Taking action with data and analytics

Global Banking Industry Marketing, Big Data, IBM

This series presents, in small, easily consumable bites, the findings and insights from the IBM Institute for Business Value (IBV) study, 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. 

Part eight of the series provides recommendations and practical actions using data and analytics that organizations need to take when they strive for speed to action in their businesses. Part nine begins examining the final step necessary to create speed to action: taking action on the data to enhance business outcomes. 

Act and act quickly

The final step necessary to create the speed to action in demand today is to act, and act quickly, on the data. This step may sound simple—and it is. However, in many ways the hardest part of using analytics to create a competitive advantage is the step in which many organizations can stumble. Even the front runners are less confident about their capabilities here, although not as uncertain as other clusters. 

Collecting, managing, storing and analyzing data are valueless activities unless an organization is prepared to act on those insights. The 2013 IBV study, Analytics: A blueprint for value, identified the nine levers needed for an organization to create value; only two of those levers reference the data management or technical capabilities of the organization. Successfully creating value depends heavily on the culture, people and management processes of the organization itself. that front runners represented 10 percent of the study’s respondent, data-driven organizations using analytics to drive business processes within most business functions. Front runners understand that once an organization decides to act on analytics, the results can be transformative. They understand that the insights derived from data can create new opportunities to engage with customers and new ways of doing business. Three characteristic actions differentiate front runners in their ability to act quickly on data insights: 

  • Integrate digital and process transformations to create comprehensive speed that drives business outcomes
  • Embed analytics within business processes to enable precise, quick actions
  • Use comprehensive visualization techniques to quickly understand and act on large or dynamic data sets

Integrate digital and process transformations

While there are numerous case studies of analytics driving incremental change within organizations, the speed at which front runners drive change enables them to realize the transformative power of analytics as well. Analytics transformations can be divided into two focal areas: digital interaction and process re-invention: 

  • Digital interaction: Re-imagining everything about the way people connect, transact and engage with companies, institutions and governments—and how they create mutual value
  • Process re-invention: Transforming the organization for agility, flexibility and precision to enable new growth

A majority of front runners are focused on creating an end-to-end transformation, incorporating both digital interactions and process re-invention, while the majority in the other three clusters are more likely to undertake either a digital or a process transformation. In a digital transformation, organizations are focused on ways to leverage the available data either to grow revenues or cut costs; although, the majority of digital transformations are focused on customer-centric outcomes. Developing new social and mobile capabilities to engage both customers and employees with anywhere access to the organization is the focus of many digital transformations today. 

Data has been an integral part of operations for decades, with many organizations investing in ongoing efforts to streamline and optimize business processes with traditional analytics. Front runners, however, are collecting and analyzing new forms of data and using increasingly advanced analysis methods to create new avenues of cost reduction and efficiency within business processes. Finance, supply chain and operations are among the business processes undergoing transformation from the infusion of big data capabilities. 

In a combined digital and process transformation, organizations examine the comprehensive process or experience and both integrate analytics into the business process and streamline operations simultaneously. For example, complex algorithms help guide customer service interactions to make them more mutually beneficial, which is the result of structured and unstructured data analyzed offline and then integrated into context-aware, front-end dashboards to create personalized marketing and service solutions. 

Embed analytics within business processes

One of the key components of both a digital and process transformation is integrating analytics into the targeted business processes. While not all business processes require the same level of integration, front runners and the process-minded joggers recognize the speed advantage of using analytics to automate, drive or inform key business processes within their organizations. 

For front runners, using analytics to inform back-office business processes such as finance is sufficient. But for customer-facing processes such as call centers, or online interactions and operational processes such as manufacturing, front runners also recognize the benefits of using algorithms and predictive models as actions to optimize and drive the process. 

A majority of joggers, who hail from more process-centric industries and cultures, embed analytics directly within business processes to enable precise, efficient actions. These organizations use business rules to direct processes and highly prescriptive algorithms, machine learning and artificial intelligence to automate them. 

Use comprehensive visualization techniques

In addition to embedding analytics into business processes, front runners and joggers share another characteristic that helps them quickly act on insights: visualization. Front runners use advanced visualization techniques to quickly comprehend and act on large or dynamic data sets, while joggers use animation to visualize operational processes. 

Analytics can help reduce the size and complexity of big data to a point at which it can be effectively visualized and understood. In a well-suited scenario, the visualization and analytics are integrated into an emerging field known as visual analytics, wherein visualization not only supports interpretation of data, but it is also used to analyze it. Visual analytics is evident in the front runners’ use of techniques such as visual data mining and exploratory visual analytics. 

Part ten of this series, the penultimate part of the series, will look at recommendations and practical actions to take on data and provides some final conclusions. 

Catch up with previous parts of this series: