The rate of creation and consumption of data has being studied, hyped over, and predicted for years now. Estimates suggest that 90% of the data available today was created in only the last 2 years. We, as a race, create 2.5 quintillion bytes of data on a daily basis. With the growth in the amount of data, an industry that is bound to flourish is the data analytics industry. Dan Vesset, group vice president of Analytics and Information Management at the IDC, predicte global revenues for big data and business analytics will increase from $130.1 billion in 2016 to over $203 billion in 2020, with a CAGR of 11.7%.
The industry is characterized by humongous amounts of data and a new generation of technology tapping into well-structured mathematical algorithms. Industries across all verticals – discrete manufacturing, process manufacturing, federal/central government, telecommunications, utilities, insurance, transportation and professional services – have joined the bandwagon of trades, after banking, investing in data analytics.
It’s pretty obvious therefore, that data analytics is the place to be. Here are some in depth incentives.
1.) The sheer volume and variety of data is larger than ever
An organization pools in data from multiple sources, including employee records, revenue reports, and competitor performance reports. Depending on the industry the organization deals in, there are additional documents and data sources. This causes disparity and huge amounts of data being collected and consumed in a single organizations. The catch however, lies in integrating, centralizing and analyzing the disparate data to derive useful information.
Unless a core data analytics infrastructure is set in place, the data flowing in from various sources will still be utilized scarcely and will thus add on to the noise that goes into the trash of all organizations. Setting up a dedicated data analytics teams on the other hand, will enable teams to assemble data, that seems isolated from the source. Coupling that with competitive technology and mathematical tools can help one automate tedious processes that go into analyzing and consuming the data in an efficient way.
2.) Data Analytics help you engage better with your customers
Most industries in the current scenario are customer-centric. They strive to make experiences for their customers better. However, the challenges lie in insufficient data, inaccurate data and slow processing speeds. The analytics industry not only makes data procurement simpler, it also helps you derive insights better. Hypothesis designed around quantitative data, helps one conduct experiments to study and improve the customer lifetime-value.
Data can help one identify trends in customer-needs, purchasing habits, and social behavior. This can further be used by the organization to develop targeted marketing campaigns. Analytics has thus, helped companies to focus better on strategies around customer-acquisition, retention and customer support.
3.) The industry is pretty well-accustomed to data analytics now
Data Analytics is no more an unfamiliar concept. Most market players have already experimented with most analytical strategies and technological platforms. There are some good case-studies and stories out there covering cases where multiple approaches have been tried across various industry-paradigms. It makes it simpler to use these stories as blueprints, learn from them and then improvise to apply tools and methodologies to your problem statement. It also leaves room to experiment with different technologies or even design an indigenous analytical-infrastructure with modified algorithms and platforms, to obtain the best results.
A 2015 Forbes report stated that 83% of organizations had invested in structured data initiatives and had marked them as critical or high priority. Moreover, 36% of the firms were planning to increase their budgets for data-driven initiatives in 2015. Since most of your competitors have already adopted the data-driven approach to maximize returns, not investing in the same might hold you back in the competition. Thus, investing in data analytics will also help you study industry and market trends.
4) It speeds your company’s operations up efficiently
Publishing reports is an integral part of corporate operations. A lot of companies still resort to allotting human resources for basic computational processes. These reports are then consumed by planning and forecasting teams and even for major decision-making operations. Implementing a technology-backed data analytics team will improve the quality of these major business goals: decision-making, planning and forecasting and implementing or piloting projects.
Companies require advanced data analytics to keep up to the changing industry-trends. Firms dealing in financial services and manufacturing companies have shifted focus from pre-built dashboards with conventional metrics and KPIs to design their own data models in metrics is the future. While financial institutions are developing flexible dashboards to integrate new metrics as their business models change, manufacturers need analytics for interpreting shop floor data to revenue reports. These implementations are helping industries improve their efficiency and the speed of their operations.
5.) Data Analytics makes your organization more secure
With massive amounts of data comes high degrees of vulnerability and fear of being hacked into. Data security is a major concern for most people in the market. This calls for newer and more impervious security standards. Data analytics plays a major role in this fight against data-threats. Predictive analytics helps you identify masked forms of fraud and threats. Algorithms like regression and trend-analysis helps one identify irregularities and suspicious cases, thus highlighting problem areas that deserve more attention.
Prediction and forecasting algorithms can then learn these trends. The learning can be used to foresee potential threats. When implemented in a real-time scenario, these analytical-models can help you improve your organization’s performance and data security. Having covered the grounds on data-security, the organization can then design strategies on other operational-areas, to improve the overall performance.