Companies of all shapes and sizes are striving to become more data driven. A 2019 survey of executives from Fortune 1000 companies revealed 92 percent of those organizations are “increasing their pace of investment in big data and AI.” What’s more, 62 percent of respondents have seen measurable results from doing so.
This raises the question: Why are enterprises today investing more resources into their data analytics initiatives? While it may be difficult to calculate a precise return on investment, businesses prioritizing data analytics have reaped tangible benefits.
Here are four potential business benefits of an effective data analytics strategy.
Improving Internal Decision-Making
In terms of day-to-day impact, data analytics can influence decision-making both small and large — helping employees make informed decisions with a greater likelihood of positively driving business outcomes.
Where employees may have had to rely on instinct or static reports in the past, more decision makers at every level are gaining access to straightforward search- and AI-driven analytics tools. The result? Employees can ask ad hoc questions and receive answers in seconds, then keep drilling down into the results to consider what the data is saying from multiple angles.
As Techopedia notes, this ability to incorporate data into routine decision-making processes makes it “possible to ensure each new idea, direction or project will build the business — rather than set it back.”
Identifying Operational Inefficiencies
According to the aforementioned survey, more companies are investing in data analytics with positive goals — like transforming the business, becoming more agile and staying ahead of the competition — than for outright cost reduction.
However, it’s impossible to ignore one of the basic benefits of data analytics is the ability to bring to light costly operational inefficiencies. Only when companies are aware of waste can they take corrective action. Analyzing data can help employees identify areas ripe for optimization.
Reducing waste looks different depending on the organization. For a manufacturer, data analytics can provide valuable insights about current machine downtime and engineering bottlenecks. Healthcare organizations can use data to reduce unnecessary patient readmissions, optimize staffing and improve their supply chain purchases. Retailers can seek out opportunities to reduce inventory consumption, improve employee scheduling and decrease expensive returns.
Uncovering Causal Relationships Within Data
Data analytics can uncover patterns and help decision makers figure out why — based on factors hidden within data. Artificial intelligence (AI) algorithms are especially adept at diving deeply into data and returning to the surface with potentially notable trends and causal relationships to consider. These are insights that would have been all but invisible without the ability to gain a bird’s eye view of billions of rows of data and pick out what’s likely to be most relevant.
Here’s just one example of how this looks in action: Healthcare organizations have been using data analytics to predict patient readmission outcomes based on individual factors — like prior admissions, ER visits and high-risk conditions. But advanced predictive models have helped hospitals take this one step further, identifying socio-economic factors from the larger population that also contribute to patient outcomes — like “living alone, lack of a relationship with their doctor, no credit cards, health illiteracy, poor behavioral health” and more.
The discovery of a wider range of casual relationships within data can help organizations predict outcomes and address these factors head-on.
Boosting Revenue Through New & Existing Products
One of the more measurable benefits of better data analytics is boosting revenue, either by using data to help target and launch new products, or by improving existing product offerings based on what the data is saying about customer purchasing behavior and preference.
These are just four of the potential business benefits of data analytics, all of which help explain why organizations are investing more in their data strategies.