This is part five of our series on the findings and text from IBM Institute for Business Value’s latest study and paper: “Analytics: A blueprint for value - Converting big data and analytics insights into results," from my colleagues Fred Balboni, Glenn Finch, Cathy Rodenbeck Reese and Rebecca Shockley.
In part four, we examined enabling value creation with a big data platform. In this part, we will look at the second level of impact, Drive, and examine Drive’s first lever, Culture, and its impact on the availability and use of analytics.
The second level of impact, Drive, consists of the levers that start the process of moving an organization from analytics discovery to value creation. Organizations that lack the capabilities represented in these levers will struggle to create value from their analytic investments. Levers at the Drive level are Culture, Data and Trust (see Figure 6).
Driving an organization toward value creation requires a data-driven culture that encourages the use of analytics within decision-making processes and makes data available and accessible to those who need it. Strong governance and security are important in instilling confidence in the data, and trust is necessary – both in the data and in individuals – for individuals to act on data and insights.
Availability and use of data and analytics
The goal of analytics investment is to influence business outcomes. To achieve that, an organization has to use data and analytics within its decision-making processes. Organizations that do not adopt a fact-based culture will struggle to create value from analytics investments and capabilities.
Organizational culture is cultivated from the top down. An organization’s tone and culture generally align with the attitudes and behaviors exhibited by its chief executive officer and other senior executive team members. Infusing the use of analytics into an organization’s culture typically requires advocacy and action from the most senior levels of the organization.
The Chief Executive Officer (CEO) and Chief Operating Officer (COO) serve as the top advocates for the use of analytic insights in about one-quarter of all organizations (24 percent). However, non-Leader organizations are, on average, two times more likely than Leaders to be without an advocate for analytics.
Leaders make their decisions based on data and analytics because they have access to the information needed to make those decisions. Fifty percent of Leaders make more than half their decisions based on data and analytics (see Figure 7). Moreover, almost half of Leaders (42 percent) frequently or always have the information and analytics they need to make decisions.
One global electronics manufacturer is striving to manage its massive amount of customer data to make it accessible to those who can use it in their decision-making processes. The company is gaining greater insight into customer buying behavior by consolidating vast amounts of customer purchase information into a single repository and applying advanced algorithms to analyze the data. By clustering and analyzing customer buying history and preferences, and making this data available throughout the organization, the company can now optimize both its regional and channel distribution and sales strategies by understanding which products sell best, as well as where and how. It can also use this detailed customer analysis to create and target specific customer segments with more effective, personalized marketing campaigns.
By employing these approaches and using analytics in its decision processes, the manufacturer has been able to boost sales revenue, increase sales volume and lower sales costs by improving sales forecast accuracy. It was also able to use the insights to facilitate product innovation and new product sales by analyzing customer responses to key selling features of existing products before new product development got underway.
While this global manufacturer and the majority of other Leaders may be using data and analytics within their decision-making processes, there are still vast stores of data that go untapped. In fact, Gartner predicts that through 2016, 90 percent of business decisions will be based on a fraction of the available relevant data.
In part six we will continue to look at the second level of impact, and what is needed to realize value from data and analytics by examining data management practices.
Catch up on the entire series so far with parts one through four:
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