5 Traits of an Effective Data-Driven Enterprise

Although virtually every business acknowledges that Big data is changing the way businesses operate, very few are prepared to benefit from it. The companies best-suited to compete have transformed themselves into data-driven enterprises.

Data-driven organisations use data to inform decision-making and business strategy. What differentiates them from others is that they have built the necessary technological capabilities for it and their culture doesn't interfere with their ability to use data.

It can be difficult to become a data-driven organisation. Although every organisation has loads of data, their ability to gain meaningful information from it varies from one company to the other. Even if an organisation has the technology to collect, cleanse, manage & analyse data, it can be difficult for a business to realise it's true value if its corporate culture is not in sync with its technological capabilities.

Here are the 5 traits of an effective data-driven enterprise:

1. Use data as a means of growth

Data-driven enterprises evaluate where they stand, where they need to go and how to get there. To ensure that they are on the right track, they establish KPIs to monitor business operations, activities, departments & processes. They also create cross-functional team of decision-makers and stakeholders who ensure that business goals, company practices and technology go hand-in-hand.

Enterprises that integrate data into their business processes see it as a means to grow their business and differentiate from their competitors. It enables them to focus on long-term objective instead of short-term tactical gains.

2. Spot Opportunities & Risks quickly

Traditionally, enterprises adopt Business Intelligence & Data Analytics to make better decisions faster. However, data-driven enterprises go a step further and also use data to uncover growth opportunities & risks which may have previously unknown due to lack of data or technology.

According to Gartner, more than half of Big Data projects are not focused on decision-making. Instead, they focus on sales & marketing growth, improvement of operational and financial performance, compliance management and product or service innovation.

3. Hypothesis is valued over Assumption

Generally, enterprises employ database querying and reporting to find answers to their questions. This works under the assumption that you are asking the right questions. Data-driven enterprises constantly try to improve the questions they are asking and come up with hypotheses to explain trends and outliers. Using machine-learning or other techniques, some of them even try to understand what questions they need to ask. They design data analytics models to test their hypotheses and arrive at the answers. They even enable self-service data analytics for their business users so that they can iteratively adjust their approach based on the latest insights.

4. Decisions are based on Data Analytics

Data Analytics has completely tranformed the way every department operates. More departments than ever are using Business Intelligence & Data Analytics to improve process efficiencies, streamline costs, calculate ROI on initiatives, boost operational performance and improve customer satisfaction. In a data-driven enterprise, each role has the ability to influence what data needs to collected and how it needs to be used. Conventionally, this privilege was confined to the data analytics team. Big Data and Analytics are on the agendas of directors and executives, which means they have to adopt these technologies and lead by example. According to a survey by Aberdeen, data-driven companies are 63 per cent more likely to adopt advanced analytical capabilities among the senior management.

5. Contant experimentation & exploration

Many organisations have invested heavily in BI, Data Analytics & Big Data. However, they tend to hesitate when it comes to encouraging experimentation among those who are not business analysts or data scientists. This discourages innovation and original thinking. Data-driven Enterprises encourage employees to experiment with data and explore them for new insights. Such experimentation can sometimes, result in failure. Progressive companies are willing to accept such failure within certain limits. They understand that failure to taks risks is more dangerous than risking failure.

Data-driven organisations enable the use of data across various business functions, from C-level executives to frontline managers. Rather than waiting for employees to adopt Business Intelligence and Analytical Tools, they train their employees, make the systems easy-to-use for everyone, and monitor the use of these systems. Their ability to compete effectively depends on how they leverage data. Such data-driven organisations ensure that their values, goals, and strategies are aligned with their ability to execute.