We provide you with a simple explanation of the different applications of data science to help you better understand what it can do and help spark ideas for your own business.Data science is now considered one of the most influential factors affecting the success and failure of many modern business ventures. Businesses that embrace data science tend not only gain a competitive edge over rivals, but are also able to maximise growth through innovation. However, the general understanding of data science and its applications remains vague at best, preventing business owners and their employees from tapping into its full potential.
With data science, firms can gain insights and explore provide solutions for their business. It sounds simple until companies begins sorting through massive amounts of data within and outside the organisation. However, to data scientists, the more the data variety the better. It enables them to explore different approaches and impact the business in different ways.
Data science promotes new ideas and innovation that can lead to growth. Data science is the key to unveiling better solutions to old business problems. It also uncovers hidden issues and provide solutions to them. Knowing how to glean insights and drive action from an existing data analytics product can significantly help a company focus on critical business challenges. Insurance company Manulife created a new mobile application based on its database of existing user data in Hong Kong. As a test market, it offered members the opportunity to decrease their premium payments if they voluntarily utilised the insurer’s MOVE application, which would track their exercise activities on a daily basis. Those who exercised regularly would receive a discount on their health premiums. This application incentivised new and old members to buy Manulife’s products.
2. EXPLORE TRANSFORMATIVE PATTERNS IN DATA
Through data science, leaders and organisations can better explore transformative patterns provided by big data and turn them into values that can drive revenue growth. Data scientists use different techniques to probe current processes and develop new methodologies or analytical algorithms. Their primary task is to continuously improve the value extracted from the organisational data that they have at their disposal.
The Singapore Actuarial Society ran marketing predictive analytics over a set of data comprising information on 41,188 individual telemarketing records for a Portuguese bank. They knew from the outset that for 200,000 calls $500,000 of profit was likely, based on the existing knowledge. That equated to a 10% success rate. The actuaries knew that by using predictive analytics, they could rank customers ranging from 50% to 5% based on their likelihood to purchase, and by eliminating calls to the customers least likely to purchase, they could increase successful sales from 10% to 80%.
3. RADICAL NEW SOLUTIONS
With data science, industries are now approaching complex data-rich problems on a scale larger than humanly possible. Data scientists are now using machine learning algorithms to solve sophisticated problems. The machine spots patterns within historical data and recommends solutions that are radically new or hyper-personalised to each situation. There is virtually no limit to the number of real-world business challenges that data science can tackle. Airbnb achieved 43,000% growth in five years; this was not an accident. It was one of the few startups of its time to have a data scientist onboard in its early days. They took the approach of recharacterising data as human decisions, whether that was the data coming in from user questions and feedback, or whether it was Airbnb itself analysing that data to make decisions. Airbnb says that “we’re at a point where our infrastructure is stable, our tools are sophisticated, and our warehouse is clean and reliable. We’re ready to take on exciting new problems.”
4. IMPROVEMENT OF EXISTING PROCESSES AND PRODUCTS
Besides providing new ideas, data science can also be used to enhance current business processes and products. This is, in fact, the most common application of data science that many organisations can benefit from. For instance, data scientists can work to improve production processes by refining the established procedures and products based on the data gleaned by the organisation. One such example was so groundbreaking and effective they made a movie about it. Moneyball is about the use of a single data scientist to beat financial disadvantage and change the way an entire sporting profession analyses and selects players.
5. IDENTIFY PROBLEMATIC AREAS OF BUSINESS
This particular category uses the same methodology as when exploring transformative patterns in data. Data science techniques, such as categorisation & sentiment analysis, are used to determine the drivers of undesirable situations in the business. During these cases, data scientists are solely focused on identifying the root causes of these problematic issues. Businesses often use this method as a response initiative to crises like sudden drops in profit or an increase in customer complaints. One multinational business, that shall remain unnamed, was facing a highly critical report from a well-known international NGO. They feared the critique would cause a backlash of public opinion and bad media coverage that might erode sales. But data analysis of web and social media interactions showed that there was very little public concern. The multinational decided to reserve their response instead of creating a bigger deal out of it, which may have caused more controversy than the original NGO report itself.
Data is a driving force that can transform businesses and lead them toward success. As a business owner or executive, it is vital that you understand the amount of value that can be extracted from the massive data that your organisation generates every day. Take advantage of it and embrace the opportunities data science presents.
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