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Big Data Manufacturier Innovant Industrie 4.0

Why should your company be interested in Big Data?

The use of Big Data, large amounts of data that can be collected and analyzed to discern trends and make better decisions will become the basis for business competition and growth, improve productivity and create considerable value for the global economy by reducing waste and increasing the quality of products and services.

From the beginning of time until the year 2003, the whole world had only collected 5 billion gigabytes of data. This same amount of data was generated in two days in 2011. In 2013, this volume was produced in 10 minutes. It is therefore not surprising that 90% of all data in the world has been created in recent years. This mountain of information can be extremely useful when it is processed, but it has been largely neglected before the concept of big data was born.

Data Valuation

“Knowledge is power!” as Francis Bacon said. And boy was he right! When you are at the helm of a company and you have to make crucial decisions, it is good to get as much information as possible, while still being able to interpret and understand them. The era of Industry 4.0 and connectivity means that a ton of data can be made available to leaders of all industries and this data is now an invaluable solution to solidifying the success and sustainability of companies. The notion of Big Data becomes important because the amount of data grew so extremely that it becomes difficult to manage with traditional database management tools. So we are talking about a valuation of data by activities such as:

  • Real-time analysis of a data flow;
  • Trend inference from multi-structured datasets;
  • The visual representation of the results;
  • Discovering and exploring data across different sources.

To explain all the value this data collection might have, one often resorts to the analogy of oil. The data itself, just like crude oil, has little value. But once processed and refined, they become very powerful.

The Basics of the Concept

Big Data is an emerging concept in the business field. On the other hand, the concept is based on the experience of mathematics and science that has been using sophisticated statistical analysis for years. To understand it well, you have to look at the basics of Big Data, the 4V.

Big data profile in Québec
© Big data profile in Québec


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Make Data Profitable

The first decisive step for companies that want to use advanced analytics to increase yield is to determine how much and what kind of data they have at their disposal. Most companies will collect a huge amount of data but only use it to track, not to improve operations. For these types of companies, the challenge will be to invest in systems that will allow them to optimize the use of current information transfer processes, for example, centralizing or indexing data from different sources to to be able to treat them more easily. The use of data analysts who can discern trends and transform them into actionable information might be essential.

The power of Big Data

Every business uses data differently, but the more efficient their usage, the greater the growth potential. Logic! Optimal data analysis allows you to find answers that help to generate:

  1. Cost reduction:
    Big Data can push a company to want to change internal processes. The information generated can help reduce production, packaging and maintenance costs during manufacturing. In addition, it could also reduce transportation and inventory costs and lead to significant savings.
  2. Increasing efficiency:
    Some Big Data analytics tools can provide immediate analysis and help executives make quicker decisions. These same analysis can be used to improve the speed of production, especially for factories that work with large volumes. It also allows executives to differentiate processes by product to target the necessary adjustments.
  3. Job enrichment:
    These time-saving analyzes free employees to focus on value-added tasks. In addition, the synergistic flow of information across management, engineering, quality control, mechanical operators and other aspects of the organization allows these different departments to work together more efficiently. Some employees even consider that the arrival of Big Data makes their work much less repetitive and therefore more stimulating.
  4. Improved Customer Connection:
    Big Data can also extract valuable customer information. By knowing how consumers buy as well as their level of satisfaction, we can not only make products according to their specific needs but also do targeted marketing. In the end, we are talking about a possible increase in income.
  5. Online reputation control:
    Analysis tools can measure feelings. It is therefore possible to obtain precise feedback on what the public thinks and says about a company. The online presence of your company can therefore be monitored and improved.
  6. Controlling competing strategies:
    Just like analytics tools can monitor customer needs and the online reputation of your business, they also can quickly detect new strategies implemented by your competition.
  7. Improving quality assurance:
    Using Big Data to do preventive analysis significantly reduces testing times and allows a firm to focus on specific tests.
  8. Risk reduction:
    The study of the extracted data makes the detection of bad practices, anomalies and possible frauds much more efficient. Adequate measures can then be applied to minimize the damage.
  9. Improving the Supply Chain:
    By using Big Data to predict potential raw material delivery problems, a company can evaluate the potential delay probabilities on a map, analyze weather contingency for tornadoes, earthquakes, hurricanes, etc. Predictive analysis calculates the probabilities of delays. The results can help identify alternative suppliers and develop a plan B to ensure that production is not interrupted.


The Concrete Impacts

Intel has been using Big Data for their manufacturing of processors for some time. The chip maker must test each chip that comes out of its production line. This normally means that each chip passes through roughly 19,000 tests. Predictive analysis has made it possible, thanks to the large amount of data collected, to considerably reduce the number of tests required for quality assurance. The duration of testing has been reduced and the company is now focusing on specific tests.

Savings of $ 3 million in manufacturing costs have been realized for a single line of Intel Core processors. By developing the use of Big Data in the production of its chips, Intel plans to save an additional $ 30 million.

Big companies are increasing their investment in Big Data and such efforts are opening up new opportunities that are paying off which are measurable through tangible results. For a typical Fortune 1000 company, an increase of just 10% in data accessibility will translate into an additional net benefit of more than $ 65 million.

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Emilie from ThirdBridge (BRIDGR's Partner)

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