Page 124 - DCAP208_Management Support Systems

Unit 8: Usages, Benefits and Success of Business Analytics and Data Visualization

8.1 Usages of Business Analytics and Data Visualization Notes

In this section, we will discuss the usages of Business Analytics and Data Visualization.

8.1.1 Usages of Business Analytics

Leading banks use business analytics to predict and prevent credit fraud, saving millions. Retailers
use business analytics to predict the best location for stores and how to stock them. Pharmaceutical
firms use it to get life-saving drugs to market more quickly. Even sports teams are getting in on
the action, using business analytics to determine both game strategy and optimal ticket prices.
But these advanced business applications tell only part of the story. What’s going on inside these
market-leading companies that sets them apart? They have committed to deploying their people,
technologies and business processes in new ways. They have committed to a culture that is
based on fact-based decisions – which helps them anticipate and solve complex business problems
throughout the organization. By embracing an analytical approach, these companies identify
their most profitable customers, accelerate product innovation, optimize supply chains and
pricing, and identify the true drivers of financial performance.
And you can too. Get started with business analytics by taking these eight essential actions:
1. Improve the flow and flexibility of data: High-quality data must be integrated and
accessible across your organization. It should also be structured in a flexible way that
allows your analysts to discover new insights and provide leaders the information they
need to adjust strategies quickly.

Notes Strengthening and flexing the data backbone of your enterprise will pay off when
you need to change business processes quickly in response to market shifts, regulatory or
stakeholder demands.
2. Get the right technology in place: Take an enterprise approach to data management and
analytics to effect better decisions. Remove disconnected silos of data, technology or
expertise. Your technology portfolio should include:

Optimized data stores to support core business processes and discovery.
Data integration and data quality software.
Analytical software with the means to effectively deploy, explore and share results
in a meaningful way.

Integrated analytical applications designed to solve defined issues quickly.
When selecting technologies, consider “risk-to-value”: Can the technology be applied to
help reduce costs and increase revenue? And getting the right technology in place doesn’t
have to mean a complete overhaul.
3. Develop the talent you need: Develop or recruit analytic thinkers who seek and explore
the right data to make discoveries. To make analytics work, analysts must also be able to
communicate effectively with leaders and link analytics to key decisions and the bottom
line.
4. Demand fact-based decisions: An analytical company makes a wide range of decisions.
Some are ad hoc; some are automated; some are transformative. The common thread?
Evidence backs them all. Managers encourage asking the right questions of the data to get

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