Power of data
Understanding data at hand is a must for business growth, opines Dr Abhishek Narain Singh, Institute of Management Technology Nagpur.
When it comes to using data to drive business, organizations such as Google or Facebook are iconic… When they started in 2007, big data was not what it is today. All four Vs that define big data—volume, variety, velocity, and veracity—were at lower levels. But perhaps more importantly, there was not much previous experience of working with big data and using it to drive decision making in organizations. At that time, the question was still out as to whether having all that data is useful. Today, the feeling is that the value of data has been proven, and it’s more of a question of how to get it. 1 Diligent businesses are those that ensure data privacy and security while leveraging its multiple advantages.
In the world we live today, data is king. Many economists believe that ‘data to this century is what oil was for the last century’—a driver for growth, change, and success. The findings of The Digital Realty Data Economy Report2, a study by Development Economics, suggest that there is huge potential for the data economy to grow further, boosting businesses and creating more jobs. As per the report, the size of the data economy of Germany accounts for ¤108.3 billion, creating 1.95 million jobs, and has an untapped potential of ¤87.9 billion. The data economy contributes $1 trillion to the US economy every year. The numbers look promising and encouraging enough to have strong faith in the power of data.
According to a May 2018 Forbes article, the amount of data created every single day amounts to 2.5 quintillion bytes. To put it another way, almost 90 percent of the data in the world was generated over the last two years. Now, one can imagine the speed and volume of data being generated through innumerable sources like IoT, sensors, wearable devices, tweets, YouTube videos, mobile communications, chats, pictures, emails, blogs, Skype, print media, TV, smart devices, and so on. To give some statistics, Google processes more than 40,000 searches every second (ie, 3.5 billion searches per day), 456,000 tweets are sent and 4,146,600 YouTube videos are watched per minute; and every minute, 154,200 Skype calls are made, 156 million
emails are sent, 16 million text messages are written, and 15,000 GIFs are sent via Facebook messenger. On top of this, we have humongous amounts of data generated through platform-driven services like Uber, Venmo, and Spotify. Precisely, big data is getting bigger and bigger day by day in volume, velocity, variety, veracity, and ‘value’.
According to estimates, by 2020, 15 to 20 percent of global GDP will be based on data flows. It is believed that by 2022, the size of the digital economy in India will be approximately $1 trillion, and it could constitute almost 50 percent of the entire economy by 2030. The Indian government’s thrust on Digital India and ecommerce space are the building blocks for this. In such a scenario, entrepreneurs and even established businesses constantly look out for new opportunities and unique value propositions for customers. Paytm, Ola, and BigBasket are a few examples. With all this abundance of data getting generated all around, the vital question that a decisionmaker has in mind is: how to make sense of it? How this massive data (structured and unstructured) generating from multiple touchpoints in different formats, offers insights into the products or services offered by the company and help managers sense the pulse of customers, which may enable them to make the right move at the right time?
turning data into insights
It often happens that organizations have a lot of data (internal as well as external collected through a range of sources), but they do not know how to process it to gain value. Habitually, they collect data they themselves do not know what to do with. At times, either it is a mandate from the head office or a regular, not-so-required exercise. Many a time, this job is outsourced to a market research agency, supposedly an expert in converting data into insights, without expecting much in return. However, if followed correctly with mindful efforts, the journey of converting data into insights can be an enriching exercise for any organization. Leading to a data-driven discovery—finding hidden patterns and unusual correlations—this may help businesses and decision-makers know the unknown.
Irfan Kamal, Senior Vice President, So[email protected] in his Harvard Business Review article ‘Metrics are easy, insight is hard’, argues that in contrast to abundant data, insights are relatively rare. In the context of marketing, he suggests a four-step marketing data-centered process: 01 collect, 02 connect, 03 manage, and 04 analyze and discover. He further reasons that brands and companies that are able to develop insights from any level of data will be winners. Thanks to disciplines like data science, business intelligence, and big data and analytics, organizations are equipped with a variety of tools to map data with business requirements and outcomes.
Data-driven decisionmaking has multiple advantages, which make business processes more agile and help managers make betterinformed decisions.
There have been successful cases where data and intelligent techniques (derived from past data and experiences) put together have solved problems in mapping crime, disaster management, marketing campaigns with greater accuracy, predictions with respect to consumer demand/preference and positioning offerings accordingly, providing government schemes and services more effectively, and many more.
data management and decision-making
Unlike earlier, when hardware and later software used to drive (or dominate) the entire knowledge discovery process, organizations have now realized that data is at the core of their business. In any given situation, availability of relevant data and required capabilities to analyze it enable better decision-making. Instead of relying on gut feeling—which may have the limitations of over- or underestimation, wrong judgment, or biases—managers prefer to go with ‘what data says’. This also helps them rationalize their decisions and the decision-making process. Chances of error get minimized and you are ready to deal with a range of scenarios, thanks to simulations, predictive modeling, and sensitivity analysis. Datadriven decision-making has multiple advantages, such as better understanding of the situation at hand (due to the availability of historical data), assessment of alternative solutions (on key performance indicators), and mapping it against the best possible outcome (benchmarking), which make business processes more agile and help managers make better-informed decisions.
To deal with the unprecedented speed at which data is being generated, captured, stored, and disseminated, and gain an edge over others, organizations need a robust data management strategy. Ultimately, in this age of cutthroat competition, one who has the right data can make the right decisions and win the game. It is pivotal for businesses of this age to source data from multiple touchpoints—wherever there is a potential customer and whichever medium he or she engages with—and collate it to get a holistic view for devising strategy. The role of the Chief Data Officer (CDO) becomes very important in this respect. He or she is responsible for putting a data governance structure in place. As data derives value for any decision, its management and safekeeping are crucial.
data privacy challenges
It is good to have a heap of data to take better and informed decisions for your business and customers. But, at times, companies collect too much of user data (that too without their consent) in the name of providing them convenience—for example, serving relevant ads and targeted promotional communications. In the digital age, many believe data privacy is a myth. Tim Cook, CEO of Apple Inc., in his keynote speech at the 40th International Conference of Data Protection and Privacy Commissioners held in Brussels in October 2018, emphasized the fact that data itself is being weaponized against people and societies, arguing that ‘privacy is a fundamental human right’ and that trade in digital data has exploded into a ‘data industrial complex’. Organizations need to be cautious while collecting users’ data and while sharing it with third parties. Cook strongly voiced the need for a privacy law that prioritizes data minimization—minimum users’ data to be collected by companies, transparency, right to access, and right to security. In the digital economy, which thrives on users’ data, privacy and data protection are of paramount importance.
To deal with the unprecedented speed at which data is being generated, captured, stored, and disseminated, and gain an edge over others, organizations need a robust data management strategy.