Analytics in the Cloud and the ROI for B2B

Editor's Notes

• #5: IBM Institute for Business Value Source: Analytics: The speed advantage, IBV, ©2014IBM POV statement In 2014, several important shifts occurred in the world of big data – shifts that business executives around the globe cannot afford to ignore. The most significant change is that velocity is now the value driver for big data. Our sixth annual analytics study revealed a group of organizations differentiating themselves with speed-driven data and analytics practices that significantly impact business performance and competitive position. To compete in today's digitally infused marketplace, other organizations need to emulate these outperformers by acquiring, analyzing and acting on data with a focus on speed to action. Capabilities that enable an organization to consume data faster – to move from raw data to insight-driven actions – are now the key differentiator to creating value using data and analytics. In addition to this focus on speed, our latest analytics research reveals several significant evolutions in the era of big data. Based on survey responses of more than 1,000 business and IT executives from more than 60 countries, our 2014 analytics research revealed four transformative shifts affecting the fast-paced digital marketplace: A solid majority of organizations are now realizing a return on their big data investments within a year. Customer centricity still dominates analytics activities, but organizations are increasingly solving operational challenges using big data. Integrating digital capabilities into business processes is transforming organizations. The value driver for big data has shifted from volume to velocity. Let’ walk through the data behind each one of these. About the research The IBM Institute for Business Value’s 2014 analytics survey was a comprehensive look at the use of data and analytics by companies, governments and other organizations around the globe. We surveyed more than 1,000 business and IT executives from 67 countries (see Figures below). The survey was available online for eight weeks in 2013 (July through August) and offered in six languages: English, Simplified Chinese, French, Japanese, Russian and Spanish. Some respondents self selected based on interest in the topic, and additional invitations were sent based on IBM relationships. Survey topics included executive activities, business process activities, data management practices, human resources management, competency measures, software usage and hardware implementation. The questions were designed to help us understand how and why organizations are using data and analytics today. To identify which capabilities were most responsible for value creation though the use of data, we started with a wide ranging survey to examine more than 50 analytic processes, as well as understand the collection level of 18 types of data; the competency level of data and analytics skills for key analysis techniques; and implementation levels of hardware, software and data management components.
• #6: About the research The IBM Institute for Business Value’s 2014 analytics survey was a comprehensive look at the use of data and analytics by companies, governments and other organizations around the globe. We surveyed more than 1,000 business and IT executives from 67 countries (see Figures below). The survey was available online for eight weeks in 2013 (July through August) and offered in six languages: English, Simplified Chinese, French, Japanese, Russian and Spanish. Some respondents self selected based on interest in the topic, and additional invitations were sent based on IBM relationships. Survey topics included executive activities, business process activities, data management practices, human resources management, competency measures, software usage and hardware implementation. The questions were designed to help us understand how and why organizations are using data and analytics today. To identify which capabilities were most responsible for value creation though the use of data, we started with a wide ranging survey to examine more than 50 analytic processes, as well as understand the collection level of 18 types of data; the competency level of data and analytics skills for key analysis techniques; and implementation levels of hardware, software and data management components.
• #7: Shift 1: A solid majority of organizations are now realizing a return on their big data investments within a year. Most organizations (63 percent) realize a positive return on their analytic investments within one year, and more than one-in-four respondents (26 percent) realize a positive return within six months. This marks the start of a trend toward positive returns, with a 10 percent year-to-year uptick over the 57 percent that reported a return within a year in 2013. Moreover, 49 percent of organizations that have implemented one or more big data technologies into production reported that returns met or exceeded their expected returns; another 45 percent of implementations were under evaluation. Only 6 percent reported that returns failed to meet expectations.
• #8: Shift 2: Customer centricity still dominates analytics activities, but organizations are increasingly targeting operational challenges. While customer-centric objectives are still the primary focus for a majority of organizations, more are starting to integrate big data technologies into back-office and operational processes. In more than half of all organizations, business executives are demanding more data insights primarily to create stronger relationships with customers: 31 percent are working to improve customer acquisition through the use of data and analytics, while the other 22 percent are targeting improvements in customer experience But it’s not all about the customer. Two out of five organizations – 40 percent – are focusing data and analytics on operational objectives, a significant increase from 2013 when only 25 percent of organizations were focused on operations. In the past year, as executives have seen front-office analytics deliver powerful results, they have started to apply these new technologies to manage operational costs even more tightly.
• #9: Shift 3 Integrating digital capabilities into business processes is transforming organizations. A near majority of organizations (46 percent) are re-inventing business processes by integrating digital capabilities. By transforming processes, these organizations are creating the agility, flexibility and precision that enable new growth. And they are using digital capabilities -- like social and mobile technologies -- to change the way people connect, transact and engage with companies, institutions and governments, as well as how they create mutual value. In a digital transformation, organizations are focused on ways to better leverage the available data to either to grow revenues or cut costs, although the majority of digital transformations are focused on customer-centric outcomes. Meanwhile, new forms of data and advanced analysis methods have opened up new avenues of cost reduction and agility within business processes. In a combined digital and process transformation, organizations examine the end-to-end process or experience and both integrate analytics into the business process and streamline its operations simultaneously.
• #10: Shift 4: The value driver for big data has shifted from volume to velocity. Big data's initial impact on organizations came in 2012 as the deluge of data crossed its tipping point. Organizations initially aimed big data investments at managing the often overwhelming amount and types of data suddenly available. In our 2012 analytics study, "Analytics: The real-world use of big data," we identified the characteristics differentiating organizations most was a scalable and extensible infrastructure. But just managing the volume and variety of data is no longer enough to outperform competitors. Organizations using big data technologies broadly throughout their business functions -- capabilities that enable business functions to consume the data rather than just absorb it -- are creating the greatest impacts on business performance. Now we find the components most differentiating organizations creating the most value from data and analytics are those capable of creating an agile and flexible infrastructure, one designed to manage data efficiently and move it through the analytics process quickly. Schroeck, Michael, Rebecca Shockley, Dr. Janet Smart, Professor Dolores Romero-Morales and Professor Peter Tufano.
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• #21: March 13, 2015