their decision making process. Yet it is not easy, why? Because data is valuable only if you understand it and can translate it into actionable decisions. This is where experts who can gain insights from raw data, like Nuage, play an active role by utilizing tools to analyze data.
What makes data actionable based on insights?
The real gain from insights into behaviors of all stakeholders from the analysis of data is when they result in actions. These could result in:
- A new blueprint for the organization to help streamline processes and optimize productivity
- Increases organizational efficiency
- Provide greater value to the consumers.
How do you categorize the process of using actionable insights to meet client expectations? The answer is a list of key attributes that act as a guide to business and IT team analyzing the data. These help guide the team to achieve the goals in an optimal manner and timeframe.
List of attributes:
- Understanding client business and demands: The first and most important aspect is to know the client’s demands on collecting data and implementing necessary actionable insights. Preparing an analysis of how the actionable insights will affect the company’s business.
- Relevance: Numerous insights can be separated from a single dataset. However, this insight obtained is useless if it is not relevant to the problem or demand raised by the business. Choosing your measures relevant to the business demand is crucial to generate effective actionable insights.
- Specificity: Detailed insights will provide ease in generating actionable insights based on the data analyzed. Also, having detailed and in-depth data capable of providing genuine results will help gain business’s trust.
- Context: For analysis to churn out significant meaning for the business, it is important to define why such data was selected and where its actionable insights will be implemented.
- Alignment: The generated actionable insights are to be validated with an alignment test prior to their implementation. Because insights generated from KPI data will match in the test but not all insights are based on KPI parameters. Thus this allows you to match and align the data with the customer requirements.
Our team of experts at Nuage with all these attributes in place will help you extract meaningful information and make the most out of data. We have experience working with multiple clients where we helped them create efficient data extraction models for data analysis and visualization resulting in generation of actionable insights.
If you too are interested to optimally utilize the data while gaining profits and meeting business expectations contact us at info@nuagebiz.tech