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TIBCO Spotfire's Business Intelligence Blog

Category Archives: Manufacturing analytics


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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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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3 Steps for Manufacturers to Unlock the Value of Big Data

Manufacturers are awash in data. But too often it’s trapped in data silos, and it can’t be leveraged to help organizations compete in an increasingly complex market landscape.

manufacturer 3 Steps for Manufacturers to Unlock the Value of Big DataManufacturers can use data as a key currency to unlock value to drive better efficiency and productivity, according to a recent research report from Aberdeen Research.

But they must take three key steps to leverage data to fuel the potential boost to the bottom line:

1. Study data management opportunities and challenges
2. Pinpoint data management capabilities
3. Prioritize data analysis initiatives

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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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Data Analysis to Rule a New Manufacturing Era – Part 4

The manufacturing sector is poised on the cusp of a new era, one that will see the development of a new, large consuming class in developing economies that will bring with it many opportunities but also new, substantial market risks.

manufacturing4 Data Analysis to Rule a New Manufacturing Era – Part 4While manufacturing has always included more than production, over time the services like research and development, marketing and sales, and customer support have become larger parts of what manufacturing companies do, notes a report on the future of global manufacturing from McKinsey Global Institute.

Depending on the market segment, 30% to 55% of manufacturing jobs in advanced economies are service-type functions, and services make up 20% to 25% of manufacturing output, the research report notes.

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Analytics = Better Manufacturing Outsourcing

Discrete manufacturers often partner with third parties to produce specific components or parts used in the development of their products. In some cases, third parties have the expertise to produce such components or they’re able to offer prices that are lower than the costs to develop these components in house.

manufacturingoutsurcing Analytics = Better Manufacturing OutsourcingHowever, for a variety of reasons, including distances between manufacturers and partners and time to market pressures, manufacturers often aren’t able to determine whether they’re paying the lowest possible prices for the parts or components they rely on third parties to produce.

Manufacturers sometimes end up paying more than they should for outsourced parts because there simply isn’t enough time to solicit bids from other factories, as Julie Driscoll points out in a recent article for Supply & Demand-Chain Executive.

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Data Analysis to Rule a New Manufacturing Era – Part 3

In his recent State of the Union address, President Barack Obama outlines a new public-private initiative to create 15 manufacturing hubs in the US. The plan calls for the private sector to work with the federal government to offset some of the domestic manufacturing jobs that have been lost for years to outsourcing.

PLM mfg data crunch Data Analysis to Rule a New Manufacturing Era – Part 3Indeed, manufacturing is entering a new era, one with a competitive landscape that’s been forever changed by the recession that has stifled demand for many goods and services.

Yet, at the same time, manufacturers will soon encounter a new paradigm shift where emerging economies like China and India, once seen only as sources of cheap labor, will be home to the vast majority of the world’s consumer class.

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Data Analysis to Rule a New Manufacturing Era – Part 2

Developing countries have been the go-to options for US manufacturers for many years because of low labor costs. But a new global consuming class will have emerged by 2025 and the majority of consumption will take place in developing economies, according to a new report from McKinsey Global Institute.

digitalmanufacturing Data Analysis to Rule a New Manufacturing Era   Part 2This will provide a wealth of new opportunities for manufacturers in these emerging markets, especially given the recent decline in US manufacturing during the recession, according to the report.

But these opportunities are developing in a volatile new landscape with dramatic swings in the cost and availability of things like labor and natural resources – a landscape that combines with rising complexity, uncertainty and risk to create an environment that is far more uncertain than it was before the Great Recession, according to McKinsey.

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Data Analysis to Rule a New Manufacturing Era – Part 1

As the world slowly recovers from the Great Recession, the competitive landscape for at least one sector – manufacturing – is entering a new era, ripe with opportunities but also fraught with challenges, according to a new report from McKinsey Global Institute.

developpement capteurs optiques sensor development Data Analysis to Rule a New Manufacturing Era – Part 1The winners in the global manufacturing arena will be those companies that can adeptly harness big data with manufacturing analytics to uncover customer insight, identify new markets, monitor sensors and collect after sales data.

This is the first article in a series that delves into how manufacturers can effectively compete domestically and globally in the new post-recession era by wielding big data as a weapon to drive innovation and growth.

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