There is no denying that big data and analytics are now entrenched and vital components of modern business and the information technology systems that power today’s organizations. Although the big data trend has cooled off, the reason for amassing all of that data and performing analytics on it for business insight has become a permanent fixture in most organizations.
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Analysts estimate that the amount of data we use and manage doubles annually, and performing analytics on that data can uncover heretofore unknown insights that lead to competitive advantage. Furthermore, the big data used to power analytics is being adapted for use by AI and machine learning software that will further improve the return on our computing investment through automation of processes and tasks, thereby increasing productivity and operational efficiencies.
Types of Analytics
Before moving on to discuss the trends, let’s briefly examine the four types of analytics: descriptive, diagnostic, predictive, and prescriptive.
- Descriptive analytics focuses on what has already occurred.
- Diagnostics analytics focuses on understanding why things happened.
- Predictive analytics focuses on what could happen next.
- Prescriptive analytics attempts to inform us as to what should happen next.
All are important and growing within organizations today. Nevertheless, there are clear trends that resonate with current analytics efforts today.
Key Trends in Analytics Today
Continuing Impact of the COVID-19 Pandemic
Any discussion of the current state of analytics has to begin with the way the pandemic has significantly altered many aspects of not just business but also everyday life across the globe. The disruption to business as usual imposed on organizations as healthcare and government officials attempted to slow the spread of COVID-19 caused many significant and, possibly permanent, changes to how we work.
The impact of the pandemic has been to speed up the need for digital transformation. Improved data analytics is one aspect of this.
Social distancing and work-from-home (WFH) efforts advanced the notion of “distributed everything”—data, devices, and people. Organizations had to adapt to this distribution and have been aided by data analytics.
With a WFH workforce, HR analytics can be an important tool for monitoring the health of both companies and employees. Analytics can be used to increase the effectiveness of onboarding, employee engagement, morale, and productivity. Of course, this type of data should be anonymized to protect the privacy of individual employees before it is shared within the company.
Analytics also has played a role in understanding and reacting to the COVID pandemic. Organizations that have adopted analytics to monitor consumer spending data, coupled with other data (such as vaccination rates, COVID hospitalization cases, and governmental rules), are better prepared to survive the continuing pandemic. By spotting trends and predicting changes in upcoming economic patterns, companies can make better decisions about staffing, supply chain management, stocking, and so on.
Most consumers are not capable of predicting their own behavior shifts, but data analytics can sift through multiple types of data and deploy models to predict changing consumer activities. This can have a far-reaching effect on the economy as businesses need to remain nimble to react to the complexities of the health crisis caused by COVID and its variants.