There's been a shift in how companies operate, interact with consumers, and design internal roles. If you've been paying attention, you may have heard buzzwords like "data-driven" and "customer insights" being thrown around. You might also have heard colleagues ask questions about quantifying, tracking, or syncing data about customer and employee behavior.
And you've probably noticed changes in many job scopes, as more deal with interfaces that collect, store, and interpret information. This all points to the idea that organizations have entered the golden age of data. Exchanging information via technology is no longer an afterthought. It's ingrained into how businesses, governments, and everyday citizens operate and live. Here is why some believe the world is experiencing data's peak.
The Emergence of Big Data Tools
While many organizations collect and work with large amounts of data, they're not necessarily good at optimizing it. The C-suite might be looking at customer acquisition and churn numbers to decide whether a market expansion is fiscally possible. Meanwhile, the marketing department is analyzing surveys and focus group responses from the same area. And sales representatives responsible for the territory are evaluating the number of leads versus actual conversions.
Different sources and types of information might lead each team to distinct conclusions about the same market. Without data tools and infrastructure that bring all sources of information together, these teams' conclusions could be incorrect. There might be disparate grains of truth in the findings, but it takes synchronization and optimization to see the big picture.
Organizations that use data observability tools are better able to understand the complexities that come from large amounts of information. You might think you're making a sound business decision based on data. But if you have data quality issues, you won't get the results you were hoping for.
An increased focus on building solutions that manage and optimize data from multiple sources shows that organizations have an immediate need for these capabilities. Employees must have a way to wrap their heads around the uptick in information. Data observability can help businesses predict, prevent, and even fix problems before they cause damage to your decisions.
Real-Time Insights Are Becoming More Valuable
Business leaders are used to developing strategies based on historical data. By the time a market research company or ad agency gathers information, it's far from recent. It may only be a year old, but the global pandemic revealed just how fast data can become irrelevant. Predictive models for consumer behavior are no longer working, as explained in an interview with leading data and analytics innovators.
While forecasting models for demand have been reliable in the past, consumer choices and behaviors are highly influenced by uncertainty. If people start doubting they'll have a job next week, they'll automatically tighten their belts. If people start doubting there will be toilet paper on the store shelves tomorrow, they'll put multiple packages in their carts today. Even if those fears are pure speculation, volatility in the economy or sudden changes can lead to skewed behaviors.
Companies and data analysts are rethinking their strategic approaches and information practices because of what occurred in 2020. They're not just relying on historical data and predictions based on that information. Businesses are injecting real-time analytics, often from front-line sources, to make more accurate moves.
Rapid macroeconomic shifts like those that happened at the onset of the pandemic could lead to instantaneous surges or drops in demand. The restaurant, travel, and hospitality industries all experienced a near halt. Yet telecom, internet, and videoconferencing services all saw a massive jump.
It's more critical than ever to adjust to real-time signals and have plans in place for meeting current customer needs. Businesses that can't understand consumers in the here and now could get left behind. By the time these companies are done playing catch-up, consumer demands and environmental factors may have shifted again.
Data Skills Are Part of Everyone's Job Description
While the separation between "thinkers" and "feelers" or "analytical" and "intuitive" workers still exists, the gap is closing. It's not enough to base conclusions on your gut or subjective experiences. More roles and job descriptions include interacting with and relying on information.
Building and running reports, using and interpreting analytics, and designing data collection methods aren't responsibilities only IT handles. In the past, dealing with data required specialized knowledge and narrowly defined positions. While some of these roles are still around, it seems everyone - whether customer-facing employee or marketing professional - is now using analytics.
Today web-based tools with interfaces that are easy to manipulate and understand are integrated into everyday tasks. There are programs and dashboards for collecting surveys and reporting organic and paid website traffic. Graphic designers and marketing managers can see performance trends and data for digital ad performance. Retail sales and customer service reps pull up programs that generate a customer lifetime value score before they offer solutions.
Using these tools, interpreting the data, and acting on it are core skills employees are expected to develop. More companies also require some experience and familiarity with specific platforms and data skills from candidates. It's hard to find a job advertisement without something about data or a preference for experience with specific tools.
With corporate data volumes increasing by 63% each month, according to a 2020 IDG survey, specialized roles can't handle everything. It's impractical and inefficient to expect a few departments or teams to manage that amount of information. Ensuring data gets used and optimized to an organization's benefit takes cooperation and support from all functions.
Conclusion
The signs that the world is living in the golden age of data are clear. Information flows in from innumerable sources, and real-time consumer insights are more valuable than historical data. Nearly all roles in organizations require baseline data skills and familiarity with software that produces analytics. This increasingly means data observability and big data tools that manage and improve gathered information aren't options - they're necessities.
* This is a contributed article and this content does not necessarily represent the views of sciencetimes.com
