Data Analysis: The Key to an Agile, Successful Business

With an unlimited amount of information about products and services accessible from as close as their smartphones, customers are more empowered than ever. To adapt and succeed in this increasingly competitive landscape, companies must rely on employees at the front lines of customer interactions to stay ahead of consumer demands.

To Manage Change Start with the Customer

Front-line workers in the trenches must be armed with the right tools to discover insights and be agile enough to keep up with evolving customer demands. Forrester Research has found that successful companies have one thing in common: the ability to effectively manage change.

“Employees down in the trenches, in individual business units, are the ones who are in close touch with customer problems, market shifts, and process inefficiencies,” notes Boris Evelson, Forrester vice president and principal analyst, in a blog post. “These workers are often in the best position to understand challenges and opportunities and to make decisions to improve the business. It is only when responses to change come from within, from these highly aware and empowered employees, that enterprises become agile, competitive, and successful.”

Without the right tools, however, many companies struggle to stamp out “shadow IT,” disparate data analysis methods that employees may have turned to in the absence of flexible technology.

“Point-and-click, drag-and-drop guided user interfaces may be intuitive to an experienced professional with a background in command line interfaces, but not so obvious to a millennial who grew up with a thumb-typing mobile phone UI,” Evelson adds.

Data Analysis Tools to Become Agile, Manage Change

To become agile enough to manage change, companies must embrace data analysis tools that allow them to identify and react quickly to change, including:

• Self-service analysis: “What are the BI platform features that enable technology professionals to empower business user self-service capabilities?”
• Automated analysis: “Does the business intelligence (BI) platform support various self-service BI automation processes that allow business users to do more with less?”
• Self-provisioning applications and data: Business users must be able to quickly connect to data sources.
• Data integration: Users need to be able to perform data transformation tasks such as data mashups.
• Effective user interfaces: Front-line employees need to be able to create their own reports and dashboards.
• Advanced data visualization: Business users need rich content visualization like custom charts and graphs and geospatial representations. They should be able to efficiently and effectively visualize data sets and socialize insights.