15Jul - by aiuniverse - 0 - In Data Science

Source: analyticsinsight.net

COVID-19 has swept through the world, bringing disruption with it. It has spread with alarming speed, infecting millions of people. As the health and human toll grows, the economic damage is already evident and represents the largest economic shock the world has experienced in decades. Global Economic Prospects has envisioned a 5.2 percent contraction in global GDP in 2020—the deepest global recession in decades. Over the longer horizon, the deep recessions triggered by the pandemic are expected to leave lasting scars through lower investment.

In such times, it is pivotal to spread the utmost awareness about the pandemic to ensure the safety of people. To assure this, organisations such as verloop have partnered with the government and various companies. They have affiliated with the Canadian and Goa embassy, by providing their Chatbot to be used by the public. These bots are equipped in answering all questions around coronavirus, helping people discover a hotline, check if their symptoms are in line with the virus, amongst other things

In such times of economic uncertainty it is sure that recession is upon us and it will prevail for a long time. In such times, one question which pops up in our minds is that will the current recession slow the demand for analytics and data science?

In these conditions, the first step which the companies follow to ensure their survival is cost cutting. ROI is one of the principal measurements utilized when organizations go to cost cutting in a downturn. ROI is a tough standard for data science, because many algorithms never get deployed into production applications. This is the reason why many companies aren’t getting the ROI they expected.

Analytically mature organisations are much safer in times of recession. This is because a centralized group with strong leadership and proven ROI can, in fact, experience an increase in demand. In contrast to this, organisations which are still developing their analytical proficiency might face difficulties because recession leads to less resources and constraints on the financial liberty of the firm.

Another sizable impact that recession has on organisations is layoffs and furloughs. Sadly, even data scientists and analysts are not immune from this. In a survey conducted by TDWI (a U.S based organisation) it was found that 13% of data and analytics professionals cited that their companies were either furloughing or laying off data and analytics professionals. 40% of respondents stated that hiring of data and analytical professionals was frozen.

However, the silver lining is that although new job postings in data science and analytics have declined overall, they currently appear to be declining at a slower rate than that of most other occupations.

In contrast to this, some experts believe that analytics industry will not be affected by the global recession. They believe that analytics can give an edge at the time of recession. Analytics can allow companies to evaluate which parts of their solutions or services are most likely to flourish regardless of what the global economic circumstances are. There’s an abundance of data available which can minimize losses in an economic recession.

According to a study the global predictive analytics market size is estimated to be at $23.9 billion by 2025, with a CAGR of 23.2% across the projection period between 2019-2025. This means that analytics will play a huge role in assisting businesses in the decision-making process in the future. Apart from this, with the help of analytics different companies can identify quickly how the recession has affected their customers’ buying behaviour, and tailor their marketing and products strategies in alignment before significant damage is caused.

Furthermore, it is also believed that analytics can empower companies to expand operational efficiencies and reduce costs. With traditional data architecture and models, it becomes challenging for organizations to maintain data and make decisions effectively. Businesses have realized the need for solutions that can access a large volume of data and entitle data analysts to focus on data-driven justifications to gain data insights.

The analytics solution is fit to support big quantities of data in a consistent way with algorithms to drive real-time results. Modern big data analytics systems will provide organizations with speedy and efficient analytical approach. This ability will allow organisations to work faster and achieve business goals.

There is no denying that in recent times, analytics and data science professionals have experienced acute demand for their services over the past decade. However, factors such as recession can efficiently hamper the growth of this industry. Organizations dealing with repeatedly changing conditions will need to understand where they are now and plan how to move forward in a dynamic environment.

This is possible by gaining insights into customer behaviours, which impact products and pricing, optimizing supply chains, and constantly updating revenue forecasts. Analytics can be seen as a much needed innovation tool that ought to be leveraged across different activities- from discovering income opportunities, preventing frauds, minimising wastage, optimizing workforce, and even predicting the next pandemic.

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