Learn more about how your organization can apply data to make smarter, more informed business decisions.
As digital transformation initiatives have accelerated over the past year, data analytics is becoming more important for gaining a competitive, efficient edge, and the applications are almost endless. Not only can they reduce guesswork in everyday tasks and save companies money, but robust data analytics capabilities can also help inform long- and short-term business strategy.
However, while data can be relatively easy for most companies to acquire, research shows that 95% of businesses struggle to actually manage it. Aggregation and reporting tools can process the basic pieces of business intelligence a company collects, making large volumes of data easier to interpret. Most data analytics tools offer built-in dashboards that enable users to organize and visualize key performance indicators (KPIs) in a given area at the company.
When it comes to interpreting big data, machine learning can help companies identify patterns and inconsistencies. Such tools can empower leaders to gain deeper insight into factors influencing their business — for example, linking payment patterns to industry trends.
Making Smarter Decisions
With the right volume of information, data analytics tools can also be used to forecast trends and KPIs. Forecasting tools can be used for a variety of purposes, such as projecting revenue or the value of certain products in order to ensure accurate market pricing.
On the financial side, data analytics can help convert data into tangible business recommendations. For instance, if your capital reserves reach a certain level compared with market trends, your accounting department can recommend a cap on cash spending or alert leaders of investment opportunities.
Such tools can also be invaluable when it comes to both marketing and customer experience. For example, if your forecasting model shows a potential turnover in your customer base, an algorithm can trigger an outreach initiative to help you improve retention. Historical data can also be applied to tailor ads to specific customer segments, enabling companies to better reach the right audience in the right place at the right time.
Ultimately, data can help organizations better understand the bigger picture. But while such tools can be insightful and informative, advanced data analytics can’t fully replace humans just yet. When it comes to interpreting data, remember that context is key.
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