Data analytics is the foundation of the business decision-making process. Making decisions based on intuition is no longer enough. Today, informed decisions and business intelligence are the driver of any business. We discuss the role of data analytics in business.
Data analytics has become an essential business process for any company. Executives require in-depth knowledge of their business, the market, competitors and customers to make the right decisions and steer their business towards prosperity.
The good news is that we are producing more data than ever before (IDC). The bad is that, despite having data at our fingertips, most companies are still failing to harness its value. According to Forbes research, companies are becoming less and less data-driven.
"Data is not information, information is not knowledge." Clifford Stoll, astronomer and writer.
As Stoll already noted in 2000, in his book The Knowledge Management Yearbook 2000-2001, data alone is not information and information is not knowledge. For data to become valuable information it must be integrated and consolidated. Likewise, in order to extract knowledge from our data, it is essential to subject it to an exhaustive and conscious analysis that allows us to take advantage of it in our business intelligence plan, decipher what we really need to know and transform it into business insights.
In other words: data analytics.
What is data analytics?
Data analytics is the process of turning data into knowledge, intelligence and business insights.
In the business context, data analysis is used to understand the state of the business, the behaviour of customers, competitors and the market; identify pain points, errors or unproductive strategies, define target customers and buyer personas, test or discard theories, etc. Undoubtedly, the fundamental function of data analysis is to support the decision-making process and provide a solid, reliable and trustworthy basis on which to make decisions.
However, for data analysts to be able to extract value from data, it is essential that they have first undergone a long process that starts with data collection and culminates in data visualisation. Unifying it (data integration), transforming it, normalising it, consolidating it, ensuring its quality (data quality), cleaning it, etc
In the same way that a carpenter would never think of trying to assemble a table from a tree trunk, data analysts cannot analyse data with 'dirty' data that is not formatted properly, is not integrated or contains errors.
Likewise, for a data analysis process to be adequate and efficient, it is essential that it is carried out by experts in the field —data scientists, analysts and engineers— and that the business questions to be answered and the business objectives to be achieved have been formulated prior to the analysis. In other words, data analytics must be integrated at the highest level of business strategy.
Today, data analytics must be placed at the core of any organisation. Data is no longer only relevant for the IT department, as it is closely and directly linked to a corporation's entire business intelligence strategies and actions, as well as to the decision-making process.
The same way a carpenter can not build a table out of a log, nor a haulier can drive a car without petrol, a CEO can not make intelligent decisions without data.
Rather than a set of materials kept in a drawer, it is now essential that data becomes part of the overall business culture. In other words, companies must work to build a data-driven culture and to achieve that data analytics plays a fundamental role in all business departments, not just IT.
The role of data analytics in business
As we have already mentioned, data analysis underpins the decision-making process. However, beyond the fundamentals, organisations today use data to ensure the smooth running of many other business routines, as well as to study their performance, uncover business opportunities and create new strategies.
What can we use data analysis for in a company?
There are so many uses for data analysis in the business environment that it is impossible to mention all of them. However, here are some of the most frequent among companies:
- Interpretation of the business reality
- Acquisition of a global, comprehensive and reliable vision of the business and all its areas
- Critical thinking capabilities
- Obtaining insights and valuable information
- Enhancing the monitoring of the business activity
- Fostering inter-departmental cooperation
- Optimising processes
- Streamlining work routines
- Identification of errors, weaknesses and potential areas for improvement
- Prediction of future scenarios (forecasting)
- Increased knowledge of customers
- Definition of target customers and buyer persona
- Identification of business opportunities and generation of actions towards the market
- Improving the customer experience
- Optimisation of existing markets
- Reorientation of business strategies
- Adaptation to an uncertain and unstable market
- Increasing Return on Investment (ROI)
- Risk reduction
Whether it is good or bad news, today it is impossible to deny that we depend on data, especially in the business environment. Data has become the lifeblood of any organisation, a trend that is only going to proliferate in the near future.
However, despite the fact that organisations have more data than ever before in history, it seems that harnessing it and transforming it into value is not as simple as it may seem. For that to happen, companies need data analysts and must strive to build a comprehensive data strategy that cuts across all spheres of an organisation.