How Analytics and BI Shaped the Modern Organization

How Analytics and BI Shaped the Modern Organization

In the past few years, we’ve seen how analytics help data-driven organizations outperform peer groups and create more innovative opportunities.

Today, analytics defines the modern organization by harnessing its collective intelligence. This next-gen collaboration combines the wisdom of people with the power of machine learning and Artificial Intelligence.

For decades, business data lived in silos with only the highly specialized data analysts using outdated business intelligence (BI) software to generate reports, charts and forecasts.

But as the amount of relevant business data generated grew exponentially (more than 2.5 exabytes daily), advanced programs that are simple to understand and operate are now critical for empowering non-technical employees.

Analytics is also shifting the way non-technical employees are conducting their jobs. Only five years ago, research firms were predicting a talent shortage of data scientists.

With the advances in data discovery, analytics and visualizations, today's modern manager can use big data analytics software platform to drive the insights and reveal the significance of the data.

"Data modeling, simulation and other digital tools are reshaping how we innovate. And that has changed the skills needed by our employees," said Procter & Gamble CEO Bob McDonald.  "To meet this challenge, P&G created a baseline digital-skills inventory that's tailored to every level of advancement in the organization."

While the market lagged for years, there are standout examples of this evolution of analytics and business intelligence.

We've all heard the story of how Bank of America was one of the first companies to use transactional data and analytics modeling software to identify customers who may be thinking of jumping to a competitor to refinance their credit cards or mortgages. The bank would then sift through its customer online banking activity, through its call center, or by customer visits to a local branch and then would make a competitive offer based on a broad analysis.

Similarly, mobile communications firm T-Mobile uses its analytics and business intelligence tools to reduce customer turnover rates – also known as churn. The company analyzes social media data alongside its own customer relationship management software (CRM) and internal billing to slash by half the number of people leaving the carrier.

Business leaders and technology professionals now expect and demand their analytics perform beyond visual data exploration and discovery.

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