Done right, big data can unlock big profits for firms

Affordable, and efficient information gathering in combination with the right analytical tools can transform businesses.
20 July 2022

Big data beneficiaries: aviation is just one of many industrial sectors that are gaining ground thanks to large datasets. Image credit: Shutterstock

‘Big data’ may be a buzzword, but there’s a good reason why businesses are keen to get their hands on it. Datumize, a Barcelona-based deep tech venture, sums it up well, noting that the investments being made by Fortune 1000 companies in big data analysis can drive up profits significantly. Even finding ways to collect the data more efficiently – for example, by using vendor neutral solutions to break out of proprietary and expensive to access systems (something that Datumize was able to arrange for one of its oil refining clients) – can deliver a noticeable payback.

Predictive power

Aircraft makers have long relied on service data to enable predictive maintenance programs, with each flight easily filling up a laptop with thousands and thousands of descriptors of the plane’s performance. Improvements in sensors, with costs dropping as well as gains from miniaturization, has expanded the amount of data that’s become available to fleet operators and their suppliers. Predictive maintenance offers the highest rewards – shrinking costs by more than 30%, according to aviation solutions provider EXSYN, which operates out of The Netherlands.

While we’re on this topic, it’s important to draw the distinction between ‘predictive’ and ‘preventative’ maintenance. The latter can leave profits on the table as it’s underpinned by age-based algorithms that can result in parts being swapped out at the wrong time whenever there is a weak correlation between equipment age and failure rate. Predictive maintenance on the other hand is badged as maintenance timed ‘just right’ and, according to UK firm Dashboard, is “the industry 4.0 version of maintenance.” To get ahead, operators mine mountains of data to build a model that captures the full story on what needs to be replaced and when.

Warehouse savings

As well as lowering maintenance costs directly, there are also inventory savings, as providers can build ordering into their model and stock only the parts that will be needed in the short term. Or at least that was the thinking before global events threw a spanner into the world’s supply chains (for more on that subject, you might want to read – ‘Mixed views on the best play for post-pandemic supply chains’).

Striking a more upbeat tone, the great thing about the big data expertise offered by Dashboard, Darumize, and others in the market, is that it can be applied across multiple sectors. Once you’ve built a predictive maintenance model for aviation, you are well placed to do the same for rail operators, automotive firms, manufacturers, providers of civil infrastructure, and the list goes on.

New sales models

By capturing rich datasets, operators can build up a detailed picture of how their products perform in service. They can adjust the price offered to customers based on the number of hours that the client intends on using the product each month, as this figure can now be tracked and maintenance costs accurately factored into the proposal. Alternatively, they can reward careful operators when they avoid turbulence and perform well-judged landings, as this behaviour will reduce the stress placed on the aircraft.

Providers of motor insurance have shaken up the market in a similar way by rewarding customers for driving safely. This is enabled by drivers either completing an assessment facilitated by the accelerometers and GPS receivers in their smartphone (when they have it with them in the vehicle) or by fitting a black box tracker (containing similar electronics). Insurers can now examine this data to log any incidents of sharp cornering, harsh braking, and speeding and adjust their premiums accordingly. And cars and planes are not the only examples.

The Internet of Things (IoT) is peppering the planet with sensors. Devices such as smart doorbells and thermostats give firms access to behavioral data that could be used to target homeowners with products at different price points based on the occupancy of the property or its energy usage, to give a couple of ideas.

Not a fad

Almost a decade ago now, Bain & Company, a US consulting firm with interests in industry 4.0 and digital operations, surveyed 400 companies around the world, most with revenues in excess of $1 billion to examine the difference that big data analytics can bring to firms. And the results fly the flag for getting serious about big data. Companies that were using analytics as part of their day-to-day operations were “Twice as likely to be in the top quartile of financial performance within their industries [and] five times more likely to make decisions faster,” reported Rasmus Wegener and Velu Sinha, who led the study.

Today, business intelligence (BI) packages are leading the charge to help companies identify patterns in their data and spot trends. And the more data you have at your fingerprints, the stronger the insights that can emerge.