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Trends and Outliers

TIBCO Spotfire's Business Intelligence Blog

Category Archives: Manufacturing


Solving Problems with Data Visualization

It’s an age-old problem in business. A mishap occurs, like a flawed batch of products that are produced due to an as-yet-unknown manufacturing glitch.

shutterstock 4457203 300x225 Solving Problems with Data VisualizationDowntime to analyze and fix the malfunction could take hours or days, depending on the severity of the problem and whether defective manufacturing parts have to be ordered, shipped, and installed.

Collecting the Data & Describing the Problem

Depending on the nature of the business and the items being produced, even a temporary halt in production could cost a manufacturer thousands, perhaps even millions, of dollars. Where do decision makers turn? Data visualization tools are great first steps.

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Analytics to Help Mitigate Price Volatility Risk in Manufacturing Supply Chains

Manufacturers consistently face numerous risks related to protecting the operational integrity of their supply chains, including heat and vibration that can impact the operations of plant equipment and production systems to unforeseen glitches such as transportation problems, and natural disasters.

shutterstock 106896005 300x240 Analytics to Help Mitigate Price Volatility Risk in Manufacturing Supply ChainsThese and other issues can adversely affect the abilities of suppliers to deliver raw materials and other vital products manufacturers need to produce products and meet market demands.

Manufacturing leaders know all too well that even the slightest disruptions to their supply chains can have significant impacts on their quarterly profits.

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Building Intelligence into Manufacturing with Data Analytics

Many manufacturers have invested heavily in information technology systems to make decisions and execute plant operations. But these same firms often find that they’re missing key pieces of information needed to detect problems before they negatively affect operations.

images Building Intelligence into Manufacturing with Data AnalyticsHowever, there are ways that manufacturers can build intelligence into their plant operations, according to a new report from Aberdeen Group that details the ways top performing companies successfully adopt big data analytics.

“Technology has given us the capability to access information as never before, so it’s ironic that manufacturing data continues to be trapped,” the report notes.

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Evolving to the Analytics of Things

The Internet of Things – where sensors and other devices are interconnected to one another – continues to garner attention from researchers, industry leaders, and practitioners.

internet of things 1 300x245 Evolving to the Analytics of ThingsBiometrics Research Group Inc. forecasts that the Internet of Things will skyrocket from two billion connected devices today to nine billion connected devices by 2018.

And Google appears to be making a “land grab” for the Internet of Things through its recent acquisitions of robotics companies including Boston Dynamics, Nest, and DeepMind, which could be used to support a network of artificial intelligence-driven robots and other devices that could be used to improve transportation, manufacturing, and other aspects of day-to-day life.

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How Manufacturers Can Use Analytics to ID Transformative Technologies

Manufacturers continue to invest in technology that can accelerate output while driving heightened productivity. Take D’Addario, a Farmingdale, N.Y.-based maker of musical strings for instruments such as cellos and guitars, for example.

images2 300x164 How Manufacturers Can Use Analytics to ID Transformative TechnologiesD’Addario operates a 110,000-square-foot lean manufacturing facility that relies on robotics, software, and other advanced technologies to help it increase productivity, operate more efficiently, and compete more effectively in the global marketplace.

Increasingly, manufacturers are turning to emerging technologies such as 3D printing, which can take a digital file and turn it into a physical object. But the technology, which has been around for 30 years is still nonetheless very much in its infancy.

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Manufacturing New Relationships with Customers via Data Analysis

While much of the buzz around data analysis for manufacturers has revolved around the ability to improve production via monitoring the data streaming in from machinery sensors, manufacturers can see bottom-line benefits from analyzing customer data.

shutterstock 120483295 300x193 Manufacturing New Relationships with Customers via Data AnalysisIn fact, 43% of manufacturers note finding new ways to serve customers as a primary focus for their business intelligence activities, according to Aberdeen Group.

And firms using marketing analytics achieve a 38% greater increase in the number of new pipeline accounts they identify than companies without marketing analytics, Aberdeen notes.

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Taming the Monster of Machine Big Data

Facebook, emails, smartphone apps, embedded sensors – we live in an era where 2.5 quintillion bytes of data are generated daily. The velocity and volume of data generated today are forcing companies to think and act in new ways.

The prevalence of a social and mobile workforce has transformed the way you do business and interact with your customers. Big data is a real, growing phenomenon and it’s something that should command your attention.

To stay competitive, you must use data to your advantage – to reduce downtime, maintain the integrity of your assets and improve the quality of your future asset purchases.

Remember, the winners will be the companies that are best able to gather data in real time, then analyze and use that data to operate more efficiently, save money and increase revenue.

This infographic lays it all out for you. Take a look.

Tibco Manufacturing Big Data.v.5c Taming the Monster of Machine Big Data

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Big Data in Manufacturing: Rise of the Machine

The vast amounts of data streaming into corporate networks come from numerous sources including so-called smart machines that use sensors to automatically monitor a wide variety of conditions and generate reams of performance data.

riseofmachines 150x150 Big Data in Manufacturing: Rise of the MachineFor manufacturers, these Machine2Machine (M2M) interactions hold the potential to reduce cost and boost revenue.

For example, more than 70% of manufacturers are evaluating, planning or putting into place smart technologies for maintenance and optimization of their assets and their customers’ assets, notes IDC Manufacturing Insights.

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Predictive Analytics to Cut Manufacturing Risk

For manufacturers to be successful in today’s volatile economic landscape, they must react quickly to challenging events and rely more often on managing operations on a predictive basis.

risk Predictive Analytics to Cut Manufacturing RiskIn fact, 86% of the top performing manufacturers are using analytics to reduce risk and improve operating performance, compared to 38% of average performing companies and 26% of industry laggards, according to research from Aberdeen Group.

Companies that feed data from their risk management systems into analytics and dashboarding applications can “more easily get the ‘big picture’ view of that state of their manufacturing operations – where the biggest risks lie – and most importantly where they should focus their efforts,” the report notes.

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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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