When the peril of a recession occurs, businesses must analyse every source of revenue using data analytics.
With companies grappling to overcome declining sales over the past few months, experts feel that the gap between successful businesses and those struggling to make ends meet will become wider with the oncoming recession. With an economic downturn anticipated to approach soon, there has never been a more critical time for businesses to future-proof their operations.
In times of economic boom, many companies spend funds on their IT expansion budgets with anticipated loads on systems to meet customer demands. Now that there is a looming recession, IT spending would undoubtedly see a decline. But, what about analytics?
Can technology tools like analytics and business intelligence be applied to alleviate risk during the coming recession as well? The answer is in the affirmative.
But, there can be speculation about the outcomes of the recession on the analytics and business intelligence market, and how this may negatively impact enterprise spending and associated vendor sales of analytics products. But, looking at history, there is no evidence to support this.
The Great Recession of 2008 catapulted analytics into mainstream enterprise use as organizations tried their best to save money on operations and achieve efficiency.
Analytics Can Give An Edge At The Time Of Recession
Analytics can aid companies to estimate which parts of their solutions or services are most likely to prosper regardless of what the global economic circumstances are.
When the peril of a recession occurs, businesses must analyze every source of revenue using data. From the prospects of revenue creation, companies can use analytics tools to gain insights on what has occurred. Based on which solutions and products are performing best in the market, companies can extend data mining and predictive analytics technology to discover cross-selling and up-selling opportunities as well as gain new sales possibilities.
There’s a plethora of data available which can minimize losses in an economic recession. At the time of a recession, it is essential to be even more decisive with your inventory money. With the in-season business intelligence models, retail organizations can adopt a reallocation plan for inventory so that stock is cleared at favorable prices through omnichannel routes.
For different companies, they can determine quickly how the recession has affected their buyers’ buying practices, and tailor their marketing and goods’ strategies in parallel before significant damage is caused.
What The Future Holds For Analytics Industry
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, according to a study.
Significant data dependency and appropriation of advanced technologies such as AI, machine learning, and big data have been considered to drive the demand for predictive analytics across domains like customer analytics, financial analytics, marketing and sales analytics, network analytics, risk analytics, supply chain analytics, web and social media analytics, among others.
Other reports found that business intelligence and analytics tools have the most significant impact on businesses’ profitability over the next few years.
Advantages During Bad Economic Times
By analyzing different applicable social media communications, the company’s machine learning models can recognize and predict emerging trends months in advance, which can give them a tremendous advantage in a competitive market with fewer users.
For example, businesses can utilize an analytics-based predictive model that helps estimate future sales and enable companies to respond more promptly with data-driven insights.
Another attractive way for businesses to use artificial intelligence is by diving deeper into their social media insights. Companies can get hold of trends using the data collected from various social media sources.
In periods of economic crisis, fraudulent events also become commonplace in businesses -, particularly in banking and finance. Business intelligence and fraud analytics can be applied to trace and examine such attempts, and data insights can be utilized to foretell general features of users anticipated to be connected to such activities.
The bottom line is that the application of BI software and analytics should not be deemed extravagant during bad economic scenarios. Instead, it should be seen as a much-needed technology tool that should be leveraged across all business actions – from discovering revenue opportunities, preventing frauds, getting rid of fund wastage, optimizing the workforce, and even sales and marketing.