Case studies regarding the importance of analytics in enabling innovation, achieving competitive advantage and realizing business strategies abound. Why then, with all things being equal in terms of access to data and analytic tools are some organizations able to capitalize and change the game through analytics while others struggle to make a dent?
You can’t have a high-performing and analytics-enabled organization without the foundation of an analytical culture. It doesn’t matter what pronouncements management makes about being data-driven and analytical. If the behavioral norms are to ignore inconvenient evidence, defer to the person with the most power, avoid difficult questions and disagreements, and go with the gut at will – the organization will never develop real analytical capability or capitalize on analytics.
More and more CIOs are saying, “I want to build a Data as a Service offering” to the rest of the organization. In the past several years, structured and unstructured big data, data fragmentation, data sprawl, and the complexity of governing data assets are driving new trends in data management. Data as a Service (DaaS) represents one opportunity to centralize and virtualize resources and thereby improve IT efficiency and performance.
In just 6 weeks, IIA will convene the greatest minds in analytics and host the 2nd annual CAO Summit June 18-19 in Chicago. We have a confirmed roster of Analytics All-Stars and thought leaders who will lead sessions, including Daniel Wagner, CAO of the 2012 Obama Presidential campaign who harnessed the power of analytics to help POTUS win the White House.
If you want to build an analytical organization, you need a critical mass of analytics professionals to mine the data and build the models, plus a large population of analytical amateurs who put the analytics to work. The most direct way to develop amateurs is on the job, one-on-one, through interaction with analytics and analytical professionals acting as Personal Trainers.
What do I mean by “analytic workbench?” Basically, the compute-resource environment with which data analysis takes place. All of us deal with data at some level, and all of us can benefit from making sense of our data more efficiently and effectively. See if there are opportunities to make the analytic workbenches in your organization more productive.
We are only two months away from the IIA’s Chief Analytics Officer Summit (June 18th -19th) in Chicago, IL and have created a particularly exciting agenda this year. Whether you are the Chief Analytics Officer (CAO) or play a leadership role in driving analytics within your organization, the Summit has been designed to give you tangible, thought-provoking strategies and tactics that can be applied to advance any analytics program.
IIA is talking about analytics entering a new era, Analytics 3.0, The Era of Impact. What is Analytics 3.0?
According to IIA, Analytics 3.0 marks the stage of maturity where leading organizations realize measurable business impact from the combination of traditional analytics and big data. High-performing companies will embed analytics directly in decision and operational processes, and take advantage of machine-learning and other technologies to generate insights in the “millions per second” rather than an “insight a week or month.” Given this definition of Analytics 3.0, what is the role of Decision Management and of Decision Management Systems?