There are big companies like Amazon, Uber and Netflix that use data to move the entire business context. And then there are those who treat data only as an aspect of technology projects.
Based on a Gartner material, it is possible to understand the role of data and analytics as a corporate asset and its importance. In addition, the means of dealing with them and the human role in the actions. Follow!
Data usage
Data and analytics are a catalyst for digital strategy and transformation as they enable faster, more accurate and relevant decisions in complex and rapidly changing business contexts.
The digital strategy therefore consists of turning numbers and information into insights. Therefore, it is important that strategic managers are able to ask more specific questions through data, to improve the outcome and impact of these decisions.
Importantly, decisions drive action, but they can also determine when not to act. To take advantage of the full potential that data has, there are some types of analysis that are fundamental. Are they:
• Predictive analytics: the use of past data to predict future events;
• Prescriptive analysis: Aims to turn the analytical look to the consequences of past actions;
• Descriptive analysis: Mining in real time to get quick answers to today’s questions;
• Diagnostic Analysis: Performs a broader view of the data. It is used for planning.
What are the key elements of the data and analytics strategy?
It is important for each organization to define what data and analytics mean to them and what initiatives (projects) and budgets are needed to capture the opportunities. Here are the key steps in strategic data and analytics planning:
1 – Outline the mission and objectives of the organization;
2 – Determine the strategic impact of data and analytics on these objectives;
3 – Connect every action to achieve business goals using data and analytics;
4 – Build a strategic data and analysis roadmap;
5 – Implement this roadmap (ie projects, programs and products) with a consistent and modern operating model;
6 – Communicate the data and analytics strategy and its impact and results to build support for execution.
The entire strategic data analysis procedure is handled more simply if those involved have a mindset focused on applying these steps. This mindset is developed gradually and is called data literacy.
What is data literacy?
Gartner defines data literacy as the ability to read, write and communicate data. It requires an understanding of data sources and constructs, analytical methods, applied techniques, and the ability to describe the use case application and resulting value.
This might sound like an argument for training all employees as data scientists, but this is not the case. From a business perspective, you can simply summarize data literacy as a program to help business leaders learn how to ask smarter questions about the data around them.
Building data literacy within an organization is a culture and change management challenge, not a technological one. However, this kind of lasting and meaningful change requires people to learn new skills and behaviors.
Best practices for organizations include putting much more emphasis and energy on the change management portion of the data and analytics strategy.
How to implement strategic data analysis in my company?
Implementing data literacy is a necessary investment, but one with long-term results. To anticipate the use of data as precisely as possible, it is interesting to have the support of specialized companies.
The greater the amount of information to be collected and treated, the greater the difficulty of handling it. iBlue has experience with large companies, offering strategic ways to visualize and use them in the best way.
Follow our blog and understand more about iBlue’s expertise with data and analysis.