Coupled with technology, data can transform the way businesses operate to stay ahead of their competitors.
Consider this example: A growing number of companies in the country give their customers loyalty cards on which they earn points every time they shop.
Those cards collect immense data about shoppers and their shopping habits.
Besides the demographic information of the shopper, the cards collect data on the number of times the shopper makes purchases in a particular period; the amount of money he spends every time he shops; the outlets where he buys his goods, what he buys and much more.
These companies dole out thousands of such cards to their customers, effectively turning their clients to data collectors.
These data can be used for many things. They can be sold to other companies.
They can be analysed to shore up important insight, which could propel the company to higher profits.
Companies that sell their products online always have potential for more data.
They can track online shoppers. They can see what products they buy, and other products they click on but don't buy.
"Clicking" on a product means that one may be interested in it.
Armed with these insights, a company can send the client information about similar products, and increase the chances of selling.
The point is, embracing data as a competitive advantage is a necessity for today's business.
The declining costs of all elements of computing - storage, memory, processing and bandwidth - means that previously expensive data-intensive approaches are quickly becoming economical.
The question is, why are many companies not delving into data as they should?
It is because preparing and packaging data for analysis is tedious and calls for rare skills.
Expertise to mine these treasure troves is in high demand, but in short supply.
Data scientists understand how to fish out answers to important business questions from the information Tsunami.
Data science is broad - it is not all about data and technology. It's also about the business.
To stand out as an authority in data science, look at the business you serve and the critical issues you face.
As a data scientist, make sure to use the data to tell a story that will make decision-makers in your company see the new insights.
Always make clear the assumptions, uncertainties and concerns in the data that you present.
But don't stop there. Ask yourself if the results you unravel match your feeling and understanding of the situation.
If you see something that doesn't add up, ask yourself whether there was an error in the data.
True data scientists are comfortable speaking the language of business, the same way they talk technology and data.
They help leaders reformulate their challenges, guided by new awareness emerging from data.
Data scientists must regularly update their skills to remain at the top of the game.
They read, study, and attend conferences in their field.
They find mentors in their field to challenge them to grow and see different perspectives than they are used to.
Like great sportsmen, they engage coaches to work with them to narrow the gap between their performance and their potential.
When faced with important decisions, a common question among leaders who seek the counsel of data is, "What is the data saying?"
They submit to data. They introduces a culture of conceding defeat when data disapproves their hunch.
They belong to the tribe of leaders who ascribe to the philosophy of evidence-based decision-making.
The evidence is clear: Data-driven decisions tend to be better decisions. Business leaders will either embrace this fact or be replaced by those who do.
Source: Daily Nation