It’s not an understatement to say that most enterprises today have more data than they know what to do with it. IBM discovered that we create nearly 2.5 quintillion bytes of data each day. To give you a better picture of the significance of 2.5 quintillion, picture a whopping 17 zeros behind 2.5. This massive number means that simply describing it as “data” is an inaccurate representation—when data sets get this large and complex, so much so that ordinary computing systems crash under their sheer digital weight, the only phrase to comprehensively define them is big data.
With mountains of big data stacking up for many organizations across the world, smart, innovative companies are leveraging it through big data analytics in order to inform operational strategies and drive transformation of business processes. Research firm IDC predicts that by 2019, enterprises will spend upwards of $187 billion on big data and analytics technology. That’s because organizations harnessing big data in savvy, intuitive ways are becoming market leaders in their industry—something that Sutherland was recognized for recently in ISG’s “FAO Digital Outsourcing Services 2018 Archetype Report.”
Big data is being used to help companies gain a competitive advantage, enabling them to plan for growth, revenue and risk when it’s analyzed and harnessed effectively. To do so, a big data analytics system is necessary to gain real-time insights into what is and isn’t working for a given company and make effective, on-the-fly business decisions. It’s not enough anymore to simply collect data and process it at a whim—big data is facilitating a new wave of predictive and prescriptive insights that serve almost as a crystal ball into the future for companies to gaze into, confidently predict outcomes and implement fast decision-making to achieve these big data-driven prognostications.
With that said, it should come as no surprise that the effective, holistic deployment of big data analytics is one of the major methods for driving successful business process transformation. To keep up in our rapidly evolving digital and technological landscape, businesses need insights from big data to remain relevant and be more forward-thinking. Real-time data can also offer a more in-depth understanding into customer behaviors and preferences that allows companies to offer greater, more targeted value. This combination of strategic decision-making and customer insight from big data analysis allows a company to truly grow, scale and reach newer, more profitable heights.
Not convinced? IDC reports that 71% of so-called big data innovators (early adopters who prioritize big data analytics) employ advanced technologies and tools that offer them real-time visualization into big data and higher-level forecasting to reap the above benefits. Here are some other commonalities among companies taking this approach to influence business outcomes and revamp business processes for the better:
- Receive support from all organizational levels championing big data analytics
- Achieve data mining in a more secure, timely and efficient manner, making big data analytics much more relevant to business goals
- Attain a faster ROI from big data analytics (generally within the first six months)
- Strive for continued advances in big data technologies to drive business growth and transformation
At Sutherland, our unique approach to business transformation—combining big data analytics, machine learning and design thinking with process-level automation—has given us a critical competitive advantage, according to ISG. What results is more informed business insights, more confident decision-making and greater visibility across business operations for companies and customers alike. None of this could be achieved without a simple, comprehensive big data platform that offers predictive and prescriptive analytics. No matter how well your business is operating and performing, there’s always room to be better. That starts with embracing big data analytics.