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Teradata Universe: Six Ways Data Can Make Your Business A Digital Leader

Sam Pudwell joined Silicon UK as a reporter in December 2016. As well as being the resident Cloud aficionado, he covers areas such as cyber security, government IT and sports technology, with the aim of going to as many events as possible.

Data has gone mainstream, but can you be considered a digital leader?

Teradata Universe 2017 officially got underway in Nice, France today, with a host of keynote speeches from senior executives kicking the day off.

Teradata Universe, the firm’s annual conference, is underway in the South of France and is the platform CEO Victor Lund used to declare the company has got its focus and “swagger” back – a sentiment shared by fellow executives given the role of big data in digital transformation.

“In the last decade we have seen data go mainstream,”added Mikael Bisgaard-Bohr, chief business development officer, adding data is now seen “as the new raw material that drives business”.

But the bulk of his talk involved outlining six key characteristics that define digital leaders in today’s information-driven world, which are listed below.

Data at the core

‘Data at the core’ is a principle that we’ve heard plenty of before. For Teradata, it means there needs to be a realisation and understanding from senior executives within a business “that data is not a by-product of the business, it’s actually a core asset of the business”. More than anything else, it’s a mindset.

Bisgaard-Bohr cited FedEx founder Fred Smith as an example. Smith is quoted as saying that “the information of the package is as important as the package itself”, meaning he understood early on the FedEx was as much a data company as it was a logistics and parcel delivery company.

“The data that resulted from moving all the goods around has almost as much value as the service itself,” Bisgaard-Bohr said.

And that is more true today than it ever has been. I’m sure most people have heard the phrase “every company is a data company” and if businesses don’t realise this and put data at the core of their operations, no matter what the industry, they will ultimately be left behind.

data centre

Design for data

This is slightly different from the first characteristic, in that it concerns how a business is designed operationally in order to make data-driven decisions.

Walmart was cited as an example. Sam Walton, the company’s founder, once said: “People think we got big by putting big stores in small towns. Really we got big by replacing inventory with information.”

Bisgaard-Bohr explained that was Walmart did was invest in their Point of Sale operations to collect data that no-one else was collecting. “They understood that the data would allow them to understand selling patterns at the store level and would allow them to synchronise the supply chain,” bringing benefits that weren’t available to Walmart’s competitors.

A US-based online insurance company called Root is another example. Root tracks new customers through a mobile app to understand their risk profile, tracking information related to how and where the user drives. This enables the company to be able to “uniquely understand the risk profile of each individual customer so they can quote your insurance to a higher degree of precision than almost any of their competitors”.

Essentially, this characteristic refers to “a desire to acquire data”, which can potentially result in significant performance and financial business improvements.

Experimentation

Now, collecting all this information is all well and good, but businesses also need to be able to put it to use.

“Companies that really want to be digital leaders need to make that data available to their business people,” Bisgaard-Bohr said, allowing them to experiment and gain actionable business insights.

In practical terms, this translates into a higher number of small, iterative, low-cost projects where failure is accepted, as opposed to the old model of slow, expensive, low-risk projects which must succeed.

“Some of them will be successful and will merge up into the big projects, but 90 percent of them will fail and that’s OK because really what they are are analytics experiments.”

It essentially requires a cultural shift within organisations, moving from the traditional paradigm of using analytics to answer specific questions, to one of collecting as much data as possible, making it available to people within the business and allowing experimentation to take place. 

“If you give data to the business users, once they understand what the problem is they’ll be compelled to fix it, because an individual with information cannot take responsibility, but one with information cannot help but take responsibility. It’s a big cultural change, but it’s very powerful.”

Find out the final three characteristics on page 2…