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Trends and Outliers

TIBCO Spotfire's Business Intelligence Blog

Monthly Archives: May 2013


Data Analytics to Cut Healthcare Costs: Just What the Doctor Ordered

As medical costs continue to soar, employers are struggling to provide health insurance to their workers and families. To fight these costs, companies have to find new ways to keep spending down.

cut small business healthcare costs1 Data Analytics to Cut Healthcare Costs: Just What the Doctor Ordered Enter data analytics.

More employers are turning to data analytics to find ways to save money for themselves and their employees without reducing their workers’ healthcare benefits, according to an article in The Institute for HealthCare Consumerism.

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From the Marketing Trenches: Data Analysis Success Stories

While many organizations are interested in the potential of big data and are beginning to shape their data analysis strategies, some of the world’s biggest are well on their way to becoming data-driven to connect with customers and boost revenue.

key success 150x150 From the Marketing Trenches: Data Analysis Success StoriesFor example, companies like Macy’s, JPMorgan Chase and Starwood Hotels and Resorts are incorporating data-driven marketing into their efforts, according to Data Marketing News.

The biggest impact of data analysis on the retailer’s marketing efforts is that the company now measure success in terms of the response of real people over time, notes Julie Bernard, Macy’s group vice president of customer centricity, direct marketing and loyalty.

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Is Big Trouble Brewing for Big Data Adoption?

There’s so much hype about big data these days, industry observers such as Gartner Inc.’s Svetlana Sicular are beginning to express concern that it may dissuade companies from pursuing big data analytics initiatives.

Unknown 150x150 Is Big Trouble Brewing for Big Data Adoption? Gartner publishes a “hype cycle” for different technologies based on the stage at which the interest of a technology is rising or falling.

Big data has plunged into the “trough of disillusionment,” according to Sicular. This includes disappointment that Sicular is seeing with her Hadoop clients who have “fascinating ideas” but are “disappointed with a difficulty of figuring out reliable solutions.”

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Data Analysis: Creating a Customer ‘Database of Intentions’

Top performing companies are using data analysis to create a “database of intentions” to more accurately predict and respond in real time to customer behavior.

want Data Analysis: Creating a Customer Database of IntentionsIn fact, 90% of the top performing companies have a marketing analytics initiative in place, compared with 69% of all other firms, according to a recent survey by Aberdeen Group.

The biggest goals of these top performing companies for marketing data analytics are to increase the response rate of marketing campaigns; increase the accuracy of audience targeting; and boost revenue from cross-selling.

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Data Analysis to Tame Manufacturing Complexity

The manufacturing sector is still struggling to emerge from the recession. Industrial production shrank 0.5% in April, according to recent data from the Federal Reserve.

tamingmanfacturing1 Data Analysis to Tame Manufacturing ComplexityIn addition, the country is using about 77% of its total industrial capacity, nearly three percentage points below the 40-year average.

American manufacturers are suddenly grappling with the influx of cheaper goods from Japan, China and other overseas competitors.

“[Manufacturing] has flattened out completely and is not contributing to GDP growth right now,” Jacob Oubina, senior economist at RBC Capital Markets, tells Businessweek.

But top industry performers are building up their big data and advanced analytics to support efforts to help them take control of manufacturing complexity, according to a recent survey of more than 100 manufacturers by research firm Aberdeen Group.

“Understanding customer demands must take into account the complexities of the manufacturing process, such as time-to-market expectations, product customizations and best practices,” according to the report. “Change can be an overwhelming task – especially for companies trying to take control of the process variability. But employees must be ready to interact with operational processes and take control of the fast changing manufacturing environment.”

The report notes that top performing manufacturing companies – more so than lower performing companies – are more likely to adopt time-sensitive metrics that foster this sense of urgency including:

  • Time to decisions (33% versus 13%)
  • Time to market (46% versus 34%)
  • On-time and complete shipments (46% versus 36%)

In addition, top performing companies are more likely than lower performing companies to turn to data analysis to support effective decision making to stay competitive.

For example, 33% of top performing companies say they have to provide timely data for critical decision making to line of business management compared to 23% of lower performing companies.

And 25% of top performing companies say they need to provide data analysis tools for various levels of the organization compared to 9% of the lowest performing companies in the survey.

“Leaders are more likely than followers to connect effective decision making with the ability to improve planning and empowerment with data,” the report notes. “For leaders, line of business managers need access to critical data in order to manage decisions impacting incremental improvements and cost cutting activities. They also see as a top priority the ability to aggregate and analyze business data across multiple products or functions.”

According to the report, manufacturers face the following data challenges:

  • Complex data is fragmented across operations (45%)
  • Data isn’t available when needed (31%)
  • Users don’t trust the data (25%)
  • Complex dashboards with too many metrics (24%)
  • Old data that’s used in business activities (24%)

“Leaders see data as the new business order.  . . .  Top performers are more likely to understand that the ability to turned data into insights and actions is a game changing strategy,” the report notes. “Supported by analytics and statistical models they must characterize the impact of their decisions on engineering, supply chain and customer management and everything else affected by these decisions.”

Manufacturers identify myriad benefits from using big data and analytics including:

  • Combining customer behaviors and transactional views to help establish priorities
  • Identifying potential new micro-markets based on events or trending customer preferences
  • Combining user requirements, new features and bug fixes to create ROI for new product launches
  • Predicting recalls, supplier disruption and other crises can boost organizational readiness

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Data Analytics and the Loch Ness Monster

As many of the regular readers of our blog probably know, I sometimes like to write about the off-beat uses for data analytics. Remember the Geico Gecko? And what about this post where I have some fun with big data and data analytics?

Nessie pic 300x245 Data Analytics and the Loch Ness MonsterI don’t always go looking for this stuff – well, OK, maybe I do. I guess I’m always looking for answers to the strange and the mysterious. I’m a reporter, it’s in my blood.

So I decide to check around to see if there’s anybody out there using big data analytics to solve some of the world’s unexplained phenomenon.

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Data Analysis to Better Manage the Sales Pipeline

sales pipeline Data Analysis to Better Manage the Sales PipelineThe recent Spotfire on-demand webcast, “What’s Hiding in Your Sales Data?” covers the many challenges faced by sales organizations trying to turn hot leads into new customers.

The webcast also discusses how Spotfire is used to seamlessly access data and enhance traditional reporting capabilities.

One of the most common reasons given for higher than anticipated losses in any quarter is that deals in the pipeline fail to close as expected.

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The Case for Risk Analytics in Banking

As regional and international banks emerge from the 2008 financial crisis, many institutions are continuing a strong focus on risk management to ensure that they’re complying with more stringent regulations and are loaning and investing cash wisely.

risk management under implementation 250x250 The Case for Risk Analytics in BankingRisk concerns continue to be top-of-mind for bankers. A combination of lower asset yields and loosening loan terms for mid-market and large businesses amid an uptick in commercial and industrial lending is increasing risks for banks, according to an article in American Banker.

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Analytics to Identify the ROI for Renewable Energy Investments

A big part of the challenge for companies looking to pour money into renewable energy sources such as wind and solar power is determining whether there is enough sustainable wind or sunlight in a particular geography to maximize investments in these technologies.

RenewablesLeadPic 150x150 Analytics to Identify the ROI for Renewable Energy InvestmentsCompanies looking to reap the benefits of Mother Nature’s renewable energy sources can use analytics to evaluate multiple factors, including the average amount of cloud cover, direct sunlight, and the wind energy potential that’s available to justify investments in renewable energy systems.

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Analytics, King James and the Next Generation of Moneyball

Perhaps the most visible evidence of the competitive advantage that can be fueled by data analysis is LeBron James’ performance in the NBA playoffs this year and last, compared to previous lackluster post-season play by the Miami Heat superstar.

nba Analytics, King James and the Next Generation of MoneyballBut King James’ less-than-stellar performance on the basketball court happened before he took a hard look at the analytics behind his play, notes Michael Schrage, a research fellow at MIT Sloan School’s Center for Digital Business, in a post in Harvard Business Review.

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