Whether you realize it or not, our life is already driven by data. Recommendation engines drive your daily entertainment choices, social media affects your decision-making and so on. The question we should ask ourselves is, are we data-focused in the way we run our companies or not. Do we understand the value of being data-driven?
A data-driven company uses past data from the choices and preferences the company utilized to leverage values, boost productivity, enhance corporate efficiencies and improve overall effectiveness.
This means that the company's strategic decisions are be based on research, data analysis and interpretation, coupled with market reports and "traditional methods." This process should involve the whole company, not just the head office or executives only. In a genuinely data-driven company, the work of every department is driven by the reality of its data. When that combined work effort pursues the goals and objectives of the larger enterprise, then the entire organization benefits from the focus on and clarity of a data-directed vision in all of its parts.
Research has shown that strong data have driven culture grants an organisation greater speed and agility, and thus a competitive edge. Through data, a business can make better decisions, reduce the cost of capital and improve asset utilisation.
Data will play an ever more complex and important role in every organisation. For the potential of data to truly be realised, its use needs to form a part of an organisation’s DNA. Data success demands a data-driven culture.
Data is now the difference between an organisation’s success and failure. Leaders have the responsibility to look for opportunities and prepare for technological challenges, while also having a good understanding of the regulatory framework in which the business operates. By fostering a data-driven culture, the responsibility for these things can be spread, and the likelihood of success can therefore increase.
A data-driven culture can lead to a boost in customer acquisition and growth. The use of big data allows businesses to observe various customer-related patterns and trends. Observing customer behaviour is important to trigger loyalty. Theoretically, the more data that a business collects the more patterns and trends the business can be able to identify. In the modern business world and the current technology age, a business can easily collect all the customer data it needs. This means that it is very easy to understand the modern-day client.
For example, Coca-cola utilized a data-driven culture to drive customer retention. In the year 2015, Coca-Cola managed to strengthen its data strategy by building a digital-led loyalty program. Through the interview undertaken by ADMA managing editor, it was clear that big data analytics is strongly behind customer retention at Coca-Cola.
Several companies are also making use of data to drive more focused customer insights. After years of cautious enthusiasm, marketing and advertising technology sector is now able to embrace data culture in a big way (Medal, 2017). The marketing and advertising sector can make a more sophisticated analysis through data. This involves observing the online activity, monitoring the point of sale transactions, and ensuring on the fly detection of dynamic changes in customer trends. Gaining insights on customer behaviour takes collecting and analyzing the customer’s data. This is done through a similar approach used by marketers and advertisers as illustrated. This result in the capability to achieve focused and targeted campaigns.
For example, Netflix is a big brand that uses big data analytics for targeted advertising. With over 100 million subscribers, the company collects huge data, which is the key to achieving the industry status Netflix has. If you are a subscriber, you are familiar with how they send you suggestions for the next movie you should watch. This is done using your past search and watch data. This data is used to give them insights on what interests the subscriber most.
Currently, because of the pandemic and economic recession, companies need to manage risk very well. A risk management plan is a critical investment for any business regardless of the sector. Being able to foresee potential risk and mitigating it before it occurs is critical if the business is to remain profitable. Business consultants will advise that enterprise risk management encompasses much more than ensuring your business has the right insurance.
UOB bank from Singapore is an example of a brand that uses data analytics and machine learning to drive risk management. Being a financial institution, there is huge potential for incurring losses if risk management is not well thought of. UOB bank recently tested a risk management system that is based on big data. The big data risk management system enables the bank to reduce the calculation time of the value at risk. Initially, it took about 18 hours, but with the risk management system that uses big data, it only takes a few minutes. Through this initiative, the bank will possibly be able to carry out real-time risk analysis soon (Andreas, 2014).
Amazon is one of the best examples also of companies that are benefiting greatly from a data-driven culture. Amazon Fresh and Whole Foods is a perfect example of how big data can help improve innovation and product development. Amazon leverages big data analytics to move into a large market. The data-driven logistics gives Amazon the required expertise to enable creation and achievement of greater value. Focusing on big data analytics, Amazon whole foods can understand how customers buy groceries and how suppliers interact with the grocer. This data gives insights whenever there is a need to implement further changes.
General Electric (GE) is using the data from sensors on machinery like gas turbines and jet engines to identify ways to improve working processes and reliability. The resultant reports are then passed to GE's analytics team to develop tools and improvements for increased efficiency. The company has estimated that data could boost productivity in the US by 1.5%, which, over a 20-year period.
While it will take time and money to set your organization on a data-driven path, once you've established the necessary culture and foundation, you can make much more informed decisions.
Benjamin Sombi is a Data Scientist, Entrepreneur, & Business Analytics Manager at Industrial Psychology Consultants (Pvt) Ltd a management and human resources consulting firm.
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