Making your Balance Sheet Look Good with Big Data!


For any company, there are two ways to make your balance sheet look create, one – Make Big Money and two – Save Big Money. 

Big Data solutions and analytics can do both of these tasks with ease. So why not use these technologies to cut costs and improve revenue? It is 2021 now and companies have been doing it from 2010.

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Staying ahead of the curve and keeping up with the technology advancements is key for any company to stay afloat and to thrive.

Let me give you a few use cases to demonstrate how big data and analytics proved to be efficient and money saving.

  1. Let’s take the case of the semiconductor powerhouse, Intel. With the aim of bringing chips to the market faster, Intel has been using big data and predictive analytics from 2012. Each of these chips are put through a barrage of extensive tests to ensure quality. To be precise, each chip goes through 19000 tests. Intel started gathering historical data from pre-release chips to reduce the test time. They took the information of the pre release chips and analyzed it at the wafer level. The aim was to focus tests on specific chips rather than to run each chip through 19000 tests. The predictive analytics process of finding the faulty chips was implemented on a single line of Intel core processors. This process saved Intel $3 million in manufacturing costs in 2012. In 2013-14, the company wanted to extend the process to more chip lines to save a further US$30 million.
  2. We are all quite familiar with the supermarket chain Tesco. Tesco made use of big data solutions to cut down its annual refrigeration cooling costs by 20%. They did this across 3000 stores in Ireland and the UK. IBM’s research laboratories were brought into the picture for this exercise. The research lab in Dublin analyzed tons of refrigeration data and came to the conclusion that Tesco stores in Ireland were running their refrigerators at temperatures lower than required. The team from IBM developed KPIs that analyzed the data aggregated every month over a year. With this data, they came to the conclusion that many of the refrigerators were functioning in anomalous ways.
  3. The entire campus of the Massachusetts Institute of Technology (MIT) is a shining example of the use of big data analytics. The theme behind this is that the whole MIT campus is focused on being sustainable and energy efficient. The buildings on campus are color coded based on their energy consumption status. Say a building is color coded red, which means there is a water leak or probably an energy leak in the ventilation systems, lighting or the climate control mechanism. The energy monitoring system makes use of big data analytics to even predict where a problem is likely to surface next. This makes MITs system a lot more efficient as they know exactly what to look for.

When it’s all about the Moolah!

Big data and advanced analytics can drive success in just about every industry vertical.

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  • Telecom giants like Vodafone are using predictive analytics to forecast customer purchase patterns. The company also uses predictive analytics to achieve data modernization.
  • Predictive analytics can help manufacturing companies with predictive maintenance for their equipment, helping maximize uptime and deploy maintenance cost-effectively.
  • Big automobile manufacturers like Volkswagen are using big data to influence our buying decisions.
  • Online companies make use of a combination of 3rd party big data technologies and in-house big data technologies to understand their customers in their entirety and to perform audience analytics for their next campaign.
  • Predicting sales volumes during peak sales periods allows for better inventory planning thereby cutting down on waste inventory or over stocking.
  • Improving the supply chain to optimize shipping costs and in turn reducing over expenditure. Amazon and Zara is the best example of integrating big data in their supply chain to reduce supply chain costs.
  • Reduction in costs of marketing strategies is achieved with the use of big data technologies. Creating customer personas and analyzing buying behavior help in creating the perfectly targeted marketing strategies.
  • In the e-commerce space, with the integration of big data technologies, companies can find out which cities are responsible for the maximum product returns, or which customer frequently exchanges the products. Along with this, a proactive approach to obtain feedback from the customer can be done. This in turn will help reduce costs in terms of transportation and logistics.

Being Big Data Ready

I have quoted just a few examples of where and how big data influences decisions, reduces costs and generates revenue.

Big data is not bound to companies in the tech space. I have taken you through the applications of big data and analytics in a supermarket, in a semiconductor manufacturing company and in a college. 

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Big data analytics and visualization can help you out in just about any industry. If you want to cut costs and generate more revenue, big data is the way to go! What are you waiting for? Get your big platform ready right now!

Author: Abhimanyu Sundar
Abhimanyu is a sportsman, an avid reader with a massive interest in sports. He is passionate about digital marketing and loves discussions about Big Data.