Data is information in its raw form and it can be collected to be examined in an effort to gain knowledge, draw conclusions and make decisions. The field of data analysis is called data analytics and it involves studying past historical data to research potential trends, to analyze the effects of certain decisions or to evaluate the performance of a given idea or scenario.
Data analytics is a very important tool in business, especially in the modern Internet of Things era where products are connected to record and transmit usage and performance data. Companies can employ qualitative and quantitative techniques and processes to enhance productivity and business gain. Data can be extracted and categorized to identify and analyze behavioral data and patterns. Companies can collect and analyze data associated with customers, business processes, market economics or practical experience in an effort to study purchasing trends and patterns and anything that is relevant to company verticals.
A data driven approach to business means using all information drawn from data analysis to optimize existing business goals and investigate new possibilities. Banks and credit card companies can analyze withdrawal and spending patterns to prevent fraud or identify theft. E-commerce companies can examine Website traffic or navigation patterns to determine which customers are more or less likely to buy a product or a service based upon prior purchase or viewing trends. In the modern business world, companies that are getting ahead are using lots of analytics to make the right decisions.
Building a data-driven business requires building of the right data infrastructure. This is the underlying technology that will be used to collect, transmit, store and deliver data for analysis so as to monitor the business and understand new opportunities. With increasing and continuous changes in technology, a company will need to adopt the kind of infrastructure that will gather the relevant data and be aligned with the company’s goals. Therefore, a company needs to approach the infrastructure with their goals in mind, while at the same time creating room for flexibility because as the company grows and evolves, its needs will change and this would require adjustments to infrastructure.
Managers need to source data creatively and choose the relevant data. Before gathering any given data, companies should have a solid understanding of what exactly is being measured or examined, why it is important to the business and how the results might influence decision-making or change how things are done. Each and every piece of data collected should attempt to answer a fundamental business question, such as ‘Is the company’s brand awareness improving?’ There is no inherent value in data collection-it is only valuable insofar as it helps the company.
2. Accessibility of Data
Data should not be restricted to employees in the Information Technology or technical departments only. Companies should strive to allow all employees and staff to also have access to the data. The more people who can access and use the data to measure performance , evaluate improvements, and learn about the business and customers’ needs, the better for the company, shareholders, managers, employees and even customers. The key is to get data into the hands if those who recognize what it means and for that data to correspond to clearly defined metrics.
For a truly data-driven business to function at its peak, the ethos of analysis must permeate the entire company.
Companies should also create room for experimentation. Executives can provide the ability to test innovations and treatments and learn from the performance data before making big decisions.
3. A Data-Driven Culture
Creating the right corporate culture that goes in line with the companies goals goes a long way in helping the company achieve its goals. In building a data-driven business, a company should therefore foster a data-driven culture. This goes in line with data accessibility in that creating a data-driven culture will require the infusion of data collected into the whole workforce. Data analysts should be part of the workforce.
It also requires a company-wide philosophy of innovation and experimentation, where employees are constantly seeking opportunities for new products, services or features. Companies should establish corporate cultures that request evidence from data as part of standard decision-making processes.
4. Social Media
Social media platforms are changing the marketing landscape by proving analytics for companies for free. They generate terabytes of nontraditional, unstructured data in the form of conversations, photos and video. This is a shift from the conventional model where companies had to rely on consulting firms to gather data relevant to their businesses. Companies can therefore integrate social media capabilities into the decision-making environment. They can use social media data analysis tools to monitor social networking sites for comments about the company and its products, and to measure the company’s social media strategy in influencing things such as brand recognition and customer sentiment. Some examples of statistical data that can be collected from social networks and then analyzed include audience distribution, number of impression per posts, mobile device interactions and responses by users.
Those metrics can be broken down by different dimensions, including time of day, geographical location, browser type and corporate domains. This can go a long way in helping a company make appropriate decisions and social media analytics tools can be very reliable especially to the customer service and marketing departments.
The Internet of Things is about data and having a data-driven business is a sure way of gaining competitive advantage over other companies.