Leading organizations use real-time analytics
This is part five in a series presenting, in small, easily consumable bites, findings and insights from the IBM Institute for Business Value’s latest study and paper: “Analytics: The speed advantage - Why data-driven organizations are winning the race in today’s marketplace,” by Glenn Finch, Steven Davidson, Christian Kirschniak, Marcio Weikersheimer, Cathy Reese and Rebecca Shockley.
In part four of this series we looked at the capabilities required to enable speed to action, examined four distinct clusters of organizations that were identified as a result of the study and introduced three key stages within the analytics lifecycle to outline how leading organizations are outpacing the competition. In part five, we will explore the first of those stages—Acquire—which provides the ability to acquire and integrate data quickly.
The ability to acquire and integrate data quickly is foundational to creating a speed advantage. Organizations must be able to source and manage data in ways that create flexibility and agility in how and when the data is used. The study identified three capabilities that most differentiate Front Runners in terms of their ability to ingest data quickly.
- Blend traditional data infrastructure components with newer big data components
- Use real-time data processing and analysis to act in the moment
- Implement information governance to accelerate trust, integration and standardization within their data environments
Blend traditional and new components
Front Runners source and manage data more quickly by integrating traditional and big data infrastructure components.
In the traditional approach, business users determine what questions to ask, and their IT departments structure the data to answer those questions. This is well suited to many common business processes and recurring reports (such as monitoring sales by geography, product or channel) and remains a key part of a speed-driven data infrastructure. Integrated data warehouse developers are indoctrinated to believe the data must be pristine, integrated, aggregated, properly documented and modeled. This makes sense for a vast majority for reports, dashboards and OLAP-based analyses.
But preparing data for advanced analytics requires very different practices: data is seldom made widely available within an organization and doesn’t carry the same reuse and publication requirement. Rarely does big data initially meet the full brace of data cleansing, data quality, metadata and modeling associated with a traditional data warehouse.
In the big data approach, IT delivers a platform that consolidates all sources of information and enables creative discovery. Business users can then utilize that platform to explore data for ideas and possibly see brand new solutions to existing problems.
In examining the data landscape across organizations, we find four data acquisition components that most differentiate Front Runners from other clusters:
- Almost all Front Runners have an integrated data warehouse to consolidate and analyze the structured transactional and operational data used to run the business. An integrated data warehouse is foundational to an organization’s ability to effectively leverage data across the enterprise.
- More than three-quarters of Front Runners use a shared operational data store, accelerating their ability to ingest and analyze data.
- More than three-quarters of Front Runners have invested in data acquisition capabilities to support sourcing the wide assortment of data they are ingesting, which is in varying formats, standards, structures and speeds.
- Front Runners are 10 times more likely than The Pack to have a big data landing platform, which expands the availability of structured and unstructured data and augments more traditional storage structures.
While we do not see the same level of integration between the traditional structures and new components among the Joggers, we do see a solid start to the adoption of big data components, with one-third implementing data acquisition capabilities and one-in-five implementing a big data landing platform.
Use real-time data processing and analysis
As business and IT professionals accelerate the demand for speed-to-action from insights, consumers are increasingly engaging digitally with companies and with one another. It’s not surprising then that a majority of organizations refresh the data within business functions at least daily.
But Front Runners are significantly more likely than other clusters to be using real-time data processing and analysis, which enables them to act in the moment and keep pace with customer demands. In fact, a majority of Front Runners are using real-time analytics processing and real-time event analysis to manage, analyze and act on data as it streams into the organization (see Figure 6).
Implement information governance
To create speed within an organization, data needs to be viewed as an enterprise asset, one that can be used throughout the organization with confidence. Reflecting this need for confidence, the top three data priorities for the next 12 months selected by each cluster were “trustworthiness,” “standardization” and “integration,” although Front Runners were the most emphatic in their choices. Part of data governance, thus, should involve policies that promote trust, standardization and integration:
- The ability to trust data from disparate sources, as well as trust between the people who manage and analyze that data, is key to business-driven information governance and the ability to create value from data.
- Standardization enables various facets within an organization to speak the same language.
- Integration is the data foundation for collaboration, and it enables an enterprise to work together to achieve its business outcomes.
Another function of information governance is to oversee access to data, both to help provide access to employees who need data and to prevent those who don’t need access from getting it. Reflecting the challenges of this function, a majority of survey respondents still believe they do not have access to the timely data they need to perform their job, a statistic that has been flat since 2011. Forty-one percent of this year’s respondents said they only have access to the data they need some of the time, and another 17 percent reported they rarely or never have access to the data they need.
An unsettling finding was that all clusters rated data protection lowest on the list of data priorities; only 11 percent of respondents identified it a “top three” priority. Given the proliferation of large-scale data breaches in recent years, organizations risk the loss of customer and business partner confidence if adequate precautions are not taken to safeguard data, as well as legal and remediation fees. Moreover, business leaders should thoughtfully consider how their organizations use data to minimize any potential backlash in perceived privacy infringement.
In part six we will look at the study’s recommendations and practical actions for the Acquire stage. These recommendations will focus on the flexibility and agility needed acquire and manage data at the speed necessary to create value.