Big Data: How Rio Tinto, UPS and others are increasing efficiency and saving millions

These days it is possible that big data is as important to businesses as the Internet is to society. The data itself has always been there, but the technology to analyse it has only recently become sophisticated enough to handle the sheer amount of information available.

Industry analyst Doug Laney developed the mainstream definition of big data through the use of three words: volume, velocity and variety. All of the data stored accounts for the volume – a somewhat obvious component of the definition. But the velocity at which data travels currently is unprecedented, and companies must handle it in a timely matter to stay on top of their analytics. There are a variety of formats of data – structured, numeric data, data from transactions, unstructured text documents, emails, video, and many others.

SAS Institute, a global leader in business analytics software and services, believes there are even more layers to big data. Variability (the changes in data flows throughout the day, a marketing campaign or the year) and complexity (several different pieces of data from several different sources processed through several different programs and people does not always provide the big, cohesive picture) are two more things business owners should account for when considering analysis of big data.

It was the big trend and buzzword of 2013, and now we know why. Several companies have been reporting massive savings from utilizing analytics garnered from big data.

Increased efficiency

As of 2013, Australia had one of the lowest rates of big data usage; however, Australia ranked as one of the highest countries in terms of median spending per company – about US$50 million. Comparatively, the median spending in the US was about US$9 million per company. The companies that are spending on big data however are getting their money’s worth.

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"The Commonwealth Bank and Medibank Australia are using big data analytic solutions to extract more accurate and clearer data of their customers to deliver better products and services to the right customers,” said Frost & Sullivan research analyst Vu Anh Tien.

By enhancing marketing strategies and practices through improved data analytics, companies like the Australian Post have been able to deliver better value to businesses and better support to customers. Telstra has also invested in big data, with the hopes of improving unique customer marketing strategies to enhance their value to their users.

Rio Tinto’s huge savings

Rio Tinto’s Pilbara region mines, railways and ports generate 2.4 terabytes of data a minute, and its new, state-of-the-art processing centre in Brisbane is working towards processing this valuable information. The company recently reported that its new processing centre in Brisbane has already reduced the company’s costs by US$80 million. The most impressive thing to note however, is the savings come specifically from analysing data from hundreds of thousands of data points just at Rio Tinto’s copper plants.

As the new processing centre – complete with the newest technology, including a wall-sized multi-platform touch screen – gears up to analyse data from other sites and machines, one can only image the possibilities. By focusing on technological advances more so than their competition, Rio Tinto has distinguished themselves as leading innovators in their sector. The data from the company’s plants, drill rigs and automated trucks will continue to play a huge part in Rio’s productivity push.

"Expert operators can analyse this data in a way you couldn't do on a single site, comparing operating parameters and comparing performance (with other sites)," said Sam Walsh, Rio chief. "The potential is huge in terms of taking our business forward.”

After the success of the copper plants’ data analysis and the subsequent savings, Rio Tinto is looking to increase cost savings by analysing data from underground drill and blast rigs. This specific data has the ability to help the company tailor the use of explosives at coal mines, potentially preserving the coal that was once rendered useless by the blast for mining.

The company’s automated trucks, which have 400 data points and continually send out information regarding fuel efficiency and tyre pressure, are also in line to have data analysed. The information will help to make sure the trucks are in top running form, and will provide the details of issues in real time, potentially reducing costs of maintenance.

UPS: “We Heart Logistics”

UPS has been in the data game for a long time – they began gathering information about package movements and transactions in the 1980s. They are currently tracking over 16 million packages a day for nearly 9 million customers. The amount of data the store is mind-boggling: 16 petabytes, or 16,000,000,000,000,000 bytes.

A majority of their data comes from the sensors on their several thousand vehicles, which measure speed, direction, breaking, etc. This information is not just measure to monitor daily performance or whether issues arise – it’s main goal is to monitor drivers’ routes. UPS recently retooled the drivers’ route structures; in 2011, this major redesign lead to over 8.4 million gallons of petrol savings, and cut close to 14 million kilometres off of drivers daily routes. The company has claimed saving one daily mile per user saves the company US$30 million – so the total savings is astronomical.

In the future, UPS is looking to apply data, analytics and this savings model, a modified version, to the efficiency of their 2,000 daily aircraft flights.

In the end, the savings do not come from big data alone, it comes from what you do with the data. Having a crack analytics department or centre will keep the influx of date under control, and provide you with several strategies to possibly increase your efficiency and savings exponentially. The other key to staying in control of big data is investing in new and emerging technology when you have the chance. Technology moves fast, and frequently replacing it is not an option for most companies. Big data is a daunting subject, but when you’ve got the right tools and people, savings could be right around the corner for your company.